 Live from Cambridge, Massachusetts, extracting the signal from the noise, it's theCUBE, covering the MIT Chief Data Officer and Information Quality Symposium. Now your host, Dave Vellante. Welcome back to MIT IQ, everybody. This is Dave Vellante. We're here in Cambridge, Massachusetts at the Tang Center. This is theCUBE's third year covering the MIT Information Quality Chief Data Officer Conference. We're really pleased to have David Levine here. He's joined by Mark Johnson, a CUBE alum, David's Vice President at Fusion Alliance. Mark is a data guru, data executive, architect. Good to have you back. Mark, David, good to meet you. Great, great to be back. So you guys have been a sponsor of this event now. Since we've been here, I think, several years goes back, Mark. What has this event meant to you and how has it evolved? Well, I think there are a number of things that really strike me as important from the work that MIT does. The first thing is that they bring a community together, both across academia and the commercial sector and the public sector, focused on the most strategic aspects of data management. And that global intersection that gets created here in Cambridge is really key, because the collaboration that happens, the leadership that we get access to, the best practice techniques that come out of that allow this community to be a very substantial community in the data space. And I think that's really key, Dave. So Dave, maybe talk about Fusion Alliance, sort of what you guys specialize in, help our audience understand your role. Sure, we've been around for 20 years and we're an interesting combination, I think, of the industry, a little bit different than a lot of our competitors. We're a combination of a digital agency, a mobile solutions provider, a software development firm, and an enterprise strategic data management consultancy all under one roof. I think it gives us a little bit of a different perspective sometimes on things like how people are consumerizing their data, monetizing their data, how they're optimizing their data program. And that's why we formed the relationship that we have with Gavrosh that's led us to where we are today, and brought Mark into the firm to help us from a strategic data management perspective. Yeah, so how'd that all work? Did you guys acquire Gavrosh? Because that's when we first met you with Gavrosh. Right. Yeah, so we started working together at the beginning of 2014, and Gavrosh was really looking for partners that had an appetite for the strategic dimensions of data management to complement what they were doing at a technical level. As you are aware, Gavrosh was a strategic data management firm focusing on strategy, governance, stewardship, quality, and architecture. Fusion had a very extensive data practice, but on the technology integration side, so design, build, deployment of BI solutions, analytics solutions, and data warehouse backends. So with the complement of the two was a very, sort of an easy thing to get and understand because it gave us a full suite of capability from strategy all the way down to delivery, and from traditional data management analytics all the way out to big data analytics and data science. So that combination really took wind and its sails last year quite significantly. We went to market with a number of accounts in the combination of our services, and at the end of the year, we decided it probably made sense for me to step across and really focus on helping the Fusion sales teams and solution delivery teams understand what we truly could bring to a customer. And so we pulled in a very tight strategic alignment with Gavrosh and that creative union that we have today. Gavrosh is still a freestanding company, but focuses primarily on this relationship. I see, and David, what's the digital agency angle? That's an interesting twist. Well it's really, you know, it's about how people use the digital world to represent their brands, right? And everything that goes along with that, how do they reach the consumers in more effective ways? So when you talk about all the data that's generated in the mobile space and social media today and how that's changed the strategic data management environment with all the new tools and paradigms that exist, that's a place where Fusion can have a dramatic effect on the relationship that our customers have with their customers. That's what we're really about. It's tightening that bond that exists between our customers and their customers to a level that it's never been before. So what's the role of data in that bond? It's very central. So that's one of the reasons why Gavros chose to really partner with Fusion, is when you think about the digital agency side or mobile app development capability and you think about our technical solution delivery services out of the Fusion side and you add data to that, the world is increasingly becoming digitized. And so our behaviors are more and more happening on the road in a mobile context. We're doing more and more of the activities like shopping, booking reservations, doing research, you know, investing, doing banking transactions online, all of those activities lead behind a very significant digital footprint in terms of the exhaustive data and the opportunities to analyze that data are just increasing as you know. We've been talking about big data and big data analytics at this event. So Fusion brings complement to the ability to understand and strategically position technology and approaches to harvest the data, to integrate the data and to provide analytic insight over that data and deliver it through an omnichannel capabilities that really are where the industry is, where business is moving, increasingly mobile and increasingly digital. And I think if you think about the first presentation of the day to day and the fact that all that research was around the kind of social aspect of what people do in the physical world, I