>> Male Narrator: Live from San Jose, it's theCube. Presenting Big Data Silicon Valley, brought to you by SilconANGLE Media and it's ecosystem partners. >> Welcome back to theCube's continuing coverage of our event, Big Data SV in downtown San Jose. I'm Lisa Martin, my co-host is Dave Vellante. Hey Dave. >> Hey Lisa, how's it going? >> Good. >> 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. A lots of different topics there, 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 Maccaux, 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 and 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? >> Yeah, it's interesting that what we see across the business in terms of, especially in the big enterprises, there, 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. They, 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 own, their own organization, we're doing things like DevOps. So, why would we treat the notion of creating a data model 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, infrastructure's code, these concepts of quickly and rapidly repeatedly doing these things, those are the organizations that are really starting to pull away from their competitors in industry. So, Dell EMC, our consulting group and our product lines are all there to support that transformation journey by taking those best practices and DevOps DataOps 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 value, creating value is, let's simplify it, increasing revenue or cutting cost? 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 kicked the tires and covered some use cases, we took them through a very slow, methodical business case RY 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. Well, we're doing less and less of that these days because organizations have a good feel for where they want to go 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 RY 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 somehow I 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, ya know, no doubt, certainly risk assessment, ya know, 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 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. 'Cause if you can prevent a customer from leaving in real time, right, say, 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 'cause they can focus on the ones they have. So, I think that, sort of, time between customer and streaming is where the next set of, I think, money's 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, in 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 and 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, there 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, "Well, 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 the line of business and customer always crosses the line of business, you end up with turf wars. And so this, 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, that, and it's not a CIO responsible for data, it is a business aligned executive reporting to 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 BUs. 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, ya know, 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 is 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-liked or CIO-for-data and that's when you ended up with the turf wars. And then 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 can 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 the, and if it's a full profit company, what's the monetization, where does that come from? Not selling the data, as we were talking about earlier. And then there is what data, what data, where are, what 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, not, none, no technology in here. And then somehow they're going to form relationships with the line of business and it's simultaneous to figuring that out. Does that seem like a reasonable framework for the CIO, CDOs job? >> It does, and you call them Chief Data Governance Officer, I mean, 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 computes. 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, actionable, timely?" "Then yes, then we'll proceed with this." "No, it doesn't pass." 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 non-profit, 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 'cause it's a long, slow process and, ya know, you should've started 10 years ago on it and if you haven't, it feels like this mountain that is really high to climb. >> What you're saying is 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, ya know, 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. That's 'cause you, do you agree it's kind of bifurcated? >> Matt Maccaux: Yeah, it is. >> The Spotify's and the Ubers and the Airbnb's that are crushing it and then there's a lot of traditional enterprises that are still stove pipe and struggling. >> Yeah, it's funny, when we talk to customers, we've got our introductory power points, right, it always talks about the new businesses and the old businesses and, 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 the, 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. >> Dave Vellante: Grocery. >> Nobody thought that the taxis, who the hell would come in and disrupt the cab industry? Ya got to hire all these people, the cars are junk, 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 of 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, the socioeconomic trends that I think drive that, as well. >> But even, ya know, 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," the CDO role sounds like it's a matter of survivability. >> Yes. >> Without putting that in place, you can't capitalize on the value of data monetized and et cetera. Well guys, I wish we had more time 'cause 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. (upbeat music)

>> Announcer: Live, from Austin, Texas, it's The Cube, covering KubeCon and CloudNativeCon 2017, brought to you by Red Hat, the Linux Foundation, and The Cube's ecosystem partners. >> Okay, welcome back everyone, we are here live in Austin, Texas for KubeCon and CloudNativeCon 2017. This is The Cube's exclusive coverage, I'm John Furrier, the co-founder, of SilconANGLE Media, analyst here with SilconANGLE Media, next guest, Justin Garrison, co-author of the Cloud Native Infrastructure book. How about us wrap up day one with two days of live coverage, Justin, welcome to The Cube. >> Justin: Yeah, thanks for having me. >> Stu, day one wrap-up, guys what are you seeing? Justin, what's your perspective? >> There are a ton of announcements today, it was kind of crazy. It's amazing being part of the CNCF community and everything, and everything happens in the open, but then there's so much other stuff in the ecosystem that just happens and gets announced. >> I mean, real accelerated growth, if you look at KubeCon, this is the second year doing the event, last year's kind of an inaugural event, the first