informatica was on that knife's edge they had a good product set in the sense that they foresaw that data was going to become more important and they are a good data company they've got a great suite of data management tool that's very relevant today's marketplace in many respects the question was were they going to step up and be one of the companies that successfully transition to the cloud and the services model or where they don't try to fight against it with products that and they have been making that transition and it seems to go be going quite well as data gets into the cloud and as people are using all of these different types of new data processing techniques to your point about the catalog if you don't have a fundamentally if you don't have a catalog that tells you where your data is who is using it what it is for etc you just lose control you just cannot keep an Olaf your data and so what people are realizing is as they do new business initiatives they gotta have the data catalog in a place where technology is changing unbelievably fast we're graduating you know nearly as many went men as women in you know fields of science data analytics Computer Engineering etc but we're not seeing a combination of women in leadership roles as much as we would expect we're not seeing the retention of women in those roles disruption with a purpose is intelligent and we believe with our technology that our customers can then unleash the power of their data to create what we call their next intelligent disruption so we were very thoughtful about the choice of words there because disruption can be considered a negative but we see it is very much a positive and a way for customers to leapfrog the competition and set set the tone for their markets

why from Las Vegas it's the cube covering implementing a world 2018 machito by informatica okay welcome back everyone's the cube live here in Las Vegas at the Venetian ballroom is the cubes exclusive coverage of informatica world 2018 I'm John for your host in analyst here with Peter Baris host and analyst here for two days of coverage our next two guests are jitesh guy who's the senior vice president general manager data quality security and governance for informatica and barry green the chief data officer for bank of ireland great to see you attached great to have you on the cube and great to be here so love having two to smart people talking about data GPRS right around the corner and friday you're at the bank of ireland so in the middle of it while you're in you're in this in the territory you're in the heart get any sleep what talk about your role at the bank what are you guys doing I want to get into the GDP RS right on our doorstep it's going to major implications for data as a strategic asset talk about what you do so for me we've created a daily management framework frameworks pretty simple map process get context for data put it into the business data model or sign ownership put data quality over it and then maintain it using a risk model operational risk model now it doesn't matter with GDP our or becbs whatever it is it's about adding value to data understanding day they're using it for them and making sure you've got better customer experience all the good things you know GDP are is important but it's not the only thing you guys are new to managing data and certainly complies your financials bank so it's not a new thing what is how is GDP are being rolled out how is it impacting you guys what are you paying attention to what's the impact so the big thing about GDP are is we're having to understand where our key customer data's sits in the physical systems we're looking at mapping key processes something to see and what it's used for we're assigning ownership to people who own data so we can basically make decisions about it in the future GDP ours a bit like becbs that's going to evolve right you're not going to be GDP are compliant on May 25th you're gonna have to put in place the infrastructure the tooling the governance the management to make sure that as an organization you know you were using data the way it's supposed to be if you want to be a digital organization you have to manage data this is just pushing along they had evolution of data being important to an organization but just as y2k wasn't about making the world safe for mainframes in the year 2000 it forced a separation and understanding of the separation that's required between applications and data so gdpr is another one of those events it's forcing a separation in this case between data and the notion of data assets great so take us through how the thought process of gdpr has catalyzed new thinking within the bank about how we think about data differently as a consequence I think what it's done so we've developed the framework so we can apply it to any problem right I think what it's done is it's raised up data's the risk of data more generally so people talk about data as an asset I've talked about data as a liability right so it's a contingent liability if you think about gdpr it's raise that awareness up that we can't continue to operate and tricked out of the way we have in the past so there's a whole cultural change going on around how we treat data and there's a big understanding training going on about everyone knowing why they use data making sure that they don't use it for the purpose it's not used for and generally it's a big education cultural change very how would you describe the mindset for this new thinking it certainly I agree with you it's at the strategic nature center the center of the center of the value proposition right now on all aspects not just some department what's the mindset that people should be thinking about when they think of data okay should I have access to this data but do I need it for the role I'm undertaking and if it was my data would I be treating it you know how would I shred it how would I want it to be treated even if you're the subject yeah exactly it's almost like you know if I had my data being used for certain thing context is that the way I'd want my data treated there's almost in the old adage you know do unto others as you would have you done to you yeah ethics is important yeah to church talk about the informatics opportunity because you guys really timings pretty awesome for informatica with the catalog you guys have an interesting opportunity right now to come in and do a lot of good things for clients that's that's exactly right we've we've been working very hard with our clients over the last 18 months to help them on this gdpr journey what we you know think of as supporting their privacy and protection and and you mentioned catalog you know our we have our enterprise data catalog powered by Claire our AI machine learning capabilities and metadata and that helps you get an organized view of all your data assets within the enterprise leveraging that same technology we have a security source offering which is effectively a data subject catalog to help our customers understand where exactly is the data subject sensitive data not where the organization's data is but the data subject sensitive data within the organization where their national identifiers information is how where their personal home address email phone etc is and how many occurrences and what systems why so that our customers can take that information and more effectively respond to the data subject if the data subject wants to invoke you know the right to be forgotten or right for data portability etc as well as take that same information and demonstrate to the regulator that they are processing this sensitive data with the appropriate with the appropriate consent from the data subject as well as have the systems I presume to then be able to expose to the subject the reasons why the data may in fact still be part of the asset of the bank correct so I I hadn't heard that before we've had other company cells that they're going to help companies find subject data but you guys are taping us taking a step further and allowing the bank for in this case do we have to look at that data from the subjects perspective exactly right because it's not just with some regulations financial regulations you need to demonstrate the quality and trustworthiness of the data here at to the regulator here it's demonstrating to the data subject themselves the individual themselves how you're processing how you're treating their data how protected or unprotected it is and and how you're using it to market to them how you using to become part of the metadata that's exactly right it's using the same metadata foundation too but focused on the data subject specifically interesting interpret ection aspect of it if I say I want my right to be forgotten and you can hold data for something mean where's the where's the protection aspect for the business and the user is there conflict there how do you guys handle that yes that's interesting there is a conflict so there's a conflict already with an existing regulation so you know um the thing that a lot of people aren't talking about is you can hold data so if someone can't just delete data if you want to hold an account or you know these reasons for using it you got a legitimate use for using it you can still hold it you have to tell a customer why you're using it so there's a lot of context here which they didn't have before so it's giving the customer the power to understand what the data is being used for the context is being used for and so they know it's not gonna be used for sort of spiritless marketing campaigns it's being used for you know the reason that does that extra work for you guys is that automated this is where we start to get into the question next yeah which is a context the context is the metadata and you're going to be able to capture that context explicitly as these data elements have this context in metadata allows you to do that with some degree of certainty and you know relatively low cost I assume it's all about reuse right so a lot of what we've done in the past and on its way at the bank um to me everyone's done in the past is they've understood something and then thrown it away so with Exxon you can record it you know record it then with the metadata you can join the metadata in Exxon so you can do in a high level process understand what data is used at the context is used for who owns that quality all these kind of business relevant things then you put the metadata out and you've got a system view it's very very powerful so the technology is starting to allow us to automate but it's all about gathering it reusing it and making sure you understand it right that's for you know from a from a data subject catalog standpoint you get the technical metadata it tells you across your data landscape where all the sensitive information is for Barry green you marry that up with the business metadata of how is that sensitive information being used in every step of let's say customer onboarding your mission critical business processes within the organization and that's what you demonstrate to a data subject or a regulator if this is how I'm processing it based on this consent now if they invoke the right to be forgotten there's various things you can do there because there's conflicts you can just mask the data using our masking capabilities and then it's true forgotten or you can archive the data and remove it from a particular business process that is marketing or selling to them if that's so yeah choice is it some flexibility correct or or slight maybe slightly differently Mystere forgot that's right you can get work out of that data in an appropriate way so the customer can be forgotten so that this this kind of work now that you cannot apply that data to marketing whatever else it might be for when it comes to understanding better products or building better products whatever else through masking you can apply the data still to that work because it's a legitimate use under the law exactly also think about the fact you've mask key critical data right so the thing about data privacy in general was you know if you can't understand a data subject so if you can hide certain pieces of data and you can't identify them you didn't aggregate it you can it's not personal data anymore so you know there's this some real nuance there's a lot of people aren't talking about these things but these new icers will be surfaced yeah yeah because certainly it's a it's the beginning of a generational shift there gonna be some pain points coming online I mean we're hearing some people complaining here and there you guys are you know used to this some industries are like used to dealing with Brad you know compliance like no big deal some people are fast and loose with their data like wait a minute I said you can't be a digital wanker we can't be a head of digital propositions you don't understand your data you know you and you don't understand it and manage it so this is an opportunity to do this across the enterprise it exposes companies that have not planned for an architected data whether that's investment in data engineering or have staff this is a huge issue and pools and tools that can't support that process I mean if you got a I mean people are looking in their organization going oh man we've really don't have it or they're ready the exciting part is you know organizations have focused on quality and trustworthiness of their data we're now taking that same data and focusing on the privacy and protection and the ethical treatment of it and leveraging the appropriate technologies which happen to be very similar fundamentally for quality and Trust and privacy and protection and and in the absence of a global standard for GDP our we're we're seeing organizations without GDP our as a de facto standard in fact Facebook just announced that they're treating all users data you know that was one of our research predict yes yeah very obvious I mean we'll see how eleven have any teeth or anything but you know Facebook's got their own challenge but it's an opportunity for a clean sheet of paper Friday May 27 I'm sure there's gonna be a ton of class-action lawsuits against Facebook jitesh Barry thanks for coming on great to see you thanks for everything in Ireland we're here on the open and informatica world right and written the solutions expose the cue bringing you all the data right here in the catalog you got the cube dotnet check it out I'm people John free with Peterborough's stay with us for more day to coverage at different Matic world after this short break

>> 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)

>> Announcer: Live from Las Vegas, it's the Cube. Covering Informatica World, 2018. Brought to you by Informatica. >> Okay welcome back everyone, this is the Cube live here in Las Vegas for Informatica World 2018 exclusive coverage of the Cube. I'm John Furrier co-host of the Cube with Jim Kobielus, my co-host this segment and with that we'll keep on continue with the Cube. Our next guest is Vira Shanti who is the chief data officer at Lippo Digital Group, welcome to the Cube. >> Thank you so much, very excited to be here. >> Thank you for coming on, but people don't know before we came on camera, you and Jim were talking in the native tongue. Thanks for coming on. I know your chief data officer, we've got a lot of questions we love these conversations because we love data, but take a minute to explain what you guys are doing, what the company is, what the size is and the data challenges. >> Okay, maybe let me introduce myself first, so my name is Vira, my role is the chief data officer. Responsibility, that actually is cover for the big data transformation for the Lippo group data. Lippo group is actually part of the one of the largest in Indonesia, we serve a middle class for the consumer services, so we are connecting I think more than 120 million of the customers. What's Lippo as a group doing is actually we do many things. We are the largest of the hospital in Indonesia or just super market, we do department stores, coffee shop, cinema, data centers. We on bang as well, news, cable TV, what else? >> You have a lot of digital assets. >> What you do is you drive to any state in Indonesia and you see Lippo everywhere. >> Yeah, education as well, from the kindergarten to the university, that's why it's a lot of diversity of the business, that owned by Lippo. But recently we're endorsing a lot in the digital transformation, so we're releasing a new mobile app, it is called OVO, O, V, O. Actually it's like centralized loyalty E money to providing the priority bills to all the Lippo group customers, so they're not going to maintain their own membership loyalty program, it's going to just like the OVO, so it's not only being accepted by Lippo ecosystem, but also to the external ecosystem as well. We start to engage with the machine partner, we just today sorted like reaching out 30000 machine outlets. >> Let's get Jim's perspective, I want you to connect the dots for me, because the size and scope of data, you talk about deep learning a lot. And let's connect the dots, cuz we've heard a lot of customers here talking about being having data all over the place. How does deep learning, why do you catalog everything? If you've always diverse assets, I'm sure there are different silos. Is there a connection, how are you handling? >> Okay, differently it's not easy job to do, implementing big data for this kind of a lot of diversity of the business, because how to bring all of this data coming from the different source, coming from the different ecosystem to the single analytical platform is quite challenging. The thing is, we also need to learn first about the business, what kind of the business, how they operate, how they run the hospital, how they run the supermarket, how they run the cinema, how they run the coffee shop. By understanding this thing, my team is responsible to transform, not start from the calling the data, cleansing the data, transform the data, then generate the insight. It has to be an action inside. Then we also not only doing the BI things, but also how from their data we can developing the analytical product on top of the technology big data, that we own today. What we deliver is actually beyond the BI. Of course we do a lot of thing, for example, we really focusing in doing the customers 360 degree profile, because that's the only reason how we really can understand out customers. Today, we have more than 100s of customer attribute teaching for individual customers. I can understand what's your profile for the purchasing behaviors, what kind of the product, that you like. Let's say for the data coming from the supermarket, I know what's your brands, your favorite, whether you're spending is declining. How you spend your point, part of the loyalty program. Then many things, so by understanding very deep these, that we can engage with customers in the better way in providing the new customer experience, because we not only let's say providing them with the right deals, but also when would be the right time, we should connect to them providing something, that they might need. This is the way how from the data we try to connect with our customers. >> Yeah, provided more organic experience across the entire portfolio of Lippo brands throughout the ecosystem. It doesn't feel to the customer and so it isn't simply a federation of brands, it's one unified brand in some degree from the customer's point of view delivering value, that each of the individual components of the Lippo portfolio may not be able to provide. >> Yes, yes, so many things actually we can do on top of that 360 degree of the customers. Our big data outcome in the form of the API. Why it has to be in the API, because when we interact with the customer, there could be unlimited customer touch point to call this API. It could be like the mobile apps after smart customer touch point or could be the dashboard, that we develop for our Lippo internal business. Could be anything or even we can also connect to the other industry from the different business, then how we can connect each other using that big data API, so that's why-- >> Is it an ecosystem, isn't that one API, or it's one API, when unified API for accessing all the back end data and services? >> For something like this, there are to type of the API, that we develop, number one is the API, that belong to the customer 360 degree. Every entry would then attach to your profile and say we can convert it to the API. Let's say smart apps, as part of customer touch point, for example like OVO, we would like to engage with our customers, meaning, that the apps can just designing their online business orchestration, then calling a specific API by understanding let's say from the point of view of loyalty or product preference, that you like, so that then what kind of offers, that we need to push to the customer touch point general using the OVO apps. Or even let's say other supermarket have their on apps, so the apps can also following our API based on their data to understand what kind of the brand or the preference probably they like. Let's run in their apps, when the customer connects, it's going to be something, that really personalized. That's why it's in order to manage the future, actually it's very important for us to deliver this big data outcome in the form of the API. >> It scales too, not a lot of custom work, you don't have to worry about connecting people and making sure it works, expose an API and say, there it is and then. >> Different countries, in terms of privacy in the use of personally identifiable information, different countries and regions have their own different policies and regulations, clearly the European union is fairly strict, the European union with GDPR coming along, the US has its own privacy mandates, in Indonesia, are there equivalent privacy regulations or laws, that we require for example. You ask the customers to consent to particular uses of their data, that you're managing with your big data system, that sits behind OVO. Is that something in your overall program, that you reflect? >> Yes, there are some regulation in Indonesia governed by the government, they'll call having their own regulation, but we let's say part of the thing, that, yes, there is a specific regulation. But regulation for the retail is not really that clear yet for now, but we put ourself in the higher restricted regulation, that we put in place as part of our data protection, part of our data governance compliance as well. If until we do this demonetization or consolidating this data, there is no data, that's being shared outside the entity of the organization. Because let's say, when we do that demonetization everything's done by system to system, when it's called the API, so there is no hands off for other customer in individual data. Let's say if our partner FMCG digital agency or even advertiser, future wise they would like to call our API, what they can see, but that target lead of the customers, that they would like to connect is actually not individual of the data. It's going to be in the aggregated format. Even though many segmentation, that we can deliver is not going to expose every individual customer. >> You have a lot of use cases, that you can handle, because of the control governance piece. How about, by the way, that's fantastic and I know how hard it must be the challenge, but you have it setup nicely. Now that the setup with Informatica and the work you're doing, how are you interfacing with developers, cuz now you have the API. Is it just API based, are you looking at containers, kubernetes, clout technologies? Are you guys looking at that down the road or is that part of the, or is it just expose the API to the developers? >> For today, that actually who's going to consume our API actually? Definitely it's going to be the ecosystem of the Lippo internals, how the customer touch point can leverage the API. Then for the external, for example, like FMCG, the digital agency, when they call our API, usually it's like they can subscribe, there could be some kind of the business model divine there, but once again, like I mentioned to you, let's say it's not going to reveal any individual customer information, but the thing is, how we deliver this API things? We develop our own API system, we develop our API gateway, in simple thing, that actually how to put the permission or grant the access of any kind of digital channel, when they consumer our API and what kind of subscription meta? What we did for the big data actually is not really into, we investing a lot of technology in place for us to use. The thing, that makes my team so exciting about this transformation, because we like to create something, that's we create our own API gateway. We create some analytic product on top of the technology, that we have today. >> When they subscribe to the API, you're setting policy for the data, that they can get and you're done. >> Something like that. >> You automated that. Cool, well we see a lot of AI, any machine learning in your future, you, guys, doing any automation, how are you guys thinking about some of the tools we've been seeing here at the show around automation and AI, Clair, you tapping into any of the goodness? >> Yes, if everybody like to talk what AI right? >> John: You got API, you're good, you don't need anything. >> Many organization, when they're really implementing big data, sometimes they start jumping, I need to start doing the AI things. But from our point of view, yes, AI is very important, definitely we will go there, but for now, what's important for us is how we really can bring the data to single analytical platform, developing that 360 degree customer profile, because we really need to understand our customer better. Then thinking about how we can connect with them, how we can bring the new experience and especially at the right time. >> Actually let me break down AI, cuz I cover AI for Wiki bond, it's such an enormous topic, I break it down in specific things, like for example, speech recognition for voice activated access to digital assistance, that might be embedded in a mobile phones. Indonesia is a huge diverse country, it's an acapela, you have many groups living under the unitary national structure, but they speak different languages, they have different dialects, do you use or are you considering speech recognition? How you would tailor speech recognition in a country, that is so diverse as Indonesia. Is that something an application of AI you're considering using in terms of your user interface? >> Okay, for now we not really into there yet, because you are definitely correct. Developing that kind of library for Indonesia, because different dialect, different accent, it's tough, so the AI things, that we're looking for is actually going to be product recommendation engine. Because you know, let's say, that a lot of things on top of this customer 360 degree, that we can do, right? Because meaning it's going to open unlimited opportunity how I can engage to the customers, what kind of the right offer. Because there's a lot of brand owners, like FMCG, that they would like to connect, also getting in touch, reach out our customers. By developing this kind of product recommendation engine, let's say using the typical machine learning, so we can understand when we introduce this thing, customer like it, introduce that thing, they don't like it. >> Let me ask the next logical question there, it's such a big diverse country, do you, in modeling the customer profile, are you able to encode cultural sensitivities, once again, a very diverse country, there's probably things you could recommend in terms of products to some peoples, that other people might find offensive or insensitive, is that something, that in terms of modeling the customer, you take into consideration? It doesn't just apply to Indonesia, it applies here too or anywhere else, where you have many people. >> Of course can to do that the modeling, but we're doing right now, let's say once again, speaking about the personalized offer, from that point of view, what we see is to create the definition based on customer spending power first, buying power, we need to understand, that this customer's actually in which level of the buying power. By understanding this kind of buying power level, then we really can understand, that should we introduce this kind of the offers or not. Because this is too expensive or not. Because customer spending level can be also different. Let's say when our customers spend in our supermarket, maybe it's going to medium spending level, but let's say when they spend their money to purchase the coffee, maybe it's regular basis, so it's more spending. Could be different spending, so we also need to learn this kind of thing, because sometimes the low spending or medium spending or high spending, sometimes it's not something, that we put in the effort level for everything, sometimes it could be different. This is the thing, that also very exciting for us to understand this kind of spending, buying power. >> Great to have you on the Cube, thanks for coming, so I got to ask you one final question. I heard you were in an honorary Informatica innovation award honoree, congratulations. >> Thank you. >> What advice would you have for your peers, that might want to aspire to get the award next year? >> The thing is, our big data journey just start last year. Really start from the zero, so when yesterday we get an award for the analytics, so actually what we really focus on to do something, that actually is very simple. Some organization, when they're implementing big data sometimes they would like to do everything in the phase one. What we're planning to do is number one, how to bring the data very fast, then understand what kind of value of the data, that we can bring to the organization. Our favorite one is developing the customer 360 degree profile, because once you really understand your customer from any point of view, it's going to open unlimited opportunities how you can engage with your customers, it also open another opportunity how you can bring another ecosystem to our business to engage with our customers, that one point of view is already opening a lot of thing, huge. Either that thinking what would be the next step. Of course, that API is going to simplify your business in the future scale so on. That's becoming our main focus to allow us to deliver a lot of quick low hanging effort at the same time. I think that's a thing, that makes us really can, within a short period of time, can deliver a lot of things. >> The chief data officer at Lippo digital group, thanks for sharing your story, it's the Cube, we're here live in Las Vegas. They're going to be bonding here talking about all the greatness going on there. This is the Cube here in Las Vegas, stay with us for continuing day two coverage of Informatica world 2018, we'll be right back.

