 from San Jose. It's theCUBE, presenting Big Data Silicon Valley, brought to you by SiliconANGLE Media and its ecosystem partners. Welcome back to theCUBE's continuing coverage of our event, Big Data SV in downtown San Jose. I'm Lisa Martin, like our host is Dave Vellante. Hey Dave. Hey Lisa, how's it going? Good. We're doing a great job here by the way. Well thank you sir. Keeping the trains going? Yeah. Well done. We've had a really interesting couple of days. We started here yesterday interviewing lots of great guys and gals on Big Data and everything in between. Lots of different topics. There are opportunities, challenges, digital transformation. How can customers really evolve on this journey? We're excited to welcome back to theCUBE one of our distinguished alumni, Matt Mako, the global Big Data practice lead from Dell EMC. Welcome back. Well thanks for having me. Appreciate it. It's a pleasure to be here. Yeah. So lots of stuff going on. We've been here as I mentioned. We're down the street from the Strata Data Conference. So we've had a lot of great conversations, very educational, informative. You've been with the whole Dell EMC family for a while now. We'd love to get your perspective on kind of what's going on from your team's standpoint. What are you seeing in the enterprises with respect to Big Data and being able to really leverage data across the business as a value driver and a revenue generator? It's interesting that what we see across the business in terms of, especially in the big enterprises, many organizations, even the more mature ones, are still struggling to get that extra dollar, that extra level of monetization out of their data assets. Everyone talks about monetizing data and using data, treating it as an asset. But organizations are struggling with that not because of the technology. The technology's been put in, they've ramped up their teams, their skills. It's what we tend to see inhibiting this digital transformation growth is process. It's organizational strife and it's not looking to best practices even within their own organization. We're doing things like DevOps. So why would we treat the notion of creating a data model at any different than we would regular application development? Well, organizations still carry that weight, that inertia. They still treat big data and analytics like they do the data warehouse. And the most effective organizations are starting to incorporate that agile methodology and agile thinking. No snowflakes, infrastructures, code. These concepts of quickly and rapidly and repeatedly doing these things, those of the organizations that are really starting to pull away from their competitors in industry. And so Dell EMC, our consulting group and our product lines are all there to support that transformation journey by taking those best practices in DevOps data ops and bringing that to the analytical space. Do you think that companies, Matt, have a pretty good sense as to how applications that they develop are going to affect, create values, creating values, let's simplify it, increasing revenue or cutting costs. Generally people can predict with the impact, they can write a business case around it. My observation was that certainly in the early days of so-called big data, people really didn't have an understanding as to the relationship between their data and that value. And so many companies mistakenly thought, well, I need to figure out how to sell my data versus understand how data affects monetization. I wonder if you could comment on that and how has that progressed throughout the years? Yeah, that's a good point. We, from a consulting practice, used to do a lot of what we call proof of values where organizations after they kick the tires, uncover some use cases, we took them through a very slow methodical business case ROI analysis. You're going to spend this much on infrastructure, you're going to hire these people, you're going to take this data and poof, you're going to make this much money, you're going to save this much money. We're doing less and less of that these days because organizations have a good feel for where they want to do and the potential upside for doing this. Where they're now tend to struggle is, well, how do I actually get there? There's still a lot of tools and a lot of technologies and which is right for my business? What is the right process and how do I build that consensus in the organization? And so from a business consulting perspective, we're doing less of the ROI work and more of the governance, the sort of governance work by aligning stakeholders, getting those repeatable patterns and architectures in place to help organizations take that first few wins and then scale it. Where do you see the action these days? I mean, there's some high profile use cases, obviously getting people to click on ads, big data has helped with that. Fraud detection has come such a long way in the last 10 years, no doubt. Certainly risk assessment from the financial services industry. Those are the obvious ones. Where else do you see big data analytics to the changing the world, if you will? Yeah, so I'd say those static or batch type workloads are well understood that, hey, is there fraud on transactions that occurred yesterday or last night? What is the customer score, lifetime value score for customer? Where we see more trends in