>> 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)