>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Welcome back everybody, Jeff Frick here with theCUBE. We're at AWS re:Invent 2018 at the Sands Convention Center and all over Vegas. I don't know how many people are here. We haven't gotten the official word. 60,000, 70,000, I don't know. There's a lot of people. We're excited to have our next guest, but before we get in, happy to be joined by Lauren Cooney. Lauren, great to see you, as always. >> Great to see you, as well. >> You know, one of my favorite things about doing Cube interviews is we learn about new industries that we didn't even know about. So, while we're here talking about IT, it's really about the application of IT that I think is really more interesting, more fun, and a great learning experience. So, we're really excited to have our next guest on. He is Kevin Smith, the director of MIS for Transcore. Kevin, great to see you. >> Hello. >> And many time Cube alumni, Sazzala Reddy. He is the CTO and co founder of Datrium. Sazzala, great to see you. >> Happy to be here. >> So, Kevin before we get into it, tells us a little about Transcore. What are you guys all about? >> Basically, we are the leading toll authority for kind of of Continental United States and we are trying to expand that throughout the world. We do the whole engineer all the way through manufacturing of toll systems for vehicles and cars throughout the U.S. So, the little stickers in you car all the way up to the readers that read them. They're coming through my place some how or some other. >> So, everything from the reader in the car-- >> Yup, the little sticker tag that sticks in your window or suction cups in. Wherever you are, yes you may hate us, but I'm not the one collecting the tolls. (laughs) >> I don't like it when you miss the picture. >> Well, let's input some design here. (laughs) >> Trust me, I've tried. (laughs) >> But then the huge back in process to pull that up, get it into the system, billing systems. >> Yeah, all integrated. Yep. >> And how big is the company? How long has it been around? >> We were acquired by Roper. We've been many divisions, but Los Alamos was technically, founding fathers 1954. >> 1954, so you've been around a long time >> Oh yeah, yes. They started with cows. >> RFID's on cows? >> Yes, tracking cows in the pastures of New Mexico. (laughs) >> With the little tags in their ears I imagine. Alright, great. We can talk about traffic probably all day long, but that's not why were here. That's not your day job you're not out there with the little RFID scanner. >> Not anymore, thank God. >> Let's talk about some of the challenges 'cause you know, obviously, the toll business has been around for a long time. But the automation of tolls has really changed a lot over the last five years. You probably know better than me from somebody in the booth taking my money and giving me a receipt to some places it's almost exclusively electronic. So, how's that business grown, and what have been some of the accompanying challenges have you seen that been grown? >> Part of the performance issues we were running into was the quantity. Because the man is gone from the booth, we have to produce more tags that become more readable. So, that creates more back in work, more transactions. And, in the long run, producing more tags. You know, we've gone to millions and millions of tags being produced, in a quarter, to where it was just hundreds of thousands. So, with that requires scalability that we can grow with our systems and our systems we had just wasn't doing it. >> So, you got the manufacturing of the tags as well, I didn't even think of the manufac- you got to make them in the first place, too. >> That is our bread and butter. Manufacturing those tags and the millions of millions of transactions that we test, because we have to test every tag that goes out the door. Every tag gets tested. >> How far away do they work, on those readers? I'm just curious. >> It depends on your speed. We've tested up to 200 miles an hour. And I think it's, like, 40-50 feet? So, as long as you're going under 200 miles an hour, we can get ya. >> Okay, so, how did you meet Sazzala in Datrium? How did that come about? >> We went looking for a product that could give us a one stop solution. We wanted something that was basically, I wanted to get out of the storage business, I wanted to get out of the management business. I didn't want to be having to worry about all these different vendors, all these different solutions. And Datrium was able to provide that. Compared to some of the other products that we were looking at, we did test with other products, and Datrium came out on top. They gave us the total package. >> Sazzala, when you looked at this oppurtunity, what did you see? Anything unique and different? What were some of the challenges that you tried to figure out how to help Kevin? >> So, what we are finding is that more and more companies, every company is a software company, every company is a data company, right? Every body wants to move faster. Everybody wants to things faster. I can't wait for my movie to start in two seconds. I'm like, Why is it taking two seconds? So, everybody wants things faster. We live in this instant economy where everything needs to be either you transform or you die. So, how do we make that transition into the speed? How do you build your data center, whatever your doing, to match that speed of innovation? Any system you're going to deploy in a data center, has to be not in the way. It has to be less management, less overhead. Look at Amazon, very successful because there is less to manage. And, you mostly manage your applications. That's what the business moral is going to be going forward. That's why people like the Cloud. Why does CIO like the Cloud? Not because it's cooler, or whatever, but because it makes things faster. It's expensive, yeah, but it makes things faster in some ways. >> Go ahead. >> I was going to say, on issue we ran into and we came to him with was our CAD designers. 