>> Announcer: Live, from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. Okay, welcome back everyone, this is theCUBE, live here in Las Vegas at The Venetian, this is Informatica Worlds exclusive coverage with theCUBE, Informatica World 2018, I'm John Furrier, with my co-host Jim Kobielus, analyst at Wikibon, SiliconANGLE, and theCUBE, our next guest is Tracy Ring, Vice President at Deloitte Consulting, great to see you again. >> You as well! >> So, love havin' you on, last year, you know, we go through all the interviews and, you know it always comes up, and this is important, you know we are passionate about women in tech, inclusion and diversity, huge topic, the job's never done, in fact, I was in New York last week for a blockchain event, and I wore a shirt that said: Satoshi's Female. (Tracy laughing) And I literally was getting so many high fives and, but it's not just women in tech, there's a role that men play, this is, sort of an ongoing conversation so. What's the state of the industry, from your perspective, how do you see it? Obviously the data world is, indiscriminate data is data, >> Tracy: Absolutely. >> It should be 50/50. >> Yeah, you know I think that the, the opportunity is multi-faceted, right? So we're in a place where technology is changing unbelievably fast, we're graduating nearly as many men as women in, fields of science, data analytics, computer engineering, etc. But what we're not seeing, a combination of women in leadership roles as much as we would expect, we're not seeing the retention of women in those roles. And for me, I'm really passionate about the fact that supporting, attracting, and keeping women in those roles, is really critical, right? There's an interesting facet to how this all really, really plays together, Deloitte for 20 years has a women initiative, right? 20 years of supporting women, embracing them, helping them support leadership roles and, and I think that the time is now. If not, it's long overdue, to really support them within this field. I also think that women in data, an initiative that we're launching this year, and having our launch event today, is sort of super timely because women in data is not women who only become CIOs, or will only become CDOs, these are women that will be the Chief Marketing Officers, the CHROs, and using data to tell their stories. >> You know, we had a guest on earlier, who was a man, but he was the head of the CDO for the Ireland Bank, and Peter Burris asked the question, said hey, where did you come from technical? No, he came from the business side, who knows technology, this is what you're getting at, and I think this is something that we've been seeing as a pattern that you don't rise up through the ranks and be super nerdy, although that's cool too, and there's a lot more STEM action but there's also multiple vectors into the field. You can come from business, and know tech, and a lot more tech is consumable, and learnable, either online, or through some sort of other proficiency so, this is a big story and so, how do you guys, looking at that, at Deloitte, I know Deloitte's got the track record, but this all scales beyond Deloitte, right? It's an industry thing. >> Tracy: Absolutely. >> How are you guys seeing this? How are you looking at helping people, either connect the dots, or support each other? What's some of the latest and greatest? >> Yeah, I mean I think Informatica is part of what has created the case for change, right? We've democratized data integration, we have, you know, made self-service analytics, we've put data in the cloud in everyone's hands, right? So technology is out there more, every single day, and I think the unique part is, is that, when we think about diversity wholistically, and I think of diversity from ages, and geographic, and gender, etc. I think really being able to take all of that diverse experience, and be able to listen to business user's requirements in a way that they can hear it! And listen for something different, right? And brings skills to bare, that aren't necessarily there. I think if we can build better technology, that's more future-proofed, based on having a diverse crowd listening, and trying to build something that's far more compelling than, you know, I asked for X, build me X. I think when we really do our clients, and the world of justice is when we, you know, someone asks for X, and you ask them 10 more questions, and heavy--what about this? And what, and what, and what? And I think really being much more inquisitive, giving people the ability to be inquisitive, and bringing more opinions to the table to be inquisitive. >> And bringing more diversity of practice, makes the applications better, so that's clear. We see that in some of the conversations we have, but I got to ask about the question of roles, what are you seeing, kind of, you look at the trends, are there certain roles that are, that are being adopted with women in tech more than others? Less, trending down, up? What are some of the trend lines on, either roles in tech, for women? >> Yeah, you know, I think that over all, when I had the opportunity, so when we decided, we're going to launch a program within Informatica. We want the women who are going to be the Chief Data Officers of tomorrow. And it was a great question because, actually what we ended up saying is, the Chief Data Officers of tomorrow could be so many different current roles right now, right? And how do we really, kind of, attract the right women into this cohort, support them for a long year and, provide them the forum to network, connect with others, understand different career paths. You know, looking at what we're seeing, you know, with GDPR, and regulations, and all these other things happening, you know, the concepts and roles that didn't even exist years ago, right, so data governance leads and, Chief Analytic Officers, and all of these-- >> James: Or Chief AI Officers! >> Exac--(laughing) >> How do we bring women into the hottest fields like AI, deep learning? If you look at the research literature, out of, both the commercial and the academic world, many of the authors of the papers are men, I mean, more than the standard ratio of men to women in the corporate space, near as I can tell, from my deep reading. How do you break women into AI, for example, when they haven't been part of that overall research community? That's just a, almost like a rhetorical question. >> Yeah, how do you not, you know, it's just impossible to not bring them to bear, the skills, the talent, the ingenuity, I think it's absolutely mandatory, and someone said to me, they said well, why are the men not invited to this event? Why are they not in the cohort? And I said, you know, because there's a component of all this, that we want to grow and foster and support, and create opportunities. You know, one of the women that sat on our board today said, you know, I'm not somebody who's going to golf, I'm not someone who's going to go to a sports game, I'm going to meet you in the board room, and we're going to talk about compelling topics there. And so I think it's about, encouraging and fostering a new way of networking that's more aligned with what women are interested in, and what, you know, sometimes we do best and, I think creating an opportunity for a different type of everything, in the way that we operate is important. >> I think self-awareness, for men, and this also, creating a good vibe, right? Having a good vibe is critical, in my opinion, and also, you know, not judging people right, you know, based upon, you have some women say, hey I like to get dressed up and that's what I am, some people who don't want to go to sports and, some guys want this, so I think generally, there needs to be, kind of a reset, like hey, let's just have an open mind and a good vibe. >> It's like lunch and learns, you know, lunch and learns are, are a great enabler for centers of confidence, to get together on a regular basis, to talk about business and technical-related things, but also it's a social environment. How can you build more of those kinds of opportunities into the corporate culture, where, they're not skewing, the actual socializing, to traditionally male-dominated hobbies or interests, or traditionally female-dominated hobbies or interests? How can you have, sort of a balance, of those kinds of socialization opportunities in a professionally appropriate environment that also involve a fair amount of shop talk? 'cause that's what gets people bonding, promoted in their careers is that they do deep shop talk in the appropriate settings. >> Yeah, it's interesting, one of the women that I personally consider a mentor, she said if it wasn't for data, I wouldn't be where I am today. And she said, you know, I grew up in and industry where, unfortunately, I really didn't have a voice at the table, and my voice at the table came from data, it came from my ability to see connections, patterns, and detect things, and also for my ability to create networks of people, and make connections and pull things together in a way that my colleagues weren't doing. And, you know, when she tells that story I think that's, that's the template, right? >> John: That's the empowerment. >> We want to say, use everything at your bevy to bring the best value to your business end-users, and she's connecting the dots in a way that no one else had, and is using data as really, the impetis to really, solidify everything that she's saying, it's inarguable. >> That's a great story, it's a phenomenal story. >> It's just amazing. >> Once she got into power she really drove that hard, that's awesome. Well, let's take that to the next level, so, you know, I have a daughter as a junior at UCAL Berkeley, and she's a STEM girl, and so she's got a good vibe in there >> James: STEM girl, I have a stem girl too, mines 28 now. >> You know, and so, kind of aside, but she, turned away from computer science because, at, you know, in middle school the vibe wasn't there, right? And it was kind of a social thing, we mentioned social. You're advice to young women now? Because we're seeing people with the democratization, you see YouTube, you see all these tools, you got robots, you got makers, of course, you got data, you've seen a lot more touch points where people can, you know, ingratiate in unthreatened, un, you know, just, getting immersed in tech. So you have, you're starting to get people the taste of not being tracked into it. So, what's the advice for young folks trying to navigate? And is it networking groups, is it mentoring? What's the playbook in your mind? >> Yeah, I think it's a combination of everything that you've mentioned, right? I absolutely think that your network, and what one of my mentors calls your sleeper network, right? The network that's out there, the people that I worked with five years ago, and we worked, and were in a war room til two a.m. and you know, then I, I just got busy, right? And reactivating your sleeper networks, you know, having the courage to kind of, keep people apprised, using social media, in a way that people, you know, the number of people that say, oh I didn't know you were up to this, that, or the other, thank goodness you posted. And so, I think using all of the technology to your advantage. And I also think there's a component of someone, I mean, I had an MIS degree for undergrad, and I started out as a developer. >> You might have to explain what this is for the younger generation. (laughing) >> Oh, I know, how crazy is that! Oh my gosh, >> Is that in the DP department, was that in the DP department? >> Can you imagine. But I wasn't interested in technology that much, it was what was going to get me a job and, and I thought I would become a business analyst, I've stayed with it, and now really passionate about tech, but, I think there's a component of all this that, every job, you know, the CHROs, the CAOs, all of the roles that roll up, you know, every finance person I know that's exceptional, is phenomenal with data! Right? And so, I think, not only creating a network of people that are in the industry, but I think it's about telling the stories outside the industry, and telling the oh my gosh, you'll never believed what we learned today. And I think that's the magic of the stories, and being transparent. >> Well Tracy, you're an inspiration, thanks so much for coming on theCUBE, really love the story. I got to ask, what are you up to now? Tell us what's up with you, obviously you've moved on from MIS, Management Information Systems, part of the DP, Data Processing department, that's many computer days. >> Tracy: Oh my. >> Oh my God, we're goin' throwback there. >> Tracy: Absolutely. >> What're you up to now? What are you havin' fun with? >> Yeah, so my day job, I have the luxury of working across our cognitive analytic, and our PA alliances, which is an insane mouthful, but it means I get to work with some of our most exciting alliance partners that Deloitte is building solutions, and going to market, and getting really great customer stories under our belt. And I think really kind of blowing the doors off of, of what we did three years ago, five years ago, and 20 years ago, when MIS degrees were still being handed out, so. >> A lot more exciting now, isn't it. >> (laughing) It's way better now! So. >> I wish I was 23 again, you know, havin' a good time. (Tracy laughing) >> Yeah, so, really wholistically, seeing what we consider ecosystems and alliances, is, that's my day job. >> Tracy Ring, Vice President at Deloitte, great story, fun to have on theCUBE, also doing some great work, super exciting time, you got cloud, you got data, it really is probably one of the most creative times in the tech industry, it's super fun to get involved. This is theCUBE, here out in the open, at Informatica World in Las Vegas. I'm John Furrier with Jim Kobielus, be back with more, stay with us! From Vegas, we'll be right back. >> Tracy: Thank you. (bubbly music)

