 It's the Cube at the MIT Chief Data Officer and Information Quality Symposium with hosts Dave Vellante and Jeff Kelly. Hi, but we're back. This is Dave Vellante and this is the Cube. We're here live at MIT IQ. MIT IQ is the Information Quality Symposium. It's an offshoot of the Chief Data Officer Conference. We were here last year at the MIT CDO and we have had, let's see, probably Jeff, I went here with Jeff Kelly. We've probably had about 30 or 40 guests over the last two years now talking about this issue, the role of the CDO, how it's evolving, where it makes sense and really where it's applicable. Pamela Wise Martinez is here. She's a senior strategic enterprise architect at the Office of the Director of National Intelligence and taking a very wide purview trying to make things more standardized and more common within the government. Very good to have you here and welcome to the Cube. Thanks for coming up. Thank you, thank you. So describe your role a little bit. We're talking about off camera and it's a big scope that you have. Talk about it a little bit. Sure, as the enterprise architect, strategic enterprise architect, I really helped the program manager for information sharing environment to really lay out the portfolio of common good. So what does that really mean, common good? So the things that we focus on is interoperability, data standardization, disciplines around information technology, disciplines around business architecture. So all those things really bring together best practices for how you deliver services for interoperability, how you deliver data. And at the highest level, what frameworks make sense for you as an organization? So you may have organizations that are quite frankly really good at doing something like sharing information. So how do you take what they're doing and share that in a way that other organizations can break it down into chunks that make sense for them? So you're at the intersection of business and technology. Yes. So you're an enterprise architect? I do consider myself an enterprise architect, although as I come to this forum and I speak with people like Jim Ming and Professor Dr. Wang, I understand the need for this chief data officer. So the enterprise architect may in some ways fall under the chief data officer is what I understand. And that makes a lot of sense because the CIO is really focused in lots of ways on operational aspects and who is minding the shift for the strategic portion of what the organization should be doing. Certainly the CIO does some of that and they do quite a bit of it, but who better than the enterprise architect would sort of lay out that portfolio? And then who better than a data scientist or a chief data officer will be able to utilize it? So I wonder if we can unpack that a little bit because it's an interesting point of discussion and I think a lot of organizations are struggling with this. So you think of an enterprise architect, oftentimes that enterprise architect will reside within the office of the CIO or even maybe be part of the CTO team. Absolutely, that's correct. So you're proposing a possibility that the enterprise architect actually could have, maybe it's a matrix, but also in some cases could be part of the chief data officer. I think take more of a data-driven role. Absolutely. Do you feel like that's a transformation that's occurring because of all this intense focus on data analytics and becoming data-driven or is that just sort of a natural sort of outgrowth and evolution? Yeah, I think you hit it right on the head. It is a natural evolution because the enterprise architect really focuses on both. They focus on technology and they focus on business. Well, what does that really mean, the technology roadmaps and then the business capability? So you want to tie both of those things together so as part of my mission is really understanding what the business, the capabilities, and so in the federal government, that really means unpacking the mission, the capability, the functions, the applications. Well, the chief data architect or the chief data officer will really have a strategic focus on where that data is going from an enterprise perspective, how it's being used. And the enterprise architect should be the facilitator and sort of really lay out those capabilities and the portfolio so the chief data officer can really take advantage of it and then speak to the CEOs and then in the case of federal government, make sure the assistant secretaries and those folks understand exactly how their data's being used, how it can better be used, how it can be more efficient, those kinds of things that work hand in hand with the CIO who's trying to deliver the platforms and the technologies and the virtualization and the cloud strategy. So the CIO is essentially a services organization, infrastructure services, that's clear, that's clean. When you start getting into application delivery, now you're starting to touch the business more, you're certainly touching more of the data and this is where there's some gray area. And so in my mind, I say to myself, okay, the CIO has had this vision, has had this charter, but he or she's got to keep the lights on. Stuff goes down, their phone rings and that's really where all their time gets sucked up, very tactical. Absolutely. And so the CIO, is it more of a strategic role? I absolutely agree with that. I think it is a more strategic role and more importantly, it's a role that's very well needed because the CEO of a company has