'Cause we designed the product. And, the rendering was just dragging on our old systems. And, we went from two to three minutes rendering to seconds rendering new graphics. And, so, before they were like I'm not going to save it yet, I'm not going to re-render it. Now, they're re-rendering every time they're making a change. It helps in performance, it helps the application, and it helps increase the productivity of my CAD designers. >> Right. I was going to say, it was probably the customer service pretty significant, as well, so they can get the version that they want. >> Definitely, definitely. And, you know, the nice thing is is Datrium allowed us to scale. We couldn't go out and just Okay, revamp everything. You got to do baby steps. And Datrium gave us that scaleabilty, to where I could add anything from 1 to 128 nodes. You know, I was able to increase performance by just adding a server node, or increase the rights by adding a data node. That's the flexibilty that I needed from a vendor. >> So, when you said that Datrium had the whole package, you looked at some other solutions out there. When you were trying to find the whole package at the beginning of the process, what were the key attributes that you said I would love to get all these from one place? >> I was looking for performance and scale. Which I got. I was looking for back-up. God, I wanted to get out of the back-up business. I was tired of tapes, I was tired of third-party solutions. >> Tire of tapes? (laughs) >> Trust me. Shh, don't tell the tape vendors here. >> Tape is good, if you have the right application. >> Security, I stay awake at night. I lead our security teams. I stay awake worrying about Is my data protected? You know, with their encryption, that gave me that whole protection. And the last thing was DR. DR is adorned in every IT manager, every IT director, every, you know, CTO. And, with their whole Cloud shift, that DR? What DR, it's done. It just happens. And those four things is kind of what led us to finding Datrium. 'Cause some of them gave us one or two, but not everyone could give us all four of the options that we were looking for. >> What I love about the story is those are kind of concrete savings and doing your job easier. What your excited about is enabling your CAD designer, your kind of proactive sales process, your proactive design, your proactive innovation to actually move faster. That's not a cost saving mechanism. That's really a transformational, kind of positive revenue, side of the tale that I don't think is told enough. People focus on the cost savings and execution. That's not what it's about. It's really about innovating and growing your business faster. Do you think? >> Oh no, our ROI, that we calculated in, was just on hardware. Just on my cost savings that I could put a penny to. The time, it's so great. I mean, my CAD designers producing product faster, my developers are asking for more VMs. For me to spin up because the speed is so much faster. We're used to being Oh, don't touch it. I got this guy tuned exactly where I want it. We got the memory. But now, they're asking for more and more, and it's my in users, who are really the engineers, my manufacturing people, they're wanting more and more out of the product and Datirum is delivering. I don't go to dashboard and look to try and figure out how to tweak it anymore. I don't have any complaints. And, if I don't have any complaints, were doing something right. >> That's a good thing. >> So, it just works? >> Oh, it was beyond just works. >> Literally. >> Trust me, I was ready when we bought product to bring in a whole team and I was like, Oh, I'm going to have to hire all these people. And the guy came in and he goes, Okay, turn it on. Okay we're done. I was like, Nu-uh. He goes, Oh yeah, you have to plug that cord in back there. I was like, Wow. 'Cause, you know, usually it's-- >> I'm looking at a number right now, and it is 617% three year ROI. >> It's across many customers (mumbles) >> I totally believe you with what-- >> So we are aiming for a U.S. designer came and asked me one day, What should I aim for as a design principle? I said, We should aim for zero UI. That's what we should do. It should be transparent, it should just work. That's what we really aim for. I'm not saying we have zero UI today, but that's our goal. >> It's good to have goals. >> Let's just make it work automatically, right? That's kind of the goal. >> Well, and that was one thing, we wanted something integrated, so we didn't have to go looking. And, that's one thing I tell the engineers all the time. I go into the UI just to kind of see how cool the systems running. You know, because there is no issues. It just works. Everything's integrated, I don't have to go in and click and click and click and click to get through stuff. It just works and integrates well. We're a big Vmware shop, big Dell server shop. All of that, one-stop shop. I was telling Sazzala, you know, it's great when I get the e-mail that there's a problem with my Datrium system before my help desk is getting the notification. I can't buy that service. >> So, Kevin, there's a lot of peers that will be watching this show. Peers of you. Having gone through this process and now you are on the other side and you're on to some new things, in terms of innovation, what would you share with a peer whose trying to sort some of this out? It's a confusing landscape. There's so many options, and you got to do your day job, too. Besides, putting out new technology. What would you share with a peer if you're sitting down over a beverage on a Friday afternoon? >> You know, I would talk to them about having that capability, really a performance scale. Being able to not worry about controllers, not worrying about what SSDs you got to put into something to make it work. Pop 'em in. SSDs are cheap nowadays. Pop 'em in. It increases your reads. Going back to the whole no more third-party solutions for back-ups. Every SIS admin, every manager knows, back-ups are only good for restores. That's the only reason you do a back-up, is 'cause you got to do that restore. And, it becomes invisible. It's all running in the background. I don't even think about it anymore. My old systems, we still think about. That aren't on the Datrium product yet, but all our production (scoffs) When I'm backing up every hour, and my RTO almost becomes zero if something happens, you can't ask for that. That's critical, I think, for every manager, every director, even the SIS admins. No one wants to really think about back-ups. And, when you're comparing your products, take a look at that. How quick can you get something back up when that hard drive went out, you know? That's critical. And, of course, DR is, you know, everyone needs that checkbox checked for recovering. It just comes right away, with that. >> We've run out of time. Going to ask you the big question. Do you sleep better? >> Oh, much better. (laughs) Easily now. Yes. Now I get to worry about other things. Like keeping my CFO happy about something else. >> And, I've got a list of people we need to introduce to you. Definitely. >> Fortunately, you always move through your next point of failure. Once you fix one spot. Watch Lucy check out the chocolate-- >> Hey, but if I can have this one off my plate, that's one better for me. >> Well, Kevin, thanks a lot for telling your story. It's a really impressive story And, I'll think of you as I go across a Dumbarton Bridge some time. >> Think about that, yes! >> Absolutely. >> Thank you for having me. >> Sazzala, great to see you, as always. Lauren, lots of fun. I'm Jeff Frick, you're watching theCube. We're at AWS re:Invent 2018. Thanks for watching. (electronic music)