year before that was just an idea, side break out kind of thing going on, just forming, and then just took off. Obviously containers with DockerCon, and Container Ecosystem, kina floating that boat up. Kubernetes, I mean those tracks are huge, the agenda looks like, it's like a university of geeks here, I mean, this has been ramped up pretty fast. What's your take on that? >> I mean, I was at KubeCon last year, and about a thousand people was a great little environment, and a lot of stuff that was still emerging, and being discovered, and now it's everyone is in the middle of it, and trying to learn as fast as they can to pick up these projects, and see how to actually make this stuff production-ready, and how to actually use it. And not just in the environments that they used to be, they're rewriting all of their environments, it's no longer a here's how I run my app the old way, and a VM statically, it's I you know, we're beyond running containers, and they realize that's not the end goal anymore. >> Justin, when we were talking to you before the segment here, and you're like oh, I've been working on Kubeternes for like two years more and everything, and it's funny in the career. It's like oh, well two years, in some ways it's a long time, in CloudNative time it's a long time, in career wise, it's a rather short time, give us a little bit about what you've been seeing, you know, what's interesting, you mentioned there's a whole lot of announcements, I mean, obviously new projects spinning up, new, new releases, so you know, if you could give us a little bit of a historical view. >> Yeah, I mean from last year, it was really hard to get a cluster. It was something that was really, like you had to know what you were doing to make Kubernetes run, and make it highly available and production-ready. And now, club dividers give you a button, you click it, how big do you want it, how much do you want to auto-scale it, and it's all about the application, and bringing business value to whoever's running it to say, like, my application runs here, and now there's more involved with Istio and these network proxies that give you more resiliency in the claw providers, because people don't run their own infrastructures much anymore, it's all in a cloud, and they don't care about the underlying infrastructure, they care about their apps. >> Yeah, so you tell them about CloudNative infrastructure, so one of the things we're teasing out here is, you know, Kubernetes, all this CloudNative stuff will make it easy to be able to do the application, but you know, infrastructure, it matters. I love Dan Cone's line in the Keynote this morning is you know, it's exciting times for boring infrastructure, so you know, talk about that layer, what's important about infrastructure, and bring us in a little bit, you know, why you wrote the book with Kris Nova, and you know, how that fit. >> Really wanted to write it to help people not make a lot of mistakes to help them kind of level up and get a head start in building the infrastructure in the cloud, cause it's not something that they own anymore, it's not this server that they rack, and they take care of it for years. It's something that comes and goes, it's quick, you know, you have to design for failure and resiliency, and that layer of infrastructure isn't important because you don't run it anymore, but it is important to build a platform on top of that that your applications are still resilient. There's no more scheduled down-times in the cloud, like websites aren't gone, you know, Sundays at midnight. >> Yeah, don't you have to be pretty brave, cause you don't own it anymore, but if something goes wrong, you know, you're the one whose job's on the line. >> You own the failure. >> Justin, talk about the feedback that you might have for the industry. Stu and I were looking at the growth, we certainly love the excitement, but they're still running as fast as they can, they're pedaling as fast as they can, they're trying to introduce all these services. You see some good news here, some new releases coming out, some key services for monitoring, tracing, and whatnot, but what do they need to do better, in your opinion as a practitioner, someone who's out in the trenches, what's the critical analysis, in a good way, constructive criticism, what needs to happen? >> Right, moving forward, I mean there was this, you know, since configuration management, everyone said infrastructure is code, and really we need to level up to be, Kris actually coined this to me in the book, was infrastructure is software. Where it is a piece of software that's running that you declare that has a two-way relationship. It's not get repository that statically defines things, it's a declarative thing that mutates the infrastructure and talks back to the user so that things can auto-scale, and have same defaults and you don't have to do every last little piece of it, but the declarative nature and policy-based roles in all the infrastructure you're building, and everything around your application, and with your application need to be defined and controlled by software and not people anymore. >> But what needs to happen to make that, obviously STN, software-defined data center, we've seen a lot of that go on at the network level's door right now, are they there, what's the progress meter on that? How would you peg the progress of the evolution, making that happen, cause that's really what people want, I mean at the end of the day, that's what Lambda is for Amazon, that's what serverless is, that's what virtual Cubelets are for. >> Yeah, and it's funny, cause you can run Lambda in a very non-CloudNative way, I mean you can have, you know, individual deploying code to Lambda, and not checked in to get anywhere, you can do all those things, you can go against the CloudNative model very easily, and so it's interesting just seeing that evolution as well, of people actually adopting how Netflix has been doing it for a long time. >> Yeah, we should call it SoftwareNative. (laughter) I mean, but this is kind of what we're getting at, I mean, people on the buyer side are looking and saying oh, I get it, I see the new wave coming, I want to get out there, I want to ride this, and they want to kind of vet out whose pretender, who's the player, how should businesses evaluate the pretenders and the players in your mind? >> Moving to the cloud should be, you know, and easy sell. Like people building data centers anymore, you have to have immense scale to really care about those things, and really get any sort of benefit. If you can beat Amazon and Google and Microsoft at the pricing game, then you're still not ahead because you still have all the people managed. They have so many thousands of people that are doing this stuff that you can't keep up. And so, I mean, just adopting one of those clouds, and not worrying about the vendor lock-in. But yes, Kubernetes