 Live from Las Vegas, extracting the signal from the noise. It's the Cube, covering IBM Insight 2015. Brought to you by IBM. Now your host, Dave Vellante and Paul Gillin. We're back in Las Vegas, everybody. This is the Cube. We're here at IBM Insight 2015. Ritika Gunners here. She's the vice president of information integration governance within IBM's analytics business. Ritika, welcome to the Cube. Thanks for coming on. Thank you. I'm delighted to be here today. So we were talking off camera about sort of what all that means, you know, IBM's famous for its long title. So break it down for us. What's your scope? Where do you fit inside of the 17? It's growing now, 20% of years. It's on its way to $30 billion. I've said IBM analytics business. Tell us where you fit. That's billion, not million. Billion, I mean a big B. A big B. So yeah, information integration and governance. It sounds like a really complicated thing, but when you break it down, it makes fundamental sense. If you think about the vast amounts of data that are out there, integration is really about how do you make sense and understand that data? How do I take data from multiple different data sources and be able to bring that together in a very insightful and constructive way? And the governance aspect simply means how do I know the data, where that data resides is actually trusted and that it actually makes sense so I can do things like compliance reporting if I have to. I understand the lineage of where all of that data comes from. To me, governance is really about making sure the right people have access to the right data at the right time. And that's really important in today's environment. So when the federal rules of civil procedure changed in 2006, where electronic evidence became admissible, your business exploded. Absolutely. Everybody looking for the smoking gun and lawyers came out of the woodworks trying to sue large companies that didn't have a process and people sort of scrambled. And they started with, okay, let's plug the hole with email archiving. Yeah, we got that checked, but there's so much more to what you have to do. And then in the 2010s, if you will, the whole thing flipped where data was once viewed as a liability and now it's becoming an asset. I wonder if you could sort of talk about your strategy in terms of that balance sheet of data as information, really, as an asset versus a liability. How has that affected your business? Absolutely. I think that there has been a real focus traditionally on governance being seen as something that is really overwhelming, centralized, and is very process-oriented for businesses. And that is true in the sense of you have to prove that data, as I mentioned, that data is in the hands of the right people. But there's another trend that's emerging very vehemently in the market today and that is the access for self-service data, the line of business. CFOs, CIOs, everyone in the line of business wants access to their data and they don't want to deal with IT and the time it takes to be able to get that data. So this notion of democratization of data is extremely important and governance plays a really important role there too because you want to make sure that, for example, the CIO has access to the data that he needs and the data may not be quote-unquote of the right quality but he can make pretty significant decisions based on the data that he has with good enough data because there's a lot of pressure on the line of business to make decisions in real time and we don't have the luxury of waiting like we used to because those insights are really important to get now. So used to be, not that long ago, okay, how do I defensively delete data? Now it's, I presume the general counsel still wants to do that but there's, as you mentioned, the line of business they want access to the data so they can turn it into gold. So how do you see that shift in the market and how is IBM responding and what are customers asking you to do? In terms of the shift between archiving to access of the data? Yeah, well, I mean, again, there's this, the general counsel, he or she is saying, wait, wait, we got to delete that, we have to be really strict about that policy but then you've got the line of business tension saying, well, no, we don't want to delete anything, we want to keep it all forever. So who wins in that battle? I mean, it's a balance, but. It is a balance and I have to tell you the line of business is winning more and more every day and they have to for the decisions that they have to make for the business and because of that, we're seeing a big push towards what we're calling a data reservoir which is a notion of, I may not need to keep everything in data that is immediately accessible but I want to have it accessible in some way, shape or form so I can make decisions on all data that exists and so that shift to be able to provide that type of access to reservoirs, to the line of business is where we're seeing a lot of the shifts happening today. We saw this morning, the focus was all on Watson Analytics in the opening keynotes. Not much talk about analytics as a data quality tool. Do you see applications of Watson? Are you getting demand for that now? Absolutely, you know, one of the things that was not mentioned this morning is do you know that the data preparation capabilities, the data cleansing and the quality capabilities are actually very pivotal to Watson Analytics and we actually announced last week that a lot of the data preparation capabilities that we are building are infused as part of that and what that means is that we have the ability to have connectivity to numerous different sources even in Watson Analytics, we're able to ingest that and do data quality and cleansing as the first step in Watson Analytics and the reason this is important is in any insight or analytics driven activity, 80% of the time, 80% of the time is actually spent cleaning the data, making sure that data has the right type of quality and it comes from the right places. You talked about data governance, giving business users more control over data governance or giving them more access to data that would have been previously strictly controlled. How are your customers balancing that need, particularly in regulated industries where this push pull is so evident? How they're dealing with the data governance push pull? With the importance of protecting and validating and tracking data and also