a strategic role as well. I mean, that's, he's the owner, or she is the owner and the visionary of the company. Well, who is really helping to charter and to manage and to help his vision become reality, more so than a chief data officer? It has to be someone that understands the enterprise and where the data is resigning, how flexible and scalable it is, how the things that you would want to use the data for and then from the big data discussion, how would you take those analytics and use them in ways that make the business more efficient and bring back that capital? So from a business perspective, that's clear to me. From a federal perspective, now how do I use data to, I guess, enable our citizens? So the citizen aspect of it, so being more citizen-centric, even borrowing from some of the European counterparts, being more citizen-centric, how do you use the data to be more citizen-centric? Well, one of the focuses and ideals is becoming what we call life events. So life events is sort of an ideal that says, use the data, develop the data, but use it multiple times. So as a consumer or as a citizen, I'm born, I pay taxes, I have health care. I mean, all those complexities and organizations, if I have data that can be reused across those organizations, well, guess what, now we've just saved millions, perhaps billions of dollars of time and effort, resources, if we can use our data more efficiently. So that's kind of the big sort of thinking out there. I've just been fortunate to be a part of some of those great think tanks and particularly at PMISC, I've had the opportunity to learn from people who have really been thinking about these things and so, that's where we are. So let's dig a little bit into, so you mentioned that you're reusing data, so you've got those life events you described, and those different life events are probably the data that essentially, that is captured around those life events is most likely stored in the domain of different departments within the, in your case, federal government, it could be an enterprise where there's different departments. Right, state and local, yeah, now you're even talking about different layers. So clearly there's a need to share data. That's one of the key challenges there. And we've heard over the years, challenges within the federal government, the intelligence community about sharing data, connecting the dots, if you will. Inside the enterprise, we've been covering this for years and really that's been one of the big challenges. People get into their little silos, they cling to their data, they don't want to share it, the marketing department doesn't necessarily want to share it with the sales department, this is my data, you'll just, you'll screw it up, you won't understand it, that kind of thing. So there's a technical component, of course, to sharing data, but there's also kind of that political component. Well, there's privacy, there's trust. There's all those components that really say, we've got to be really smart about how we share the data, we have to have the right privileges, we have to provide the right access, we have to really think very broad and smart about how we use that data. And because we want to prevent things that could happen that may be either something that might not be, something that we want to happen. And so privacy is at the top of the list in terms of how and when and why you share the data. So this is sort of that think tank, kind of initiative that's happening, smart lane government, I'm part of that team that's working on this sort of thinking, but at PMIC, we're focused on information sharing. And it's more strategically, justice information sharing, justice information sharing framework. So how do you help public safety and how do you help healthcare? How do you share data in ways that can promote the health and wealth of the country? So have you run up against, in your experience, situations where data owners, for lack of a better term, are reluctant to share data with other stakeholders and how do you approach that? Is that a- I never see it as reluctancy, I don't believe that it's reluctancy, it's caution. I mean, because you have to be smart about how you're sharing the data. And so what strikes me is it's very much a relationship building exercise as anything else. Absolutely, it is, it takes organizational change and it takes people that understand organizational change and how you use and go in and your stakeholders and what that really means in terms of sharing information. So the catalyst for this role came out of 9-11. Yes, absolutely. And so much has changed. Absolutely. Back to early 2000s, I mean, Facebook didn't exist. I'm not even sure if Skype existed at the time. So technology, the big data, Hadoop thing wasn't around. So so much has changed technologically. You also deal probably a lot more with people and process. I wonder if you could talk about the changes in the last decade plus. Yeah, I think a lot of things have changed but the principles and the disciplines have stayed the same. So over the last 15, 20 years, I think most people were pretty focused around service-oriented architecture, modular development, trust sort of aspects of data, privacy. So those things, those principles haven't really changed. I think what's really changed is the increased necessity. The necessity of really using that data smartly and using the technology to really sort of push and help this evolution of really sharing information. So how do you work with