you live from Orlando Florida it's the cube coverage conf 18 got to you by Splunk welcome back to comp 2018 this is the cube the leader in live tech coverage my name is Dave Volante I'm here with my co-host Stu minimun we're gonna start the day we're going to talk to some customers we love that John Morris here is the MIS program director at UConn the Huskies welcome to the cube good to see you and he's joined by Ryan O'Connor who's the senior advisory engineer at Splunk he's got the cool hat on gents welcome to the cube great to have you thank you thank you for having us so kind of a cool setting this morning is the Stu's first conf and I said you know when you see this it's kind of crazy we're all shaking our phones we had the horse race this morning we won so that was kind of orange yeah team are and team orange as well that's great you're on Team Orange so we're in the media section and the median guys were like sitting on their hands but Stu and I were getting into it good job nice and easy so Jon let's start with you start always left to start with the customer perspective maybe you describe your role and we'll get into it sure so as you mentioned I'm the director of our undergrad program Mis management information systems business technology we're in the school of business under the operations and information management department the acronym OPI M okay cool and gesture Ryan tell us about your role explain the Hat absolutely yeah so I'm a member of an honorary member of the Splunk trust now I recently joined Splunk about a month ago back in August and yeah and outside of my full-time job working at Splunk I'm also an adjunct professor at the University of Connecticut and so I helped John in teaching and you know that's that's kind of my role and where our worlds sort of meet so John we were to when I were talking about the sort of evolution of Splunk the company that was just you know okay log file analysis kind of on-prem perpetual license model and it's really evolved and its permanent permeating throughout you know many organizations but maybe you could take us through sort of the early days and it was UConn for a while what what was life like before Splunk what prompted you to start playing around with Splunk and where have you taken it what's your journey look like so about three years ago we started looking at it through kind of an educational lens started to think of how could we tie it into the curriculum we started talking to a lot of the recruiters and companies that many of our students go into saying what skillsets are you looking for and Splunk was definitely one of those so academia takes a while to change the curriculum make that pendulum swing so it was how can we get this into students hands as quickly as possible and also make it applicable so we developed this initiative in our department called OPI M innovate which was all based around bringing emerging technology skills to students outside of the general curriculum we built an innovation space a research lab and really focused in bringing students in classes and incorporating it that way we started kind of slowly different parts of some early classes about three years ago different data analytics predictive analytics courses and then that really built into we did a few workshops with our innovate initiative which Ryan taught and then from there it kind of exploded we started doing projects and our latest one was with the Splunk mobile team okay you guys had some hard news around now well today right yeah maybe take us through that absolutely wanted sure yeah I'll take that so we we teach a course on IOT industrial IOT at the University of Connecticut and so we heard about the mobile projects and you know the basically they were doing a beta of the mobile and application so we we partnered with them this summer and they came in you know we have a Splunk Enterprise license through Splunk for good so we're able to actually ingest Splunk data and so as part of that course we can ingest IOT data and use Splunk mobile to visualize it all right right right maybe you could explain to our audience that might not know spun for good absolutely yeah so spun for good is a great initiative they offer a Splunk pledge license they call it to higher education institutions and research initiatives so we're able to have a 10 gig license for free that we can you know run our own Splunk enterprise we can have students actually get hands-on experience with it and in addition to that they also get free training so they can take Splunk fundamentals one and two and actually come out of school with hands-on experience and certifications when they go into the job market that's John name you know we talk so much about them the important role of data and you know that the tools change a lot you know when we talk about kind of the next generation of jobs you're right at that intersection maybe you can give you know what what are what are the students what are they looking for what are the people that are looking for them hoping that they come out of school with you know yeah it's it's um you have two different types of students I would say those that know what they're looking for and those that don't that I really have the curiosity they want to learn and so we we try to build this initiative around both those that maybe they're afraid of the technology and the skills so how do we bring them in how do we make a very immersive environment kind of have that aha moment quickly so we have a series of services around that we have what's called tech kits the students come in they're able to do something applicable right away and it sparks an interest and then we also kind of developed another path for those that were more interested in doing projects or they had that higher level skill set but we also wanted to cultivate an environment where they could learn more so a lot of it is being able to scaffold the learning environment based off of the different student coming in so it's interesting