 Live from Boston, Massachusetts, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit. Brought to you by IBM. Now, here's your host, Dave Vellante. We're back, Caitlin Lepic is here to close the IBM Chief Data Officer Summit with me. Caitlin's an executive inside of the IBM Chief Data Officer office. Welcome back. Thank you, thank you so much. I'm breathing a sigh of relief. We had a great event and we're just wrapping up. So, you know what's kind of cool? I don't know if it's theCUBE first or not. I'm sure it isn't, because we've done women in tech shows before, but every single guest segment we had today involved at least one woman. So, that's kind of cool. We do a lot of events that there are zero women, and I'm really happy about that. So, good job IBM, props. Thank you, and I think you mentioned it earlier. We have our data divas breakfast this morning kicking things off, and we talk about the importance of diversity, and it's something we believe in, and hopefully we're able to say it's important, and then follow it up with some actions. Yeah, there's some data dudes there. Dance of data dudes, data divas and data dudes. So, put a wrapper on this event. You know, we weren't here yesterday, so maybe take us through sort of what you guys did, and some of the conversations that you heard, the topics that were of interest, some of the concerns people had. Sure. You know, we tried a new format this year. We haven't done this before, but we got a lot of feedback from our participants that what they find is most valuable in these sessions is the peer-to-peer sharing amongst themselves, both within the same industry and same background, as well as cross industry opportunities. And so we set it up yesterday where we kicked off, we had a lunch, gave folks an opportunity to network, and then we dove right into our deep dive segments. And I heard a lot of good feedback that people came prepared with use cases, with stories of how they're implementing some new initiatives within their own organizations, data analytics initiatives, starting to talk a little bit about cognitive and what that means. So I think that went really well, and we'll consider doing it that way again. And then today we reconvened for a plenary session. So we had a nice keynote this morning, Bob Picciano and Inderpal Vendari. I know you had them both on earlier, so that was great. Great keynotes and great segment. It was a lot of good discussion there. Good, good. And hitting some of those key themes, we tried to carry that throughout the day. So we had some really nice panel discussions. A couple that stood out, we're talking about governance versus innovation. And our message as we work with CDOs, you still have to care about data management, data governance. How are you orchestrating data that perhaps you're acquiring as part of your acquisition strategy? How are you pulling that in combining with data that exists within your own organization? So all of those issues. And then the innovative side. And I think we talked about this earlier. Now we've got, we're seeing this real growth in data science, engineering. We're recruiting ourselves for a data, excuse me, a deep learning expert as another area. And so you start to see the real sophistication around those technologies and opportunities. So I think that one always resonates with our attendees. The governance versus innovation and as those coexist. I'll make an observation when I first started covering this whole big data thing. Some of us made the observation we're further away from a single version of the truth than ever. And the problem with pre this big data movement is the version of the truth that we had was too narrow. It wasn't doing enough for us. And to your point, this notion of governance and bringing together some kind of data architecture gives us hope that we can actually innovate on top of this data and have a single version of the truth that meets our business needs. Absolutely. And so there's a data quality aspect of this. And this has kind of been the holy grail of this field for a long time. How can we create value beyond just risk avoidance? How can we, and data quality is part of that answer. And then cognitive is of course the other piece that obviously IBM is pushing hard. So sounds like there was a lot of discussion around that. There was, there was. And I think there's a recognition amongst leading CDOs. And we had some of the absolute experts in this space here with us the last two days, which was great. And there's this recognition that there's a progression path from the data analytics, the governance, the trust in that data through to cognitive. And it's been really interesting to see that evolve. Yet we always go back to, do you have an enterprise wide view across your organization to answer some critical business questions? And can you trust in that single version of the truth or not? And we have, I think there were some really good conversations about how do you validate the quality of your data? How are you able to answer the key questions you need to answer? And then I work for Enderpaul, our global chief data office in Enderpaul's vision is how do you then start to transform to cognition and infuse cognition throughout your business processes? So that's been a really fun, I think, vision forward as we look ahead. Well, a big part of this, too, Katelyn, is access to data. Bob had his slide with all these different roles, new personas, which is something else I want to pick your brain about. But the upper left was the citizen data scientist. So