brings a lot that you can move from cloud to cloud, but really it's about moving to a cloud provider that provides what your application needs, and at the rate of innovation that you need, and if you can match those two things, if you can stay innovation-matched, I mean Amazon is probably going to pull ahead of you, because they're doing this as their job. >> If I hear you correctly, what I'm hearing is that look for people that are players, that are constantly introducing more innovative services? >> If that's what you need, if that's what you need. If you do not need a high rate of innovation, if you have a lot of policy, or a lot of rules and regulations around your industry, then you probably will get lost in Amazon, and they'll move ahead, they'll move too far for you. And so, you need to find what matches for your industry, and your application. >> Justin, 4,000 people here, over 4,000 people here, for those that didn't come, what are they missing, what's exciting you the most, you know, is it the hallway track, is it, you know, some of the special interest groups, you know, what are you excited that you've seen so far, and are looking forward to seeing? >> Really missing out, I just love the community. I mean, every talk is recorded, if you really care, like, go watch them on YouTube, they're great, like every one of these things is fantastic, but engaging with people, meeting face to face, cause a lot of people are online. Like I mean, on Twitter, or on social networks, like thousands of people here, aren't, and you get to meet those people and find out what their struggles are and what they're working on, and then learn from them, either you know, where they're headed, or where they were before. >> I mean, you can meet the people who write the code, and they're going to give you the straight scoop, or tell you they don't know it, it's real authentic. >> Yeah, any things that you're hearing, kind of what's the buzz, what's the pain point, you know, that you're hearing from the community so far? >> A lot of people still aren't in cloud, they're still doing it themselves, standing up a cluster on pram, you know, has struggles, Kubernetes cluster that is. I mean, you can't really adopt some of these patterns, until you have an API that declares all of your infrastructure, and that's still hard for people. And OpenStack was going to bring some of that stuff, and sometimes it did, sometimes it didn't, but really it's about people and processes, and getting those things right, and being able to change the culture of your environment, and for your applications, that's what's important for the business, and that's where you can learn from people face-to-face and actually talk to them, and not just read a blog post about it, and just hear a one-way tell me what you did, I need feedback, and I need this feedback from whoever's doing it to say, well, why did you do that, and that's really important in the community to learn. >> Well, one of the preferential I was looking for, it's one thing to say, you know, some of these CloudNative companies, like, you see in Netflix, you see in Lyft, you know these are companies where, you know, digital is their business. What about, you know, more traditional businesses, you know, are they able to make that change, is it too challenging for them, you know, what are you seeing? >> The people and the culture's the hardest thing to change, it always is. And if they can change the people, the Keynote today, Netflix was talking about the tools influence your culture, and if you can influence your culture positively, and do that intentionally to actually change the people, then absolutely, they totally can pivot and make that change, but again, do they need to? I mean, if there's other government restrictions, or something else that like, they could move too fast and cause other problems for their industry. >> What's a practitioner dream scenario right now out there that you see, cause you made a good point, sometimes you might want to have more services, sometimes you might want to pull back so it kind of depends on the perspective, but generally speaking, CloudNative Kubernetes, offers an opportunity, what's the nirvana, what's the ideal use case for practitioners these days, what's the key things that need to be rolled out or on the table should be taken advantage of? >> You mean as far as technology goes, or? >> Whether it's technology, whether it's mindset, culture, people, personnel, package, ops. >> I mean, if we can change the people mindset of how they do things, how they deploy applications, and how they manage those applications, the technology would fall into place, I believe, because the people would drive towards this way of working, and then they would build those tools just naturally. A lot of times, like with Kubernetes, Google was in that mindset, and so they did that, they had that culture, and now they're trying to share that with everyone else, and then everyone else has to learn from the tool, rather than the people building. >> Did you see the Netflix talk on the Keynote was culture and tech, and I think that's a real good point, because if you think about your other point, if you got a lot of compliance issues, you might not want to go fast, you really want to move fast, or you like a, you know, fast dot com or web services company, you might want to compete on value and services. Know your culture and hire right. >> Know what your benefit is of your application, and what environment it plays in, and then you can, from there, figure out. >> Well that's been a struggle for the DevOps world is they're taking a square and trying to put it in a round hole, you know what I'm saying? >> Everyone want to move fast, but should everyone move fast, I don't know. It depends. >> Yeah, alright Justin, well thanks so much for coming on. >> Thank you. >> Biggest surprise in this whole Kubernetes movement for you, just in terms of shock factor, or blew you away, did you fall out of your chair, share some color, personal perspective. >> The community is just humongous now. I mean, joining it a couple years ago, it was pretty small, and things were really difficult, and now I play with, you know, clusters in Amazon and Google and Microsoft and just one quick button, I play with it for a few hours and I throw it away, and I got a bill for like four cents, I was like that was amazing, like this would take so long, you know, a couple years ago, and the growth of the community around that, just to be able to say like this is easy now, let's level up what we're doing and working on, and figuring out where the benefit is. >> When we were talking earlier in The Cube, and we've been saying for a couple months, this is going to bring back more time for the developers, to bring craftsmanship back to the development process, bringing artistry and artisan kind of, real software development, not like UX stuff, but like really solution-driven. >> Focus on the business application, where's the application in the business struggle and don't worry about the infrastructure. >> Justin Garrison, co-author of the Cloud Native Infrastructure book, it's on the web, check it out, thanks for coming on The Cube, thanks for sharing your perspective. Day one wrap- up here in Austin Texas for KubeCon and CloudNativeCon, I'm John Furrier, thanks for watching, see you tomorrow for day two coverage. Thanks for watching.