the need to give people places to play with it. Yeah, I think it was interesting because we had an advisory council with a lot of our integration and governance clients earlier in the weekend and I think there are two trends that are really emerging in this area. The first is this notion of the chief data officer and the chief data officer having responsibility for making sure that we're giving access to the right people at the right time. And the second is, within those CDO organizations or the chief data officer organizations that are created underneath them, there are governance initiatives so that we can give more data to the line of business. So that's CDO, how are you seeing that emerge? Obviously you do a lot in financial services, presumably healthcare, maybe even government. Those are the three biggies in terms of where CDOs. What do you see? I mean, what percent of the organizations that you work with even have a chief data officer and how is that growing? It's growing quite significantly. In fact, some of the analysts that we talked about this morning, they were talking about statistics where 30 to 40% of the organizations that they're seeing right now have chief data officers where even last year it was just 10%. And that takes into account all industries. It is more concentrated in a lot of the industries that you're talking about as well. And does that individual report to the CIO, the COO, the CEO? That's a very interesting discussion as well. We talked about it this morning and initially when this notion of a chief data officer came up, they were reporting in through the CIO. And a lot of the cases, the analysts who I actually spoke to this morning says, they're seeing a lot of chief data officers now report to the CIO. And this proves to the point that this notion of data as an asset to the company is really fundamental and we're seeing that shift. Yeah, you talked about 80% of the time is spent just getting the data right. And that's so true. Only 20% of the time left over to actually add value to it. So I want to talk about how IBM is addressing that. If I'm a customer, I want to build a data factory essentially. If I'm really data driven, I want to build a data factory and have a full end-to-end data pipeline where I'm ingesting data maybe through all kinds of external sources and internal sources and I'm blending it and then I'm driving it through my operations. I mean, Pitchiano essentially described that this morning. So where does your group fit into that? Are you building the entire data pipeline? Are you a piece of that? I wonder if you could talk about that. We're definitely a piece of it. And you've heard many announcements that we've done before on really embracing open source in our organization, embracing Apache Hadoop, embracing Spark, and we're leveraging open source capabilities to help us advance a lot of the technological capabilities that we're building for that data pipeline. And as we do that, we're using the data pipelining and data preparation capabilities and infusing that all over the organization. So as I talked about, we're using data preparation capabilities as part of Watson Analytics. You'll see data preparation capabilities as part of all different types of analytics, analytics for the data scientist, as well as for the data engineer. And that's what you're starting to see and the changes that we're trying to make so that it not only provides continuity of having the same data preparation type capabilities within different offerings, but it offers that continuity between the different personas in the organization. So the data scientist can use data preparation tooling just like the line of business can and kind of a view that makes sense to them. Somebody use the term citizen analytics this morning, but go ahead, please. Is the leverage point changing in corporations? I mean, it used to be that companies that own the database essentially own the customer. That's right. And now we're seeing that maybe that trend is moving upstream and the analytics are the real ownership point of the, or maybe the analytics is not a leverage point. But do you see that dynamic shifting where core database are not as important as they were? Well, core databases I think are always important, but the function of a lot of these capabilities being driven from the business is absolutely there. And we're seeing it fundamentally with many clients that we talk about. Another kind of key characteristic that came up this weekend when we were talking to over a hundred clients, they said that traditionally a lot of data integration and governance initiative started within the IT organization. Now they're actually starting with data analyst and analytics groups. So we're fundamentally seeing a shift where a lot of larger organizations are creating analytics center of competencies that are responsible for driving insight for the business. And those organizations are shifting requirements on what needs to happen downstream. What percentage of your clients, would you say are doing something really, really different with analytics? Something that is really going to change the business in a meaningful way. Oh, not, I think there's a significant number. It's probably in like the 20, 25% range right now. I think a lot of them are still trying to grasp this notion of multiple different types of content of data and making sense of that data. And as they do that, driving to what it means to drive insight and driving to change what it means to change business processes in the business itself, I think a lot of them are embarking on them, but they're not yet completely there. I would say they're more kind of driving in the insight-driven area than where it's really changing the business. They look to IBM for guidance on those questions or they look more to the Accenture's and the McKinsey's of the world. Well, IBM has a great practice there as well. It's a difference. So we have a wonderful practice. Yeah, we do have a wonderful practice to be able to do that as well. So they do look to IBM and we do consult with our clients all the time about the right direction they need to go to. I thought today's keynote on where we're moving with cognitive and where we're moving with all these capabilities to really drive clients from where they are today on understanding their data to how to build cognitive and how to build insight and how to use that to transform their business. That's