>> From Cambridge, Massachusetts, it's The Cube! Covering MIT Chief Data Officer and Information Qualities Symposium 2019. Brought to you by SiliconANGLE Media. >> Welcome to Cambridge, Massachusetts everybody. You're watching The Cube, the leader in live tech coverage. My name is Dave Vellante and I'm here with my cohost Paul Gillin. And we're covering the 13th annual MIT CDOIQ conference. The Cube first started here in 2013 when the whole industry Paul, this segment of the industry was kind of moving out of the ashes of the compliance world and the data quality world and kind of that back office role, and it had this tailwind of the so called big data movement behind it. And the Chief Data Officer was emerging very strongly within as we've talked about many times in theCube, within highly regulated industries like financial services and government and healthcare and now we're seeing data professionals from all industries join this symposium at MIT as I say 13th year, and we're now seeing a lot of discussion about not only the role of the Chief Data Officer, but some of what we heard this morning from Mark Ramsey some of the failures along the way of all these north star data initiatives, and kind of what to do about it. So this conference brings together several hundred practitioners and we're going to be here for two days just unpacking all the discussions the major trends that touch on data. The data revolution, whether it's digital transformation, privacy, security, blockchain and the like. Now Paul, you've been involved in this conference for a number of years, and you've seen it evolve. You've seen that chief data officer role both emerge from the back office into a c-level executive role, and now spanning a very wide scope of responsibilities. Your thoughts? >> It's been like being part of a soap opera for the last eight years that I've been part of this conference because as you said Dave, we've gone through all of these transitions. In the early days this conference actually started as an information qualities symposium. It has evolved to become about chief data officer and really about the data as an asset to the organization. And I thought that the presentation we saw this morning, Mark Ramsey's talk, we're going to have him on later, very interesting about what they did at GlaxoSmithKline to get their arms around all of the data within that organization. Now a project like that would've unthinkable five years ago, but we've seen all of these new technologies come on board, essentially they've created a massive search engine for all of their data. We're seeing organizations beginning to get their arms around this massive problem. And along the way I say it's a soap opera because along the way we've seen failure after failure, we heard from Mark this morning that data governance is a failure too. That was news to me! All of these promising initiatives that have started and fallen flat or failed to live up to their potential, the chief data officer role has emerged out of that to finally try to get beyond these failures and really get their arms around that organizational data and it's a huge project, and it's something that we're beginning to see some organization succeed at. >> So let's talk a little bit about the role. So the chief data officer in many ways has taken a lot of the heat off the chief information officer, right? It used to be CIO stood for career is over. Well, when you throw all the data problems at an individual c-level executive, that really is a huge challenge. And so, with the cloud it's created opportunities for CIOs to actually unburden themselves of some of the crapplications and actually focus on some of the mission critical stuff that they've always been really strong at and focus their budgets there. But the chief data officer has had somewhat of an unclear scope. Different organizations have different roles and responsibilities. And there's overlap with the chief digital officer. There's a lot of emphasis on monetization whether that's increasing revenue or cutting costs. And as we heard today from the keynote speaker Mark Ramsey, a lot of the data initiatives have failed. So what's your take on that role and its viability and its longterm staying power? >> I think it's coming together. I think last year we saw the first evidence of that. I talked to a number of CDOs last year as well as some of the analysts who were at this conference, and there was pretty good clarity beginning to emerge about what they chief data officer role stood for. I think a lot of what has driven this is this digital transformation, the hot buzz word of 2019. The foundation of digital transformation is a data oriented culture. It's structuring the entire organization around data, and when you get to that point when an organization is ready to do that, then the role of the CDO I think becomes crystal clear. It's not so much just an extract transform load discipline. It's not just technology, it's not just governance. It really is getting that data, pulling that data together and putting it at the center of the organization. That's the value that the CDO can provide, I think organizations are coming around to