>> Announcer: Live, from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hello everyone welcome back, this is theCUBE's exclusive coverage at Informatica World 2018 here live, in Las Vegas at The Venetian Ballroom. I'm John Furrier, your host of theCUBE, with Peter Burris, my co-host this week, Analyist at Wikibon, Chief Analyst at SiliconANGLE and theCUBE. Our next guest is Sanjeev Vohra, Group Technology Officer at Accenture, in charge of incubating new businesses, growing new businesses, handling the talent. Great to have you on thanks for spending the time coming on. >> Pleasure, it's my pleasure to be here. >> So we have a lot of Accenture interviews, go to thecube.net, type in Accenture, you'll see all the experts. And one of the things we love about talking with Accenture, is you guys are in the front lines of all the action. You have all the customer deployments, global system integrator, but you've got to be on top of the new technology, you've got really smart people, so thanks for spending the time. So I got to ask you, looking at the landscape, of the timing of Informatica's opportunity, you've got data, which is not a surprise for some people, but you've got GDPR happening on, this Friday, you've got cloud scale on the horizon, a lot of interesting things are going on right now around data and the impact of customers, which is now pretty much front and center. What're you guys doing with Informatica, what are some of the things that you guys are engaging with them on, and what's important to you? >> We have a very deep relationship with Informatica for many years and, we have many, many, joint clients in the market, and we are helping them sustain their businesses, and also grow their businesses future. Right? In future. And I think, I think there's a lot going on, there's a lot going on sustaining the core of the business, and improving it on a continuous basis, by using new technologies, and, you know, like today's keynote went on a little, talked about the new stuff and it's, there's a lot of things, actually, clients require, or our customers require for, just sustaining their core. But then I caught something in the middle, which is basically: how are you building your new business models, how are you disrupting the market your industry, what's new around that? And, in that piece, I think that's where, we are now starting working with Informatica to see what other pieces we need to bring together to the market, so we can generate, so we can help clients or customers to really leverage the power of technology. And I'll tell you, there are four areas of discussion priorities, that are, you know, you get a sense, and we get a deep dive depending on what you want to see. The first one is, I think the customers now have data warehouses, which are Data 2.0, as is what's told in the morning, so these are still 15 years old data warehouses, they are not in the new. So a lot of customers, and a lot of organizations, large organizations, including some organizations like ours, they're investing right now to make sure that they get to Data 3.0, which is what Anil was saying in the morning, which is around the new data supply chain, because without that, you cannot actually get real data analytics. Right? So you can't generate insight on analytics unless you actually work on your data's infrastructure layer below, so that's one area where we are working with them, that's where the cloud comes in, that's where the flexibility of cloud comes in. The second piece is around, around data compliance and governance because, guess what, there're regulations which are coming up now, which are towards data privacy and data protection. And the data infrastructures which were built 15 years back, actually do not handle that so effectively. >> In being polite, yeah. I mean, it wasn't built for it, they didn't have to think about it. >> Sanjeev: It was not built for that, exactly. So now, now, the point there is that, now there is a regulation coming in, one of them is GDPR, Global Data Protection Regulation, it impacts all the global companies who deal with your EU residents. And now they are looking at how they can address that regulation, and be compliant with that regulation. And we believe that's a great opportunity for them to actually invest. And see how, not only comply with regulation, but actually make this a benefit for them. And make the next leap towards building a next level of infrastructure for them, their data, right? >> And that is doing a lot of the data engineering, actually getting data right. >> And that's the third piece. So the first two are this: one is infrastructure, second is compliance, and the third reason, they're all interrelated finally, but I'm just saying, it depends on, from where do you want to begin your journey, right? And the third piece is around, I think you got it right, is about quality of data, but actually it is not quality, we call it data voracity, it's much beyond quality. We talk about more completeness, and also things like provenance, integrity, and security along with it, so if we, and it's very much business contextual element, because what's happening is, you may have heard the story is that, clients have invested in data lakes, for years now, it's been there for like, eight, nine years, data lake concepts, and everybody talks about it-- >> John: Throw everything into the lake. >> And everybody says throw everything into the lake, and then they become a data swamp. (John laughing) - That was last years theme. >> That was last years theme, and the reason is because, because it's not IT's failure, IT is actually pretty advanced, the technology is very advanced. If the business is not as involved as it should be, and is not able to trust the data, and that's where your point comes in, whether you have the right data, and trusted data with you. >> Though, well we had Toyota on earlier and they said, one of the customers said, we had this 2008 post crisis thing and then, they had all this stuff channeled, they had product in channel, and they had the data! They actually had the data, they didn't have access to it! So again, this is like the new data center, data first, get it right, and so with GDPR we're seeing people saying okay, we've got to get this right. So that's, investing engineering involved, governance, application integration, this is all, now, a new thing. How do you guys advise you clients? 'Cause this is super important and you guys are, again, on the front edge. As a CTO group, you got to look at the new tech and say, okay, that's baked, that's not baked, that's new, that's old, throw a container around it, you know. (laughing) How are you sorting through the tools, the platforms? 'Cause there's a lot of, there's a lot of stuff out there. >> Oh yes, absolutely, and there's a lot of stuff, and there's a lot of unproven things as well, in the market. So, the first and foremost thing is that, we should understand what the context in the market right now is. The first question is, mine is, is everybody ready for GDPR? The answer is no. (John laughs) Are they, have they started into the journey, have they started getting on the racetrack, right, on the road? >> Yes? Yeah? It depends on a majority of that organization, some people have just started building a small strategy around GDPR, some people have actually started doing assessments to understand how complex is this beast, and regulation, and some people have just moved further in the journey of doing assessment, but they're now putting up changes in their infrastructure to handle remediation, right? Things like, for example, consent management, thinks about things like dilation, like, it's going to be a very big deal to do, right? And so they are making advantageous changes to the infrastructure that they have, or the IT systems to manage it effectively. But I don't think there's any company which properly can claim that have got it right fully, from end-to-end, right? So I think that's happening. Now, how are we addressing? I think the first and foremost thing, first of all we need to assess the majority of the customers, or the organization. Like BHD, because we talk to them first and understand, we understand, right? Usually we have various ways of doing it, we can have a chit-chat, and meet the person responsible in that company, it could be a Chief Data Officer of a company, it could be a CIO of a company, it could Chief Operating Officer of a company, it could be a CSO of a company, depending on who has a baton in the sea of suites, to kind of handle this problem. >> So it's different per company, right, so every company has their own hierarchy or need, or entry point? >> Data companies have different entry points, but we are seeing more of the CSOs and CIOs playing a role in many of the large organizations, and our, you know our clientele is very large companies, as you know. But we see most of these players playing that role, and asking for help, and asking for having a meeting, and starting with that. In some cases, they have not invested initially, we talked to them, we assess them very quickly, very easy, quick as it's in, you know, probably in a couple of days or day, and tell them that, let's get into a, what we call is, assessment as step one, and that takes four to six weeks, or eight weeks, depending on the size of their application suite, and the organization. And we do it quite fast, I mean initially, we were also learning. If you were to have asked me this question 12 months back, we had an approach. We've changed that approach and evolved that approach now. We invested hugely in that approach itself, by using a lot of machine learning to do assessment itself. So we have now a concept called data discovery, another concept called knowledge graph. >> And that's software driven, both with, it's all machine learning or? >> Sanjeev: It's largely computer driven. But obviously human and computer work together, but it's not only human. A traditional approach would happen to do only with humans. >> John: Yeah, and that've been takin' a long time. >> And that has changed, that has changed with the new era, and technology advancement, that even for, things which are like assessment, could now be done by machines as well, machines are smart enough to do that work, so we are using that right now. But that's a step one, and after that, once we get there, we build a roadmap for them, we ensure that they're stakeholders are agreeing with the roadmap, they actually embrace the roadmap! (laughing) And once that's done, then we talk about remediation to their systems. >> So, you mention voracity, one of the, and you also mentioned, for example, the idea of the, because of GDPR, deletion, which is in itself a voracity thing, so you, it's also having a verifiable actions on data. So, the challenge that you face, I think, when you talk to large customers, John mentioned Toyota, is, the data's there, but sometimes it's not organized for new classes of problems, so, and that's an executive issue 'cause, a lot of executives don't think in terms of new problem, new data, new organization. You guys are speaking to the top executives, CSOs, CIOs often but, how are you encouraging your clients, your customers, to think differently, so that they become data-first? Which is, kind of a predicate for digital business transformation anyway. >> So I think it's a great question. I think it depends again on, who you're talking to in the organization. I have a very strong perspective, my personal view is that data is an intersection of business and technology, it is not a technology, it's not a business, right? It's an intersection of both, especially this topic, it has to be done in collaboration within business and technology. Very closely in terms of how, what is the, how you can drive metadata out of your data, how can you drive advantage out of your data? And, having said that, I think the important thing to note down is that: for every, when you talk about data voracity, the single comment I will make that it is very, very, very contextual to business. Data voracity is very, very contextual to the business that you're running. >> Well, but problems, right? Because, for example, going to Toyota, so, when the Toyota gentleman came on, and this is really important, >> Absolutely. >> the manufacturing people are doing a great job of using data, lean is very data-driven. The marketing people were doing a great job of using data, the sales people were making a great job of using data, the problem was, the problems that Toyota faced in 2008, when the credit crunch hit, were not limited. They were not manufacturing problems, or marketing problems, or sales problems, they were a wholistic set of problems. And he discovered, Toyota discovered, they needed to say, what's the problem, recast the problem, and what can we do to get the data necessary to answer some of these crucial questions that we have? >> So, I think you hit the nail, I can tell, I mean, I think you're spot on, and the one way we are doing right now, addressing that is through, what we call our liquid studios, >> John: I'm just going to-- >> Peter: I'm sorry what? >> Liquid studios. >> Peter: Liquid studios. >> We have this concept called liquid studios. >> John: Yeah, yeah. >> And actually, this concept we started, I don't know if you heard about this from Accenture before? we started this thing couple of years back-- >> John: Well take a minute to explain that, that's important, explain liquid studios. >> Okay, so liquid studios, so what, when we were thinking about these things where, we talked to multiple clients, they called us, exactly the point, they may be working in silence, and they may be doing a great job in their department, or their function, but they are talking across enterprise. As to how they can, if you are doing great work, can I use your work for my advantage, and vice versa, right, because it's all sharing data, even inside enterprise, forget outside enterprise, and you will be amazed to know how much sharing happens today, within enterprise, right? And you're smiling, right, so? So what we did was, we came to this concept, and the technologies are very new and very advanced, and many of the technologies we are not using beyond experimentation, we are still in the COE concept, well that's different than enterprise ready deployment. Like, if we talk about ERP today, that's not a COE, that's an enterprise ready deployment, in most of the companies, it's all there, like, you run your finance on ERPs right, most of the companies, big companies. So we felt that, technology's advancing, the business and technology IOs, they all have to still agree on a concept, and define a problem together. And that's where the studio comes in, so what we do is, it's actually a central facility, very innovative and creative space, it's unlike an office, it's very much like, new, new thing, it's like very, differently organized structure to generate creativity and good discussion. And we bring in core customers there, we have a workshop with them, we talk about the problem for one or two days, we use design thinking for that, a very effective way. Because one thing we've learned, the one thing that brings our table to agreement on a problem. (laughing) (John and Peter laugh) In a very nice manner, without confronting, in a very subtle manner. So we, through this timeframe, we get to a good problem situation, a good problem definition and then, the studio can actually help you do the POC itself. Because many times people say, well I understand the problem, I think I kind of get your solution, or what your proposing, my people also tell me something else, they have a different option to propose. Can we do it together? Can I get the confidence that, I don't want to go in enterprise ready deployment and put my money, unless I see some proof of pudding, but proof of pudding is not a power point. It's the actual working mark. >> Peter: It's not?! >> It's not! (all laughing) and that's where the studio comes in picture because, you wouldn't believe that we do these two days of workshop without any Powerpoint, like we aren't on a single slide. >> So it's creative, it's very agile, very? >> It's more white boarding, come and talk, it's more visitation, more visitation now, more human interaction, and that's where you open up everybody saying: what is your view, what is your view? We use a lot of post-it stickies to kind of get the-- >> I think the business angle's super important, I want to get your thoughts. 'Cause there's a lot of problems that can be solved once you identify them. But we're hearing terms like competitive advantage, 'cause when you solve some of these problems, these wholistic problems, that have a lot of interplay, where data's shared, or where there's internal, and or external with APIs and cloud-native, you start thinking about competitive advantages, being the data-first company, we've heard these terms. What does that mean to you guys? When you walk into an executive briefing, and they say look, you know, we've done all this work, we've done this engineering, here's where we're at, we need help, but ultimately we want to drive top-line results, be more competitive, really kind of move with the shift. This is a, this is more of a business discussion, what do you guys talk about when you have those conversations? >> I think we, so first of all, data was always a technical topic, do you agree? Like if you just go back, 10 years back, data was always a CIO discussion. >> Well, >> Unless you're in a regulated industry like financial services or, >> Or I guess I'd say this, that the, that the notion of getting data out of a system, or getting data into a system, was a technical discussion. But there was, you know, we've always used data, from market share growth, etc. But that was relatively simple, straight-forward data, and what you're talking about, I think, is, getting into considerably greater detail about how the business is really operating, how the business is really working. Am I right? >> You're right, considering data as an asset, in a discussion in terms of, how can you leverage it effectively, that's what I was saying and, so it is, it's definitely gone up one more level upstaged or into the discussion that is, into the companies and organizations. And what we're saying is, that's where the business comes in effectively and say that, helping them understand, and by the way, the reason I was making that comment is because, if you have ever seen people expending data 10 years back, it is very complex explanation. >> Schemas, this, that, and the other thing. >> You got it, yeah. And it's very hard for a business guy to understand that, like if I'm a supply action lead, I don't get it, it's too complex for me. So what we did, I'm just letting you know how we started the discussion. The first and foremost thing is, we tell them, we're going to solve the business problem, to your point, that's what we think, right? And, every company now-a-days, they want to lead in their industry, and the leadership position is to be more intelligent. >> Yeah, and it's got to hit the mark, I mean, we had Graeme Thompson on, who's the CIO, here at Informatica, and he was saying that if you go to a CFO and ask them hey where's the money, they'll go oh, it's over here, they get your stuff, they know where it's stored, at risk management, they say, where's they data? You mentioned asset, this is now becoming a conversation, where it's like, certainly GDPR is one shot across the bow that people are standing up, taking notice, it's happening now. This data as a asset is a very interesting concept. When I'm a customer of yours, say, and I say hey Sanjeer, I have a need, I got to move my organization to be data-first but, I got to do some more work. What's my journey? I know it's different per customer, depending on whether it's top-down, or bottom-up, we see that a lot but. How do you guys take them through the journey? Is it the workshop, as you mentioned, the assessment, take us through the journey of how you help customers, because I'm sure a lot of them are sittin' out there goin' now, they're going to be exposed with GDPR, saying wow, were we really setup for this? >> Yeah, so I think in the journey, it's a very good question that you asked. The journey can start depending on the real, the biggest pain they have, and the pains could be different on the majority of that particular organization, right? But I can tell you what client position we are having, in a very simplified manner, so that you understand the journey, but yes, when we engage with them, there's a process we follow, we have a discovery process, we have a studio process, together have a workshop, get into a POC, get into a large-scale deployment solution en route. That's a simple thing, that's more sequential in nature, but the condition is around four areas. The first and foremost area is, many companies actually don't have any particular data strategy. They have a very well articulated IT strategy, and when you go to a section of IT strategy, there's a data component in that, but that's all technology. About how do you load, how do you extract those things. It talks about data architectures, and talks about data integration, but it doesn't talk about data as a business, right? That's where it's not there, right? In some companies they do have, to your point, yes, some companies were always there in data, because of regulatory concerns and requirements, so they always had a data organization, a function, which thought of data as different from other industries. And those industries have more better strategy documents or, or they're more organized in that space. But, guess what, now companies are actually investing. They're actually asking for doing help in data strategies, that's one entry point which happens, which means, hey, I understand this, I understand governance is required, I understand privacy's required, and I understand this is required, I also understand that I need to move to new infrastructure, but I can't just make an investment in one or two areas, can you help my build my strategy and road map as to what should be my journey from now til next three years, right, how does it look like? How much money is required, how much investment is required, how do I save from something and invest here, help me save internal wealth, right? That's a new concept. Right, because I don't have so much that you're asking for, so help me gain some savings somewhere else. That's where cloud comes in. (laughs) So, that's one entry point, the second entry point is totally on, where the customers are very clear, they actually have thought through the process, in terms of where they want to go, they actually are asking, very specifically saying, I do have a problem in our infrastructure, help me move to cloud. Help me, that's a big decision right, help me move to cloud, right? But that's one, which I call is, new data supply chain, that's my language. Which means that-- >> John: I like that word actually. >> Yeah? I'm making your supply chain and my supply chain in business terms, if I have to explain business, it's different, technically it's different. Technology, I can explain all the things that you just mentioned, in business I explain that there are three Cs to a supply chain, capture it, curate it, consume it, and they so, oh I get it now, that's easy! >> Well, the data supply chain is interesting too, when you think about new data coming in, the system has to be reactive and handle new data, so you have to have this catalog thing. And that was something that we saw a lot of buzz here at the show, this enterprise catalog. What's your take on that, what's your assessment of the catalog, impact to customers, purpose at this point in time? >> I think it's very important, especially with the customers and large companies, who actually have data all over the place. I can share, as an example, we were talking to one of the customers who had 2600 applications, and they want to go for GDPR, we had a chat with them, and we said look, they were more comfortable saying, no, no, let's no use any machine. Because when you talk about machine, then you have to expose yourself a bit, right? And I said look, the machine is not going to be in my place, it's going to be in yours, your boundaries of firewall. But they were a little more concerned, they said let's go with a manual approach, let's do that, I said fair enough, it's your call, we can do that as well. But guess what? 2600 applications, you can't discover manually, it's just not possible. >> John: Yeah, you need help. A lot of data streaming and-- >> I guess I'm just letting you know it's very, I'm just answering your question. The data catalog is extremely important, if you really want to get a sense of where the data is residing, because data is not in one or two applications, it's all over the place. >> Well I'm impressed by the data catalog positioning, but then also, when you look at the Azure announcement they had, that Informatica had. You're essentially seeing hybrid cloud playing out as a real product. So that's an easy migration, of bringing in some of those BI tools, bringing some democratization into the data discovery. Rajeev, thanks for coming on theCUBE, really appreciate it, love the work you do, and I just want you to take a minute, just to end the segment out. Explain the work that you do, you have two roles, real quick, explain your two primary roles. You've got the, you incubate new stuff, which is hard to do, but, I'm an entrepreneur, I love the hard problems, but also you're doing talent. Take a minute to kind of explain, real quickly, those two roles, for, super important. >> well, the first one is basically that I, my role, I look at any ideas that are, that we can incubate as a business, and we can work within Accenture, different entities within Accenture to make sure that we go to clients in a much more quiescent manner, and see how we can have an impact to our top line. And that's a big thing, because our, we are a service as a business and, we have to be very innovative to come to know how do we increase our business. >> Any examples that you can share, of that stuff that you worked on? >> So, one is, right now, I'm spending a lot of my time in, on fueling our data business itself. We just recently launched our data business group, right? We have our market way in this position, is called applied intendance, which you may be aware, which includes data, analytics, advanced analytics, and then artificial intelligence, all put together, then we can solve these problems. >> And you guys got a zillion data scientists, I know that, you guys have been hiring really, really strong people. >> It's a very strong team. But on that, what I feel is that, the data is a critical foundation, really critical foundation for an intelligent enterprise. You can become and intelligent enterprise unless you have right data, to your point. And right data means curated data, in the set, in the fashion that can help you become, draw more insights from your enterprise. And that's possible if you invest in data strongly, and selection of data so strongly, but that's why we are fueling that, so I'm just letting you know that I'm spending most of my time right now to enhance our capability, you know, enhance our power in on that, and go to market with that. The second thing which I am investing right now, which is, there is a few more ideas, but one more, which could be very useful for you to know, is, while companies are moving to the new, they have to also, they have to rely on their people. Ultimately the companies are made of people. Like us, right? And if you can, if you are not retooling yourself, you cannot reimagine the future of your organization as well. >> You're talking about the peoples, their own skills, their job functions, okay-- >> So I'm working on a concept called workforce of the future right, how can 44 companies, large companies, how can they transform their talent, and their, even leadership as well, so that they are ready for the future and they can be more relevant. >> Yeah, and this is the argument we always see on theCUBE, oh, automation's going to take jobs away, well, I mean certainly automating repetitive tasks, no one wants to do those, (laughing) but the value is going to shift, that's where the opportunities are, is that how you see that future workforce? >> Absolutely, it's one of the complimentary, we have Paul Daugherty, whom you know, who's the Chief Technology Officer of Accenture Technology. Accenture, Accenture as a firm, he, he's a Chief Technology and Innovation Officer for Accenture He has recently written a book called Human + Machine, exactly talked about the same concept that, we actually all believe, very, very strongly that, the future is all about augmenting humans together. So there are tasks which machines should be doing, and there are tasks where humans should be doing, and there are tasks which both of them do collaboratively, and that's what we are trying to boast. >> Cloud world, we're doing it here in theCUBE, here at Informatica World. Rajeev, thanks so much for spending time-- >> Sajeev. (laughing) Sajeev, I mean, thanks for coming on. Sorry my bad, a little late in the day. But we're bringing it out here at Informatica World, this is theCUBE, I'm John Furrier with Peter Burris, here with Accenture inside theCUBE, here at Informatica World in Las Vegas. Be right back with more coverage, after this short break. Thank you. (bubbly music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Informatica World 2018. Brought to you by Informatica. >> Okay, welcome back, everyone. Live here in Las Vegas at the Venetian, this is Informatica World 2018, CUBE's exclusive coverage. It's our fourth year covering Informatica World, and boy, what a transition; it's been fun to watch. I'm John Furrier, the co-host of theCUBE, with Peter Burris, Head of Research for Wikibon, SiliconANGLE, and theCUBE. Our next guest is Sally Jenkins, Executive Vice President, Chief Marketing Officer at Informatica. Welcome back, good to see you. >> Thank you, John, it's nice to see you too. >> Very comfortable here, you guys having a great event, congratulations. It's crowded, but it doesn't feel crowded. A lot of sessions are going on. What's going on with the event? Give us some stats, you've got a lot of partners here. >> Yeah, so we are very happy to be back in Las Vegas, and we are taking this up a whole notch a bit, if you can notice. We've got close to 4,000 folks who saw the Opening General Session this morning. For the first time ever, we're live streaming, and sent out a note that we were live streaming to over 250,000 customers, so I'm real happy about that. Because, as you know, with the rebrand last year, it was all about getting our message out and upleveling our message, so we're really happy that our message is getting out there, with everything that came from General Session this morning, and then, tomorrow with Closing General Session. >> Just gets bigger every year, so congratulations. >> Thank you. >> Great to see that everything comes in. Of course, the products are just right in line. The timing couldn't have been better. Multi-cloud, everything's kind of clicking. GDPR over the top, little push there for all the international customers. But the big story that we see is the journeys that are happening. You guys have been on a journey as your own company, digital disruption, digital transformation. But there's multiple journeys. Can you just take us through the vision of how you guys see the journeys, and how does Informatica fit into the customers, 'cause your customers are also changing? >> Sally: Yes, that's right. >> Do you change your business model? Anil laid it out, customers have this journey. What's the four journies? >> Yes, that's a great question, John. So we have, of course, been customer-centric ourselves. We've adapted our journeys to accommodate the journeys that we know our customers are on. And this whole conference is centered around those four journeys, so hybrid cloud, next-gen analytics, 360 engagement, and data governance and compliance. So that's what we've heard our customers deal with day in and day out, in their data-centric initiatives, and so we wanted to encapsulate that into the entire conference. So that's what it's all about, and that's an extension of our messaging that we laid out last year. So you'll see that again and again and again in a consistent fashion. >> "Disrupt Intelligently", I saw the messaging. First of all, great artwork, great branding, a lot of the images; what does that mean? 'Cause you've got all kinds of great imagery, people on the move, mobile, data's involved, obviously, the center of it. >> Well, that and data is the critical foundation for what we call "Intelligent Disruptive". So disruption with a purpose is intelligent. And we believe, with our technology, that our customers can then unleash the power of their data to create what we call their next intelligent disruption. So we were very thoughtful about the choice of words there, 'cause disruption can be considered a negative, but we see it as very much a positive, and a way for customers to leapfrog the competition, and set the tone for their markets. >> This is an interesting concept. We were talking with a lot of the customers you've had on; we've had Toyota on, and they said, quote, these testimonials just kind of pop out, "We knew we had the data; we had all these problems "we hadn't connected, but we actually had the data "when they actually connected us, and said, "we could have foreseen this." >> Sally: That's right. >> So they were disrupted in a negative way, the fact that they were trying to connect, now they're set up. And then he used an example, once they got set up, that they didn't predict that all this inbound data from the cars were coming in. So again, that's a disruption, but now they've handled it. Is that kind of where you guys were kind of connecting the dots on the intelligent piece? >> Yeah, that's right, we're helping our customers understand what to do with the data, right? So they know the data exists, but we need to help them turn it into actionable insights that leads to their next disruption, and again and again and again with their different projects. And so those are the conversations that we've been having with our customers. Just helping them, we say, unleash the power of their data. The data's there, we need to make it useful and valuable to them. >> And competitive advantage, obviously, seeing data, ease of use as a competitive strategy. Now the Microsoft announcement was interesting, because you can see that you can take an on-prem dataset, go through the Azure portal in their console, which is very cloud-native, you know, press a few buttons, connect to Informatica's intelligent cloud service, and move data. >> Sally: That's right. >> I mean, it's not like there's someone behind the curtain; it's actually a working product. >> No, it's real, it's real and it's available for preview, and if you saw the keynote this morning, you heard from Scott Guthrie. He said this whole partnership between Informatica and Microsoft, and I quote, "A match made in heaven". So there's something real there. Microsoft and their customers see the value in partnering with us, so we were really pleased to announce that today. >> I'm going to check the Internet, but I think this might be the first iPaaS integration into Azure at this level. 'Cause it's pretty deep with these guys. So that's going to certainly set up hybrid cloud instantly. >> That's right, that's right. And scale, right, we're enterprise-scale to begin with, obviously, so is Microsoft. So it's a good partnership. >> Okay, from the branding piece, I got to ask you, you guys did the rebranding, what's your one-year review, if you have to give yourself a report card, check, check, check, straight As, perfect score? If you could go back and do- >> Well, I'd like to say that we were in the honor roll. And we measure ourselves based on what our customers tell us, so we were very deliberate in choosing a few areas of which we wanted to see progress, and that is, the first one is, were people aware that we're a cloud company? And I'm delighted to say that, yes, we've absolutely moved the needle on that, so they associate Informatica with cloud, as you know, we're the number one in enterprise cloud data management. That's what we kicked off last year. And so you'll see a continued investment around the globe in the brand. We believe that good brand health is what leaders do, in terms of setting the pace for their industry. And that's exactly what we're doing. So, one year into it, we feel really good. We did what we set out, and we delivered on what we said we were going to do. And if you all remember last year's part of the rebrand, as soon as we went external, then we needed to shift our focus back internally, and think about what does this mean to our employees, and how do we leverage the culture that we already had inside Informatica and build upon that? And that's exactly what we've been working on. So we rolled out a new set of values in January. To no surprise, they're called We-DATA. And DATA stands for Do Good, Act as One Team, Think Customer First, and Aspire for the Future. And so that's what we're doing right now, is rolling that out around the world to our employees. And that was based on employee feedback, as well. >> That's bottoms up, that's good organic listening. I got to talk about branding, 'cause this is something that we're seeing a lot of. We're seeing a lot of shifts going on. When you have these shifts you mentioned earlier, about getting a competitive advantage, a leg up on the competition, you guys had that same opportunity. Because the brand, pecking order of companies is going to change with these new waves coming. With data, certainly, so it's a huge opportunity. Do you guys talk about that when you're in the brand meetings, and you're talking about with the execs, the power of the brand, and building the brand? >> Sally: Absolutely. >> And what are some of the things you're focused on to help continue to build that brand? >> Well, I think where you're going with this is what's the financial impact or value that the brand has? And everybody, from our industry analysts, to the financial analysts, to our customers, partners, they put a value on the brand. So if you don't define who you are in the market, then you let everybody else define you, and then there's no value in that. So that's really what we set out to do last year, is we wanted to define who we were, and be proud of it, and take ownership of it. >> Put a stake in the ground. >> Yeah, and then continue to invest in that. So when I say we'll continue to invest in the brand, that is about our messaging, and making sure that we are very clear as to who we are, as I said, 'cause we're setting the pace for this industry. >> And the brand promise real quick, just to summarize, if you had to kind of sum up the bumper sticker for Informatica, Disrupt Intelligently, kind of add to that, what would be the brand promise to your customers? >> Yeah, so it's the Disruptive Power of Data. And then what falls out of that is Unleashing the Power of Data, right? So that's our brand promise to our customers, is that's what we were talking about earlier, that's exactly what we do for them with our technology, and how can we help them stay ahead of their competition? >> That's great, look at the trends too. Look at what GDPR's doing, and some of the block chain stuff that's kind of emerging, it's power to the people. People want to have control of the data. >> Sally: That's right, putting the control back in their hands. >> Great stuff, so thanks for coming on theCUBE. Appreciate it, great to see you, congratulations. >> Thanks, John. >> And great to have our fourth year, our fifth year with Anil, we saw him at Amazon re:Invent in 2014, so great to continue to watch you guys grow. It's been fun to watch. >> Great, good, well stay tuned, there's more to come for sure. >> Right, can't wait to hear. It's theCUBE live here at Informatica World, two days of coverage here. We're getting down to the second day. We've got more action coming; stay here with us. I'm John Furrier, Peter Buriss, we'll be back after this short break.