think the same thing's true in the digital world, right? So people will give you information about them that's demographic and nature and it'll tell you something about them but it's not always predictive of how they actually behave. If you have the ability to listen to things like social media platforms, tools like Radiant Six and different software capabilities like that, you'll find that you're able to really, really have a better understanding of how they actually behave versus how you perceive they were going to behave. And that's the significant paradigm shift and that's all driven by data, right? It comes in huge volumes and being able to actually troll through all that information and make sense out of it very quickly is a huge big data challenge. So the interesting thing about that conversation this morning is Sandy was saying that essentially it's not the individual, it's really the peer group that that individual participates in. So, but when you think about some of that tooling, a lot of the data's in silos, whether it's Twitter data, Facebook data, LinkedIn data, some other, weather data, whatever it is. So can you talk about how you address that or how clients are addressing that problem, how you're helping them and is there hope to bring all that data together? Is that actually happening today? Well, I think actually that's a great question and it's something that I think we really need to accentuate in this discussion over the next, you know, day and a half. So data integration in the traditional data warehousing context required, as we talked about this morning, data architecture work, it required creating a semantic model to represent the integration of data. A lot of work to do ETL and to prepare that data and make it available. That equates to time and today's business needs time compressed out of the equation. So faster time to insight is really key. So the new technologies that are evolving out there in the marketplace, big data, the Hadoop platform being a perfect case in point are creating the opportunity to stage data into a Hadoop environment and to have that data be immediately accessible for purposes that the organization might use that fit for purpose quality of that data can fuel even before you transform content into a structured data warehouse. You apply data quality and integration disciplines to it. You move it into another platform and you certify that content. And so as we look at the architectural implications of driving the future of analytics and reporting through the use case lens, what problems am I trying to solve? What characteristics or constraints are around the time to value in solving that problem? Then what data assets can be created or technologies can be applied like data virtualization as an example that will allow us to access data in place but not have to replicate it and so take the time of preparation out of the equation. We have a greater, really a greater, what I would like to say is a greater smorgasbord of options for delivering value. And that's really key. So I wonder if we could follow up on that. I like that Jeffrey Moore, George Gilbert are big data guys picked up on this a lot. The whole notion of systems of record, systems of engagement and now systems of intelligence, IBM calls it systems of insight. And you have this narrative in the industry now. If you listen to guys like Gartner and IDC, they talk about, Gartner talks about bimodal IT. Gartner talks about platform two or IDC talks about platform two and platform three almost like more stovepipes. But I'm wondering, do you see customers sort of extending existing systems, those systems of record, the transaction systems, bringing in systems of engagement, extending into mobile and other systems of intelligence, or do you actually see those sort of systems emerging as stovepipes? Will those worlds come together or will they stay separate is essentially my question. Dave, do you want to take that first? Well, I think the reality is they have to come together, right? I think if you don't operate that way, you're kind of in the aisle and eventually you're going to pay the price for it, right? The reality is, if you think about the value, if you think about data from like Maslow's hierarchy of needs, but you think about it from a business perspective, right? In the beginning you want to be compliant, then you want to be secure, then you want to be efficient, right? But then you want to start to enable your business and you can't get to the self-actualized end of that range if you don't have all those stovepipes knitted together, right? In a meaningful way. And I think what Mark was getting to is as the intellectual capability of property of the people in your organization allow you to use data towards the kind of early end of its first push in to say a Hadoop environment, right? As long as they can intelligently analyze that raw data, it can have value and you need to get value from it very quickly, right? As opposed to waiting for certain periods of chronological things to happen in order for that data to become available. You need to make it available to people that can use it effectively as soon as they can get it, right? Well, and interesting, I wonder Mark if I could follow up with you on what David said. So a lot of the big data initiatives are driven by lines of business who say, I forget compliance, screws, security, I don't care about governance, I want effective. Go. You must be seeing that. Yeah, we hear it a lot, I think it is a concern. But there are, so one of the biggest areas of innovation around the Hadoop ecosystem is security. And that's a critical element of being able to manage an environment where essentially you're pulling the enterprises of data, it might be PCI compliant data or HIPAA data if you're in healthcare. You're pulling it into an environment that's going to be fairly open. So data obfuscation approaches become really