that. >> Yeah and so we've seen over the last 10 years the decrease, the rapid decrease in cost, the cost of storage. Microprocessor performance we've talked about endlessly. And now you've got the machine intelligence piece layering in. In the early days Hadoop was the hot tech, and interesting now nobody talks even about Hadoop. Rarely. >> Yet it was discussed this morning. >> It was mentioned today. It is a fundamental component of infrastructures. >> Yeah. >> But what it did is it dramatically lowered the cost of storing data, and allowing people to leave data in place. The old adage of ship a five megabytes of code to a petabyte of data versus the reverse. Although we did hear today from Mark Ramsey that they copied all the data into a centralized location so I got some questions on that. But the point I want to make is that was really early days. We're now entered an era and it's underscored by if you look at the top five companies in terms of market cap in the US stock market, obviously Microsoft is now over a trillion. Microsoft, Apple, Amazon, Google and Facebook. Top five. They're data companies, their assets are all data driven. They've surpassed the banks, the energy companies, of course any manufacturing automobile companies, et cetera, et cetera. So they're data companies, and they're wrestling with big issues around security. You can't help but open the paper and see issues on security. Yesterday was the big Capital One. The Equifax issue was resolved in terms of the settlement this week, et cetera, et cetera. Facebook struggling mightily with whether or not how to deal fake news, how to deal with deep fakes. Recently it shut down likes for many Instagram accounts in some countries because they're trying to protect young people who are addicted to this. Well, they need to shut down likes for business accounts. So what kids are doing is they're moving over to the business Instagram accounts. Well when that happens, it exposes their emails automatically so they've all kinds of privacy landmines and people don't know how to deal with them. So this data explosion, while there's a lot of energy and excitement around it, brings together a lot of really sticky issues. And that falls right in the lap of the chief data officer, doesn't it? >> We're in uncharted territory and all of the examples you used are problems that we couldn't have foreseen, those companies couldn't have foreseen. A problem may be created but then the person who suffers from that problem changes their behavior and it creates new problems as you point out with kids shifting where they're going to communicate with each other. So these are all uncharted waters and I think it's got to be scary if you're a company that does have large amounts of consumer data in particular, consumer packaged goods companies for example, you're looking at what's happening to these big companies and these data breaches and you know that you're sitting on a lot of customer data yourself, and that's scary. So we may see some backlash to this from companies that were all bought in to the idea of the 360 degree customer view and having these robust data sources about each one of your customers. Turns out now that that's kind of a dangerous place to be. But to your point, these are data companies, the companies that business people look up to now, that they emulate, are companies that have data at their core. And that's not going to change, and that's certainly got to be good for the role of the CDO. >> I've often said that the enterprise data warehouse failed to live up to its expectations and its promises. And Sarbanes-Oxley basically saved EDW because reporting became a critical component post Enron. Mark Ramsey talked today about EDW failing, master data management failing as kind of a mapping and masking exercise. The enterprise data model which was a top down push for a sort of distraction layer, that failed. You had all these failures and so we turned to governance. That failed. And so you've had this series of issues. >> Let me just point out, what do all those have in common? They're all top down. >> Right. >> All top down initiatives. And what Glaxo did is turn that model on its head and left the data where it was. Went and discovered it and figured it out without actually messing with the data. That may be the difference that changes the game. >> Yeah and it's prescription was basically taking a tactical approach to that problem, start small, get quick hits. And then I think they selected a workload that was appropriate for solving this problem which was clinical trials. And I have some questions for him. And of the big things that struck me is the edge. So as you see a new emerging data coming out of the edge, how are organizations going to deal with that? Because I think a lot of what he was talking about was a lot of legacy on-prem systems and data. Think about JEDI, a story we've been following on SiliconANGLE the joint enterprise defense infrastructure. This is all about the DOD basically becoming cloud enabled. So getting data out into the field during wartime fast. We're talking about satellite data, you're talking about telemetry, analytics, AI data. A lot of