 So you don't necessarily have to come in here, but if you don't really give a crap about what we have to say Just keep it down. So those that do care can listen great Thank you. All right. We got a great Customer perspective panel And in the case of Merv independent analyst panel Matt, how you doing? Thank you Okay On the far left is Linda Apsley I love there. I love this title vice president of revenue and data engineering at time So we're gonna talk about that a little bit Linda Linda's got a you know really interesting background from the Seattle area has touched a couple of the bases up there with some of the Big companies like Amazon and Microsoft So thank you very much for making the time to come on the panel Ben Garrett is the director of platform architecture and operations at auto trader or Okay, so auto traders sort of the umbrella. So we'll talk about that And of course Merv Adrian vice president of Gartner very well known analyst pundit thinker George Gilbert is gonna join me and sort of co-moderating this panel. So then let me start with you I asked you about the title Where does that come from and we've been geeking out here? You're really you know the one of the questions that we haven't addressed is the business value piece That's kind of your job revenue in the title. Talk about the title your role and we'll get into it Here we go time started this initiative recognizing that data is our future and Interestingly enough what I heard initially when I was given this role was you need to figure out how to make time a data-driven company And what I learned really fast was the time is already a data-driven company circa 1996 and So we needed to modernize and along with this data piece my team owns the consumer marketing Tools right what is it the consumer marketing uses to drive additional revenue and also the advertising tools? So when I met with my new leaders when I came into the stroll and I put it out to the team What should we call them and call the team and I had two of my leaders say well We we drive revenue for the company because without the advertising platform and without the subscription platform We wouldn't be bringing the money in so we should claim it Let's let's just say that that's what we do and I thought okay So we took the revenue piece that speaks to the consumer marketing and the advertising platforms And then the data which really speaks to our future in predictive intelligence So the data vector and the revenue vector have come together and essentially that's how you and your team are measured That's right. That's cool. Hi Ben. I wonder if you could talk about a operations perspective and I'm going to have a little Q&A with you to those in a scenario hypothetical scenario But talk about your role and I'm specifically I saw a presentation that you gave an informatic a world And I'm specifically interested in what's changed because you had sort of this is the way it used to be This is the way it is now So I wanted to talk about your role and your role as a change agent Cox Automotive, which is the parent company for Alder Trader Kelly blue book Manhole auctions and a lot of different companies in automotive space for about two years now And I was brought on to bring in big data technologies to the organization So it's been a big change and a big transformation for the org on the whole, right? So we were very much a an MPP database and a teaser shop across the board and that's how we sort of did all of our data processing and data provisioning and You know, it's been sort of a challenge for us and almost a necessity to move to this new big data technology because You know Cox Automotive was formed from about 27 different business units in the automotive space that touches entirely the whole life cycle of the vehicle all the way through and Each of these companies generates and shares a lot of data And in fact in a lot of cases we have data that travels back and forth between orgs and gets value added throughout the chain Sort of this whirlwind of of data flow and it becomes a very difficult thing for us to manage So what we've done is built this central enterprise data hub partnering with cloud era to provide one place for us to store all the data that we that we generate Both internally and externally right so that we can all share it and provide entitlements on top of that So that all the different business units and analyst communities can get access to and leverage that data So that's been a really fun challenge because it changes the mindset of a lot of folks I mean you you go from a very traditional sequel world to this new world where you know You're doing development as opposed to just writing sequel and and the tools are sort of evolving as we go along So it's been a very cool challenge to sort of sit down and do this and I'm enjoying a lot All right, Murph. So Been a lot of discussion about the survey that you guys just did a little bit of controversy around it It's kind of survey week. We did our little survey a little humble survey Gartner came up with a survey Databricks came up with a service that sparks gonna eat the world There was another survey. I saw that was you know a couple thousand that was kind of interesting I love survey data, right to everybody what everybody does is they they glom on to whatever You know supports their scenario and say oh here's the data But what I like to do and I'm sure you do too is to try to find the commonalities So I wonder if you could talk a little bit about what that data says what the Gartner survey says and then we want to try To relate it to what's actually happening within the practitioner community There was an interesting metaphor used a little while ago for what we do by someone from Red Hat, but but I won't go there We we collectively you us spark other people We survey population segments And how those population segments are chosen and how they describe themselves is as important as the data We get from them so in Gartner's case They're two very different specific surveys one that's about big data and one that's about Hadoop specifically The good news is we get relatively similar data back from those two separate surveys about Adoption rates which you asked about before But Sean pointed out before that the numbers that Gartner has published that said 44 percent of people that we surveyed These are I'll describe them enterprise senior executives C-level executives Not practitioner level people who tend to skew much higher by the way on these tools Sean and I kind of agree that we're at a moment where the rise is just about