important. How do you mask the data as it lives in that environment? Also the ability to provide access to it in terms of a hierarchical or a data values oriented security paradigm or framework on that data is becoming really important. We're not there yet, but the innovation and research is happening and there are really almost quarterly releases of new capability to secure that environment. That said, if you think about the traditional data warehousing paradigm where you had, you pull the content out of your production systems, you'd stage it someplace. We had a large, one of our large clients in insurance industry was staging all of their data into their terror data complex and then doing ETL work to transform that data, moving it into the structure portion of terror data, but they were incurring the cost of managing multiple petabytes of data inside terror data. That was dark data. It wasn't being used for any purpose. It didn't have a framework around it to provide access. And yet, if you think about the data scientists, that's exactly the data they want to get to. So there's incremental business value for providing direct access to that newly landed or staged data content. And so by providing a security framework around that, you're able to then address the concerns of the people who do audit and control and the security and privacy issues that surround that data. And if I heard you correctly, it's not one size fits all. It's the value of the data that informs the security and governance edicts. That's correct. And the other key is, on the not one size fits all statement that you just made, that what we see is really a purpose driven world of data assets that are deployed, they're built and configured for the specific use case or the purpose, the fit for purpose that the business has, right? And at the end of the day, our goal is to enable decision making, it's to enable cost optimization or efficiencies of operation. It's to enable incremental revenue growth through data products. So what we have to do is look at each one of those use cases, understand the characteristics and dynamics of that use case, then look at this portfolio of options to deliver data and insight through a technology platter that has lots of options to configure and deliver that information. And that's a really big shift in the way we think about these things now. So David, talk about where you want to take the business. What's your vision for fusion and where are you going? That's a good question. I think the reality is, so today I think the reality is we serve the highly regulated verticals today, right? So we serve financial services, we serve life sciences and we serve energy. And we certainly have customers in other industries, but that's the predominance where we spend our time because we understand the compliance needs at the regulatory guidelines at a very intricate level. And I think we'll continue to do that in the future. I think the reality is we're predominantly a Midwest based company today. We will expand geographically doing the things that we've always kind of done. But I think the reality is the two things that are the three things that will drive us forward are the enterprise mobile delivery capabilities that we have, the digital capabilities that we have, and the data space, right? The reality of those three things together in our minds will forever be intertwined. And because we made the decision that we made to add a digital agency 14, 15 years ago to the company, I think we're in a very good position to bring those three pieces together in a meaningful way for all of our customers. And what about other regulated industries like healthcare and government? Well, healthcare is a place where, so we have a couple of payers as customers today, right? And we have a couple of providers as customers today. I think the things that are going on in the healthcare space are very our data demand driven as well. And that's definitely a space that we plan to play in in the future. We're just not there yet from a knowledge perspective. Excellent. All right, so we're out of time, but maybe Mark, to give you the last word, you've seen this event evolve. Talk used to be, is there a need for a CDO? Will it go mainstream? It seems to be taking hold. The data governance discussion is sort of moving toward data innovation. I wonder if you could summarize sort of the evolution, the journey and where you see it. I think we are on a journey and I think the journey is from really managing data to managing analytics to managing insight. So when we think about prescriptive and predictive analytics, we know that that's all fueled by data. It's fueled by data in different configurations and at different levels of quality. I think that in terms of the traditional approach to managing data and delivering business intelligence, we're going to see a shift. We're going to see a shift in the way people approach the challenge. We're going to see a shift in the skills required to get the job done. And we're going to see a shift in the direction of prescriptive and predictive outcomes. So analytics is going to be the key. I think one of the presenters this morning mentioned, it's no longer a question of, do we need a CDO? It's a question of, should we add analytics to the CDO title, chief data and analytics officer? And I think that's the direction we're going in. I also think it's the right direction. I almost think that it may be when we get there, that it should be the chief analytics and data officer as opposed to the chief data and analytics officer. Because really the value comes out of the analytics and that's where we've got to be focused. Just saying. All right gentlemen, thanks very much for coming back on theCUBE and on theCUBE. It's good to see you guys. All right, keep right there, everybody go back with our next guest. This is theCUBE. We're live from MIT IQ in Cambridge, Massachusetts. Right back.