other agencies? We talked a little bit about this off camera. I wonder if you could share it with our audience. A lot of attention was paid to when Amazon AWS won the CIA contract and Amazon put out a big push around how that's going to help sharing and services across government agency, organizational services. How do you interact with initiatives like that and there must be dozens, if not hundreds, if not thousands? Absolutely. So there's lots of what we call, there's lots of stovepipes of excellence. There's lots of organizations that are doing things really, really well. And so what we do from a PMIC perspective is really focus on those organizations that are doing things well. Then we want to learn from those organizations and then share them with organizations that what we call less mature. So you have mature organizations that frankly won't benefit as much from what we're doing because they're smart and they've done things well and they have a roadmap and they have a plan on how they're gonna use and share their data. But there may be other organizations with less funding, less political will, whatever it is. But we want to bring those organizations up to, from a CMMI perspective, which is the capabilities maturity model perspective, bring them up to a managed or even an optimized. That's not too far away from where we want to be. We want to be optimized. And so you have to look at these one, two, three, a hundred organizations, determine what they do really well and then isolate those best practices and turn them into lessons learned and things that we can share with the rest of the country. What's the incentive for the organizations to adopt your models, your frameworks? As any organization, it always comes down to money. It comes down to funding and resources. So one of the principles about service-oriented architecture and barring the technology portion of that comes down to these principles. These principles come down to agility. They come down to intrinsic interoperability. It comes down to resource dependency. And what you really want to do is really focus on less IT burden. So if you can reduce the IT burden, reduce complexity using common terms, common business practices, patterns, if you will, then you can help organizations become more efficient and ideally reduce their costs. So is part of your role sort of the selling of the business case? Is that part of it? Or is there another sort of division to that? Or is that the responsibility of the agency? Well, the agencies are very mission focused. So you take an organization large and complex like DHS, or Treasury, I can name a few others, Department of Defense, very large, very complex. Our role is not to get in front of their mission. Our role is really to support their mission by providing them tools and capabilities. So we have a project called Project Interoperability. And that project was launched in April, May. And it's fairly new and it will become increasingly improved by the lessons learned from DOD and DHS all those organizations. So our role is not to get in front of the mission. Our role is really to support their mission and what we mean by that is really helping them bringing together, bringing these communities of practice, communities of interest. So an organization like DHS, quite frankly, is very interested in sharing information with state locals, state locals interested in sharing with them for various reasons, whatever their mission is. And our role is really to facilitate that in any way that we can. So it's actually, it's a mandate. And so they see your organizations, wow, this group is doing this great work. We don't have to repeat that. We can take that, adopt it and then apply it, however we see fit. Absolutely, and they're called patterns. So there's patterns for managing identity. There's patterns for sharing information and we want to share that with the rest of the federal government and state locals as well. How do you measure success? Well, I measure success by helping, as my PN would say, building communities of sharing. So if we can build communities of sharing, we can promote the best practices and allow other organizations to learn and save money for the federal government because at the end of the day, that's what it's about. We want to save lives, save money and we want to reduce the cost. So if we can build communities of sharing around that and sharing ideals and information, that's a smart way to work in the federal government. So it's adoption of the frameworks and it's the, I guess the diffusion of those frameworks along that maturity model that you're talking about. Absolutely, absolutely. And what are the, maybe it's too early to tell, but what do the early returns say? Well, the early returns say there's a big need, right? So there's a big and huge need and also that there's value in what we're doing. There's value in having a state and local office or a fusion center, if you will, adopt some of these frameworks, adopt information sharing framework and ideals, adopt common language in terms and patterns because it saves us time and saves the money at the end of the day. So I would say at the broader scope, that's the early return. All right, we'll leave it there. Pamela, thanks very much for coming on theCUBE and congratulations on the good work that you're doing. We really appreciate it. Thank you so much. All right, keep it right there, everybody. We'll be right back after this break. 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