(upbeat synth music) >> Narrator: Live from San Francisco, it's The Cube, covering Oracle OpenWorld 2016. Brought to you by Oracle. Now, here's your hosts John Furrier and Peter Burris. >> Hey, welcome back, everyone. We are here live in San Francisco for Oracle Open World 2016. This is SilconANGLE Media. It's The Cube, our flagship program, where we go out to the events and extract the signal from the noise. I'm John Furrier, the co-CEO of SiliconANGLE Media, joined by my co-host this week, Peter Burris, head of research at SiliconANGLE Media as well as the General Manager of Wikibon Research. Our next guest is Hari Sankar, who's the group Vice President of Enterprise Performance. Welcome to The Cube. >> Thank you. >> Thanks for joining us today. So, one of the things that you're in is performance management but in a different way, kind of a CFO perspective. >> Hari: That's right. >> Which this show is all about, ROI, total cost of ownership. But Oracle has a lot of software, finance software. First, take a step back and spend a minute to describe what is performance management and your role at Oracle. >> So traditionally, performance management is really about how finance sort of manages the overall business performance of a company. It's about things like forward-looking things like planning, forecasting, and budgeting. It's about, sort of, backward-looking things like okay, our quarter is done, how do we close the books and how do we report the numbers both internally, for management recording purposes, and externally, to the street and various stakeholders. So there is the compliance side to it. There is a strategy side to it, and these things have been traditionally what is performance management. What we are seeing now is that kind of discipline is now going beyond finance into operating lines of businesses, sales and marketing and manufacturing and so on. >> The, the-- >> One of the things, sorry, John, I think one of the things that is really interesting, especially in light of this show, is as we go through a process of digital transformation, where data becomes one of the most important assets in the business, that means that the asset specificity, to use a finance term, the degree to which an asset has only one use, starts to go down because you can program it. So marketing, sales, all the assets, intellectual property, data-oriented, that they've been developing over the years now can be bought under the umbrella of Enterprise Performance Management. >> That is absolutely true. That is absolutely-- >> So how is that happening? >> So part of how this is happening is let's say you are a marketing organization. You are spending $50 million on digital marketing. Now, there is a desire from the part of the marketing department to sort of manage that spend more diligently with more discipline and drither, just like finance manages any other line item in the budget. There's more desire to provide transparency to the business, in terms of here's where we are spending it and here's where we are getting returns, here's where we are perhaps not getting returns. So that is the planning part of it, and then there is also the reporting part of it, where we are seeing the emergence of the concept of narrative reporting, where you are saying hey, look, I'm not just going to distribute numbers and charts to my stakeholders, whether it's inside the company or outside, I'm going to give them context, I'm going to give them commentary on these numbers. If there is a variance, I'm going to tell them why is this there. Do I expect this variance to be there next quarter? What am I doing about it? So, it sort of brings those numbers to life and avoids that back and forth that typically happens. >> How much is the Performance Management moving out of the CFO function, and I want to get your take on how the costs in IT is becoming not just a functional shared resource but IT is now integrated across the whole company. Mark Hurd had tweeted yesterday on Twitter, "As more CEOs and CFOs understand "the potential of the cloud, "CIOs are going to get a lot more help," implying Oracle is going to help them. But it brings up the point that the CIO now is brought into the CFO conversation, they always have in facilities and what not, but now from a business perspective their contribution is significant and now co-mingled is it. Do you see that trend happening and what does that mean for the software side of it? >> We're definitely seeing that trend happening. For example, the most important new term to come out in finance in some time is the notion of digital finance. >> John: The notion of what? >> Digital finance, right? So this is really about whether you call it digitalization or not, digital finance, digital marketing, digital sales. So this digital business idea sort of elevates this role of the CIO because, as you said, data becomes a very, very important asset in terms of how you fundamentally drive innovation in your business, and so that digital notion is sort of elevating the role of the CIO. And in the context of Performance Management, as you see this spread beyond finance into other lines of businesses, other lines of businesses are starting to be more disciplined and rigorous in how they sort of measure their performance, how they manage their performance. There's also a need to connect the dots across. You know, if I'm doing a marketing plan, which is an important element of my overall spend, if there is a fluctuation or change, a big change in my marketing spend, that needs to be reflected back in the finance budget. So connecting the dots and aligning the plans across different functions is becoming a big priority as well. So you're seeing a lot of important changes happening. >> You just said a few things that's just gotten me standing up and getting all excited. Peter and I looked at each other, digital business, digital assets, digitizing your business, these are the mega-- >> Data value. >> Data value, this comes back down to what we've been talking about all week here on The Cube and for the past year. This is now what was once a come together, have a meeting, share, cross-pollinate, somewhat automated but in the end manual, to fully integrated. This is probably the biggest business problem in digital transformation right now. How come we're not hearing more? This is a-- >> Yeah, I think that's a great point, John. At the end of the day and what we've