the enterprise space is streaming. So what can we catch in real time and help our people make real time decisions? So, and that is dealing with unstructured data. So I've got a call center and I'm listening to the voice that's coming in, putting some sentiment analysis on that and then providing a score or a script to the customer call agent in real time. And those sort of streaming use cases, whether it's images or voice, that I think is the next paradigm for use cases that organizations want to tackle. Because if you can prevent a customer from leaving in real time, right? So you know what, it sounds like you're upset. What if we did X to help retain you? It's going to be significant. All these organizations have a good idea of the cost it takes to acquire a new customer and the cost of losing a customer. So if they can put that intelligence in upstream, they no longer have to spend so much money trying to capture new customers because they can focus on the ones they have. So I think that sort of tie in between customer and streaming is where the next set of, I think money is to be found. So customer experience is critical for businesses in any organization. I'm wondering kind of what the juxtaposition is of businesses going, yes, we have to be able to do things in real time and enterprise, we have to be agile. Yet we have, in order to really facilitate a really effective, relevant, timely customer experience, many departments and organizations in a business need access to data. From a political perspective, how does Dell EMC, how does your consulting practice help an enterprise be able to start opening up these barriers internally to be able to enable data sharing so that they can drive, take advantage of things like real time streaming to ultimately improve the customer experience, revenue, et cetera. Yeah, it's going to sound really trite, but the first step is getting everyone in a room and talking about what good looks like, what are the low hanging, and everyone's going to agree on those use cases. They're going to say, these are the things we have to do, right? We want to lose fewer customers. We want to, you know, whatever the case may be. So everyone will agree on that. So the politics don't come into play there. So what data do we require for that? Okay, well we've got all this data. Great, no disagreement there. Well where is the data located? Who's the owner or the steward of that data? And now who's going to be responsible for monetizing that? And that's where we tend to see the breakdown because when these things cross line of business and customer always crosses line of business, you end up with turf wars. And so the emergence of the chief data officer who's responsible for the policy and the prioritization and the ownership of these things is such a key role now. And it's not a CIO responsible for data. It is a business aligned executive reporting into the chief, CEO, COO, CFO. Again, business alignment, that tends to be the decision maker or at least the thing that solves for those conflicts across those BU's. And when that happens, then we see real change. But if there's not that role or that person that can put that line in the sand and say this is how we're going to do it, you end up with that political strife and then you end up with silos of information or point solutions across the enterprise and it doesn't serve anyone. What are you seeing in terms of that CDO role? I mean, initially the chief data officer was really within regulated businesses, financial services, healthcare, government. And then you've seen it permeate to more mainstream. Do you see that role as having legs? A lot of people have questioned that role. What chief digital officer, chief data officer, just encroaching on the CIO territory. I'm inferring from your comments that you're optimistic about that role going forward. I am, as long as it's well-defined as having unique capabilities that's different than the CIO. Again, I think the first generation of chief data officers were very CIO-like or CIO for data. And that's when you ended up with the turf wars. It was like, okay, well this is what we're doing. But then you had someone who was sort of a peer for infrastructure and so it just didn't seem to work out. And so now we're seeing that role being redefined. It's less about the technology and the tools and the infrastructure and it's more about the policies, the consistency, the architectures. You know, I'd observe. I wonder if we could talk about this for a little bit. It's the CDO role. To me, one of the first things a CDO has to do is understand how a company gets value out of its data. What is it, and if it's a for-profit company, what's the monetization? Where does that come from? Not selling the data, as we were talking about early. And then the other is what data? What data, what's our data architecture? Data sources, how do we give access to that? And then quality, data quality seems to be something that they worry about. And then skills, no technology in here. And then somehow they got to form relationships with the line of business. So the simultaneous to figuring that out. Does that seem like a reasonable framework for the CDO's job? It does. You call them chief data governance officer. It really falls under the umbrella of governance. It's about standards and consistency, but also these policies of