my son's a junior in college at GW and he's very excited he's playing around with date he says I'm learning are I'm learning Tablo I'm like great what about Splunk and he said what's that yes so yeah then though it's a little off-center from some of the more traditional visualization tools for example so it's it's interesting and impressive that you guys sort of identified that need and actually brought it to two students how did that all how what was in an epiphany or was that demand from the students how'd that come about it was a combination of a lot of things you know we were lucky Ryan and I have known each other for a long time as the director of the program trying to figure out what classes we should bring in how to build out the curriculum and we have our core classes but then we have the liberty to build out special topics things that we think are irrelevant up-and-coming we can try it out once if it's good maybe teach it a few more times maybe it becomes a permanent class and that's kind of where we were able to pull Ryan in and he had been doing consulting for Splunk for a number of years I said I think you know this is our important skill set is it something that you could help bring to the students sure yeah yeah I mean one of the big courses we looked at was a data analytics course and we were already teaching with a separate piece of software not gonna name names but essentially I looked at it one for one like what key benefits does this piece of software have you know what are the students trying to get out of it and then just compared to one for one to Splunk like could Splunk actually give them the same learning components and all that and it could and and with this one for swum for a good license and all that stuff we could give them the hands-on experience and augment our teaching with that free training so and they come out of school they have something tangible they can say you know I have this and so that would kind of snowball once that course worked then we could integrate it into multiple other courses so you were able to essentially replicate the value to the students of the legacy software and but also have a modern platform exactly exactly yep yeah you know that and that was a what was like a Doug was talking about making jokes about MDM and codifying business processes and yeah it's a little bit more of an antiquated piece of software essentially you know and I mean it was nice it did a great job but there wasn't when we were talking to recruiters and stuff it wasn't a piece of software that recruiters were actually looking at so we said we were hearing Splunk over and over again so why not just bring it into the classroom and give them that so in the keynote this morning started to give a vision I believe they call it Splunk next and mobile things like augmented reality are fitting in you know how do you look at things like this what what how's the mobile going to impact you especially I would think yeah so when we kind of came up with our initiative we identified five tracks that both skill sets we believe the students needed and that and companies were kind of looking for a lot of that was our students would go into internships and say hey you know the the set skills that were learning you know they're asking us to do all this other work in AWS and drones and VR so as again it's part of this it was identifying let's start small five tracks so we started with 3d printing virtual reality microcontrollers IOT and then analytics kind of tying that all together so we had already been building an environment to try and incorporate that and when we kind of started working with the spunk mobile team there's all these different components we wanted to not only tie into the class but tied into the larger initiative so the goal of the class is not to just get these students the skills interesting interested in it but to spread that awareness the Augmented part is just kind of another feature was the next piece that we're looking in to build activities and it just had this great synergy of coming in at the right time saying hey look at this sensor that we built and now you can look at data in an AR it's a really powerful thing to most people so yeah they showed that screenshot of AR during the keynote and one of the challenges that we have at the farm so we're teaching that this is the latest course that we're talking about on an industrial IOT one of the challenges we have at that farm is we don't have a desk we don't have a laptop but we do have a phone in our pocket and we have we can put a QR code or NFC tag anywhere inside that facility so we can actually have we have students go around and you know they can put an iPhone upto a sensor or scan a QR code and see actual live real-time data of what those sensors are doing which is it's an invaluable tool inside the classroom and in an environment like that for sure so it's interesting able to do things we never would have been able to do before I want to ask you about come back to mobile yeah as you you just saying it was a something that people have wanted for a long time it took a while yeah presumably it's not trivial to take all this data and present it in a format and mobile that's simple number one and number two is a lot of spunky users are you know they're at the command center right and they're on the grid yep so maybe that worked to your advantage a little bit and that you know you look at how quickly mobile apps become obsolete hmm so is that why it took so long because it was so complicated and you had a user profile that was largely stationary yeah and how is that change yes honestly I'm not sure in the full history of the mobile app I know there previously was a new mobile app and I are there was an old mobile app and this new one though is you use it the new one yes oh so when we're talking about augmented reality that might be we may not been clear on that augmented reality is actually part of its features and then in addition we have the Apple TV app is in our lab we have a dashboard displayed on a monitor so not only can we teach this class and have students setting up sensors and all this but we can live display it for everyone to come in and look at all the time and we know that it's a secure connection to our back-end people walk into the lab and the first thing I see is this live dashboard Splunk data from the Apple TV based off of project we've been working on what's that well that's a live feed from a farm five miles off campus giving us all these data points and it's just a talking point people are like