>> Live from the MIT Campus in Cambridge, Massachusetts, it's theCUBE. Covering the 12th Annual MIT chief data officer and Information Quality Symposium. Brought to you by: SiliconANGLE Media. >> Welcome to theCUBE's coverage of MITCDOIQ here in Cambridge, Massachusetts on the MIT Campus. I'm your host, Rebecca Knight, along with my co-host, Peter Burris. Peter, it's a pleasure to be here with you. Thanks for joining me. >> Absolutely, good to see you again, Rebecca. >> These are my stomping grounds. >> Ha! >> So welcome to Massachusetts. >> It's an absolutely beautiful day in Cambridge. >> It is, it is, indeed. I'm so excited to be hosting this with you, what do you think, this is about chief data officer information quality. We're really going to get inside the heads of these chief data officers, find out what's on their minds, what's keeping them up at night, how are they thinking about data, how are they pricing it, how are they keeping it clean, how are they optimizing it, exploiting it, how are they hiring for it? What do you think is the top issue of the day, in your mind. There's a lot to talk about here, what's number one? >> Well, I think the first thing, Rebecca, is that if you're going to have a chief in front of your name then, at least in my mind, that means the Board has directed you to generate some return on the assets that you've been entrusted with. I think the first thing that the CDO, the chief data officer, has to do is start to do a better job of pricing out the value of data, demonstrating how they're turning it into assets that can be utilized and exploited in a number of different ways to generate returns that are actually superior to some of the other assets in the business because data is getting greater investment these days. So I think the first thing is, how are you turning your data into an asset, because if you're not, why are you achieve anything? >> (laughs) No, that's a very good point. The other thing we were talking about before the cameras were rolling, is the role of the CDO, chief data officer, and the role of the CIO, chief information officer, and how those roles differ. I mean is that something that we're going to get into today? What do you think? >> I think it's something certainly to ask a lot of the chief data officers that are coming on, there's some confusion in the industry about what the relationship should be and how the roles are different. The chief data officer as a concept, has been around for probably 10-12 years, something like that. I mean, the first time I heard it was probably 2007-2008. The CIO role has always been about information, but it ended up being more about the technology, and then the question was, what does a Chief Technology Officer does? Well it was a Chief Technology Officer could have had a different role, but they also seem to be increasing the responsible for the technology. So if you look at a lot organizations that have a CDO, the CIO looks more often to be the individual in charge of the IT assets, the technology officer tends to be in charge of the IT infrastructure, and the CDO tends to be more associated with, again, the role that the data plays, increasingly associated with analytics. But I think, over the next few years, that set of relationships is going to change, and new regimes will be put in place as businesses start to re-institutionalize their work around their data, and what it really means to have data as an asset. >> And the other role we've not mentioned is the CDO, Chief Digital Officer, which is the convergence of those two roles as well. How do you see, you started out by saying this is really about optimizing the data and finding a way to make money from it. >> Or generate a return. >> Generate a return, exactly! Find value in it, exactly. >> One of the things about data, and one of the things about IT, historically, is that it often doesn't generate money directly, but rather indirectly, and that's one of the reasons why it has been difficult to sustain investments in. The costs are almost always direct, so if I invest in an IT project, for example, the costs show up immediately but the benefits come through whatever function I just invested in the application to support. And the same thing exists with data. So if we take a look at the Chief Digital Officer, often that's a job that has been developed largely close or approximate to the COO to better understand how operations are going to change as a consequence of an increasing use of data. So, the Chief Digital Officer is often an individual whose entrusted to think about as we re-institutionalize work around data, what is that going to mean to our operations and our engagement models too? So, I think it's a combination of operations and engagement. So the Chief Digital Officer is often very proximate to the COO thinking about how data is going to change the way organization works, change the way the organization engages, from a strategic standpoint first, but we're starting to see that role move more directly into operations. I don't want to say compete with the COO, but work much more closely with them in an operational level. >> Right, and of course, depending organization to organization. >> It's always different, and to what degree are your assets historically data-oriented, like if you're a media company or if you're a financial services company, those are companies that are very strong lineages of data as an asset. If you're a manufacturing company, and you're building digital twins, like a GE or something along those lines, then you might be a little bit newer to the game, but still you have to catch up because data is going to mush a lot of industries together, and it's going to to be hard to parse some of these industries in five to ten