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

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hello, everyone, welcome back. This is theCUBE's exclusive coverage of Informatica World 2018. It's our fourth year covering Informatica on the front lines. Every year it gets bigger and bigger. I'm John Furrier, the host of theCUBE, with Peter Burris, my co-host, with some, chief analyst at Wikibon and SiliconANGLE on theCUBE. Our next guest is theCUBE alumni Amit Walia, who's been on many times, even before he was president. Now he's the president of products and strategic ecosystems for Informatica. Great to see you, great to have you on. Congratulations on your keynote. Thanks for stopping by. >> Thanks, John, glad to be here. Always good to be back. >> You're super, well, I love talking with you because one, you know, the business is growing. You've been in the product side, you guys are all great product folks. And this, they're shipping products. It's not like it's, like, vaporware. It's, like, great stuff. Now Azure deal was announced. But now the timing of the data play with Switzerland, we talked about this fabric, better time than ever. This year, you got data lakes turned into data swamps last year. This year it's about governance and catalog. Good timing. What's your assessment? Give us your point of view from the keynote, timing, product. >> Well, I mean, I think you're exactly right. We see that it's a unique time, and it was building over the last couple of years. So, you know, we have this phrase that this is a data 3.0 world where data has become its own thing. It's no more captive to an application or a database. Those days are gone. And I think in data 3.0 world, I think we talked about it this morning in my keynote, that, you know, customers have to step back and think differently. You can't just do the same old things and expect to be different, and especially as they're driving digital transformations. So we introduced this concept of system thinking 3.0, where as you're thinking about a data, you have to think about it as a platform. A nimble platform, not a ERP-ish platform. Think of it at scale. It's doubling every year. >> Yeah. >> Think of it metadata in, metadata out. Let AI assist you. You know, you've got to have, we as humans are just going to be swamped with so much data we can't process it. And last, very important thesis, as you all know, is that governance, security, and privacy have to be design principles. They cannot be an afterthought. >> Last year you announced CLAIRE AI component of the system. >> Amit: Yeah. >> How has that evolved this year? I mean, I know it was a strategic centerpiece for you guys. Obviously the catalog is looking really strong right now, a lot of buzzing to show around the enterprise catalog. Where is the AI, the CLAIRE piece fitting in? Can you just give us the update on CLAIRE? >> Well, CLAIRE's come a long way. Basically part of every product we have. So it manifests itself probably most holistically in the catalog, but whether in the data lake, it's in the context of surfacing data, discovering data, giving recommendations of data to an analyst in a very business user context, all in the context of an MBM, giving you relationship discovery of, let's say, John, who you are, into who you are. So it is in Secure@Source helping anomaly detection happen. So CLAIRE has now made its way into every product. But as you said, the one product where it basically surfaces itself in its full bloom is the catalog, which, by the way, has been the fastest growing product in Informatica's history. One year since launch, it has just gone, taken off. >> Well, presumably there's a relationship. Sorry, John. Presumably there's relationship there. Catalogs have been around for years, but they've been very, very difficult to build and sustain and maintain. CLAIRE presumably is providing a capability that removes a lot of the drudgery associated with catalogs, and that's one of the things that's making it possible. Have I got that right? >> No, yeah, absolutely. And actually, building the new catalog also has been a hard thing. So in some ways building it for scale has been a massive common sense problem that we've been solving for the last three, four years. You know, collecting metadata across the full enterprise is a non-trivial activity, so it was never done across the enterprise ever. If you remember when I was here last time, our vision for the catalog was very simple. We want to be the Google for enterprise data... >> Peter: Yeah. >> ...through metadata. >> And that's what we were able to do through the catalog. But as you rightfully said, it's very hard to consume it if you don't write AI to help it. That's where CLAIRE made a very big road. So the UI's very straightforward. It's a Google UI, and any business user can, with the help of CLAIRE, start using it. >> But it persists. >> Yes. >> So unlike just putting a search term in and getting a page of stuff back, a catalog has to persist. >> Has a persistence, exactly. >> And so describe, now that you have that in place with CLAIRE, as John asked, where does it go? >> Solving use cases. Actually, I'll give you a little preview. Tomorrow I do the closing keynote, and usually what I do, the closing keynote is all about features. So actually, it's a whole demo on CLAIRE where we're taking CLAIRE to the whole next level. As a great example, you know, building data supply chains, you know, it's a manual activity that you have to do. With the help of the catalog, we actually understand the system architecture. So if you want to add new sources of data or change anything you want to do, you don't have to go through those steps again. We will service it to you and we'll tell you what to do. In fact, tomorrow I'll show what we call a self-integrating system. It'll happen by itself. You have to just go and say whether I agree or not agree and the machine learns. Next time it gets smarter and smarter. Or in the context of governance. If a new policy comes up in an enterprise, the biggest challenge is how do I even know what the impact of the new policy is? Look at GDPR right now. So with the help of CLAIRE, we can understand across the entire enterprise what would be the impact of that policy across different functions and what the gaps are. Those are the kind of places we are taking CLAIRE towards more bigger business-driven initiatives. In fact, tomorrow there'll be a whole demo on that one. >> I mean, GDPR is interesting because it really exposes who's ready. >> Yeah. >> Who has had invested their, the engineering in data, understands the data. So that's clear. We're seeing some, and it's also a shot across the bow of companies saying, look, you got to think strategically around your data. We talk about this all the time with you guys, so it's not new to us, but it is new to the fact that some people are right now sitting there going, oh no, I need to do something. >> Amit: Yeah. >> How is Informatica going to help me if I have a GDPR awakening of, oh man, I got to do something. >> You know, GDPR... >> Do I just call you up and do the, roll in the catalog? Do I... >> That's a great place to begin, by the way. So GDPR, by the way, is a data problem. So GDPR is not necessarily a compliance/security problem, because you want to understand which data pass through boundaries, who's accessing it. It's a true data problem. So today, I mean, in fact, at Informatica World, we have customers like PayPal talking about their journey with us on GDPR. And so you begin with the catalog, and then we have three products that help in the GDPR journey, the catalog, Secure@Source, and the Data Governance Axon product. And again, each company's GDPR implications are slightly different, and companies, as I said, like MasterCard, like PayPal, that are using our products to run their GDPR activity right now, it's a... So we are seeing that going through the roof. And in fact, one of the big use cases for catalog has been in the context of governance and GDPR. >> I want to talk about the trends on, that are impacting you guys. Again, I was saying earlier that it's a tailwind for you guys. The timing's perfect. Multi-cloud, hybrid cloud. I'd say hybrid cloud's probably in its second year, maybe third year hype, but now multi-cloud is real. You have announced a Azure relationship. You guys have a growing ecosystem opportunity. >> Amit: Yeah. >> How are you guys looking at it? 'Cause it's really emergent. It's happening right now. How are you guys targeting the ecosystem, whether it's business development partnerships, joint product development go to market, and/or on the business side? What's the orientation, what's the posture? Are you guy taking a certain approach, expecting certain growth? What's the update on the ecosystem, the global partner landscape? >> You know, the way we think about ourselves is that we've been the Switzerland of data always. And customers, actually, I always say it's always customer-backed. >> John: Yeah. >> If you solve for the customer, everything goes good. Customers expect us to do that. And customers are going to be in a heterogeneous world. Nobody's going to ever pick one stack. You know, you all know, right, there are customers who are still, larger devices still running mainframe for some processing, and they are already using new platforms for IoT, so they have to somehow manage this entire transition, and there will be multi-cloud, cloud hybrid world. So they naturally expect us to be a Switzerland of data across the board, and that's our overall strategy. We will always be there for them. In that context, we work with, we have learned the art of working with their ecosystem. >> John: Yeah. >> So you saw Azure today, and we are very close partners of hundreds of customers. Amazon, hundreds of customers. Google's coming up. So those are common. So we, Adobe, tomorrow you'll have Adobe. >> John: So you're cool with all the cloud players. >> And, you know, I always look at it this way. If you solve for the customer, everybody will work with you, and I think we're doing meaningful work. So that's helping our strategy. But what we have done two very different things with that. We've gone deep in terms of product integration. I mean, you saw today. We are making it easy from a customer experience point of view to get these jobs done, right? If you are spinning up a data warehouse in the cloud, you don't want to repeat the mistakes of the last 20 years. So now it's five clicks, you should be good to go. >> John: Yeah. >> That's an area we've invested a lot to make sure that those experiences are a lot simpler and easier and very native. >> We had Bruce Chizen on earlier. He was implying that you guys have significant R&D, and he was trying to get me to get you the number. I think it was on Twitter. I think I'll ask Neal. I think he's out there already. But it's not so much the numbers. It's about the investment and the mindset you guys have for R&D. I know you had, went with a private equity company. >> Amit: Yes. >> We talked about that. >> You guy are growing. >> So this is a growth company. >> Amit: Yeah. >> You need R&D. >> Absolutely. >> What is the priority? How are you looking at that? How would you talk to the industry and customers about your R&D priorities? >> Well, I think we've been very blessed, and I think our investors, and I think Bruce, when we sit in a board meeting, you know, we always joke around. They have never skimped on investing in products. And I think that we've been, our belief is that we are the innovation leader in our markets. There is a massive opportunity in front of us to obviously capitalize on, and the only way you do it where you innovate, and innovate means we invest. And I tell you we've been very fortunate that the investment in products has continuously increased every year. I mean, this year, forget just the products and technologies. We made, John, double digit million dollar investments in building a brand-new hosting architecture across the world, in Americas, NMEI and APJ, and we benchmarked ourselves against the Amazons and the Azures of the world, not our competitors. So not just products, but taking the cloud infrastructure across the globe, most secure, most... >> So your own infrastructure. >> Absolutely. >> Well, I mean, we run our own stuff. >> Yeah. >> But we leverage both AWS and Azure in that context. But our goal is that we can be in the countries because data should not leave some of those countries. We comply to the biggest regulations. So we've made lots of investment, and hence we can also innovate and get into new product categories. I mean, you see we have a whole new cloud architecture out there. Catalog, security, these are all brand new markets that actually, some of them have all come out since we went private. Actually more innovation has come out of Informatica since we went private than in the three years previous to going private. >> So, you know, let's play a game. Let's say that the catalog, doing very well. Let's say that you, working with Microsoft, working with AWS, you're actually successful at establishing a standard... >> Amit: Yeah. >> ...for how we think about data catalogs in a hybrid, multi-cloud world. Combine that with R&D and products. If you have, in a data-first world, where the next generation of applications are going to be data-first, that catalog gives you an inside edge to an enormous number of new application forms. >> Amit: Yeah. >> How far does Informatica go? >> Well, that's a great question. I mean, I think, I generally believe that in some ways, we are barely scratching the opportunity in front of us. I mean, none of us have seen where this world will go. I mean, who would have imagined, think of all the trends that have happened. Look at the world of social, where it has brought us to bear. I generally think that, look, each company that I talk to, each customer I talk to, and I talk to hundreds of customers across the earth, they all want to become a tech company. They all want to be an Amazon or a Google. And they realize that they will not become an Amazon Google by replicating them. The best way they can become an Amazon Google is to figure out all of the data they have and start using it, right? >> Institutionalizing their work around their data. >> Exactly. So that's where the catalog becomes very handy. It's a great first step to begin that. And in that context, there are Fortune 5000, there's Fortune 10,000, there are mid-market customers. I think we have just literally scratched the surface of that. >> Do you envision catalog-driven applications... >> Amit: Oh, absolutely. >> ...that get into, with the Informatica brand on them? >> Oh, so we actually have, so a great point. We actually made the catalog rest API-driven. So there are customers who are building their applications on the catalog. In fact, I'll give you a preview of that tomorrow. I'll show a demo where Cognizant took our catalog, took CLAIRE within the catalog, used Microsoft's chatbot to create a complete third-party custom application called the Data Concierge, where you can go ask for data. So it's Microsoft chatbot, our CLAIRE engine, and a custom app written by... So the world where I see is that it will be, that is a central nervous system of the platform, and enough custom apps will be written in time. >> It's a real enabler. So I got to ask, and I know we got not a lot of time left, I mean, but I want to get thoughts on cloud native. >> Amit: Yeah. >> 'Cause you have, with containers, you don't have to kill the old to bring in the new. And what you guys are doing is with on-prem and some of the coolness, ease of use around getting the data kind of cataloged in with the metadata, you're enabling potentially developers. Where does this lead us with containers, microservices, service meshes, 'cause that's right around the corner. >> It's happening as we speak. I mean, so we rewrote the cloud platform as I just talked about. It's completely microservices-based, completely. We had to, we had a whole cloud platform. We basically said we're going to rewrite the whole thing. Microservices-based. And it's containerized. So the idea is that A, microservices give you agility, as we all very well know. We can innovate a lot faster. And with the help of containers, you can just rapidly scale, I mean, rapidly deploy. You can test. Dev becomes a whole lot easy. The, I mean, today's cycle is so short. Customers want to do things rapidly. So we are just really helping them be able to do that. >> So you see the data actually being an input into the development process... >> Oh, absolutely. >> ...via microservices and your service mesh. >> I mean, if you don't do that, you don't know what you're building. >> It's going to be a data-first world. My, going back to my point, I think there's an opportunity for you guys to then go to the marketplace with some thought leadership about what does it mean to build data-first applications. Historically we start with a process and we imagine what the data structure's going to look like, we put it in the database, and then there's all the plumbing about interaction and integration. You guys are saying get your data assets, get your data objects rendered inside the catalog and think about the new ways you can put them to work, and you think of your code... >> Amit: Yeah. >> ...as the mechanism by which that happens. >> Flips everything on its ear. >> Amit: Yeah. >> It's a data-first world, and a data-first approach to building applications seems like it's an appropriate next conversation. >> That, I agree with that, and that's a big opportunity, and obviously there's a task at hand to make sure we can help educate everyone to get there. And I think, you know, it'll take some time, but of course that's the, anything which is easy is not interesting. It's a hard problem that where you basically, you solve and you kind of make it a big industry. >> I mean, it's great to see you. We feel like we've been following the journey of the success of you guys. We've been talking, go back four years. >> Amit: Yeah. >> You can go back to thecube.net, look at the tape. You can see the conversations. You guys stayed on task. Great product team, very, you guys are kicking some butt out there. Congratulations. Final question for you. Put you on the spot. Biggest surprise this year for you. What's, obviously the catalog, you mentioned it's been taking off. What surprised you? Anything jump out in terms of successes, speed bumps in the road, architecture trends? What's the big surprise? >> You know, I think I'm actually very warmed up by seeing, I talked about the day zero. You know, it is a data-driven world where we see so many customers looking to come here. We've become the biggest data conference of the industry. In fact, we were reflecting, Informatica World has become the biggest accumulation of people who think data-first. And I think that has been more than any technology. To me, at the end of the day, look, as much technology will come and stay, I'm a big believer it's people that make the difference. >> John: Yeah. >> And I've been seeing all of those people here, seeing them make contributions, learn, and drive change has been my biggest, not only a positive surprise, but biggest, you know, gratification that I've seen at Informatica World. >> And the emphasis of not having such a big hype. I mean, getting excited about new technology is one thing, but the rubber's got to hit the road. You've got to have real performance, real software... >> Yeah. >> ...real results. >> 'Cause the pressure of scale fast, time to market... >> ...all that stuff. >> Right. >> Congratulations, great to see you. Amit Walia, president here at Informatica on products and strategic ecosystems. I'm sure he's going to continue to be busy over the next year when we see him certainly at our next theCUBE event. Amit, great to see you. I'm John Furrier, Peter Burris, live here at Informatica World 2018. It's the largest data-first conference on the planet We'll be right back with more after this short break. (musical sting)