this means putting, and this, again, is one of those holy grail moments where we want to get data beyond the hardcore data wonks, insights for a few, into everybody so that this so-called single version of the truth, there's a level playing field so that somebody in the trenches can actually provide innovation throughout the organization. That's critical. Is it happening? I think so. I think it's beginning to and starting to. And I'll start first from a vision perspective. What we see, what we'd like to get to, is this idea that a business subject matter expert could step up and ask the key questions they need to conduct business, and be able to access the data, interpret it, and apply it in their decision making. I don't think, personally, I don't think we're there yet. That's our vision. And you're absolutely right. We get really excited thinking about enabling folks, regardless of where they sit in the organization, to feel comfortable asking those business questions, gathering the data that they need, feel comfortable with some of the tools. We talk a lot about the APIs that are available. In our case, available publicly on Bluemix. We encourage folks to get in there, to contribute. People are building all kinds of really cool, interesting apps on top of those APIs. And so I think we'll continue to see more and more of that, which is something we're big supporters of. I want to talk about the personas. So Bob had another great slide up there. So he said, well, it used to be the database administrator, or maybe it was the business analyst. And he had citizen analysts, which we talked about. Data scientist, data engineer, application engineer, and of course the chief data officer. So presumably the chief data officer, he or she is serving these different roles. How do you see these personas evolving? What was the discussion like here? Absolutely, a lot of questions. It's funny too, there was a really good discussion about, I'll just take a couple examples, data science and data engineer, the application engineer of those folks, and the different types. So we talk, let's say data science for example, there's a folks that are client facing data scientists. And so they want to take a client business question, where's the new business model or revenue opportunity, and they want to be able to answer that. There's others that are more of the research at scale type of data scientist. So maybe they're taking data they own, combining it with unstructured data sources, sort of text and image and social and delivering response. And so I think we used to talk about these in broad terms, the data scientist. And now we're starting to see that there are many different types and forms that are important. And that's distinct from the data engineer and the architect. And so some of these new personas are looking, I think, to do some different things, but there's that commonality where I think this Chief Data Officer role plays an important piece is enabling those personas those roles. And so they're delivering that single trusted source of data across the organization. They're encouraging their business people, their IT folks to ask critical questions to be able to get those answered. And so I think it's been exciting to see that continue to evolve. The other thing we talked about a lot on theCUBE and we talked about today was just the, not only the role of the Chief Data Officer, but Inga Paul talked about how to get started. Yes. And he said there were, I want to repeat this because it was so good. There were five initiatives that you have to undertake. Five imperatives, I should say. Three are sequential, two have to go in parallel. The first one was architecting a data strategy. The second was identifying your data sources. Third was making those data sources trusted. And then fourth and fifth, which are parallel, was partnering with the line of business and then what I call HRPD, the human resource planning and development aspects of this. Oh, I like that. Which you have to start early. Yes, that's something that was drilled into my head years ago. And so, but the interesting thing about those, the observation I would make is nowhere in here is technology, right? I mean, that's not the Chief Data Officer's primary role. You got to partner with the technology business. So talk a little bit about that discussion, the CDO and the CIO role. Absolutely. One of the first, soon after Interpol came on board, one of the first interviews we conducted was how we work in partnership with the CIO's office and the role there. And so it's a critical partnership. It's also really interesting because I think a lot of times people look at the existing technology and dictate what sort of platform we can build or what we can do. And Interpol I think has brought a vision that has certainly infiltrated our organization that let's not start from what technology we have, let's start from what opportunity we're chasing down. And in our case, for us internally, we've heard it all day. We're looking at that move to cognitive business. So what do we need? What tools and technologies do we need to get there? And so it's flipped the question a bit and it's really interesting. It's brought us all up. And as we've met with many of our CDO counterparts and peers over the last eight months and as we meet with them and we drill into that question, how is your company gonna make money? Does your data strategy get you there? And then you figure out what tools and technologies do I want to tap into? And oftentimes it's a whole mix of