years. >> Well, precisely, one of the things you said was that the CDO, as a role, is really only 11-12 years old. In fact that this conference is in its 12th year, so really it started at the very beginning of the CDO journey itself, and we're now amidst the CDO movement. I mean, what do you think, how is the CDO thinking about his or her role within the larger AI revolution? >> Well, that's a great question, and it's one of the primary reasons why it's picking up pace. We've had a number of different technology introductions over the past 15 - 20 years that have bought us here. The notion of virtualizing machines changed or broke that relationship between applications and hardware. The idea of very high speed, very flexible, very easy to manage data center networking broke the way that we thought about how resources could be bought together. Very importantly, in the last six or seven years, the historical norm for storage was disc, which was more emphasized how do I persist the data that results from a transaction, and now we're moving to flash, and flash-based systems, which is more about how can I deliver data to new types of applications. That combination of things makes it possible to utilize a lot of these AI algorithms and a lot of these approaches to AI, many of which the algorithms have been around for 40-50 years, so we're catalyzing a new era in which we can think about delivering data faster with higher fidelity, with lower administrative costs because we're not copying everything and putting it in a lot of different places. That is making it possible to do these AI things. That's precisely one of the factors that's really driving the need to look at data as an asset because we can do more with it than we ever have before. You know, it's interesting, I have a little bromide, when people ask me what's really going on in the industry, what I like to say is for the first 50 years of the industry, it was known process, unknown technology. We knew we were going to do accounting, we knew we were going to do HR, there was largely given to us legal or regulatory or other types of considerations, but the unknown was, do we put it on a mainframe? Do we put it on a (mumbles) Do we use a database manager? How distributed is this going to be? We're now moving into an era where it's unknown process because we're focused on engagement or the role that data can play in changing operations, but the technology is going to be relatively common. It's going to be Cloud or Cloud-like. So, we don't have quite as, it's not to say that technology questions go away entirely, they don't, but it's not as focused on the technology questions, we can focus more on the outcomes, but we have a hard time challenging those outcomes or deciding what those outcomes are going to be, and that's one of the interesting things here. We're not only using data to deliver the outcomes, we're also using data to choose what outcomes to pursue. So it's an interesting recursive set of activities where the CDO is responsible for helping the business decide what are we going to do and also, how are we going to do it? >> Well, exactly. That's an excellent point, because there are so many, one of the things that we've heard about on the main stage this morning is the difficulty a lot of CDOs get with just buy-in, and really understanding, this is important, and this is not as important or this is what we're going to do, this is what we're saying the data is telling us, and these are the actions we're going to take. How do you change a culture? How do you get people to embrace it? >> Well, this is an adoption challenge, and an adoption challenges are always met by showing returns quickly and sustainably. So one of the first things, which is why I said, one of the first things that a CDO has to do is show the organization how data can be thought of as an asset, because once you do that, now you can start to describe some concrete returns that you are able to help deliver as a consequence of your chief role. So that's probably the first thing. But, I think, one of the other things to do is to start doing things like demonstrating the role that information quality plays within an organization. Now, information quality is almost always measured in terms of the output or the outcomes that it supports, but there are questions of fidelity, there are questions of what data are we going to use, what data are we not going to use? How are we going to get rid of data? There's a lot of questions related to information quality that have process elements to them, and those processes are just now being introduced to the organization, and doing a good job of that, and acculturating people to understanding the role of equality plays, information quality plays, is another part of it. So I think you have to demonstrate that you have conceived and can execute on a regime of value, and at the same time you have to demonstrate that you have particular insight into some of those on-going processes that are capable of sustaining that value. It's a combination of those two things that, I think, the chief data officer's going to have to do to demonstrate that they belong at the table, on-going. >> Well, today we're going to be talking to an array of people, some from MIT who study this stuff >> I hear they're smart people. >> Yeah, maybe. A little bit. We'll see, we'll see. MIT, some people from the US Government, so CDOs from the US Army, the Air Force, we've got people from industry too, we've also got management consultants coming on to talk about some best practices, so it's going to be a great day. We're going to really dig in here. >> Looking forward to it. >> Yes. I'm Rebecca Knight, for Peter Burris, we will have more from MITCDOIQ in just a little bit. (techno music)