there are finite resources, whether we're talking people or compute. What do you do when there's not enough resources and more demand? How do you prioritize the things that the business does? Well, do you have policies and matrices that say, okay, well, is it material, action will timely? Then yes, then we'll proceed with this. No, it doesn't pass the sniff test. And it doesn't have to be about money. However the organization judges itself is what it should be based on. So whether we're talking nonprofit, we helped a school system recently better align kids with schedules and also learning abilities by sitting them next to each other in classes. There's no profit in that other than the education of children. So every organization judges itself or measures itself a little differently, but it comes back to those KPIs. What are your KPIs? How does that align to business initiatives? And then everything should flow from there. Now I'm not saying it's easy work. Data governance is the hardest thing to do in this space. And that's why I think so few organizations take it on because it's a long, slow process. And you should have started 10 years ago on it. And if you haven't, it feels like this mountain that is really high to climb. You're saying it's outcome driven. Yeah. Independent of the types of organizations. I want to talk about innovation. I've been asking a lot of people this week, do you feel like big data, the meme of big data that was created eight, 10 years ago, do you feel like it lived up to its promises? That's a loaded question. I think if you were to ask the back office enterprises, I would say yes. In terms of customers feeling it, probably not because when you use an Uber app to hail a cab and pay $3.75 to go across town, it feels like a quality of life, but you don't know that that's a data driven decision. As a consumer, your average consumer, you probably don't feel that. As you're clicking through Amazon and they know sort of the goods that you need or the fact that they know what you're going to need and they've got it in a warehouse that they can get to you later that day. It doesn't feel like a big data solution. It just feels like, hey, the people I'm doing business with, they know me better. People don't really understand that that's a big data and analytics concept. So has it lived up to the hype externally? I think the perception is that it has not, but the businesses that really get it feel that absolutely it has. Do you agree it's kind of bifurcated? It is. The Spotify's and the Uber's and the Airbnb's that are crushing it, and then there's a lot of traditional enterprises that are still stovepipe and struggling. Yeah, it's funny, when we talk to customers, we've got our introductory PowerPoint, right? It always talks about the new businesses and the old businesses, and I'm finding that that doesn't play very well anymore with enterprise customers. They're like, we're never going to be the Uber of our industry. It's not going to happen if I'm a Fortune 100 legacy. It's not going to happen. What I really want to do though, is help my customers or make more money here. I'm not going to be the Uber. It's just not going to happen. We're not the culture. We're not set up that way. We have all of this technical legacy stuff, but I really want to get more value out of my data. How do I do that? And so that message resonates. Isn't that in some ways though? How do you feel about this? Is it a recipe for disruption? Where that's not going to happen, but something could happen where somebody digitizes your business. Yes? Absolutely, if there are organizations, if you're in the Fortune 500 and you are not worried about someone coming along and disrupting you, then you are probably not doing the right job. I would be kept awake every night, whether it was financial services or industrial manufacturing. Grocery. Nobody thought that the taxis, who the hell would come in and disrupt the cab industry? You got to hire all these people. The cars are junk and the customer experience is awful. Well, someone has come along and there's been an industry related to this. Now they have their bumps in the road, so are they going to be disrupted again or what's the next level disruption? But I think it is technology that fuels that, but it's also the cultural shift as part of that, which is outside the technologies, these socioeconomic trends that I think drive that as well. But even, and we've got just a few seconds left, the cultural shift internally. It sounds like from what you're describing, if an enterprise is going to recognize, I'm not going to compete with an Uber or an Airbnb or a Netflix, but I've got to be able to compete with my existing peers of enterprise organizations. This CDO role sounds like it's a matter of survivability. Without putting that in place, you can't capitalize on the value of data, monetize it, et cetera. Well guys, I wish we had more time because I think we're opening a can of worms here. But Dave, Matt, thanks so much for having this conversation. Thank you for stopping by. Thanks for having me here, it was a real pleasure. Likewise. We want to thank you for watching theCUBE. We are continuing our coverage of our event, Big Data SV in downtown San Jose. For Dave Vellante, my co-host, I'm Lisa Martin. Stick around, we'll be right back with our next guest after a short break.