(upbeat music) >> Announcer: Live, from Las Vegas, It's theCube! Covering Informatica World 2018, brought to you by Informatica. >> Welcome back everyone. It's theCube's live coverage of Informatica World 2018, here in Las Vegas. I'm John Furrier, your host and analyst, with Peter Burris, co-host and analyst at Wikibon and still going on theCube. Our next two guests is Gitesh Ghai, C Vice President, General Manager of Data Quality Security and Governance for Informatica, and Smail Haddad who is the Senior IT Director of Data Governance and Data Delivery Architecture at Toyota, company wide, Great to have you on Gitesh. Great to have you on Smail. So we were just talking before coming on camera, before we went on live about the massive role that you have at Toyota with data. You are looking at everything now. You're touching all the data. But it wasn't always like that. >> Smail: Yeah it wasn't always like that... >> Tell us about your journey and your role at Toyota. >> Yeah thank you. So Toyota, again, started business in North America. People know, maybe not, 65 years ago. And we started as a little dealership in North Hollywood. Bringing these Japanese cars. So we grew from that single dealership in North Hollywood to this big company we are today, with almost 25 plants around North America, Canada, US, and Mexico. And almost 2,600 dealerships across nationwide. So what that came with, it came with a big responsibility, in terms of understanding our customer base and trying to be more closer to what the customer needs. So our supply chains, where we produce the vehicles, it really was mostly a push supply chain, where we build a car and we push it to the customer to buy it. The model works very well, all the way to 2008. Where things change and we all understand what happened back in the financial meltdown and the crisis, that was a worldwide crisis. And that was a turning point for Toyota because we start seeing a shift in the demand. The customers becoming more savvy. Demanding for example, more electrical cars, less gas guzzlers vehicles and so on. The marketing department, which was a different company back then, understood that but the production companies, which was producing the vehicles, they didn't have that knowledge. So the journey to bring these two together became really critical after that 2008 crisis. Because what it forced us to do was the vehicles were being produced everyday, the dealers were not able to sell, and we were just stuck in vehicles around the lot. So why the digital disruption was so key for us, is the data was always there. Data always told us the truth. And that's what the facts are. Where we started looking at, back after that, is hey, if we look at the data and the data always predicted that the shift in the market will happen that way. And we should've have throttled down maybe, our production system better. Why we didn't do it that way? We were not looking at the data. Data was available. So what we undertook, under Toyota IS, we said, "Can we bring all this data across all these silos, "into one place?" So we build our big data solution, where the data is coming from various departments and various business lines. And it's being blended together and correlated. What that gives us is really that 360 view of our business, which we were missing. 'Cause we were looking at the business in silo, in pieces. And with that explosion of data, that we were gathering, obviously that brings a lot of questions about where this data, how good it is, if I'm going to make decisions on it, can I trust it? All that was a good takeaway into the business I'm in, which is the Data Governance. It's basically how can we govern this data that we are collecting on a daily basis today? And so my department is leading basically, the North American Governance and Quality across all the business line in North America. So as we are gathering these data points everyday, on a daily basis, even today we are gathering. What made it even, made it go even further in terms of volume, is we started capturing data coming from the cost, on a real time basis. So this is not just sales data where we capture the experience, the sales, and configuration of the vehicles on a daily basis... >> John: That's a lot of data coming in. >> A lot of it, a lot of it. So the volume exploded. With that, the responsibility to put a solution, where people can go quickly, find the right data. So basically, the time to data became so critical. How can we shorten that time to find the right data you want? And understand it, and trust it, and use it? >> John: So last... >> Sorry John, the Toyota story that you're telling us is especially interesting 'cause Toyota is legendary for empirical based management, lean manufacturing, so you have plants and marketing organizations, and sales organizations who, because of the Toyota way, have grown up on the role that data needs to play in their function. And what you're doing is you're saying, "That was great. "But we had to take it to a next level "and organize our data differently so we could look at it "across the entire company." >> Across the entire company. So absolutely, there are four, basically, goals that Toyota is trying to achieve today. One is understanding our customer in a more personalized way. Understand today's demand and hopefully predict tomorrow's demand. The second important pillar, empower our employees and our team members. By the way, Toyota, we call employees team members. And the third one is optimize our operations. And the fourth is transform our product. In order to achieve all these four goals, data is at the middle of all this. Why it's so important, we understand that today, in this day and age of digital disruption. And by the way, the automotive industry is being disrupted. Not our competition right now, Toyota, is no more the GM, and the Ford, the traditional automotive companies. But our new competition is all the technology companies, Google, Apple, Amazon. And you might have heard the news. Everyday, how they are disrupting these segments where you hear about autonomous driving cars and everybody's jumping on it. And behind all that, taking just the autonomous driving cars. The amount of data behind these so you can make the vehicle drive itself and take you from point a to point b in a safe manner and avoid all the road hazards. That needs a huge amount of data that's behind it, and fuels that. We're able to make huge stride. The new story of Data Governance at Toyota, is really, how we can enable that and not being just about compliance and risk management, which is kind of understood, that's part of the job. But we make that seamless. We wanted our business unit to focus more on the core business and goals, versus worrying about, "Am I in compliance, do I need to do this or that?" Try to seize the opportunities and put Toyota in a competitive way so they can compete with all these new disrupters like I said, Google, and the, the Apple of the world. Because what they have in common, those companies, >> John: They're data companies. >> Exactly. Data companies, technology. They understand how to use data. They understand how to analyze data. This is where traditional automotive companies like Toyota, and GM, and Ford, are basically bound to learn about that. >> But Waymo is not a car manufacturer, Uber is not a car manufacturer, they're companies that are providing a transportation service. And the only way that Toyota could provide a transportation service, is if you started organizing your data differently, in service to the idea of providing consumers a better, and businesses, with better transportation services. Whether you call it personal. I don't want to be the typical analyst that kind of goes off and starts renaming things. But that's fundamentally what you're trying to do. Is you're saying, "Our customers are mainly focused "on getting from point a to point b safely. "Let's make sure that we have products and services "that help them get there. "Perhaps through a lot of intermediaries along the way." But is that kind of how you're organizing things? >> Absolutely, so in order to achieve that goal. We wanted to bring the silos. Like I said, the data was always there but it was always built in silos, stored in silos. What we did in the next, last few years, we started breaking all the silos because we started looking at the data as an enterprise assets and no more as just a departmental assets or as a tool to get to a goal. It became the strategic assets for the company. And in order to achieve that, was to really break the silos. Bring it together so we can see across and understand how are business is operating. And hopefully, put the company in a competitive advantage to see the future coming to. >> It must be really frustrating to know that the data was there the whole time. And you're kind of kicking yourself. What did you do? I mean, you brought Informatica in. What's the Informatica connection, Gitesh? Get a word in, come on. With the Informatica connection, these guys. Are you the core supplier? Do you guys, the connective tissue between Toyota's groups? >> It's all about the data, right? It's all about the data. Informatica's role in all of this, it's a great story. Toyota's, Smail's story, is a great story. What Informatica brought to bear for Toyota, it's actually the promise of big data. The promise of big data is bringing together data that hasn't been analyzed together in a new context before. So breaking down these silos and bringing together the data. What's interesting is when you bring it together, you create a data lake. But there's a very big difference between a data lake and a data swamp. Which is why naturally, governance, quality, trustworthiness became a focus area of bringing all of this data together. >> Well last year, talking about data swamp and data lake as our core theme. This year governance and enterprise catalog is a bigger story because you guys easily could've been swamped out because of all this new data coming in, whether it's car telemetry or new data. 'Cause if you had set the table for your intercompany connective tissue, if you will, then you're like, "Oh, hey we're done, wait a minute." >> But Toyota was applying data to the work of manufacturing, to the work of marketing cars. And now you're trying to apply data to the work of providing better transportation. And the only way to think that through is to see how all this data can be reorganized and brought together. And at the same time, you can still, then turn that data around and still apply it for the work of manufacturing, the work of marketing, and the work of selling. >> Gitesh: Absolutely. >> Also I'd add, to be competitive in a new market, they are going to use their, leverage their assets. Not only data but their physical assets. To compete at a new level, a new playing field. >> Smail: Absolutely. >> With data at the center. >> And I think you said it earlier, you have to bring this data together in the lake. But you need an organized view of all the data that's out there, which starts with our data catalog. So the data catalog gives you a sense of what data do you want to bring in the lake and what data, frankly, is noise, doesn't matter? >> Whole 'nother level of operations, whole 'nother level of intelligence. Competitive advantage, competitive strategy. >> Peter: What a job. >> We're data geeks, geeking out here. Great story, I'd like to do a follow up. I think that this is a real big story of not only of digital transformation, digital evolution, digital disruption, digital business, great story... >> You used to be able to do this job in Southern California. >> Yes, absolutely. >> Thanks for bringing Toyota to the table. Thanks for coming on. >> My pleasure. Thank you for having me on. >> The beginning of a journey that's going to continue it's not ending anytime soon. Toyota company, really bringing data into the center of the action. Of course, we're in the center of the action as theCube, bringing you the data from Informatica World, right here, on theCube. More coverage after this short break. I'm John Furrier, Peter Burris. Stay with us, we'll be right back. (upbeat music)

>> Narrator: Live from Las Vegas, it's The Cube! Covering Informatica World 2018. Brought to you by Informatica. >> Welcome back, everyone. We're live here in Las Vegas at the Venetian. This is Informatica World 2018. This is The Cube's exclusive coverage. I'm John Furrier, cohost of The Cube, with Peter Burris, my cohost for the past two days. Wall-to-wall coverage. Our next two guests are Ronen Schwartz, SVP's Junior Vice President, General Manager, Big Data Cloud, and Data Integration for Informatica; and John MacIntyre, who's the product management for Azure Sequel Data Warehouse with Microsoft. Part of the big news this morning on the keynote is the relationship between Microsoft Azure Cloud and Informatica. Welcome back, welcome to The Cube! Thanks for coming! >> Yeah, it's good to be here. >> So great to have you guys on, we were looking forward to this interview all morning, all day. We heard about the rumor of the news. Let's jump into it. But I want you to highlight the relationship, how you guys got here, because it's not just news, it's not just an announcement. There's actually code, shipping, product integration, push button, console, it's cloud, it's real cloud, hyper cloud. >> John: Yeah, yeah, absolutely. >> It's a real product. >> John M.: Absolutely. >> Yeah, definitely, this is correct and I do want to encourage the audience to go directly to the Azure environment, try SQL Data Warehouse and try to load as much data as possible, leverage the Informatica intelligent cloud services. It is, as you said, available today. >> Okay, so explain the product. Let's say you got the Informatica intelligent cloud services on Azure. What is the specific product? Take us through specifically what's happening and what is the impact to customers? >> So if you are a customer and you're looking to get agility, you want to get scale, you want to enjoy the benefits of cloud data warehouse, one of the first barriers that you have is how do I get my data into these new amazing capabilities that I can achieve in the cloud. And I think with this announcement we're simplifying that process and making it really streamlined. From within the same place that you start your new data warehouse, in one click you're actually coming to the strongest IPES that exists in the market and you are able to choose your data source and actually decide what data do you want to move and then in a very simple process, move that data into Azure SQL Data Warehouse. >> John, talk about the ease of use, because one of the things that pops in my head when I think about data is, man it's a pain in the butt. I got to do all this stuff, I got to get it off a storage drive, I got to upload it, I got to set it on a drive, FedEx the drive, whatever. Cloud has to be console based. Talk about that aspect of this deal. >> Well I think, John, you know one of the things that you'll hear from Microsoft is that we want to build the most productive cloud available for customers and when we look at it as Ronen was saying, excuse me, we move data, we get data connected into the Azure cloud and how do we do that in a push button way and so what you'll see through the integration that we've done is that all the way through single sign on, that you can just push a button, build that pipeline, get that data flowing from your on-premises environment and get that into the Azure SQL Data Warehouse with just pushing a few buttons and so what we see is customers are able to really accelerate their migration and movement to the cloud through that productivity. >> And how long has it been in the works for? You guys just didn't meet yesterday and did product integration. Talk about the relationship with Informatica. >> Yeah, we've been working with Informatica for years. Informatica's been a great partner and so we started working on this integration, I think, probably over a year ago and really envisioning what we could do for customers. How do we take all of the really great capabilities that Informatica brings to customers and connect those to the Azure cloud. One of the things that we believe for customers is that customers will live in a hybrid world, at least for some foreseeable time and so how do we enable customers to live in that world, to have their data spread across that world, and get all the lineage, governance, and data management capabilities that you need as an enterprise in this world and that's one of the great things that Informatica brings to the table here. >> And Microsoft, your ethos too is also your, seems to be and you can confirm this if it's true or not, to be open for data portability. >> John M.: Yeah. >> Certainly, GDPR has certainly a huge signal to the market that look, no one's going to fool around with this. Data's at the center of the value proposition. It has to move around. >> That's right. And so when we think about data, data interoperability, data portability, recently we introduced Azure Databricks as a GA service on Azure and so we've already done data interoperability across our relational data warehouse products as well as the Databricks products, so Spark and Spark runtimes can interoperate and have data access with the relational warehouse and the relational warehouse can load into Spark Clusters and so we see this giving customers the freedom to move their data and have their data in places that they need them as critical for them to be successful. >> Ronen, let me just get specific on the news here a second. The product is GA or preview, or? >> The product is in preview and it will be fully GA'd in the Q3 time frame, hopefully the middle toward the end of Q3. Customer can start experiencing with the product today and they will actually see us adding more and more capabilities to this experience even before the GA. >> What are some of the things the customers have been asking for? I know you guys do a lot of work on the product side with the customers so I want to ask the requirements that you guys put together on defining this product. What were some of things that were their pain points that you're solving and was it the ease of use, was it part of the plan of enterprise cataloging? Where did you guys come down when you did your PRD, or your requirements and all this stuff? >> So we've been working with customers and with partners for the last few years over their journey to adopt cloud and I think what we've seen is part of the challenges of adopting cloud was where do I start? How do I figure out what data should I move to the cloud first? What is actually going to be impacted by me doing this? One impact you touch which is security and privacy. Am I putting something in risk? Am I following the company policies? But other things is like, what other system are depending on this data to exist here and so when I move to the cloud, am I actually changing my overall enterprise data architecture? Where Informatica have been focusing, especially with the new catalog capabilities is in really giving the enterprise the full picture of the data. If data is the most important asset that you have, we're actually trying to map it for you, including impact analysis, including relationship dependencies. What we're trying to simplify is actually choosing the right data to move to the cloud and actually dealing with rest of the impact that is happening when you're adopting cloud fast. I think cloud is bringing an amazing premise. We want to make it really, really easy. This latest announcement is actually touching the experience itself, how can a customer go from starting a new data warehouse to bringing the data to the data warehouse. I think we are now making it even simpler than ever before. >> So one of the challenges that enterprises have overall is that they're so few people who really understand how to build these pipelines, how to administer these pipelines. Data scientists are not, the numbers are not growing fast. Microsoft also is an enormously powerful ecosystem itself. Do you anticipate that by doing IICS in this relationship way that your developers can actually start incorporating higher, more complex, more higher value data services in a simple way so that they can start putting it into their applications and reduce the need for those really smart people at large and small companies? >> I mean, I think what we want to get to is this notion of self-service data. And to Ronen's point, but that data has to be governed, that data has to be protected, you need to know that you can trust that data, you can trust the source of that data, (coughs) excuse me, you know that you can make decisions from that data, but we hear from customers is they really want IT and these specialists to get out of the way of the business. And so they want to enable their workforce to actually do data production, to say I can create a data set that I can actually make decisions around. I know the lineage of that data set, I know the quality of that data set, and I know where it's appropriate to go use that data set. It could be for data science. It could be for a data engineer to go pick up and use for another pipeline, or it could be for a business analyst. But I think with this partnership, what we're really focusing on is how do we accelerate that productivity for those people who are discovering the data, managing the data, and then those that can then build these data streams and build these data sets that can be consumed inside an organization. Now I think to your point, once we do that, we believe that we will see a proliferation of analysis and higher level advanced analytics on top of that data. What we're hearing from customers is the challenge isn't necessarily getting machine enlargening services up and running or doing advanced analytics or building models and training models. Yes there is a narrow set of people that go and do that, but inordinately what we hear is that customers are spending the bulk of their time, shaping, managing that data, wrangling that data, getting that data in a form that it can actually be consumed and I think this partnership-- >> A lot of prep work. >> Yeah, a ton of prep work. >> Talk about the dynamic. We've been hearing on The Cube here, certainly, and also out in the industry, that 80% of the time spent managing all this stuff, you guys have a value proposition of caching all the metadata so you can get a clear view and customers, we had Toyota on earlier, said we had all the data, we just actually made all these mistakes because we didn't connect it all. What you guys are doing, coming from Ronen, you're going to bring all of the Microsoft tools to the table now, so I'm a customer, the benefit to me is I get to leverage the power, BI stuff or whatever is coming down the pipe, whatever tools you have in your ecosystem, on-prem and also in the cloud, is that? >> Absolutely and so things like PowerApps going to be an ability with no code, low code experiences to actually go build intelligent applications, build things like sales oriented applications, recruiting oriented applications, and leverage that data, that is really what we want to unlock for enterprises and for data professionals. >> What do you think the time will be, just ballpark, ballpark order of magnitude, time to, that you're going to save on the setup? If 80% is industry benchmark people throwing around, but say 80% is wrangling setup, 20% analysis. What do you guys see the impact with something like the intelligent cloud service with Azure? >> Ronen, you can speak to what you're seeing already from some of the customers, but I think even from what we saw this morning in the keynote, we're cutting down the time dramatically in terms of, from identifying what data has value and then actually getting that, moving into Azure, what you saw in less than 10 minutes today would take days if not weeks to actually get done without these tools-- >> So significant number, big number? >> John M.: Yeah, absolutely. >> And I think there are actually two parts to people going through the adoption. One is the technology of moving the data, but the other one that is even, I think, a bigger barrier and sometimes even more important is can I actually just discover and identify the data and can I actually get all the metadata needed so that I can get the approval or I can get personally comfortable with the data that I'm choosinng. I think this cost now is actually being eliminated and that is actually going to allow more people to consume more data even faster, but I do agree that I think the demo speaks better than anything else, got a lot of good-- >> John F.: A few clicks and you're there, got some great props on Twitter, saw some great tweets. The question that begs next is now that I got a pipeline and automating, all this stuff's going on, console based and cataloging all this great stuff, AI, machine learning involved, where, is there, did you guys put the secret sauce in some of the tech? I mean, can you share what's under the hood at all? (laughs) Or is that the secret sauce? >> So, I can not steal some of the demos of tomorrow, but I think you will-- >> Yes you can. (laughs) >> Come on, tell us. >> But I think you will see an interesting AI driven interface-- >> That's a yes. >> From Microsoft working very interestingly with the catalog to drive intelligence to the users, so we will definitely demo it tomorrow on stage. >> John F.: So that's a yes. >> Yes, the answer is yes. >> But I want to build on this because I asked a question about whether or not developers are going to get access to this. If I have a platform that allows me to build very, very complex, but very rich, in a simple way, pipelines to data, I have a catalog that allows me to discover data, sustain knowledge about that data as the data changes over time, and I have a very simple way of setting that up and running it through an Azure cloud experience, can I anticipate that over time certain conventions for how data gets established, gets set up, organized, formats, all that other stuff, starts to emerge as a combination of this partnership so that developers can go into an account and say, okay so we're going to do this for you, oh, you have customer data, you have this data, I want to be able to grab that and make it part of my application. Isn't that where this goes over time? >> Yes, yes, in a very substantive way. I think we're also looking at it from, you'll have stay tuned on the Microsoft side, but we're working towards looking at data entities, business entities, and how do we enrich those entities and to your point, where do they get enriched in that data pipeline and then how do they get consumed and how do they get consumed in a way where we're expressing the data model, the schema, the lineage, and all of these things in a way that's very discoverable for those consuming that data, so they understand where it's coming from so that people, so we look at this partnership in terms of getting that data, getting that data more enriched, and getting that data more consumable in a standard way for application developers. Again, it could be those building intelligent applications, it could be those building business applications and there's a whole set of tools-- >> Or some as-yet-undefined class of applications that are made possible because it's easier to find the data, acknowledge the data, use the data. >> John M.: Yeah, absolutely. >> If we had more time, I'd love to drill down on the future with Microservices, containers, Kubernetes, all the cool stuff that's going on around cloud native. I'm sure there's a lot of head room there from a developer standpoint. Final question is, extending the partnership. Is there a go to market together? Are you guys taking it to the field? What's the relationship with Microsoft, your ecosystem, your developers, your customers, and Informatica? >> Yeah, we're doing a lot of joint go-to-market. Today already we've been doing a lot all the way up to this announcement and I think you'll see that increase based on this announcement. I don't know if Ronen you want to talk about specific things we're doing. >> Yeah, I think the success with the customer is already there and there is actually a really nice list of customers here that are mutual customer of ours doing exactly these scenarios. We'll make it easier for them to do it from now on. >> Yep. >> From a go-to-market perspective, we have a really nice go-to-market motion where the sales teams are actually getting aligned. The new visible integration will make it even easier for them. >> Yeah, this really hits a lot of the sweet spot, multi-cloud, hybrid cloud, truly data-driven, ease of use, getting up and running. Congratulations, Ronen, great job. John, great to see you. Here inside The Cube, putting all the data, packing it, sharing it out over the airwaves and over the Internet. Just The Cube, I'm John Furrier, Peter Burris, thanks for watching. Back with more live coverage. Stay with us for more coverage here at Informatica World 2018, live in Las Vegas. We'll be right back. (soft electronic 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)