wow how did you do that and you know it kind of goes from there yeah and the farm managers are actively looking at it too so they can see when the doors are open and closed to the facility you know the temperature gets too high all these metrics are actually used by the you know that was the important part to actually solve a business problem for them you know we we built a proof of concept for the class so the students could see it then their students are kind of replicating another final project in the class class is still ongoing but where they have to build out a sensor for for plants to so it's kind of the same type of sensor kit but it's they're more stationary plant systems and then they have to figure out how to take that data put it into Splunk and make sense of it so there's all these different components and you get for the students get the glam factor you can put it in a fishbowl have the Apple TV up there exactly and that's I mean part of it when we when we started to think about in ishutin you know it was recruitment you know how do we get students beyond that fear of technology especially kind of coming into a business school but it really went well beyond that we aligned it with the launch of our analytics minor which was open to anyone so now we're getting students from outside the school a bit liberal arts students creating very diverse teams and even in the class itself we have engineers business psychology student history student that are all looking to understand data and platforms to be able to make decisions so there's essentially one Splunk class today instead of a Splunk 101 there this semester there's there's a couple classes that are actually using Splunk inside the classroom and I mean depends on the semester how many we have going on that are actually there's three the semester I sorry I misspoke there we have a another professor as well who's also utilizing it so so yeah we have three three classes that are essentially relying on Splunk to teach different components or you know is it helped us understand is it part of almost exclusively part of the analytics you know curriculum or is it sort of permeate into other Mis and computer science or right now it's within our kind of Mis purview trying to you know build all their partners within the university and the classes they're not it's not solely on spunk spunk is a component of you the tool so it's like for example the particular industrial IOT course it is understanding microcontrollers understanding aquaponics and sustainability understanding how to look at data clean data and then using Splunk as a tool to help bring that all together yeah it's kind of the backbone you know love it and then and I mean in addition to I just wanted to mention that we've had students already go out into the field which is great and come back and tell us hey we went out to a job and we mentioned that we knew Splunk and we were you know a shoo-in for certain things once it goes up on their LinkedIn profile and start getting yeah I mean I again I would think it's right up there with I mean even even more so I mean everybody says and right and our day it was SPSS now it's our yep tableau obviously for the VIS everybody's kind of playing around but spunk is a very you know specific capability that not everybody has except every IT department on the planet exactly coming out of school you take a little bit deeper you either you find you find that out yeah cool well great work guys really thank you guys coming on the cube it was great to meet you I appreciate it incoming all right you're welcome all right keep it right - everybody stew and I will be right back after this this is day one of cough 18 from Splunk this is the cube [Music]

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape digital transformation is the operative watchword today but what does it mean from a cxos standpoint and how do you take those perspectives and bring them into an organization to affect its strategy and turn that strategy into action hi everybody this is Dave Allen say welcome to this cube conversations of CXO perspectives I'm here with Paul Lewis who's CTO of Americas from Hitachi ventaja Paul thanks for coming down from Toronto thanks very much I appreciate always great to be in Boston okay let's start with you in your background you're a CIO by trade been with Hitachi and now Hitachi Bonterra for a few years but tell us about your background yeah so I've been here about five years running the office of the CTO which is a highly vertical based organization prior to that I was a CIO CTO of a financial services organization for about 17 years operating technology sort of being a practitioner of what it means to create applications and operate IT and implement projects and worry about you know the blinking lights in a data centre so it's a very different world being on the manufacturer side but getting to see different verticals different industries and applying that it's been intellectually appealing so something I want to come back to exceed you were CIO and CTO which is not uncommon but often times that you know CIO is you know more in a strategy or a pure business role you had both so we'll come back to that when we talk about you know organizational issues but let's start with digital transformation as I said at the top it's the buzz word you go to every conference digital transformation you must you you must not get eaten by your competitors you must be the disrupter etc etc but what does digital transfer transformation mean to you as a CTO CIO from a customer's perspective so I see it much more as being having a customer perspective when you look at your business strategy so in as much as people say sort of customer 360 or you're taking a customer centric approach it's not really that it's it's saying how do I look at my business and evaluate it from the customers point of view so you know the three aspects of digital transformation is operational efficiency new business models and of course the new customer experience so operational efficiency says you if I'm doing a whole bunch of things or to deliver value a product or service but the only thing the customer sees is what's on the shelf and what's available to purchase then everything I do behind the scenes logistics is up for grabs maybe I do it's not an azimuth amia what's on the shelf so maybe somebody else can do it make that efficiency in terms of new business models if all my competitors especially those new digital disruptors have a new way of engaging with the client and the payment maybe it's a