those. That's a key point and that's a nuance that I didn't focus on and I want to emphasize it. The data strategy piece is understanding how your organization makes money. It's not how we're gonna monetize the data. And I think that was a big mistake that a lot of people made early on is how can I sell this data? No, it's how can you utilize that data to support the activities of your lines of business? It's a critical nuance and I would tell you in some of our early CDO summits, our conversation centered around how are you gonna make money with the data you have? And then it evolves to how are you gonna make money with the data you have and perhaps some of the external data sources that are starting to come in? Are you gonna be able to monetize your Twitter, your weather, your social data? But you're right. Interpol's vision, I think our vision and as we're talking to CDOs, there's a different way of looking at it. And instead it's what's the monetization strategy of your company? How is your company not, how is it gonna make money with this data? How is it gonna make money? What products does it sell? What's the strategy? And then design your data strategy to drive that, to drive that forward and enable it. And that's an exciting new way of thinking about it that I certainly hadn't thought of before and hadn't seen a lot of conversation before. And so that's been a pretty significant shift for us. I was gonna say that follow the money and the data should follow that flow. Yes. As opposed to saying, okay, how can we package this and sell it, not that you can't. On a lot of industries you can do that. There's a lot of marketplaces going on and some exciting things there. But for a lot of organizations, it's really hard to figure out a monetization strategy. You already have one. Right, right, right. Enhance that. Okay, anything else that you wanna highlight that came out of this event? Challenges that people are trying to overcome? Any other fun facts that you wanna share? I have to say, one thing that I really feel good about is that there was a concern that as we push the envelope and start talking about deep learning, machine learning, and some of the artificial and augmented intelligence that we would exclude some CDOs or other data leaders that may say, we're just not there yet as an organization. Sounds great, a little bit too far off. And I hope, and what I've heard feedback from attendees is we've designed sessions that are inclusive of everyone regardless of where they are on the journey. So there's some folks that are really focused on that data management information governance and that's critical and that's important. Some that are starting to pilot some different analytics initiatives. Some that are starting to think, what does it mean to feed a system that gets smarter as it goes and starts thinking about the cognition? So I feel good that we've designed a program and hopefully we're designing a community that's inclusive regardless of where folks are on the spectrum. And that's a goal of mine and of ours is that we continue to do that and as we partner with CDOs moving forward. Well, we're seeing this role evolve beyond just regulated industries. So that's good to see IBM has taken a leadership there. We get on much time. Also, I'd really love to go into that. Maybe next time, maybe at Roller Watson, we can do that. See you in October. Kind of the evolution of IBM CDO office. What's next for this summit? You're talking about something in the spring next year maybe? Yes, we like to hit both coasts. So we tend to really like to do our spring event in San Francisco. So early heads up most likely will be in April of this year. I live in Palo Alto. So I'm always excited when we bring folks out to the West Coast and there's so much talent located there in the Bay Area. We do a lot of work sourcing talent with startups and other companies, which is great. So look for us in April at that summit. I mentioned it earlier. We do a lot of other events. We do some quarterly CDO roundtables, which is really nice and have CDOs join us. And then we've heard it all day, but looking forward to October and Roller Watson and Vegas. New name extending that whole, IBM never really used the term big data but what IBM did was brilliant. It took its cognitive business, its analytics business and recreated sort of the vision of what everybody used to call big data. Some many still do really driving the cognitive era, kind of created that term, creating that business certainly within the enterprise. So that's really exciting. And it's really the first conference that we've been at anyway that Ginny's speaking at. So that sort of underscores the importance of the event. And it's a great event. I think it's IBM's top event. Interconnect's really strong too, but Roller Watson's really cool. And we're gonna get Ginny on the queue, right? Yeah, absolutely. The request is in. Okay. So Ginny, like I say, if you're watching, we're like, you know, you go on CNBC a lot. We're like CNBC was in the early days. We're the future. That's right. Please join us. Well, Caitlin, thanks very much for coming on the queue. It was great to see you. Pleasure, pleasure. Wonderful having you. All right, thanks for watching everybody. This is a wrap. This was IBM CDO Summit in Boston. Stay tuned next week, big date a week in New York City. We'll be live there. We got another event going on with IBM. I talked about the NVIDIA event on Monday. Four days of theCUBE next week in NYC. Thanks for watching everybody. We'll see you next time.