distributed data at the edge bringing new challenges to how organizations are going to deal with data problems. It's a whole new realm of complexity. >> And you talk about security issues. When you have a lot of data at the edge and you're sending data to the edge, you're bringing it back in from the edge, every device in the middle is from the smart thermostat. at the edge all the way up to the cloud is a potential failure point, a potential vulnerability point. These are uncharted waters, right? We haven't had to do this on a large scale. Organizations like the DOD are going to be the ones that are going to be the leaders in figuring this out because they are so aggressive. They have such an aggressive infrastructure and place. >> The other question I had, striking question listening to Mark Ramsey this morning. Again Mark Ramsey was former data God at GSK, GlaxoSmithKline now a consultant. We're going to hear from a number of folks like him and chief data officers. But he basically kind of poopooed, he used the example of build it and they will come. You know the Kevin Costner movie Field of Dreams. Don't go after the field of dreams. So my question is, and I wonder if you can weigh in on this is, everywhere we go we hear about digital transformation. They have these big digital transformation projects, they generally are top down. Every CEO wants to get digital right. Is that the wrong approach? I want to ask Mark Ramsey that. Are they doing field of dreams type stuff? Is it going to be yet another failure of traditional legacy systems to try to compete with cloud native and born in data era companies? >> Well he mentioned this morning that the research is already showing that digital transformation most initiatives are failing. Largely because of cultural reasons not technical reasons, and I think Ramsey underscored that point this morning. It's interesting that he led off by mentioning business process reengineering which you remember was a big fad in the 1990s, companies threw billions of dollars at trying to reinvent themselves and most of them failed. Is digital transformation headed down the same path? I think so. And not because the technology isn't there, it's because creating a culture where you can break down these silos and you can get everyone oriented around a single view of the organizations data. The bigger the organization the less likely that is to happen. So what does that mean for the CDO? Well, chief information officer at one point we said the CIO stood for career is over. I wonder if there'll be a corresponding analogy for the CDOs at some of these big organizations when it becomes obvious that pulling all that data together is just not feasible. It sounds like they've done something remarkable at GSK, maybe we'll learn from that example. But not all organizations have the executive support, which was critical to what they did, or just the organizational will to organize themselves around that central data storm. >> And I also said before I think the CDO is taking a lot of heat off the CIO and again my inference was the GSK use case and workload was actually quite narrow in clinical trials and was well suited to success. So my takeaway in this, if I were CDO what I would be doing is trying to figure out okay how does data contribute to the monetization of my organization? Maybe not directly selling the data, but what data do I have that's valuable and how can I monetize that in terms of either saving money, supply chain, logistics, et cetera, et cetera, or making money? Some kind of new revenue opportunity. And I would super glue myself for the line of business executive and go after a small hit. You're talking about digital transformations being top down and largely failing. Shadow digital transformations is maybe the answer to that. Aligning with a line of business, focusing on a very narrow use case, and building successes up that way using data as the ingredient to drive value. >> And big ideas. I recently wrote about Experian which launched a service last called Boost that enables the consumers to actually impact their own credit scores by giving Experian access to their bank accounts to see that they are at better credit risk than maybe portrayed in the credit store. And something like 600,000 people signed up in the first six months of this service. That's an example I think of using inspiration, creating new ideas about how data can be applied And in the process by the way, Experian gains data that they can use in other context to better understand their consumer customers. >> So digital meets data. Data is not the new oil, data is more valuable than oil because you can use it multiple times. The same data can be put in your car or in your house. >> Wish we could do that with the oil. >> You can't do that with oil. So what does that mean? That means it creates more data, more complexity, more security risks, more privacy risks, more compliance complexity, but yet at the same time more opportunities. So we'll be breaking that down all day, Paul and myself. Two days of coverage here at MIT, hashtag MITCDOIQ. You're watching The Cube, we'll be right back right after this short break. (upbeat music)