credit card versus cash you know capital versus op X maybe I need to diversify my portfolio to be equivalent to that to find customers that I'm currently not getting and then finally new customer experiences this is the customer point of view to say the customer wants to buy from you in a certain way so you better start to sell your products and service in the way to which they want to buy just because your products on the Shelf and the customer wants to buy from you online means you have to also be online and if your customer wants to buy from your competitor your product should be at your competitor right so you've got to think about how the customer buys not just how you sell so all that sort of business strategy so we could poke that a little bit so in a positive way so when you go back to pre-internet days the brand's had all the power right the retail companies knew what the pricing was you know the the the spreads in the stock market were really large we had Nasdaq on last week at Pentaho world all we talked about is how they're becoming basically a technology company to sell their services to others if they are transforming digitally so my my point and question to you is isn't a lot of digital transformation about how you use data to compete and actually maybe regain some of that you know market power or or or at least catch up to where the consumers are cuz the consumers today have all the advantage don't they well data certainly is a value producer versus sort of a side effect that it used to be but it is fair that the consumers have much more buying power than they have before and that's that's in many ways because of those disruptors those disruptors are creating new options for consumers and option and now consumers have that choice in fact the cut the consumerization as a whole as changing how consumers even perceive companies right so if I can download an app and if I don't like it an hour I can delete that up and download they can also choose your product in the same way they're gonna buy your product they don't like it they're gonna throw it away and buy somebody else's product they now have the ultimate choice to do anything they wish buy from anybody they want to locally or globally the globalization concept is changing the way you need to distribute your products and services to yes so the power actually in influence has gone to the consumer and it's only data that you can produce and you can consume externally that'll give you that insight to determine where I need to put my puck right where I need to hockey analogy where I need to ensure that I need to have my product and service and available before the customer wants it or even perceived to want it versus sort of waiting behind the scenes so the big difference between let's say being digital versus non digital is the data yeah but what does that mean to a CTO and a CIO so okay data that's the big difference not what I would say let's take it from the top so if the CEO now is focused on creating more value quicker they probably hire a chief digital officer that's focused on those three pillars if the organization is not that big they might have the CIO perform that function that means the CIO is less about order-taking and more about value creation the only way they're gonna be of value creators if they move from an application centric world of IT to a data centric world of IT and I use an analogy of applications infrastructure and applications I'm gonna go through that way yeah so here's your more about there's the difference between infrastructure applications and data if I look at infrastructure at lasts let's say three to five years I might be able to sweat it out any longer but if I do I'm gonna have performance scalability availability problems if I add more infrastructure to infrastructure it's gonna cost me more money I need more space I need more power and more rack right same kind of true on the application side if I that the last maybe seven to nine years maybe sweated out any longer I have seen performance of scalability problems if I add more applications to applications I have modernization as simplification and rationalization problems and it's not the number of applications that matter it's that I have the same function point recreated across five to ten different applications and five different 10 teams worrying about it same cost issue and and and data quality issue absolutely but data is in fact the opposite to that data is valuable to me from the point that I created the point that I deleted if I ever delete it in fact seeing data change over time is more valuable than seeing it static in its initial State if I add more data to data the bigger potential pot of gold I have and the Nuggets that I can find the more precise my algorithms become the more insightful I'll be able to create from a client's perspective for a firm product or transaction perspective in fact it is the value creator for IT versus the side effect that it's always been so if you remove the centricity from the CIO form application which is red green yellow projects to data being the value creator you start to be a major player in the digital transformation organization instead of sort of being the order taker project so there was a lot of things you said in there that made a lot of sense to me let me start with sort of the infrastructure that a lot of CIOs have spend have to spend their time keeping the lights on and that's not a value producing activity we can agree there were in still are many CIOs that sir were application-centric as you were saying and they would add a lot of value through those applications they have you know sharp application development team they could differentiate through those applications but increasingly when I talk to CIOs you see more sass coming into play and they're trying to avoid custom modifications so when I ask them well how do you differentiate the differentiation is the data the data and the IP that we build around that data the way that data helps us monetize whether it's directly or indirectly is our new differentiator but that's a big shift isn't it it's a large shift because they're they're completely application centric all their projects are about versioning of applications all their infrastructures creating highly available for applications so the big shift is say how do I create an organization that's data centric as a whole how to create a chief data officer and that data officer is elevated to be the peer of in many ways the VP of application the VP of M their organization has all the data centric