>>live from Las Vegas. It's the Cube covering. Inform Attica, World 2018 Not you. Buy in for Monica. >>I am Peter Burroughs Wellcome. Back to Day two. Coverage on a cube of in from Attica, World 2018. We're broadcasting from the Venetian here in beautiful Las Vegas. Certainly a lot of excitement. A lot of the buzz just heard the general session empty. Probably 1000 people in the room looking at various moods. Excited to be here this morning. We're being joined by my co host. Jim Kabila's Jim is lead analyst to Wicked Bond. Silicon Angle. Looking at a lot of the data and data practice issues on our first guest is want Te'o One is a principle of data management on architecture at Deloitte one. Welcome to the Cube. >>Great. Thank you, guys. Thank you guys for having me. >>So let's kick it off. What's do you do with Deloitte? What's interesting? What a customer is talking about? >>Yeah. No, absolutely. I mean, I think you know, we are absolutely at the what I would call inflection point around the importance of data. And so my role at the Lloyd is to lead our data management and architecture practice, which essentially deals with everything from data strategy today to execution and how we enable all their transformational initiatives right to truly take advantage of the power that data has to unlock. You know, better business processes to unlock better insights, right to take better action, right? I mean everything that we've been historically talking about, right? In terms of what can organizations do around their data asset? My job is to ensure that we are leading guiding, driving and developing these solutions for our clients. >>So here's a simple question. Just kind of kick it off and see where it goes way. Think that data is becoming more important? You think the day is coming on or important? Are you finding yourself still talking to people that are data administrators or you finding yourselves being pulled into higher level conversations within the business? Talk about data asset, date ass, information, data, asset returns. How is that changing? >>I would say it's evolving, right? I mean, if I and so I have the privilege of running or practice nationally, right? So I have the approach of looking at all of the various industries and sectors right. And so I think, you know, if you take the financial service is life science, healthcare industries, right where there's a lot more regulatory demand on data ensuring that you know what it is, where it's coming from. It's got the right data standards and qualities. I would say they they've gotten it long ago, right? And they've put in place data management organizations. We hear the chief data officer, right? I would say those industries and sectors are a lot more prominent on DSO the conversations absolutely at the executive level, right? There is an executive owner that's responsible for ensuring that the data is correct. >>Tell us about changing data landscape one. Why do enterprises need to change their data strategy and architecture? What do you What do you hear from clients telling them? >>Yeah, I think it's quite simple, right? It is so absolutely enable their business strategy right. You can no longer enable your business strategy without without the data dimension, right? I mean, for many, many years we've talked about, you know, people process technology, right? Well, now there's 1/4 dimension, right? People process technology and data on dhe. That's how we like to think about it. Is that important? Right? You need that executive, and I'll use two words very, very distinctly, right. You don't need an executive data sponsor. You need an executive data owner. Right? And that's the transformation, right? In the evolution that we're seeing in the market and that we're actually advocating for right to truly unlocked that business strategy, that business outcome that they're looking >>for. So let's talk about if we're gonna do that, then we need tools to do it. Yeah, absolutely. So we're talking about data we're talking about data owners we're talking about practice is to actually create generate value out of data. That's not something we're going to manually, right? Talk about some of the tools generally that your clients are starting to apply to improve their productivity of doing these things. >>Yeah. I mean, I would say there's a sort of standard spectrum of data management tools ride from, you know, the database to master data management to quality to meta data management. Right. So each of these technical capabilities and tools right provide the capabilities required to manage that sort of data supply chain right? There is infinite sources of data and there's infinite sources of demand, right? And it is the responsibility of, you know, the data management organization, too, to manage that supply chain. And obviously you need tools and you need technology to sort of support that entire life cycle. >>What is the one thing that you tell clients that need to do with their data in order to stay competitive? Is there one imperative thing that they all need to do with their data just to stay in the thick of whatever it is they do in their industry? >>Yes. So the one thing I always advise our clients is all data is not created equal, right? So fine and identify the data that truly Dr Value for your organization. Because that's been, I would say, one of the biggest challenges in this space, right is everyone's drowning in data, right? And so to bring all these capabilities for your entire, you know, sort of landscape in your organization, it's massive, right? It's just too big, right? So ty value and outcomes to the data that matters, right? So I'll give an example, right? So in retail, right, I mean their values around knowing their customers and the products that they So to those customers, right? So let's start double clicking underneath that and figuring out and ensuring that that data right has all the rights standards is up to quality so it can meet those business strategies, right? Don't go after everything, Right, map business outcome and value to the data that supports that. >>What's the role of the chief data officer and the other C level executives in driving that sort of transformation? Yeah. How is their role changing? >>So I would say the chief date officer role is again evolving and still maturing. Not everyone has it, but I do see them as the when the next executive sea level rose. That will truly be a catalyst for change and innovation. Right where, you know, I think we traditionally think about the CTO or the C I o. Or the chief strategy officer, right? Sort of back to the now four dimensions. It's no longer three their ability to understand the business strategy, understand where their data is to support that and bring new, innovative ways to enable that, right? So it's absolutely critical. >>So what we think ultimately on justice on you is that a chief is a is an executive that's responsible for demonstrating that they're generating, return and share older capital. Exactly. Chief data officer. Therefore, be the individual that's demonstrating that they're generating return on the company state assets. When you take an asset approach, you could think about portfolio. But think about portfolio now. You're discriminating, which values most valuable. Which date is less valuable. If you agree, that suggest that there is a new class of tool that has to be bought in around this notion of port folio catalogs, minute master data management and give us a sense of that kind of new tool kit that's gonna be at the core of not just managing data inside an application like a D B. M s right, but something that's actually managing data assets, >>right? Yeah, I think it's It's the entire ecosystem of how we bring it together and how we prove we create. What I would say is, products and service is around data right so back to this construct of your managing the data supply chain, right? And so the responsibility of the CDO and how you measure and manage that too, you know, outcomes. Right and shareholder value is I've just created a product around this data, and we talked a lot about data monetization. Andi. I would say It's from a outside in perspective. Am I selling my data? Am I making money? Right? Well, and of course, that's one angle. But I would say there's also the inside out view where your monetizing to create value back to your organization, Right? So increase, you know, customer cells, right? Reduced turn right. All those things matter. And so time data products to those business outcomes. I think how you get to, you know, the return on investment shareholder value as it relates to this role in the products and service is that it's creating. >>All right, we're out of time. I want a oh, principal date architecture er and management management architecture. Sorry at Deloitte. Thank you very much for being on the Cube. >>Thank you. >>All right, so we'll be right back with another event or another segment from in Dramatic World 2018 here in Las Vegas.

(techy music) >> Announcer: Live from Las Vegas, it's theCUBE, covering Informatica World 2018. Brought to you by Informatica. >> Hello, and welcome back to theCUBE. We are broadcasting from Informatica World 2018, The Venetian in Las Vegas. I'm Peter Burris, once again, my cohost is Jim Kobielus, Wikibon/SiliconANGLE. And at this segment, we're joined by Matthew Cox, who's the director of Data & Technology Services in McAfee. Welcome to theCUBE, Matthew. >> Thank you very much. Glad to be here. >> So, you're a user, so you're on the practitioner side. Tell us a little bit about what you're doing in McAfee then. >> So, from a technology standpoint, my role, per se, is to create and deliver an end-to-end vision and strategy for data, data platforms and services around those, but always identifying a line to measurable business outcomes. So my goal is to leverage data and bring meaning of data to the business and help them leverage more data-driven decisions, more toward business outcomes and business goals. >> So you're working both with the people who are managing the data or administering the data, but also the consumers of the data, and trying to arbitrate and match. >> Absolutely, absolutely. So, the first part of my career, I was in IT for many years, and then I moved into the business. So for probably the last 10 years, I've been in sales and marketing in various roles, so it gives me kind of a unique perspective in that I've lived their life and, probably more importantly, I understand the language of business, and I think too often, with our IT roles, we get into an IT-speak, and we aren't translating that into the world of the business, and I have been able to do that. So I'm really acting as a liaison, kind of bringing what I've seen of the business to IT, and helping us deliver solutions that drive business outcomes and goals. >> What strategic initiatives are you working on at McAfee that involve data? >> Well, we have a handful. Number one, I would say that our first goal is to build out our hub-and-spoke model with MDM, and really delivering our-- >> Jim: Master data management? >> Our master data management, that's correct. And really delivering our, because at MDM, that is where we define our accounts, our contacts, we build our upward-linking parents and our account hierarchies, and we create that customer master. That's the one lens that we want to see, our customers across all of our ecosystem. So we're finishing out that hub-and-spoke model, which is kind of an industry best practice, but for both realtime and batch-type integrations. But on top of that, MDM is a great platform, and it gives you that, but the end-to-end data flow is another area that we've really put a priority on, and making sure that as we move data throughout the ecosystem, we are looking at the transformations, we are looking at the data quality, we're looking at governance, to make sure that what started on one end of the spectrum look the same, or, appropriately, it was transformed by the time it gets to the other side as well. I'll say data quality three times: Data quality, data quality, data quality. For us, it's really about mastering the domain of data quality, and then looking at other areas of compliance, and the GDPR just being one. There's a number of areas of compliance areas around data, but GDPR's the most relevant one at this time. >> There's compliance, there's data quality, but also, there must be operational analytical insights to be gained from using MDM. Can you describe how McAfee, what kind of insights you're gaining from utilization of that technology in your organization? >> Sure, well, and MDM's a piece part of that, so I can talk how the account hierarchy gives us a full view. Now you've got other products, like data quality, that bolt on, that allow us to filter through and make sure that that data looks correct, and is augmented and appended correctly, but MDM gives us that wonderful foundation of understanding the lens of an account, no matter what landscape or platform we're leveraging. So if I'm looking at reporting, if I'm looking at my CRM system, if I'm looking at my marketing automation platform, I can see Account A consistently. What that allows me to do is not only have analytics built that I can have the same answers, because if I get a different number for Company A at every platform, we've got problem. What I should be seeing, the same information across the landscape, but importantly, it also drives the conversation between the different business units, so I can have marketing talk to sales, talk to operations, about Company A, and they all know who we're talking about. Historically, that's been a problem for a lot of companies because a source system would have Company A a little bit differently, or would have the data around it differently, or see it differently from one spectrum to the next. And we're trying to make that one lens consistent. >> So MDM allows you to have one consistent lens, based on the customer, but McAfee, I'm sure, is also in the midst of finding new ways, sources of data and new ways of using data, like product information, how it's being used, improving products, improving service quality. How is it, how is that hub-and-spoke approach able to accommodate some of the evolving challenges or evolving definitions and needs of data, since so much of that data often is localized to specific activities after they're performed? >> In business, there is a lot of data that happens very specific to that silo. So I have certain data within, say, marketing, that really is only marketing data, so one of the things that we do is we differentiate data. This kind of goes to governance, even saying there's some data as an organization is kind of our treasure that we want to make sure we manage consistently across the landscape of the ecosystem. There's some data that's very specific to a business function, that doesn't need to proliferate around. So we don't necessarily have the type of governance that would necessitate the level of governance that an ecosystem level data attribute would. So MDM provides, in that hub-and-spoke, what's really powerful for that as it relates to that account domain, because you're talking about product. Products is another area we may go look at at some point, adding a product domain into MDM, but today with our customer domain, and kind of our partners as well, it gives us the ability to, with this hub-and-spoke topology, to do realtime and batch, whereas before, it may have been a latency as we moved information around, and things could get either out of sync or there'd be a delay. With that hub-and-spoke, we're able to now have a realtime integration, a realtime interaction, so I can see changes made-- >> At the spoke? >> Peter: At the spoke, right. So the spoke pops back to the hub, hub delivers that back out again, so I can have something happening in marketing, translate that to sales, very quickly, translate that out to service and support, and that gives me the ability to have clarity, consistency, and timeliness across my ecosystem. And the hub-and-spoke helps drive that. >> Tell us about, you just alluded to it, sales and marketing, how is customer data, as an asset that you manage through your MDM environment, how is that driving better engagement with your customers? >> Well, it drives better engagement, first of all, you said an important thing, which is asset. We are very keen on doing data as an asset. I mean, systems come and go, platforms come and go. It's CRM tool today, CRM tool number two tomorrow, but data always is. Some of the things we've done is try to house and put a label on data as an asset, something that needs to be managed, that needs to be maintained, that needs to-- >> Governed. >> have an investment to. Right, governed, because if you don't, then it's going to decline in value over time, just like a physical asset, like a building. If you don't maintain and invest, it deteriorates. It's the same with data. What's really important about getting data from a customer's standpoint is the more we can align quality data, again, looking at that, not all data. Trying to govern all data is very difficult, but there's a treasure of data that helps us make decisions about our customers, but having that data align consistently to a lens of an account that's driven by MDM proliferate across your ecosystem so that everyone knows how to act and react accordingly, regardless of their function, gives us a very powerful process that we can gauge our customers, so that customer experience becomes consistent as well. If I'm talking to someone in sales and they understand me differently, then I'm talking to someone in support, versus talking to someone in marketing or another organization, it creates a differentiating customer experience. So if I can house that customer data, aligned to one lens of the customer, that provides that ubiquity and a consistency from a view in dealing with our customers. >> Talk to us about governance and stewardship with the data. Who owns the customer data? Is it sales, is it marketing, or is there another specified data steward who manages that data? >> Well, there's several different roles that you've going to hit through. Stewardship, we have, within my data technology services organization, we have a stewardship function. So, we steward data, act on data, but there's processes that we put in place, that's you're default process, and that's how we steward data and augment data over time. We do take very specific requests from sales and marketing. More likely, when it comes to an account from marketing, sorry, from sales, whose sales will guide, you know, move this, change this, alter that. So from a domain perspective, one of the things we're working through right now is data domains, and who has, I don't know if you're familiar with racing models, but who is responsible, who is accountable, who is consulted, who just receives an interest or gets information about it. But understanding how those data domains play against data is very, very important. We're working through some of that now, but typically, from a customer data, we align more toward sales, because they have that direct engagement. Part of it, also, is that differentiated view. Who has the most authority, the most knowledge about the top 500, top 1,000, top 2,000 customers is different than the people you had customer 10,000. So you usually have different audiences that play, who helps us govern and steward that data. >> So, one of the tensions that's been in place for years as we tried to codify and capture information about engagement, was who put the data in, what was the level of quality that got in there, and in many respects, the whole CRM thing, took a long time to work, precisely, because what we did is we moved data entry jobs from administrators into sales people, and they rebelled. So as you think about the role that quality plays and how you guide your organization to become active participants in data quality, what types of challenges do you face in communicating with the business, how to do about doing that, and then having your systems reflect what is practical and real in the rest of your organization? >> Well, it's a number of things. First of all, you have to make data relevant. If the data that that these people are entering is not relevant and isn't meaningful to them, the quality isn't going to be there, because they haven't had a purpose or a reason to engage. So, first thing is help make the data be relevant to the people who are you're data creators, right? And that's also to your business leaders. You also want the business leaders coming to you and talking about data, not just systems, and that's one of the things we're working toward as well. But as part of that, though, is giving them tools to ease the process of data-create. If I can go to my CRM tool instead of having to type in a new account, if I can then click on a tool and say, Hey, send to CRM, or add to CRM. So it's really more of a click and action that moves data, so I ensure that I have a good quality source that moves into my data store. That removes that person from being in the middle, and making those typing mistakes, those error mistakes. So it's really about the data-create process and putting a standard there, which is very important, but also then having your cleansing tools and capabilities in your back end, like the MDM or a data stewardship function. >> So by making the activity valuable, you create incentive for them to stay very close to quality consideration? >> Absolutely, because at the end of the day, they use that old term, garbage in, garbage out, and we try to be very clear with them, listen, someday you're going to want to see this data, and you probably should take the time to put quality effort in to begin with. >> Got it, one last quick question. If you think about five years, how is your role going to change? 30 seconds. >> I think the role's going to change in going from an IT-centric view, where I'm looking at tools and systems, to driving business outcomes and addressing business goals, and really, talking to business about how do they leverage data as a meaningful asset to move their business forward, versus just how am I deploying stewardship governance and systems and tools. >> Excellent. Matthew Cox, McAffee, data quality and utilization. >> Absolutely. >> Once again, you're watching theCUBE. We'll be back in a second. (techy music)

