 Live from San Francisco, it's theCUBE, covering Informatica World 2017, brought to you by Informatica. Hey, welcome back everyone. Live here in San Francisco, Informatica World 2017, this is theCUBE's exclusive coverage from SiliconANGLE Media. I'm John Furrier, host of theCUBE with my co-host, Peter Burris, head of research at SiliconANGLE Media, also general manager of Wikibon.com, doing all the cutting edge research on data, data value, what's it mean, cloud, et cetera, and check it out at Wikibon.com. Next guest is Suresh Menon, who's the SVP and general manager of master, data management at Informatica, the key to success, the central brains, MDM, great hot area. Suresh, thanks for coming on theCUBE, appreciate it. Thank you for having me. So MDM has been in almost all the conversations we've had, overtly and some kind of implied through it. Take a minute to describe what you're managing what the role is in that data fabric, in that data 3.0 vision, why master data management is so important. Right. If you think about master data management, you know, there are two ways to look at it. The first one would be in terms of MDM, first of all, the definition. Master data is really about all the business critical entities that any organization is, you know, should be concerned about. So if you think about customers and products, that's, you know, the two most critical ones, and that's really where master data management began, but then you could also think about employees, locations and channels, suppliers, as all being the business critical entities that every organization should care about. Master data management is about making sure that you have the most trusted, authoritative and consistent data about these entities, which can then fuel the rest of your enterprise. MDM has been used in the past to fulfill certain specific business objectives or outcomes, such as improving customer centricity, making sure that you're onboarding suppliers with a minimal amount of risk, and also to make sure that your products, as being described and syndicated out to the web, are done in the most efficient manner. You guys had an industry perspective Monday night. What was the insight from the industry? I mean, how was the industry, because Ben Alpeter's got a perspective on this, he thinks there's opportunities, big time to reposition kind of how this is thought, but what's the industry reaction to MDM? The industry reaction is renewed excitement in MDM. MDM started off about 10 years ago. It where a lot of early adopters were there, and as usual with a lot of early adopters, there was a quick dip into the cycle of disillusionment. What we've seen over the last couple of years in the excitement from Monday is the resurgence about MDM, and looking at MDM as being a force of disruption for the digital transformation that most organizations are going through, and actually being at the center of that disruption. Well, it's interesting, I almost liken this to, I'm not a physicist, I wish I was perhaps, but physics encounters a problem, and then people look at this problem and say, oh my goodness, how are we going to solve that? And then somebody says, oh, I remember a math technique that I can apply to solve this problem, and it works beautifully. I see MDM almost in the same situation. Oh, we've got this enormous amount of data, it's coming from a lot of different sources. How do we reconcile all those sources? Oh, wait a minute, we had this MDM thing a number of years ago. How about if we took that MDM and tried to apply it to this problem, would it work? And it seems to fit pretty nicely now. Do you agree with that? I agree with that. There's also, although a kind of a redefinition of MDM, because sometimes when you look at what people think about, oh, that was MDM from seven years ago. How does that apply to the problems I'm dealing with today, with IOT data, social network data, interaction data that I need to make sense of, was an MDM for the structured world? And how does it apply for the new world? And this is really the third phase of MDM, going from batch analytics, fueling all real-time applications, whether it was marketing, customer service and so on. And now, to providing the context, and that is necessary to connect dots across this billions and billions of data that is coming in, and being able to provide that insight and the outcome that organizations are hoping to achieve. You mentioned, I just want to jump in for a second, because you mentioned on structured data, there's also the speed of data, getting the value. So data as a service, these trends are happening the role of data isn't just, okay, unstructured, now deal with it. You got to be ready for any data injection to an application being available. I mean, that's a big factor too, isn't it? Absolutely, and organizations are looking at what used to be a batch process that could run overnight, to now saying, I'm getting this data in real-time, and I need to be able to act on it right now. And this could be organizations saying, I'm using MDM to connect all of this interaction data that's coming in, and being able to make the right offer to that customer before my competition can. So making that, shortening that time between getting a signal to actually going out and making the most relevant offer has become crucial. And it also applies to other things, such as you identify risk across any part of your organization, being able to act upon that in real-time, as opposed to find out later and pay the expense. So I, and I know this is not a perfect way of thinking about it, perhaps will be a nice metaphor for introducing it on the side. I've always thought about MDM as the system of record for data, right? And as we think about digital business, and we think about going after new opportunities and new types of customers and new classes of products, we now have to think about how we're going to introduce and translate the concept of design into data. So we can literally envision having a, what that new system of record for data is going to look like. What will be the role of MDM as we start introducing more design principles into data? Here's where we are, here's where we need to be, here's how we're going to move MDM being part of that change process. Is that something you foresee for MDM? Absolutely, and also the definition of, MDM in the past used to be considered as, let's take a small collection of slowly changing attributes and that's what we master through the course of time. Instead now, MDM is becoming in this digital age. As you're bringing in tens of thousands of attributes, even about a customer and a supplier, MDM being part of that process that can grow and at the same time, the small collection of attributes important as a kernel inside of this information, it's that kernel that provides the connection, the missing link if you will, across all of these. And absolutely, it's a journey that MDM can fuel. We think that's crucially important. So for example, what we like to say is we can demarcate the industry or we think we're in the middle of a demarcation plan, I guess I should say, where for the first 50 years we had known process, unknown technology. Now we're looking at known technology, generally speaking, but extremely unknown process. Let me explain what I mean by that. That we used to have