responsibilities they have storage and protection and governance and analytics and stewardship they are the measured by the value they produce for the organization whether that's operational efficiency or revenue versus the projects to which they deliver on and that way the output of IT is not just projects it's not just spend but it's in fact revenue or profit let's talk about the organizational roles I said I wanted to come back to that and I do I you know you know the jokes CI o stands for career is over I was interviewing John haladki who was the CIO of Beth Israel Hospital a while back at MIT one of the shows we do and he was not optimistic about the role of the CIO Easter Day could disappear and the conversation it was a CDO conference chief data officer conference the conversation was well CIOs need to pick a path and you've got some experience here they either have to become CTOs or they have to become chief data officer x' now that was maybe two years ago I think the narrative has changed a little bit and people have calmed down about that but you've seen this these roles emerge chief data officer chief digital officer we just talked about how digital equals data so I actually see those two roles as you know more closely you know aligned or not depending on on the user but and the CIOs role I think you know and becoming more clear as as a business and strategy person but I wonder if you could weigh in as a former CI o-- / CTO current CTO you talk to a lot of customers how do you see organizations you know what's the right regime right regimes not the right that's not the proper term but what's the regime's that you see emerging I think the big shift determining what those organization roles are from standardization to verse2 diversification so it's less about single provider single process single implementation having a single set of IT services for all the potential workloads and more like what does the business and specific the line of business require and then how am I going to support that so it's now I'm going to have internal services I'm gonna have a private cloud I'm gonna use public cloud offerings I'm gonna have managed services I'm gonna go to third-party offerings I'm going to use a bunch of sass I'm going to consume a lot of cloud versions of ERP type products and that's the complexity of my environment and if that's the complexity of my environment that's the complexity and change of the shift of the roles the CIO now has to be less about project delivery in other words creating applications and more about managing an ecosystem of diverse deployments they have to manage relationships with public clouds they have to manage and create business offerings with the CFO and the CEO and the chief corporate officer in terms of creating new acquisitions or mergers right the CTO is focused on creating a highly secure framework of delivery so that not only the IT shop can deliver on value but all that shadow IT that's happening outs external to greet create a platform and a secure platform for them to deliver because the reality is of every hundred dollars of the CIO has there's $250 out in the business so why don't you make it 350 million it's $350 IT budget instead of 101 you do that by providing platforms and so therefore the CIO is part of the business leader versus being the IT leader the CTO is looking at platforms and therefore the chief data officer becomes the value producer they're the one focused almost entirely on creating revenue or creating so much efficiency in the organization that the profit margins dramatically increase so now business perspective business perspective business perspective and everything underlying is ecosystem it's not everything that I built it's things that I consume externally Wow okay so again a lot of things you said in there that make some sense that I want to better understand so the chief data officer as you described it sort of job one for her or him is to is understand how to essentially make money with data right all right and and again I don't want to say go sell your data because that's not always the answer but you're saying draw you can drive efficiencies and that the simplest form you can cut cost you can increase revenue or you can make better decisions right that's the whole champion in Channel your concept you can have a better understanding of your clients or your products and more importantly have a better understanding of clients - which currently don't purchase your products right how do I look at internal information and compared to external data to say oh how are those other consumers that are going to other my other disruptors what are they purchasing and why can't I produce something that's like or at least competitive in that world so you started off this conversation with three things operational efficiency new business models and the customer experience so there's certainly the chief data officer as you just mentioned can affect operational efficiency ways to cut cost you know through data and I guess they touch new business models as well hey if we're gonna monetize our data directly or a partner or bring in other data and you know did we talk about Nasdaq before that's a completely new before even working with the finance office to say if I were to make changes to my business here would be the net financial effect right okay now the customer experience is that the domain of the chief digital officer really more in that customer facing still still a combination but I would agree that the chief digital officer focusing on creating to matching the selling experience with the buy experience and that might be new mobile interfaces this might be creating omni-channel experiences or expanding upon that to say how do we ensure that we have an integrated channel experience it's not just that they can bribe you know a shoe and the website a shoe in a store it's that they can go online look at the shoes go to the store have those shoes be brought down automatically as soon as I walked in and then choose whether I buy it now take it home buy it online have it delivered to my house before I get home or it's $5 cheaper five stores down right so that experience will be chief digital officer but all of that requires data one can't deliver on all that unless they have a a deep understanding of their products a deep understanding of how the transactions the deep understanding how clients buy all of that experience data based whether it's mobile or human created or business data all combined together in fact that's actually a great jump into the