what we're helping our clients with. Yeah, and again, we talked about this earlier, sort of operationalizing the analytics. Are you at the point or your clients, let's talk capabilities. Can you embed those analytics into the day-to-day operations of the organization? Are organizations ready for that? You, so let me answer both of those because there were two questions. You can absolutely embed them in your applications that you're developing. I think Mike wrote in today, talked about the APIs that Watson has. He said 30 plus and he said double over the next couple of months. As well as within our analytics group, we are developing core API level capabilities all across our analytics area to be able to embed that in applications as they're being developed. So fundamentally, absolutely we can. I think we're in the curve of adoption. We're still in the initial phase where we're starting to see clients do that. But I think that is fundamentally the opportunity for analytics is to drive some of these capabilities into applications and that's where we're gonna move to. Any other things you can share with us? I mean without giving away roadmap, just capabilities the customers are asking you, what's IBM delivering? Yeah, I think there are three different areas where we're really focusing on. As I mentioned, one is not just big data, but more data and through that I talked about kind of this notion of dirty, messy data and the data swamps and making sense of that. So that's the first area that we're really focusing on. The second area is really this, we talked about it a little bit as well, that the line of business is really demanding access for that data. So this notion of self-service data preparation is really where we're focusing on. We're doing that first through Watson Analytics as well as through some announcements that you'll hear about something called DataWorks, which is in beta right now. And that kind of key capability is gonna be infused all across the analytics portfolio. And the third we talked about is this notion of governance then being really transformed for more of a regulatory kind of space to what it means to have self-service access to that data. Oh, you mentioned DataWorks, so what is DataWorks? DataWorks is the capability that allows us to have a common set of connectivity and allows us to be able to do that data preparation and it is embedded in things like Watson Analytics today. So when you go to Watson Analytics, the data preparation capabilities is actually coming from something called DataWorks. We're keeping the line of business, who's driving it? I mean, obviously marketing is getting more of the spend. Maybe talk about the roles and maybe talk about some of the use cases that you see, let's pick financial services because it's such a popular one, but let's talk about that a little bit. Well, in the financial services area, I think there are many organizations where we're actually seeing CFOs driving certain solutions that embed some of these analytics and these data preparation capabilities. So that's one area where we're seeing a lot of use cases being driven. Okay, and so these are CFOs for sort of taking their business beyond reporting or is it, or are they really trying to drive other value? Maybe you could add some colors. Okay, in terms of the use cases that they're trying to do it for. So we see, for example, for audits, for auditory purposes, for financial reporting of what they're doing and also to do predictions of where the business is actually going and moving too. So a lot of these CFOs can actually use it to pretty much with very kind of concrete belief and confidence be able to say, here's where we need to move to in the next few quarters. And if we actually adjust certain environmental factors, we can actually grow revenue, grow pipeline by this much. So a lot of what I would call predictive and prescriptive type analytics where clients are using this to figure out what kind of key things are really impacting the revenue growth and how do we transform those? Are there ways that we can actually leverage those core contributing metrics to be able to change maybe some of where the predictions are going? Okay, so it's not just sort of a risk management umbrella. No, absolutely not. And same thing in healthcare? Are you seeing, I mean, obviously HIPAA and EMR. There's obviously the compliance side of that. But some of the more interesting use cases are, for example, doing predictive analytics on things like drugs and kind of the usage of drugs and kind of how things are interacting with each other in terms of if a client is taking two or three different types of drugs, how will they be able to interact and what kind of things can we do to mitigate what clients or what end users may actually feel by in taking three different types of drugs at the same time. So there's definitely the regulatory side, but as well as some real use cases of how it's actually affecting patient health. How do you make data governance something that business users can get excited about? I don't think anyone from the business ever wakes up every day and says, yay, governance. But it matters when it comes to how the business is being impacted of whether the right people are getting access to the right data or in terms of whether that the companies are managing kind of their compliance areas and they're managing the access to that data. So it's not something that I think that any company wakes up and says we need a governance initiative, but it really does enable this growth of data and it enables kind of the sets of kind of compliance and regulations, regulatory compliance that we need to have. All right, Ritika, we're out of time, but last question, where are we in 2015, going into 2016, how would you summarize kind of the state, I mean, there's so many changes in your business, so where are we today and where are we headed? We are in such a transformative period and I think that you're going to see a lot of things happening for end users. You're going to see lots of these types of capabilities being infused all across the analytics portfolio and really driving change for the business. Ritika Gana, thanks very much for coming on theCUBE, it was really a pleasure having you. Well, thank you, I really enjoyed it. All right, keep it right there, but we'll be back with our next guest is theCUBE, we're live at IBM Insight, check out ibmgo.com, join the crowd chats right back.