>> Live from Las Vegas. It's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019. I'm your host, Rebecca Knight. We are joined by Sanjeev Vhora. He is the group technology officer and global data business lead at Accenture. Thank you so much for coming on theCUBE. >> Thanks. Thanks for having me here. >> We're hearing so much about AI lead data intelligence, and the other buzz word of course, that we hear so much of, is digital transformation. I'd love to hear your thoughts about data first approach to digital transformation. First of all, what does that mean? >> I think what we are seeing is that, if you... I think we do see that we are getting into a post digital era. Which means that in the last seven years, most bigger companies and businesses have invested in building a better customer engagement. What they did was they created properties, like portals, mobile applications, you name it, to just get better sense and touch their customers better than they were touching earlier. That was a whole investment that went in the last six, seven years. What they feel is that what's next. You do that, but does it really translate into revenue growth? Is it really translating into the experience in a sustained basis? Not one time, but on sustained basis. Every time when you touch a customer, they feel the same passion towards you. They feel that they are still engaged with you, and they want to come again to you for whatever your offering, your services or your goods. They felt that that's not actually happening. The reason why it's not happening is because the underlying data is not complete or comprehensive enough, or not accurate enough, for giving that experience. That realization is seeping up right now. They are asking for ensuring instead of looking at a use-case base approach of solving one problem for one business or one geography, is there a way to do it enterprise-wide? That a (mumbles). Point which is coming out is that they looked at that technology process that's old tradition model of looking at new businesses. Technology people processes and those three. But now they're looking to fourth element, which is foundation-call data. That's what we are calling data-first approach. You have to look at data as well, while looking at reforming your business services, and offers to the client. >> I want to touch on something you said earlier, and that is to make the customer feel passionate about interacting with you. I mean that's such a loaded, and almost romantic word to describe a customer interacting with a company. Why is it that companies are trying invoke passion, and insight passion, inspire passion? >> I think it's a way to differentiate yourself from the competition, so I think that's what in my view the businesses are doing right. Let me give an example to you to make it real, it may address your first question as well to some extent. We are working with a cruise company, one of the largest cruise companies North America based. They obviously are trying to make sure the experience of the customer is much better than had earlier. Which can resinate to a much higher revenue for them obviously, and inquisition of more customers. The friends of friends, friends of customers if you may. They had done a great job creating that digital property, and the transformation of the program. But they also realize that they are now, they realize that they don't really have a sense of who's the customer? Now that's a good question, after all this investment you still don't know who's the customer. That's where they came and talked about can I get a single view of my customer? The reason why they don't have a single view of customer is because they actually don't own all their individual customers. They only own their own individual customers, but they also work with their partners. As you can see Experian and others actually own that same customer. So they are not able to have a sense of that customer, their habits, and their behavior in one single place. They can really provide their accommodations, saying... well guest, if you're going to Italy we can probably help you this summer. >> So yes, exactly that's what I want to know; Is what, if you do have a sense of who your customer is, and that is everything from their basic demographic information, to what they do on Sunday afternoon with their families. What kinds of things then can the cruise company do to make that customer more passionate toward the cruise. >> They can do a lot, but I can tell you another example of another cruise company. Was looking at customer files and they did a fantastic job, and I'm assuming that you may have also experienced yourself. This customer they had covered the single view of customer obviously, but what they did was use a lot of IoT or sensors in their ships. They actually transformed the entire ship. Like the entire ship has been transformed to understand the customer movement, and give that flawless and seamless (mumbles) to customers. Which can help them have a pretty great on their vessels if you may. That's what they, from the day that you order the tickets for this service... From that time onward they actually send you a (mumbles). That tracks you as a person moving into the ship, and they can offer much more seamless services, and also reduces a friction of the operations staff. The staff is not in a hurry and hassle. They're actually able to understand who's actually the customer, what they want, and they are able to provide that service. So that's how they're using that feature of knowing the customer, to better serve them; being a better engagement with them. Plus also eases the operational friction in their own