sort of the IOT world the machine or the physical world where I now need to appreciate data that's happening the store in the kiosk and all of that experience data needs to be brought back and combined with the financial data to really appreciate with the transition of that digital experience money so those those roles do really span you know your three areas I can see just thinking here and hearing you speak the chief digital officer might go to the chief data officer and say hey I need this data so I can create a customer experience that gives us competitive advantage and I need that data to be accessible of high quality I maybe need you pulling some other data points exact I need real-time I need a blended I need it integrated with my ERP make it so exactly exactly that can't be too hard and then then that involves the CIO to actually provide the infrastructure and whatever SAS or internal execution but find a means to solve the problem and it's not gonna always be built it's likely gonna be consumed it's likely gonna be buy it's likely gonna be partner and so that's part of that historically it was the application kind of tail wagging the dog now it's the data that was really sort of the driver of the bus which is why you really need what we referred to as a data strategy for digital transformation creating a set of services or capabilities that are focused much more on data than IT like we're used to saying IT services make sure you have computer and storage and networking available to you but now it's saying you know what you have business data let's make sure you have services like store and manage and govern you have human sets of data that's blend and correlate and match and then you have machine data well that's much more about grid and point and and IOT related correlations and need to bring all that together as a series of data servers to which IT provides to the chief digital officer okay you talked about the edge before how do you see I mean we're seeing the pendulum now swing back from centralized you know cloud sort of decentralized this notion of edge to cloud is probably not gonna happen it's gonna be some stuff in between but how do you see let's follow the data how do you see in Itachi and Hitachi event ARRA has obviously a perspective on this you guys are an industrial you know giant how what's Itachi ventajas perspective on how the edge will evolve generally but specifically how the data model and the data flow will change so we see an Enterprise Information model has having sort of four legs to this table right and that one should keep data where it is because sometimes it's physically impossible to move data from where it was created to where it needs to be for analytics a train is example and we produce you know a high speed train that could be four or five seven terabytes per day well that's almost physically impossible to move to a server to be able to deal with right and when you look at larger machines like nuclear power plants and well treatment centers all of a sudden it's almost impossible so this four legs are you know you still need an enterprise data warehouse you still need a means to collect your business data and produce your thousands of Mis reports they actually run the business that is a ten million dollar machine - what you've created you then need a you need a content store an object store because you have all this human unstructured data - which in fairness a good portion of what might be dark a good portion of it like your twenty seven versions of your PowerPoint simply won't have any production nuggets of gold right but you still have lots of voice and video records and unstructured files that that could contain nuggets then you have your your Big Data Lake where you want to put your information that you want to do perform an analytics on right.you it's it's you don't want to worry about the data model you don't want to worry about how you're structuring the information until you actually do analytics on it and then finally the edge keeping data where it is have a federated distributed model and only when I want to do and perform specific analytics do I go collect that information bring it to the core perform the analytics produce visualization result we kind of refer to this as a as a data refinement mechanism where I'm searching for the appropriate information using those mathematical statistical algorithms in order to create you know visualizations that we can blend right back into the original sources so a lot of data will be created at the edge and and it'll stay at the edge and in fact a lot of data probably won't be even be persisted at the edge it'll be may be acted on thrown away and you'll save what you need to save is that exactly and you and you could say that there's going to be data that's at the edge that persist or not you'll might have data which might be referred to as the fog where you will collect it at the CEO or at the PIO right and you one or the pop and you want to be able to perform analytics with a little bit more compute you might bring some of that data centrally because you want to combine and blend with other information and then you might actually put it into the cloud because you want to combine other organizational related data and do very complex highly mathematical problem sets so we almost see it from sort of edge to outcome where there's edge processing fog processing core processing and then cloud processing okay so let's unpack that a little bit in the time we have remaining so you got the at least the three maybe even a four maybe it's a three in a three a tier model edge that that second tier gateway right aggregation point where you're doing some analytics and then the third tier and I guess maybe the fourth tier let's call it your own cloud private cloud or maybe the public cloud where you're doing the heavy modeling right and the training of the models and then maybe your ship in the model back down that's forever because it's now modifying the machine potentially or the machines understanding of data and then you're collecting new data based on that new algorithm to which you're now pushing out all right we don't have time but that just whole totally changes the whole security paradigm as well absolutely no had well Paul thanks very much for for coming on the cube and having this cube conversation really excellent work that you're doing congratulations and keep it up thank you very much you're welcome all right thanks for watching everybody this is Dave Volante and this is cube conversations we'll see you next time