very stylized, as you said, structured data. Accounting is a stylized data form, slow moving changes, et cetera. And that's what kind of MDM is originally built for to capture that system of record for those things. Now we're talking about trying to create digital twins of real world things that behave inconsistently, that behave unpredictably, especially human beings. And now we're trying to capture more data about them and bring them into the system. Highly unstructured, highly uncertain, learning and training. So help us connect this notion of machine learning, artificial intelligence back to MDM and how do you see MDM evolving to be able to take this massive new and uncertain types of data, but turn it into assets very quickly? Absolutely. It's a crucial part of what MDM is all about today and going forward into the future. It is the combination of both the metadata understanding about what it is that these data sets are going to be about and then applying artificial intelligence through machine learning on top of it so that MDM was always about well curated data. How can you curate data, human curation? How is that possible when you've got these real time transactions coming in at such high speed and such high volume? This is where artificial intelligence can detect those streams, be able to infer the relationships across these different streams and then be able to allow for that kind of relationship exploration and persistence, which is key to all of this. So completely new algorithms that are being built now. Metal augmented, enhanced master data, or abstracted away, what's the impact? Like Claire, for instance, what's the impact of MDM? More relevant, less relevant? Even more relevant and three key areas of relevance. Number one is about automating the initial putting together about MDM and then also automating the ongoing maintenance, reacting to changes both within the organization and outside the organization and being able to learn from previous such interactions and making MDM self-configuring. The second part of it is stewardship. If you think about MDM in the past, you always had stewards, a small number of stewards in an organization who would go out and curate this data. As we now have tens of thousands of business users across the organization saying, I want to interact with this master data, I have a role to play here. For those business users now, you have tens of thousands of them and then thousands and thousands of attributes. Machine learning is the only way that you can stop this data explosion from causing a human explosion in terms of how do you manage this? Yeah, no, no. So MD, just let me test it. MDM both is going to be improved through these technologies, but MDM also has to capture these crucial new sources of data and represent it to the business. There's all these artificial intelligence systems and machine learning stuff is going to be generating data that has to be captured somehow and MDM's a crucial part of that. So let me ask you a question. If we can boil this down really simply. He's excited about MDM. Look, I'm excited about data. This is so, if we kind of think about this, we had an accounting system, let me step back, in the world where we were talking about hard assets, we had an accounting system that had a fixed asset module. So we put all our assets in there, we put depreciation schedules on it, we said, okay, who's got what? Who owns it, who owns other things? Is MDM really become the data asset, the data asset system within the business? Is that too far a leap for you? I don't think so. I mean, if you think about, if master data was all about making sure that the business critical data, everything that the organization runs on, the business is running on. And now if you think of that, that's the data that's going to fuel or enable this digital disruption that these organizations want to do with their data. MDM is at the heart of that. And finally the last piece, I think to your point about the artificial intelligence, the third part of where MDM increases its relevance is you have the insight now, the data is being put together, we've curated that data, we've discovered those relationships through machine learning, what next? What's next is really about not just putting that data in the hands of a user or inside of a consuming application, but instead recommending what that application or user needs to do with that data. So predict what the next product is that customer is going to buy and make that next best offer recommendation to a system or a user. So you're the GM now, okay? You got the view of the landscape, you got a business to run, charge customers for the products, subscription, cloud, on-premise license, evolving. You got a new CMO, you got to now snap into the storyline. What's your role in the storyline? Obviously the story's going to be coherent around one big message and it's going to be the new logo we see behind here. What's your contribution to the story and how are you guys keeping in cadence with the new marketing mission? Oh, you know, this has been a very closely run project, you know, this entire rebranding. It's not just a new logo and a new font for the company's name. This has been a process that began many, many months ago. It started from a look at the, you know, what the direction of our products are across MDM worked very closely with Sally and her team to come up with this. So you've been involved? Absolutely. The board started, we had both board members that they were actively involved as well. Yeah. Yeah, this has been a- What do you think about it? Are you excited? It's fantastic. You know, I think, you know, it's one of those, you know, once in a generation opportunities that we get where we've got such a broad breadth of capabilities across the company and now to be able to tell that story in a way that we've never been able to before. So extremely excited. It's going to help you get some, pull you into the wind that's blowing at your back. You guys have great momentum on the product so I congratulations. Now you got the brand is going to be building. Fantastic. Okay, so what's the final question outlook for next year? How's the business going? Are you excited by things? Very much so. You know, MDM has been across the board, you know, for Informatica and I'm sure you've seen here at the conference the interest in MDM, the success stories with MDM, large organizations like Coca-Cola and GE redoing the way they do business through, all powered through MDM. MDM has never been more relevant, you know, than it is now. And the data tsunami's here and coming and not stopping. The waves are hitting, IOT, machine learning. Right. Boxing. Boxing. Absolutely. You know, we'll enable federated MDM, you know, be able to do this on a global scale, you know, and master class. Well, to have you come into our studio and do an MDM session, you guys are like, this is a great topic. Suresh, thanks so much for coming on theCUBE. Really appreciate it. General manager of the MDM business for Informatica master data management was once a cottage industry now full blown part of the data fabric at Informatica. Thanks so much for sharing on theCUBE. We're bringing you all the master cube interviews here in San Francisco for theCUBE's coverage of Informatica world. Back after the short break, stay with us.