staff. >> So the customer wins because they feel the company gets them, and knows them, and understands them; and then the company wins because they're able to make more money off that customer, because they already have predicted what that customer wants and needs at every moment. >> And they can do more with less. They can do more with less staff, less resources. >> So one of that we are also talking a lot about here on theCUBE it's the tenth anniversary of theCUBE. So we've had a lot of these conversations, is how data is becoming a C-suite discussion, and there's this growing need to appoint a chief data officer to drive data strategy. What do you see as the evolving role of the CDO, at your company; and then also at the companies that you work with? >> We see this is a very significant step in the future. There are a lot of predictions from (mumbles) An analyst saying that there will be more and more roles, like three-fourth of the companies would have a CDO (mumbles). But I think our point is likely, you know, to augment that point I think what we believe is that, we do believe in respective of who actually owns (mumbles) That a chief data officer or a CI, or a CO. They definitely need a person at the C-suite, not below C-suite. To have that discussion at the table, and show that their data strategy is attached to their business strategy, and that's not true in many cases right now. So the data is (mumbles) which is two levels down in (mumbles), and that's why it's not getting that attention as a corporate asset as a (mumbles) asset from where you can actually extract value that you're looking at right. That's what we see; so we see a very broadened role, we see who so is in that role, we think there are a few qualities that person needs to have. The first one the person has to have a seat at the table. The second, is that person should be able to understand business quite well. (mumbles) He or she should have an insider business innovation, and if the person is tech savy it's good to have, but it's not must to have. We do believe that person should be able to prepare a strategy, and the governance of data across his or her peers. So they know that what value they are able to get from that data, and how they can share it across their functions. That's where the value comes in. Plus, beyond that the last point would be making sure whatever they do, they do responsibly. Do they actually make things work; whether it's using A.I., whether it's using any machine learning or anything else they have. They make sure that it's responsible data, and make it secure for themselves, for their enterprise, and for their customer. >> Well that is certainly a theme that we're hearing a lot about at Infomatica world. Tell me about the relationship between Accenture and Informatica. >> It's quite good, it's been good for years. We have been working together for years. The last two years, or two in a half years I think it has really taken a different shape within the new companies, and that's largely because we have really gone into a strategic discussion with the companies, and seeing what is the future. I think one thing that they are doing very well with their leadership. Anil himself is CEO; and Amit, and Tracy, and everybody else. And with our leadership is that we do believe that we are on the surface of un-tapping the value, one. Second thing is I don't think that used cases will draw the benefit which large organizations are looking at. It has to be something done at enterprise level. So think about like I think there another talk in the morning about enterprise data catalog. Amit was talking about, You need that. You need that to not do one used case for one particular business, for one particular country, or one particular customer segment. We need to do that for entire businesses across the enterprise. That can only happen if you have a sense of data, and you know how to do it effectively at scale. That's what I think that people are looking. Companies are going to be looking at the solution base, and I think it's the right timing for having the discussion. >> And there are going to be learnings that you can derive from financial services, and apply to retail, and healthcare, and all sorts of (mumble). Is that what you're finding here at Informatica World? Are you having those in conversations to learn the best practices? >> Oh yeah, I think we have our customers here; Accenture, as we have our customers here. we're presenting in different session. We had (mumbles) present today morning at eleven a.m. about how master data management can actually help you drive a better strategy on transforming your operations system like ESPE. That was never talked earlier, two years back nobody talked about saying how can MDM help you have a better transformation of your ESPE systems. Well that's where we are going. We are saying that, okay you have a trandiction systems, but you also need a system of right governance. Because all of your data, customer data or other data maybe sitting in ESPE or maybe sitting in sales force. How would you connect the dots? You need something to connect that dot so you have a single source of truth, and make sure that you know your customer, or vendor, or location, or everything else in the right fashion. >> Know your customer. So another thing I want to ask you about is the skills gap. I know that workforce of the future is something that you've worked passionately on. Passion keeps coming up in our conversation. (laughs amusingly) At Accenture. Tell us your story first in terms how you came to terms with this skill gap, and what you did at Accenture to remedy it. >> So this is four years back, and we