been talking about is that so this is is a little bit of SiliconANGLE Media, Wikibon, we believe that digital business, full-stop, is how you use data to differentially create sustained customers. >> Absolutely. >> That is digital business. You can say all kinds of new channels and all this other stuff, but it all boils down to are you using data as an asset better than your competitors? >> Yep. >> So that as a basis, two things. First off, interesting that Mark Hurd, we talked about it earlier, this is a quick aside, Mark Hurd talking about how CIOs are going to get more help. Remember when we talked about how Oracle's going to have to bring a lot of the IT group forward in its new transformation. >> This is it right here. >> Absolutely, but I'm going to throw you a little bit of a curve ball. I hope I'm not going to throw you a curve ball but its a very, very important point. As the IT organization, or as increasingly, the methods that we use to create digital assets, and increasingly also products, they're iterative, they're empirical, they're opportunistic, they're agile. That the traditional, year-long budget that says you have a certain money to spend, and you spend it or it goes away and you better not fail with this money, comes under attack by Agile, and I know a lot of CIOs that I talk to are trying to reconcile the impedance mismatch between Agile and Sprints, and being opportunistic and recognizing when something isn't working, and the CFO who's still talking about annualized releases of money. So I've always felt that you could not reconcile those. You could not bring those two points of view forward without EPM. Are you seeing that as well and how are you helping it? >> Yeah, we're definitely seeing this because this older, you're absolutely right. The old notion of let's make a budget once a year, get it right, and execute on it for the rest of the year, we are seeing that seeing that fading really fast. What people are saying is, look, plans are made only to be changed. Let's not fixate on getting the perfect plan in place. Let's start with a reasonable plan with the assumption that it's going to tweak and iterate and change many, many times over the year. So the focus is now on, less on getting it right the first time, more on how do we make dynamic changes to it in an agile fashion, just to your point. >> And reflect those changes throughout the entire cost-- >> And into finances-- >> Back into finance. >> It all comes back to finance. >> It comes back to finance because at the end of the day, let's say, take a simple example of a manufacturing company-- >> Paul: Finance is the language of business. It still is. >> End of the day, your business performance is measured in dollars and cents. I mean, period, right? So, let's say, your product mix changes because your customer demand is changing. That needs to be reflected back into finance, in terms of, okay, are we making more money or less money? Is it more revenue or less revenue? That needs to be reflected back, and so we're definitely seeing, in fact, the tagline for Enterprise Performance Management that we use these days is enabling business agility. So two parts to that, driving agile decisions, to your point, the second is, once you drive those agile decisions. Let's say I decided to expand into a new business and I did an acquisition. Fast forward six months, you need to reflect the results of that combined entity into your financial results, do it quickly, do it in a way that is correct and you're confident about the results and that's the job of finance. So it's agility of operations, agility in decision making, those two have to sort of come together. >> So here's my question then. I love this conversation because I think this speaks to the full-closed loop of Cloud and DevOps and the innovation around Agile. How much flexibility is built into the software, and I'm kind of going with the database route for a second, systems of records, schemas in database 'cause business plans can say it once a year and it's failing, I agree, I can see that failing. But, also, fixed schemas, can fail too. Well, I don't want to add the new data in 'cause the database can't handle it. I've heard that from developers before. Again, it slows the things down, so as you move from systems of record, which can be fixed and tweaked, the engagement data is the business engagement gestures. So how is that factoring into your software? You guys see that and is this AI Bot revolution and the machine learning, the smart software after engagement. Can you thread that through and explain how that fits? >> Let's start simple and sort of get a little more sophisticated quickly. The first things is we are seeing a lot more people come into the planning process than before. The old model was finance did the planning for other people. Now, people are doing their own plans, then sort of feeding it into the overall plan. People intentionally are pushing that because they want plans and decisions to be made closer to the point of action. Secondly, there is a greatest emphasis on driving fact-based decisions. For instance, we are working with some large consumer goods companies where they are saying, look, don't come here and tell me that I'm going to spend 10% less on this large line item compared to last year, Throw the last year's budget out and do a zero-based budget. I mean, zero-based budgeting is not a new concept. It's been around, but it's getting a new lease of life because in industries where profits are on the squeeze, they are saying "Look, I don't want "to do the traditional budgeting. "I want to go to a zero-based budget." >> Because they get facts that are surfacing faster. Is that kind of the premise? >> Facts, but more over to the performance of the business. >> That is definitely true. The facts that are surfacing faster, and, therefore, I want to give the tools to make use of those facts to the people who are closer to where they are surfacing. >> John: This is a digitized business in that scenario. >> Definitely true. >> Everything's instrumented. >> Good value. >> Hari: Yeah, definitely true. >> We always say on The Cube, I mean, this is the first time in the history of business in the world that you can actually measure everything. >> That is absolutely true. >> If you want to measure everything, you actually can do it. >> That is absolutely true. >> Now the CFO, which was once the measurement system, has to get integrated in. Am I getting this right? >> You are getting this right. You are getting this right. And the other part of your question is about okay, how is intelligence coming into, so some of these decisions over time, if you see a pattern, they can be perhaps automated. Plan adjustments can be, maybe some elements of plan adjustments can be automated, but I don't see finance going that far. That may be taken as an input. Maybe a recommendation comes from automated