(several people talking in tandem) >> Narrator: theCUBE Alumni. (upbeat music) Live from Las Vegas, it's theCUBE. Covering Informatica World 2018. Brought to you by Informatica. >> Hello everyone, I'm John Furrier for theCUBE; we are here live in Las Vegas for Informatica World 2018. My co-host, the next two days, wall-to-wall coverage is Peter Burris, head of research at Wikibon sitting on theCUBE. We're here for Informatica World, here in Vegas. We were in San Francisco previous years. Big table being set here with the role of data we've covered in the past, in the role of data. Certainly, we've been talking about on SiliconANGLE and researching it on Wikibon. Security, data, IoT, center of cloud infracture, AI and then, emerging technologies like Blockchain and other things. This is where the action is. Peter, we've been looking at Informatica over a couple of years and the arc and change is around data, cloud; you've got the international component with the GDPR, booming front and center this month. And then you've got data as a competitive advantage You're seeing companies organized around data, but you can't ignore the explosion of AWS putting the stake in the ground with the numbers they're getting with the cloud. Microsoft as yours dominance with the install base of Microsoft now making a play in cloud. And you've got Google Cloud, and then international volley by a variety of cloud players. Huge cloud scale, IoT Edge, data. I mean these guys are...I mean are they caught in the crosswinds, do they have a tailwind, headwind? Informatica, are they positioned? What's your take? >> Well, Informatica is amongst that handful of companies that was on a knife's edge as the marketplace started moving towards the cloud. And when the move to the cloud, from a software company standpoint, is also associated with a move from a traditional business model, which is we sell our software or you give us money up front and that's how we pay our sales guys, to a services orientation which is we're going to work with you in a services mentality and expect that we're going to operate over time. So, Informatica was on that knife's edge, they had a good product set in the sense that they foresaw that data was going to become more important and they are a good data company. They've got a great suite of data management tools that's very relevant to today's marketplace. But in a manner of respects, the question was were they going to step up and be one of the companies that successfully transitioned to the cloud and a services model or were they going to try to fight against it with product set and they have been making that transition and it seems to be going quite well. We first heard about it a couple of years ago, last year we saw it accelerate with some of the new initiates that they had and their incorporation of AI into their suite and our expectations this year we'll see, it's already even further. >> It's interesting, time is a great equalizer to who is right on the vision. We hear a lot of visions and people putting out statements of intent with their organization. You see who pivots and who shifts and who zigs and who zags. Informatica a few years ago, really understood the horizontal scalability of the cloud and the data needs to move around very freely, but they also understood the challenges of governance. So, as we look at applications and the cloud and potentially de-centralized applications, data is more critical than ever that it be exposed and be addressable but yet compliant. This is a hard challenge. You're researching this and it reveals itself in the IoT Edge, to the data center and hybrid multicloud. How are companies thinking about data as it has to be frictionless horizontally, but yet, managed with compliance? >> Well, we wrote a piece a couple years ago that clearly stated that a digital business is one that uses data as an asset, and that's it. All this other transformation stuff is noise unless you're focused on the role that data is playing in your business. In fact, we believe pretty strongly, that the whole notion of digital business transformation is the process by which your organization acknowledges, recognizes what it means to have data as an asset. You're culturally setup to do it. You're organized to take advantage of it and very importantly, you're institutionalizing your work around what it means to use data as an asset. So, that's been our perspective for a long time. Companies today continue to be half-and-half. Certainly, companies like Amazon, AWS, those digital native companies, absolutely have got this. They are very much focused on the role that data is playing as the centerpiece asset for their businesses. A lot of the incumbents that are trying to move into and take on some of those digital threats, are also starting to recognize this. We've heard at a number of different CUBE events over the past few months, that an acceleration in the, at least the talk track, about the role that data's going to play out of a variety of different big companies. So, right now, most of the enterprises that we're working with are still a little bit behind, you get some arguments about it. You know, well what about this, what about that? But increasingly there's at least an acknowledgement that data as an asset, generating returns on that asset, the differences in how you generate returns on that asset, is going to become a feature of all enterprise strategies. >> I've been hearing in hallway conversations, that over a variety of the events that we've gone to, and a patter's kind of merging when it comes to data. Whether you're talking to a CEO of a company or the Chief Data Officer or even a CIO, the questions that come up, certainly on GDPR exposes this and the law that's going to be enacted this month, where's the data, what's it worth, and how do I organize around it? So, again to your point about you've identified the digital business transformation... And a lot of times the conversation is, I don't know all of them. So, this is the question I want to explore with you, here this week: where's the data, is it important, is it worth anything, and how do I organize my business around it, both architecturally because you've got the cloud right there as an accelerant potentially or it's a double-edged sword, it could hurt you. >> Yeah, absolutely. >> So, John what we've been talking about with our clients is this notion of data zoning, and the idea basically is kind of an architectural construct. Do you say, okay, what is the value proposition, what activities are essential to delivering that value proposition, and then where is that activity going to be located and what do I need to get data processed with that activity. So it's kind of a forced process and this notion of data zoning presumes that increasingly businesses have to think about the physical realities of data; latency, bandwidth, intellectual property, governance, legal considerations, as you mentioned like GDPR, but also the costs of moving data are very real and when you start talking about public cloud, can be off the charts expensive. So, those five considerations are going to be essential to how companies think about their data and how they start institutionalizing work around it. So, it's a absolute crucial focus that people have to emphasize and there's going to be some technologies that alleviates some of the pressures that they have, but the bottom line is the issues of cost, regulation and law, the latency and bandwidth, and intellectual property control are not going to go away and they will guide people's data choices. >> Intellectual property, zoning of data, these are things that scare me if I'm a data person and let me throw something at you. So, everyone's talking about the ecosystem. Oh we've got to have an ecosystem strategy. Certainly with cloud you have now diverse sets of sharing, we've seen the security, they're sharing data. So, this notion of sharing, which gives the collective intelligence, and makes data worth more and have more context, as we talk about in theCUBE all the time. At the same time, more sources of data are coming in from potentially customers, partners; this is a mashup, this is a fusion of data. This is a challenge. What are you hearing from companies on how they're posturing for ecosystem partnerships? Is it just APIs, is it just...? I mean, how are they thinking about this and is Informatica poised for that? >> Informatica, let's start with the second question, Informatica's poised for it, but every company's going to face some challenges. There are a lot of different sectors of the industry that are looking at this and saying, and licking their chops saying, man, I can make a lot of money there. But if we step back a little bit, the first thing is that, you're right, there is a mish mash and that's a feature of data. Data can be combined, it can be copied, you can do things with data without destroying data. It's like a biological catalyst, right? >> Yeah. >> It's very important to remain very cognizant of that, but when we think ultimately about where this is going, there's going to be a relationship between data protection, being able to locate data where it needs to be, at the same time, protect it; being able to move data with some degree of facility, stage it predictably around the enterprise so it's in the zone where it needs to be to support an action. And our expectation ultimately is that we're going to see an increasing merging of the issue of security and data management because ultimately, the challenge of data is not, it is how do you privatize because it is so easy to share. So, one of the key concepts is going to be moving a security orientation from restricting access to appropriately sharing as you mentioned with business worlds, and security becomes kind of the mindset, the approach of how you go about privatizing your data assets and then subsequently, protecting them and then, putting them where they need to be within the enterprise so you can support the abilities. >> And it's also enabling developers, in AI for instance, you see with the trend in machine learning which is a gateway to AI, which we're all seeing. Next generation analytics are dependent upon this. Fundamental, whether whatever architecture. Whether its cloud infrastructure or edge of network, next generation analytics have to have a feed, have to have the ability to use machine learning. I mean look at... >> It's not just next generation analytics. >> Today. >> It's next generation applications, right? >> Bingo, yeah. >> So, it's how do we incorporate some of those new capabilities within applications so that what we talk about, is we talk about systems of agency. And the idea is how am I going to let technology act on my behalf? So, we can think in terms of automation which is a process oriented, but IoT, with its models and what we call, or augmentation, with its human data interaction, human application interaction, new styles of it, are very data first. And so ultimately what we're talking about again is these new styles of applications where either we're doing something based on a model at the edge or human beings are given options to choose from and those options are crafted by the system itself. And that is an enormous set of implications, so for example we talk about Blockchain. Blockchain means a lot of things to a lot of people, but fundamentally, one of the things that becomes interesting about Blockchain is the degree to which in a computing system, an accounting system doesn't need incentives. You tell it to do something, it does it. An edge application also doesn't need incentives, it operates according to the model and the specific conditions. But when you talk about some of these high value applications with human beings, you have to incorporate incentives into how that they work. And Blockchain has the potential to provide a very powerful way of conceptualizing how you make human beings strong agents within these systems without undermining that notion of agency with the appropriate set of incentives. >> And also the ability to disrupt, intelligently, the inefficient systems. You always talk about inefficiency is an opportunity to make it more efficient with intelligent data and insights this is essentially the theme at Informatica. Twenty-five years they've been doing data, but now, more than ever, supporting kind of these use cases that are emerging very quickly. Intelligent data and insights drive ton of value from analytics to applications. >> Well let's go back 25 years, Informatica started on the basis of acknowledging or recognizing that OLAP, that new class of analytic systems was going to require new technologies. This is a company that's always had good data jobs and good data people. It's a magnet for smart people with an orientation towards data and that's why it's remained relevant. Now again, this is not a given, there's still a lot of change on the horizon. The world does not have enough data scientists, the tooling for supporting some of these rich applications has a long way to go, there's a lot of net computer science that has yet to be developed. But if you think about the handful of companies that are going to be likely in the mix, making some of these changes, leading the way, Informatica's in that group. >> We got to wrap it up for the kick off. We're going to start day one. Final question, well I'll start it by saying, I think that Informatica has a great opportunity ahead and they've got challenges. They've got great product people, they have to engage the ecosystem; if they can effectively bring the product into the market with a robust ecosystem while enabling intelligent data for insights in a way that applications, machine learning can take advantage of it and scale it, I think they've got a great opportunity. If they don't forge those relationships, and take the draft of the cloud, then I think they might have some challenges. >> I think that's accurate. One thing I'd add to that John, is that they will have to demonstrate to the ecosystem they have and they want to build, that the transition front product to service is good for everybody. >> Yeah. >> If they can do that, if they can move that, because that's a big part of the cloud, if they can be a, again, a magnet within the cloud for attracting data related companies and innovation and entrepreneurs, then this is definitely a company to watch. >> We said it last year, whoever can crack the code on letting data grow organically and be intelligent, while maintaining governance and compliance which could slow things down, that is the secret sauce. Whoever cracks that code will certainly go to the next level. This is theCUBE, breaking down Informatica World starting day one of two days of wall-to-wall coverage. I'm John Furrier, Peter Burris. More live coverage after this short break. (upbeat music)

(upbeat electronic music) >> Narrator: Live, from Las Vegas, it's the Cube, covering Informatica World 2018, brought to you by Informatica. >> Okay, welcome back, everyone. This is the Cube's exclusive coverage, here in Las Vegas, at the Venetian Hotel. I'm John Furrier, co-host of the Cube, with Peter Burris co-hosting with me the next two days, wall-to-wall coverage. Our next guest is Richard Cramer, who's the Chief Healthcare Strategist for Informatica World, back from last year, had a great chat. We talked about data swamps and data lakes. This year it's about governance and the enterprise. Great to see you again, thanks for coming back. >> Thanks for having me back. >> Actually, healthcare, we can go on and on. Peter and I can rant about that, but this is really where the healthcare has had data challenges always. They've had regulations. Governance, some will say, maybe, maybe not. What's different this year, for you and your conversations? We talked about data swamps last year, and data lakes. Where is it this year? What's the conversation with customers in healthcare? What's happening? >> Well I think it really is a reflection of the maturity of people using data, naturally coming from a data swamp or a data lake. How do we keep it from becoming a swamp? You govern it. And so as people start to use data, which we're really coming into our own in healthcare, governance becomes the top topic. When I start to share data, and people ask me where'd this come from, what did it mean? And I'm not able to answer that question, that's a governance problem. And so we're really starting to see enterprise data governance and compliance come to the forefront of almost every one of my conversations. >> And where is the catalyst coming from? Is it some of the regulation? Is it some of the awareness? Is it in a moment where the straw breaks the camel's back, so to speak? Where is it coming from, the governance question? >> It really is coming from an executive level, where as we start to use data, we have more executive dashboards, there's a desire to actually make data-driven decisions, both for business purposes and clinical care, if you can't explain where the data came from and why, what it means when people ask you questions, they don't trust it. And so I think it really is, as we start to really use data for the first time, it needs to be reliable and trustworthy, and that's a governance problem. It's not a tool problem, it's not an architecture problem, it's a people or process problem, and that's governance. >> Well one of the things that's true about healthcare, is healthcare has been driving the vanguard of ethics in society, for probably a few centuries now. And it's starting to happen in technology as well. I think the whole concept of GDPR is made even that much clearer, as a consequence of people actually becoming a little bit more concerned about their health information getting into the hands of people they don't want to get access to that information. How is this relationship between healthcare, ethics, and now governance, starting to affect the conversations that you're having in healthcare and beyond? >> Well I think healthcare has had HIPAA, which is all about privacy and protection of information. We've had that for a long number of years, but that was really a data element, not an appropriate use, but hey, this data, you can't share without permission. Now we're talking-- >> And it wasn't about the subject, it was about the data that you controlled. >> That's right. And now we're really talking about, and genomic data is a big part of this, is the ethical use of data. Can I use this data appropriately? If I'm doing it for your benefit, and to help you care for yourself, yeah, I think we probably can. But it's a governance challenge, right? What data do I have? What am I allowed to use it for, for what purpose? And who has consented to that? We have a similar issue that if you're a hospital that also has a health plan, and you can share data about a patient from that health plan with that hospital. But how about a competing hospital across town? Well I can't share that data, potentially, because of regulatory reasons. So really, the need to know what data you have, what policies apply to that data, and be able to consistently and authoritatively govern that data, I think is really a good example of what's driving enterprise data governance and compliance. >> So on the compliance side, when you think about outside the United States, obviously GDPR Friday kicks in. That's creating a lot of awareness. >> Yes. >> What's the impact of that, if any, to healthcare? Is it no big deal, we've been there, we can handle this? They have the data issues. What are you hearing on that front? >> So really, two-fold. First, GDPR is probably the best representation of really good stringent, proper, consumer privacy data controls that exist. So even if you're not compelled to abide by GDPR, it's a great roadmap and it's a great model to follow, 'cause it's just good data discipline. We also have the good fortune at Informatica, that some of the leading healthcare organizations in the country, are our customers, and they happen to have footprints in Europe. And so they do in fact have a GDPR challenge. Do I have a patient from the EU that's coming to my U.S.-based facility? Do I have a U.S.-based patient that's in an EU facility? Do I have an EU licensed provider? The complexity of the GDPR challenge for some of our U.S.-based healthcare customers is pretty involved, and they're acutely aware of it. So I don't think there's been anything like GDPR in terms of data protection, that's existed in healthcare. >> Yeah, that's going to change the game. I guess, my gut feeling, again, you're the expert on this, but my feeling is that it will slow things down. It's mind-boggling that, I don't know, I'm a European patient going to a U.S. hospital, now something has to happen that didn't have to happen before. Or, is that, am I getting it right? >> I think that it holds the potential to get it to slow things down, if you treat it as a one-off. If you treat it as good data architecture, and you implement a system that that's just an artifact of how you manage data, it doesn't slow anything down, I think it makes things quicker. >> John: So the mandate is go faster. >> Because it's just the priorities. >> That's right. >> Well it sets a priority, and it forces you to have a good data architecture that operates like a well-oiled machine. >> But let me explain what I mean by that, 'cause it's very consistent with what you're saying. One of the biggest challenges about data is a lot of executives don't understand it, don't know what to do with it, can't treat it as an asset. GDPR, amongst other things, is forcing a consensus around what data can be to the business, what it should not be to the business, and that's helping to set priorities so that folks, you may be right, it may be a one-off basis. People may complain about it, but if it's used as an architectural direction, it may actually accelerate because it sets a consensus about what the priorities should be. >> Yes, and where you started is exactly why. It is a universally-understood business imperative that every executive knows. And the fact that underlying it is great data architecture, well that's just a bonus, 'cause it sets the priority correctly. >> But here's my challenge on that, because to create data architecture is aspirational for many, but not feasible in a short-term. So how do they get there? And then they want to have, hey, let's have some great data architecture. But what the Hell does that even mean? Some customers might be, I know hospitals might be more advanced, but there might, well maybe not, (laughing) but again, again, so take us through that. Some people might aspire for great data architecture, but it might take time to get there. >> So great data architecture, though, this is part of the generational market shift in data. And in the past, we had data silos, and data silos are bad, we must break them down and we must centralize and control data, as a path to value. That took a heck of a long time, and actually could not really be achieved. What's changed now is we accept silos are going to exist, self-service for data consumption exists, the problem is not now how do I centralize and control data within an inch of its life, to get value, the challenge now is how do I manage enterprise data as an asset, accepting that that's the landscape? A data catalog changes everything. >> Talk about the impact of that, 'cause this is super-important. It's not centralizing the data, it's just having a catalog with visibility into the meta-data, of all that data. >> Exactly right. So before, I didn't know where all of my data was, and data security being, and I, if I don't know I have it, how the heck can I secure it? Well with a catalog, for the first time, it's straightforward, simple, and easy, to know what data I have. You actually have a chance of securing it. So the answer, that's the path to getting real value with great data architecture, without taking decades to try and centralize and control. >> It's time for dancing. Richard, we got the music coming on. Last year it was data lakes, data swamps. That's awareness. Now it's enterprise governance, the catalog looking good from you guys. Congratulations. Good to see you. Thanks for coming on. >> Thank you very much. >> Alright, day one. Wrapping down, kicking off the Solutions Exhibit Hall here for Informatica World 2018. I'm John Furrier and Peter Burris. Stay tuned for more coverage, here from Las Vegas, it's the Cube. (upbeat electronic music)