were looking at our tech strategy, and our strategy to (mumbles) our business going forward, or where do we invest? And we are a people centric company so we are 470,000 people, that's a lot of people. In my role, one of the thing in my role is to make sure that I look at all the investment we do on our people. As CDO of our technology business, I need to make sure that we are investing in the right places. So this came to me saying that okay, will we be relevant as 470,000 people ten years from now? That's the question right? Because of A.I., because machine in our name, because people plus machine. What happens to our work force? So that's what I was trying to solve. Instead he's saying, what do we do next, and that was the whole point about workforce of the future. We will work more closely with the machines, and how will that happen. So what skills we will need as humans to work with machines, and everything else. What's going to happen in terms of automation going forward. And plus new talent which is required for the future. So we worked hard on this we built a strategy on what we need, then we did a very simple thing, we actually went to a high speed excursion, and agile sprints. We get it the few of principles actually. I can say a couple of them to use to resinate. One is the principle saying there's only (mumbles) available in the market. So don't spend creating stuff, but spend learning stuff. The second thing the chains of (mumbles) are a vision of our people vision, employee vision. It used to be saying, That you need to preform and grow. Something like that, if you preform high in our company, you'll grow faster. We changed the saying to learn and grow. So we said learning is more fundamental because performance will become automatic when you learn more. What we did was we changed. We worked really hard on the cultural aspect. And one of the things (mumbles) used to always say in the past ten years back, you used to learn a day in a month. Well that may not be enough today. Just because (mumbles) and the change of technology is much faster. It's 10x speed. So you can learn at 10x level, that doesn't mean you need to be learning at deep level for ten things, that's going to be hard for humans to do that. But you can use some help. That's what we do a 2 pronged approach. One is what we call a (mumble) training. Which means we make you more aware of everything that's happening in the world, and we give you a chance to support people-- >> I mean how do you do that, I mean that's a tall order. >> So what I did was we went to the market, and we looked at a lot of platforms. Okay you need technology to do everything. You get it right. You will be sitting here talking (mumbles). Using right technologies, right? Maybe show that our what we're talking is for (mumbles) people to watch us right. But the same thing there when we were looking at all the platforms. I looked at all things and I felt everything was great. (mumbles) It was not something which is exponential So I had to build a platform off it all, so I spent 6 months writing a whole platform. It was a really smart team, and all the logic I used was build a platform which treats or ploy a human in the center of your (mumbles) design. So we made a very personalized platform, where it helps a person to get there, and attracts you to come back. So it's very user friendly, or a very exponential platform. We call it Accenture Future Talent Platform. We deployed it across our entire businesses, we have 70+ number of people who are already being certified to their platform. They feel goof that they've gone to the next stage of their career. And now we are actually using the same platform for our clients. So we are giving them platforms so clients can use that effectively. >> From what I am hearing from you, it's about having technology skills, know how, and expertise. But also having this mindset of learning, and a hungry for learning, and wanting to know more. How do you make sure that, that culture is cultivated in the right way? >> We did some of the campaigns, so a very simple principle that we use is that like you do a marketing campaign to attract a customer. Whether he is selling a (mumbles), or selling a cruise experience, or vacation, or whatever. Use a similar principles for our own employers, and use it as learning campaigns. So marketing campaigns are learning campaigns. So one of the campaigns that we ran was, How important was it for you to be learning fit? So just like we always measure ourselves on health everyday, instead you measure yourself in learning. So our app was actually given to everybody, so you can see whether you are learning enough or not. We're in the culture of seeing how I'm doing against my own goals, but how am I doing against Rebecca's goal. >> Gameafying it, making it a little more fun. Making it a little competition. >> We also did (mumbles) as well, Because we felt that people look at their own models and say, well this person is very sexist, why would I want to be that person. That's a normal human. That's what people see so we made sure that our leaders do what they are saying. And they can buckle it down, they should start learning faster itself, from top management perspective. So people see them learning, they would say, I want to be like him. So that means I need to have the same behavior as this person. >> No, those are critical people in companies. Well, Sanjeev thank you so much for coming on theCUBE. It's been a pleasure having you. >> Same here, it was nice talking to you. >> I'm Rebecca Knight. You are watching theCUBE Informatica World 2019. (funky techno 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)