intelligence, and people will sort of take a look at it and say, "Hey, I want to go with this because it makes sense, "or I'm going to override it this way "because this doesn't take into account "what I'm planning for in the next quarter." >> Yeah, what scares me, though, in the whole bot thing, I mean, this is not a dis on Larik, I love the vision, it's got me all excited, is if they try to get too AI before they actually build the building blocks, they really can get ahead of themselves. So, you can see that head room, for sure, but a lot of companies are kind of in that planing mode. Is that true? What's this progress bar of customers right now who are into this, are in the software? I mean, track bots are great for certain things, but you can't really automate AI yet and everything. Or can you? >> I think there is probably a class of decisions that can be automated, but when it comes to finance, and finance tends to be conservative and for good reason, they definitely see the value of recommendations based on data, based on real-time data, but they still want to have the controls. >> [John} Got It. >> So that's kind of the mindset that we have seen. >> So real options valuations could really, really be helped by AI. But at the end of the day, you have to be able to close the books, and you don't need AI to help you close the books. >> This is a fascinating conversation. >> If I can add one quick conversation, just a quick point, as Enterprise Performance Management starts to weave its way into other parts of the business, institutionally, does that mean we're going to see controllers start to end up in different functions? >> Hari: (laughs) IOD of controllers? >> As a human interface that goes along with the system so that it works together. >> It's a definite possibility, right? Because if you're planning as rigorously in marketing as in finance and if you aremeasuring and reporting as rigorously in sales as you're doing in finance, maybe there's a sales controller function that becomes a legitimate need. But at the end of the day, today, you focus so much attention on reporting your numbers to the street. You focus attention on precision and accuracy and confidence in all of that. Why is that not a requirement for internal Reporting? >> It's the same argument when we talk about the technology of a structure. You move the computer to where the data is. You could move the controller where the action is, to your point earlier. It's a fascinating conversation, Hari. Thanks for sharing the insight. Love to do a follow-up on this because I think this really connects the language of business and kind of validates the digital fabric of digitization. But quick, I want to give you the last minute to give an update on the business, how you guys are doing. This is a pretty big deal. How's your business results, what's down the roadmap, what's the sales going to be like next month? I'm only kidding, I know. (all laugh) >> Sure, sure. I think the cloud has been a really game changer in this business. What the cloud has done has lowered the bar where we're seeing many mid-sized businesses start using Performance Management best practices, just like larger companies. We are seeing divisions or functions inside of larger businesses using Performance Management software for the first time. So there's a big market expansion, and we are seeing an expansion across other lines of businesses outside of finance. We are certainly seeing that. We are seeing that, you know, we introduced our first Cloud software in Enterprise Performance Management about two and a half years ago. At that time, we were not sure how the market update was going to be because we said finance tends to be conservative. Are they going to be comfortable doing their aggregated planning in the cloud, or are they going to be comfortable doing, reporting things in the cloud? We've been sort of pleasantly surprised by the willingness of finance, helped in part by the success the companies have had in deploying HR software in the cloud or CRM software in the cloud and so on. So the cloud has taken off. We have well north of 1,000 customers that have picked up EPM software in the cloud. We are very happy to see 100, 150 deployments go live every quarter, and we are seeing use cases in marketing, we are seeing use cases in HR of strategic workforce planning or marketing spend planning happened using EPM-style software. So, happy to see mid-sized businesses see real value from planning. >> John: Good integration capabilities? >> Good integration, I'm glad you mentioned it. Very good integration back into, for example, if you have financials in the cloud and EPM in the cloud, there are nice linkages between the two. So four teams are very important to us. We are seeing pervasive use of EPM software. We are seeing agile operations helped by EPM software in the cloud. We are seeing connected operations, whether it's the backbone systems or across functions. And we are seeing people take a sort of a comprehensive view of this, whether it's across functions or across processes. >> This is fascinating. We could go another hour. This is a really interesting topic because I think it really highlights a fact that, what we always say in The Cube is, you can provision technology faster and you get time to value certainly as the customers start to be creative and implement it. They get to actually put it to work and get the data around and behind. So thanks so much for spending the time on the insights on the EPM. We appreciate it, thank you so much. >> Thank you, I enjoyed the conversation. >> Okay, you're watching The Cube, live coverage here in San Francisco at Oracle OpenWorld 2016. I'm John Ferrier with Peter Burris. Thanks for watching. (upbeat synth music)

>> Narrator: The Cube presents On The Ground. (techno music) >> Hello and welcome, I'm Peter Burris With SilconANGLE Media Wikibon, and we're here today doing an on the ground, very important on the ground at Oracle's headquarters. This segment we're talking to Bhagat Nainani who is the group vice president of product development in Oracle's IOT organization. Welcome to The Cube. >> Thank you Peter. >> Now we've got a lot to talk about and because IOT is obviously at the fore front of many people's minds. It's one of the major initiatives happening in business, although a lot business people tell us that when somebody starts throwing IOT concepts at them they're not quite sure exactly what the parameters or what it means. So let's start here. A lot of hype about IOT, what does it mean to Oracle and Oracle's customers. >> Yes so there is definitely a lot of buzz about IOT and it is effecting a lot of industries whether it be manufacturing, transportation, home automation, fleet management, and we expect around 50 billion devices to be connected in the next two to three years and even the devices already connected to the edge and reading over 5 