>> Narrator: Live from Las Vegas, it's The Cube! Covering Informatica World 2018. Brought to you by Informatica. >> Hey welcome back everyone. We're here live in Las Vegas at the Venetian Hotel Ballroom the main floor here it's The Cube out in the open, I'm John Furrier with my co-host Peter Burris this week, for the next two days. Our next guest is Richard Ganley, he's the senior vice president digital transformation solutions and global partners for Informatica. Richard, great to see you. Thanks for coming on. >> Thank you for having me, it's a pleasure. >> We have three Palo Alto people on The Cube in Vegas. We probably all flew out here last night, but Informatica is doing great, you're dealing a lot with the digital transformation, dealing with the big large projects and partners, global partners. The ecosystem here is getting robust, and were going to expected to hear some announcements. We don't yet have the news in hand, but we hear some big ecosystem kind of announcements coming. Not sure you can talk about it, but talk about the ecosystem and the partner relationship that you guys are having with your customers. >> True absolutely, well I would look at it like this, you know we've got many of our partners here and part of the reason for that is the issue many of our users are trying to solve now, we call it digital transformation, but I think it's analogous to what happened about 20 years ago, when the internet was first really coming into our lives, people were getting online in large numbers. And many companies were scrambling for a strategy. You know they were worried about ordinary internet organizations who had already started to get online, but they were particularly worried about companies that looked a bit like them, who might get there first. And if we go to where we are today, many companies now, they're trying to unleash the power of data, they're trying turn all of that data that they got into some strategic advantage. And sure, customers of ours are worried about the likes of Amazon and Tesla to Informatica customers who are obviously very data driven, but they're also worried about organizations who are very much like them and what would happen if they unlock the power of their data first. So we see some of our customers trying to get ahead, trying to steal the march on companies that look very much like them, but also many organizations just struggling to find that place to start, and I think this is such a big problem, part of the reasons so many of our partners are here is cause it will take us all working together for the benefit of our customers, to solve these very very complex problems. >> I wonder if it's actually worse than it was 20 years ago, though right? Because 20 years ago, your general arrangement of assets, which pretty much every industry is defined by having relatively common arrangement of assets. You introduce data into that, it reduces assets specificity, you make things programmable, which means not only are you worried about companies that look like you, potentially you're worried about companies that look nothing like you, because data can quickly make them look like you. How does that play out into, as your partners are thinking about their business, how they engage customers? I've got a follow on question to that as well. >> Yeah, that's a good question Peter. I think the dynamic there, what is forcing people to do is to come up with a plan. You know, I don't think anybody can sit and wait to figure out what their plans going to be for data. They need to do something today. So we see many of our customers, very much in a hurry now, and I think boards of directors have woken up to the reality that they need to do something. So it has become a board room issue, but we see many boards now employing new titles, just like we saw 20 years ago when the internet came along. New titles being created like Chief Digital Officer, Chief Data Officer, Chief Analytics Officer, many of these new titles, new budgets becoming available. The hardest part for many is finding that starting point. And I think that's where many of our partners come in is many of our customers they'll turn to us, but they'll also turn to our partners for strategic advice, so it's important for us to all work together cause we've all got different skills that are part of the overall solution. >> But one of the challenges that I think everybody in the technology industry has, is that historically partnership arrangements have been tied to what industry are you in? What size company are you working with? And as digital takes root, it's going to change that very understanding of what kind of business is that customers in, what size are they going to be, what size can they be, is that starting to effect how you manage partners as well? How you manage relationships with your partners? >> I think it is. We're having to look at things very differently. I think many of our partners, they are changing as well. They're changing their businesses to deal with the changes in the world, as our customers become data driven, the business world is becoming disrupted you know our partners are going through that too. I think all businesses are fundamentally changing the way that they do business and it's the same for our partners, so I think the whole world, even society, is going through the same thing at the same time, we're all having to think differently about what we do, and it's data, data is changing the lives of everybody on the planet and every single business at the same time, including our partners. >> I got to ask you a question. The reality that we're hearing from customers is that there is a major shift going on with data. And you outlined them. But now combine that shift with, a couple of rooms in the house burning on fire, like GDPR. So you have this shift going on right? So more than every they need partners. So what we're hearing is, "Okay, we're used to dealing with a lot of regulations and data" to "Oh my God, we've been fast and loose just trying to scale up and scale out with the cloud and what not, and now I need help." They need help right now, they don't need a ten year project or a six month project, they need stuff instantly. How are you guys bringing those parties to the table? What does a customer do, what does a prospect do, do they say, "Hey, Informatica, you guys are like the Switzerland of data, you got the catalog and stuff, MDM, I like the story, I want to move on this, what do I do?" What do you guys, what do you say to that? Obviously it's a good prospect. >> That is a great question, and for most of our customers that's the hardest thing, is where to get started. What we see is, and this theme runs through our conference, there were four journeys that we see our customers going on, it's 360, getting a single view of their customers or products, governing their data, number two, and number three, moving to the cloud or hybrid, and fourthly, next generation analytics, putting data in the hands of business people who can use it to serve customers and run their business better. We see all of our customers, they typically will start in one of these areas and it really depends on what's most pressing and burning in their business. So if GDPR is an issue for them, that's typically where they'll start. They'll start with governance, but also at the same time, there's many people looking at GDPR, they're seeing if they can govern all of their data, build a solid foundation, they'll be in a great position for the future. So that is actually a really really good starting point. And GDPR has been a goodness. I think it's driven a lot of the right behaviors and it's waking a lot of people up to the realities that they need to govern their data. >> We've been getting involved in a lot of the partnership conversations with The Cube obviously we have a lot of interviews with suppliers and their partners, you're in charge of global partners. What does that mean, and what are you doing to get them to be more effective? Either working together with each other or with Informatica and with the customer. How are you growing the partner network? What's the value purpose? Take a minute to explain the value preposition for the partners. >> Yeah, so I think for partners, there's never been a better time to partner with Informatica. These are great times, as I was saying at the beginning, the world is becoming data driven, and this is perfect. I think where our partners really come in is around those four journeys that I mentioned. They've all got different expertise on different parts of their journey and we align with partners who've got different skills that we can use. So for example, if a customer is looking to solve for GDPR and they want to become data driven, they want to govern their data, we'll work with partners who've those special skills, whether it's on the implementation side, whether it's business consulting, whether it's strategy, all kinds of different partners will support us. And really for our customers that gives them a much richer solution. >> Who are you trying to attract? Cause as you guys are growing obviously we would predict that given the value proposition of Informatica you're probably going to have some growth there. What's your value proposition to pitch to people that might not yet be a partner? What are you offering them? What's the incentive? What would you say to the people watching that might be a potential partner? That say, "Hey I want to join the Informatica partner network." >> Yeah, for many of our newer partners we signed up a huge number of new partners last year, and I think one of the value propositions is that as the world becomes data driven, we need our partners, this is perfect timing, there's never been a better time to come and work with us. I think we've got great solutions, many great products that our partners can compliment our solutions around, so I think the timing is perfect, and we also welcome new partners as well. So I think this is a great time for our partners to build their business with Informatica. It's a great time to be a partner, it's a great time to be a customer, and it's a great time to be-- >> So you bring business, growth together, grow together kind of philosophy. Is that the, does that sound right? >> Yeah, I think it's all about growing together, the markets growing really really fast, our customers need help immediately right now, and between us and our partners we're in the perfect position to help them. >> Richard great stuff. Thanks for coming on, great to meet you. Here in Las Vegas is Palo Alto native, resident of course with two other Palo Alto residents here at the Informatica World 2018. Day one of two days of coverage with The Cube, exclusively here in Las Vegas live. Stay with us for more day one coverage after this short break. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hey, welcome back everyone, it's theCUBE's exclusive coverage here at the Venetian, Live in Las Vegas CUBE coverage. I'm John Furrier the co-host of theCUBE with Peter Burris my co-host for the next two days of wall-to-wall coverage. Our next guest is Andrew Joss, who's the Head of Solutions and Data Governance for Europe, Middle East and Africa, and Latin America for Informatica. Great to have you on, thanks for joining us. >> Thank you! >> I could not stop waiting for this question because your anemia, Europe, Middle East and Europe. GDPR is kicking in this Friday. >> Andrew: Absolutely. >> So we're in May 2018. The big release of the law that kicks into place for GDPR in effect. Two things, what's the mood and then what does it mean? I mean, it's a shot across the bow of the industry. But we know what it means for people but like, what's the impact of this, what's going on? >> So I think we're seeing it at a couple of different levels. I think at a very individual level. I think the awareness of what GDPR potentially means for people, I think we're starting to feel that as individuals, in EMEA. We're seeing increasingly organizations reaching out to us, you know, we want permission to use your information or consensus in coding GDPR. You're customers of ours, here's our new privacy policy. We see lots of this and it's happening from lots of different organizations that we work with. So I think people are starting to see it and feel it, are starting to feel like it's real now, not just something we've been talking about for a long period of time. But I think also in terms of potentially what the impact of this will be, that I think organizations are starting to look at some of the major tenants that sit underneath GDPR, how are they going to address those, and what does that mean for the data subject? Like people like me, for example, I'm a data subject. What does it all mean for me? And I think they realize-- >> John: As an individual you have data rights. >> Exactly. Absolutely. >> The concern I have, I had a big rant on Facebook, it was good conversation, but here's the thing. It's like, you know, when laws came out, like it's so hard being so obviously, when your public, you're ready to go public, you have all the infrastructure to comply with all those regulations, a lot of people aren't prepared for GDPR because, where their, they might not even know where their data is, >> Absolutely. >> what's the format, what's the schema, they don't have mechanisms in place, 'cause there's IT legacy involved. (laughing) I mean GDPR, great on paper, everyone's got their own rights it sounds good, you know, but when you have to get under the hood and saying, hey Enterprise, you know that stuff you've been putting in drives, and the storage administrator quit 10 years ago and, you don't know what's going on and, guess what? You're now liable. >> Andrew: Major issue. >> People were scared. So, this is a problem, how can someone get ready, 'cause just like when people go public they have to be ready hire all these, process stuff, what do you guys see that, I mean Informatica has some solutions, I'm sure, but, what's the client relationship like for you guys as you talk to customers? >> I think it kind of varies, some industries seem to be a little bit more advanced in their thinking so, regulated industries for example, they're kind of used to regulation and compliance, they kind of get a lot of these things, so I think some of those have found this process a little bit easier. I think some industries, this is generally quite new, some of the ideas, some of the practices that come with GDPR I think are also quite new, for some of these industries. >> Internet companies, fast and loose, if you're fast and loose you're going to be doing a lot of work. >> But ultimately, when you think about, a lot of what GDPR brings to the data subject, that people like me and my colleagues, then, a lot of that then is about these rights, and the ability for us to be able to actually take back more control of our data, 'cause fundamentally it is our data. So if we have more control, then it's about how organizations help us with those rights, and help us move along that journey of what we can now do with our data, and what GDPR gives us. >> And just to be clear too, we reported on this in depth with Wikibon, SiliconANGLE, and theCUBE, GDPR it's been clear it's going to be a process. They're going to look for compliance, they're not lookin' for everyone to be like, they want to see directional progress, right, so it's not like the hammer's going to come down tomorrow, but people now, data subjects now can bring claims against companies, so. >> Actually John, I think it's, you're right but, we have a client, the Chief Privacy Officer of one of our clients, made the observation that had the Equifax breach occurred after Friday in Europe, it would have cost that company 160 billion dollars, My guess is what's going to happen is, they're going to look for that direction unless a company has a serious problem, then they're going to use GDPR to levy fines, and generate some, and remunerate back to the people affected, some real relief would you agree with that? >> Actually I see GDPR in a slightly different way, maybe that's just because it feels quite personal to me, because I feel it's something that's going to be a part of my life. And actually I think it's about organizations really respecting my data, and therefore respecting me. So, you know, when we talk about fines, yes I'm sure there's probably going to be some of those. A lot of the customers I talk to are actually, they're worried about reputational damage. You know, what's going to happen to their brand, what's going to happen to their image if something happens? And that, for many organizations, is far more serious and significant than any kind of fine potentially may be, so it's actually-- >> And there's a mega trend goin' on, you're seeing with blockchain and decentralized applications where people who create the value should capture it, hence the personal relationship to your data, and we all look at Facebook and say, hey I signed up for a free app so I could meet my high school friends and see them, do some things on Facebook, but I didn't sign a contract to give you my data to, have the election be thrown in the US, (laughing) so it's kind of like, wait a minute, what're you doin' with my data? >> Talk about blockchain and immutability of the data, if you have, does GDPR make it more difficult to use technologies like blockchain? >> I think organizations just have to look at GDPR and say, you know, it's a principles-based regulation, so it's not going to tell you, you know, the details of how you should do things, but it's tryna take you on a journey around kind of how you can then start to bring a lot more respect to the data subject, because of the data that you're managing and processing for them. The organizations are going to have to look at that and say, how do we take all of this, and how do we start to move it into our environment, whether it be blockchain, or any other technology, how does it apply, and do we have to make some changes, do we have to think tactically or strategically, I think organizations are going to have to look at this and say what does this mean longer term? Because I don't think anyone really knows right now. >> Well I want to get your thoughts on this, as Head of Solutions and Governance we chatted with the Deloitte guys came on earlier, and they kind of laid out, I mean, I'm just paraphrasing the playbook, data engineering, data governance, data enablement, so they're kind of looking at it, you know, as kind of a playbook. Got to do the engineering work to figure out where the data is, throw the catalog in there, MDM, there's a variety of solutions out there, and tools for other things, and then the governance piece is super critical. Then the enablement is where, then you're in an ideal state for a GDPR, or wherever where, everything's foundationally built and engineered and governed, ideally you could have things like consensus, you could have some security, do you see it the same way, and how are you guys at Informatica talking to customers? Does that jive with some of the things that you guys--? >> Yeah, it does, it resonates quite well, so, I think because it's a principles based regulation then, actually that has some potentially quite interesting and beneficial impacts for some of our customers, so a lot of our customers are going through some kind of transformation, mostly digital transformation, and you think about the principles that GDPR gives you, I look at that and I think, but actually some of these are just good data management practices and principles, it happens to be around personal data for GDPR right now but those principles are just valued for probably kind of any kind of data. So if you're on a digital transformation journey, with all the change and with all the opportunity that brings actually these practices and principles for GDPR they should be helping drive things like your digital transformation, and for a lot of our customers change is the only constant they've got. So actually managing all this, whilst everything is changing around you, it's tough for a lot of them. >> Opensource has been a big driver in our industry, we've seen some there, open always beats closed, and having all the open data's key, have you seen any GDPR impact around being open, is there like, opensource groups that are out there helping companies, you guys obviously can get called on, but what dose the customer do, I mean like, Peter and I say hey, maybe we're impacted by GDPR, who do we call? Is there an opensource community that can help with, you know, terms of service, if they want to go down the right roads of data hygiene or data setup cataloging, what do they do, I mean what's the? (laughing) I mean it's the shock, and people going well we're not really kind of where we should be, what do they do? With any movement? >> Yeah, I've seen quite a bit of movement, so, I think probably one of the biggest single challenges that I've seen is, for many organize--many of our customers, they'll be saying to us, okay, so what should we do in this circumstance? And actually that's really tough for us to answer, because it's a principles-based regulation than actually somebody needs to look at that, that's probably the legal or the privacy teams, say well what does that mean for us? How do we take that, and then come up with a set of requirements that says this is what we need to do for our organization, in our markets, in our territory, for example? So there's probably no one-size-fits-all answer, so, there's legal aspects to this, there's privacy aspects, data management, risk, compliance, opensource groups they can give opinion, but it's nothing more than that. >> And they might not have the talent internally to actually understand culturally what the principle is, so they got to call in the consultant, so our integrators, Deloitte-- >> Exactly, exactly. >> But fundamentally, it seems that one of the things GDPR is going to do, is it's going to force companies, force enterprises, to be very explicit and declare what attributes of that personal data they make money with. And be very, and effectively open that up, and be much more, as you said, what'd you call it private subject or? >> Data subjects. >> Data subjects, they're going to have to be more explicit declaring to data subjects, in simple terms, how they're making money off of data, or how they're avoiding that problem. >> Yeah, I think organizations, and I think about some of the privacy notices I've received, recently for example, I think, what organizations are doing, I think they're trying to explain to people, this is the kind of data we have, these are types things that we have to do with it, sometimes it's maybe regulatory, but actually other times it's about, these other types of business activities, so they're starting to be a lot more transparent, I think, in what they're doing with the data. Is it transparent enough? I guess time will tell. And the reaction of data subjects will also be the indicator whether people think that's acceptable or not, I don't think we know yet, it's early days, but actually that change, I think over time what we'll start to see is organizations are going to be looking at the way that they manage data, I think transparency, I think will be a huge topic for a lot of industries, I think that the notion of kind of having a respect for people and their data, and how it then leads to trust. So lots of industries have kind of lost the trust of people around the ability to manage their data, so how do they get that back? Well potentially GDPR might be a way of helping people access to that. >> Many of these guys, they got to get their act together and build up a quality data policy around it. Okay, final question for ya, I know we're tight on time, but I want to get it out there, what do you guys have for solutions for customers, what are you guys offering, specifically for products, that helps them with the compliance, any gap analysis, I mean what do you guys do for customers, what's the solution? >> It's, it's in a couple of different areas, so I'm going to tackle a couple quite specific things, then something slightly a little bit broader, so, organizations, I think you were mentioning earlier, just kind of knowing what their data is. Well actually we have some fantastic technology to go and discover, you know, or to make the discovery of that data, that's great for organizations 'cause that, today, a lot of them are doing it by hand, they're doing it manually, so discovery of data really important, so we have technology in that space. The ability to go and mask an archive, get rid of data, if you don't have a legitimate reason for having data, then why have you got it? So technology to help you, you know, get rid of that data. Other types of technology about being able to connect what you have in terms of your physical data assets, to actually your interpretation of what GDPR means to you and your business, that's fantastic, the ability to connect those together, that's our governance environment, and then technologies around, kind of, building that view of the data subject, so we can then enact all these rights that people like me have now got, but also then too, can sense that we may potentially have to give, how do you associate that with all the complexity of the data? So we have technologies in our massive data management space to do that. But I think probably the one thing that I hear fairly consistently for customers, it's not necessarily about those isolated kind of views, of the technology and how it solves specific problems, I think they're looking at it quite wholistically, and they're looking at solutions that can really automate a lot of this, as much as possible, they're looking for solutions that scale, some of these are very large, complex organizations, it's not small amounts of data, in cases, some cases, it's huge amounts of data, so they're tying to cope with this scale, but they're also looking to solve some very specific problems. So I think there's kind of a combination of things, which I think plays really well, through Informatica's core strengths. >> And it also creates awareness for companies to put data as a strategic centerpiece, not as a side thing, bring it right to the front and center. >> Andrew, thanks for sharing the insight on theCUBE, appreciate your time. theCUBE, live coverage here in Las Vegas at the Venetian, this is exclusive coverage of Informatica World 2018, I'm John Furrier with Peter Burris, stay with us for more, here on day one of two days of coverage. We'll be right back, after this short break. (bubbly music)

>> 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)