zettabytes of data and very little of that is actually-- >> Peter: Zettabytes. >> Exactly. >> So zettabytes is, megabytes, gigabytes, terabytes. >> Exabytes, then zettabytes. >> Lot of data. >> Lot of data and very little of that is being actually used. And if you look at top any analyst, it's they project somewhere between a one to five trillion dollar market right. But you know numbers aside, there is real business value here. I mean some companies are looking at IOT to improve operational efficiencies. Others want to use IOT to improve the customer experience or create new business models and new revenue streams. So there are clear opportunities here and that's what's affecting a lot of these organizations to the IOT. >> Now as a company tries to do something as complex as introducing a business model, they're going to need a lot of new technology as well as a lot of new good ideas. So what is Oracle's approach to engaging customers in this market place? >> So if many of our customers are going through these digital transformation or industry for all initiatives if you will. And there's some common factors in which in when it comes to IOT. Things like machine safety, productive, productive maintenance. Production reliability, worker productivity. Supply chain optimization. And all of these need extensions to existing applications or new types of applications. So Oracle's approach to IOT is to provide IOT enabled smart applications for things like manufacturing, fleet management, asset monitoring, equipment prognostics things like that. >> But that's much more than Oracle is currently providing right now. >> Exactly. >> So tell us a little bit about how this IOT ecosystem which is very broad, very complex, touches a lot of different parts of business, is embracing Oracle and how Oracle's trying to set up this appropriate partnerships so that customers can in fact get a complete solution. >> Sure, so, if you look at companies embarking on a journey to IOT, we see them go through sort of multiple phases. They start with just connecting their assets. You know so they have assets sitting on the field not connected to the business systems. They start connecting them so that they can get real time visibility for the assets and they can react more quickly to any problems that occur. So now they've reduced the time to react to any issues. That gives them sort of immediate ROI. But soon after they want to move to more of a proactive monitoring. So they're collecting information from all these assets and they want to do predictive analytics, and reduce unplanned down time and predict failures before they actually happen. Once they do that, then they want to transition to using IOT data into their core business processes. Whether it be back office, supply chain processes, ERP processes, or customer facing processes like CRM. Where they start to use IOT data to provide differentiated experiences. And the IOT offerings that we provide essentially help them go through this journey from connected assets all the way to service excellence. >> So when we're talking about connected assets, we're talking about the machinery, as well as the other resources at least that are either handling or running operations but also handling customer engagement. Now this suggests that there is going to be an intimate relationship between the technologies that are collecting all this data, sensing all this data, transmitting all this data, and the systems that are actually responsible for turning these feeds into something that is recognizable by the business as capable of generating a decision. Tell us a little bit about the relationship as you see it between IOT and big data. >> So recently we released an IOT Cloud service and the main difference in our approach to IOT versus many of the other vendors is we look at it from the applications out, as you said from the business out. We want to take the insides from these devices that data coming and make that actionable within your enterprise business processes all right. So the goal of IOT Cloud service is to actually bridge this gap between the operational technology and the IT world. And we do this be providing out of the box applications as well as platform components. I talked about applications like asset monitoring earlier. So there we have a out of the box app that helps you answer questions like how are my assets being used, where they're held. Do they need to be serviced. You look at it monitoring it's about how are my systems doing on the factory floor. Collect data from them constantly so that I can decide which ones to service in the next maintenance window right. Now I'm collecting all this data. This has to be backed by sort of platform components and the platform components fall in sort of this three broad categories right. Connect, analyze, integrate. So the connect part is where you bring the device, on board the devices. And provide bi-directional connectivity to them. So we have this concept called device virtualization which really simplifies how you interact with these devices. And provides a softer representation of those devices in the Cloud so now any application interacting with it doesn't need to know the gateways and the protocols that are used. On the analyze side there are two types of analysis. There is real time analysis which is done on the event stream. And then there's big data analysis that's done where you combine the real time stream along with contextual data sitting in your data lakes or your ERP systems. And then you apply predictive algorithms on top of it. We have a bunch of capabilities here. We provide business user friendly interfaces to model these event crossing functions. And we also provide built in algorithms using our big data services for things like equipment efficiency, remaining useful life, things like that. Right so, big data and IOT are quite related. If you look at the big data techniques like Spark, Hadoop, or some of these services, the type of data they all put it on, data with high velocity, high volume, high variety, IOT data has all the same characteristics of big data right. Now once you've analyzed this data, you also want to integrate it with your back end systems and that's where we provide out of the box connectivity with our SaaS apps as well as our E-business suite and our JD Edwards applications which are commonly used by our enterprise customers. You have the connectivity piece, you have the analytics, and you have the integration. You use these capabilities along with some of our other PaaS services like our business intentions Cloud service or our mobile Cloud source ability or IOT application. >> So you mentioned that these tools are easy to use. You also mentioned the distinction between IT and OT. This combination of IOT and big data analytics is touching a lot of different parts of the business. You have to be able to talk to operational technology people, IT people, you have to be able to talk to developers, you have to be increasingly be able to talk to business people. Historically, this all comes together when developers are engaged to create value out of all these piece parts. Talk a little bit about how Oracle is bringing greater sport to that developer community to bring this all together and turn it into value for a corporation. >> Sure so let's take an example here. Let's take the manufacturing example and then we'll I'll talk about manufacturing and then talk about some of the challenges there and how we enable that. You know we follow it up with community. In manufacturing world when you're doing these IOT kind of solutions, there's a common analysis done called a five M analysis. Man, machine, method, material, measurements. Now if you look at man, method, materials, all of this information is sitting in your ERP system or your databases. Where you have who operated on this system, what training did they receive, what techniques did they use, what raw material was used, who was the supplier. You look at machine and measurements, this is raw data coming from the equipment IOT data and measurements around the tests that were done on the system. You need to combine both of these to create a real predictable analytics solution for manufacturing right. Now today a lot of this has to be done using sophisticated sort of data scientists and you need sophisticated developers who can operate on these various big data components, whether it be Spark, Kafka, Cassandra, all of these. What we are doing at Oracle is trying to provide sort of tools and frame works that abstract away some of that and are targeted towards the citizen developer or the business users. So you don't need to have sophisticated data scientists. Right, we have tools such as big data discovery, big data prep, and other tools such as Apache learning which make it easy to build these kind of models. Now if you are a developer who wants to write all of this from scratch, you will then when you're dealing with different types of structure and unstructured store, you need an abstraction layer that simplifies how you interact with this, how you query it. And so we are providing sequel like interfaces that they're already familiar with. So whether it's a structured store or unstructured store and well, it doesn't matter which native query interface I suppose. You provide a standardized list so that they easily operate on that data. Now even that takes a long time to build an IOT solution so that's where our out of the box applications come in and by providing these out of the box applications for specific use cases around asset monitoring, equipment prognostics, supply chain, we are really trying to reduce the time it takes for you to deploy an IOT solution because these applications already have those built in algorithms. All we are doing is configuring them, providing some parameters, but you don't need to write the algorithm. You take your industrial gateways, connect the devices, and you're ready to go. >> So do you think that there's going to be new applications utilizing some of these new methods or models, or is it going to be just an extension of a lot of the traditional, more operational, financial oriented applications that are already in place. >> It's a combination. So when it comes to things like you know existing maintenance applications, or existing service applications, the interfaces of them used to be you know manual where someone would get a call and they would enter an order into a system or a work order. With IOT those are being extended to have new channels. So for example in our service Cloud, we have added a new channel with IOTs so now the equipment itself reports a problem and when the service technician gets a work order, they already know which part has gone bad. So the whole manual step is taken away. There are other areas where companies are trying to transition to this product as a service model, right. And so those need new ways of monetizing, new types of application for your capture and utilization. There you will need some new application. So it is a combination of the two. >> Now you mentioned earlier the five M model. Man, materials, machines. >> Method. >> Measurement. And method. Just to give you to date myself, the first class on technology I took talked about the four M plus I model. Men, materials, machines, money, and information. So didn't have method. But let's come back to at least what we think at Wikibon, SiliconANGLE, is still the most important piece, men. Or people, the individuals. We're talking about the, we're talking about IOT here, but presumably we're going to also start bringing in those crucial interfaces so that people become a more engaged feature of how these loops are working. Between sensing, and analyzing and printing models, and enacting something in the market place. Tell us a little bit about how Oracle sees the role that people are going to play in these transitions that we're talking about. >> So if you look at the service industry people right. I mean this I give you the example of automatically creating a work order. But with IOT enabled devices, it is transitioning to more of a self service, model or assisted service model where now people have much more information available to them at their fingertips when they are actually looking at problems. Whether it be some part that has failed or a customer has reported an issue, now you can interact with these devices remotely and so now you have significant reduced the time to actually act on any problems and overall improve the customer experience. There is the people part in sort of creating those models and providing sort of information to enrich those models because you know a data scientist can get all the information from the devices and create the models, but you also need the experts who know you know how these systems are supposed to behave. How they were designed, how they behave under certain environment conditions. You take that into account along with the real data that you're getting and that way you can predict how this particular equipment will behave in the field right. >> So Oracle open world is just around the corner. One quick idea. What are you looking for from an Oracle IOT perspective. >> From an Oracle IOT perspective, one of the things we were really looking forward to is the applications that you know we are launching as well as many other applications within Oracle who have now embedded IOT within their offering. So to make those applications smarter and you hear a lot about that at open world. >> And that is one of their key tests of adoption is how fast that happens. Bhagat Nainani thank you very much for being here. Group vice president for IOT product development at Oracle. Again, Peter Burris from The Cube. Thank you very much. >> Baghat: Thank you Peter. (techno music)