coming that we're getting into the early mainstream And I think nothing exemplifies that more than what these two folks just said Both of them talked about outcomes Not about bits and bytes not about the technologies or the version numbers or whether there's a new open source product That was announced yesterday that's going to replace the two that aren't ready yet that we're already using Yeah, they talked about what are we going to do with this and how are we going to measure the value of it? When an emerging technology market begins to define itself and market itself to its prospects and customers in terms of the value It's going to deliver Now we're talking This is when things start to happen and that's how you have to reach a mainstream market The audience at Strata is it's it's not brimming with geekitude the way it did a couple of years ago Right. It's about business people who are asking about value. Okay, so let's talk about some of those those outcomes So you both change agents in different roles within the organization. So everybody talks about trying to become a data driven company So what does that mean to you? Are you really a data driven company? How do you know when you become a data driven company? What do you do to create a data driven company? What's really different Linda? Can you help us like 18 questions in there? But it's it's a big topic and most companies that we talked to you know, aren't there You know, not even close and you may say that about yourself. I don't know But at least your your job is to get there. So I wonder if you could talk about that journey a little bit Yes, I'm happy to I I feel it from two perspectives I view it from analytics, which is how are we doing based upon the past and that's all about collecting data It's measuring for us how many subscriptions do we have how well of our advertisements performing How many people are viewing the ads, right? It's a it's a backwards view very very important I think for any company to understand what's happening currently and using data to determine Where we're successful and not that's where our company has done extremely well The please we need to add in now is this predictive capability. So as we tag this website What does it tell us about our customers so much of what's happening in the market today is about the individual? And I think especially in media, right? We need to be able to target your interests What is it you want to see if you're a Royals watcher and you want to know when the baby's born? How do we get that information to you in a way? That's that's fun that engages you in in our content and that piece really requires these predictive engines And so for my team, we've been now to take it back to the tack, you know, we've been modernizing and moving to the cloud a lot of our Backwards-looking capabilities, which are that the system analytics and at the same time We were building on the pivotal platform our predictive capability where we're bringing gathered data from all over the company Where it used to sit in silos with individual businesses using it to drive specific outcomes to look both to the past and to the future And I think that's really that the key point of where a lot of businesses are in the enterprise is Many do understand the past to varying degrees But if we don't get on this wave of understanding the future and how to engage our audience as individuals in their interests I think we'll get lost so It reminds me I heard Ray poquette. Is that his name? Analyst a gardener give a talk about hybrid IT and it was sort of these two worlds And I think the premises they've got to come together and I know I used to work at a big research company So everybody's got different scenarios, but I wanted to sort of mention that as a mental model for What we live in today this world where you've got the dev ops guys rushing hard and you've got the 19-year-old legacy apps But you deal with that every day. What's that platform look like? Is it a hybrid? IT world. Are you trying to bring those two worlds together? How do you do that? We're having those conversations now actually How do we how do we sort of move faster on the offside because we're growing from you know in leaps and bounds, you know You mentioned, you know, you asked a question about how data affects us and I'd say data is our business Right like at the core of it what we do and I'll use auto trader and Kelly blue book as prime examples for this I mean data is exactly what we do. I mean it takes the form of listings It takes the form of vehicle valuations, right? But at its core It's taking a lot of data and synthesizing it and providing it back out to the individual consumers, right? So for me, I think that's I mean that's where we need to go and and to get there requires a different kind of thinking around operations So cloud becomes a major part of our infrastructure and it's the way we're having to move in order to grow quickly I think I mean that's that's just the way we have to operate dev ops becomes a thing that is like ingrained in our Culture as a result of that. It's the only way you can move fast The only way you can develop things at rapid pace So more of we live in this hybrid world hybrid cloud hybrid it somebody emailed me for and said ask Merv about Hybrid transaction analytical processing, right? Okay? So but that's a very important. Well, yeah, that's a very please weigh in H-tap our acronym. It's about the notion that long-running activities in a business You can call them transactions if you want but the old notion of what a transaction this has changed a bit But before we get done with it there are analytics in stream We don't separate the two although many of us conceptually do in our organizational structures of the tools We choose but they come together when we really start to think about not the past because It's good to understand it. We can't change it. We can change the future. So predictive turns into proactive and If I can do the analytics within the context of whatever it is I'm trying to do that presumably delivers value. I do it differently. I change literally midstream I change the discount rate. I'm offering. I offer a different subscription. I Direct this person to a different car than the one they were thinking about just based on what I've learned while the transactions going on That's affecting transformation. That's what we're talking about here. That's what this technology All the technology we're talking about here uniquely differs from the former technologies in because the the synergies that come when you put those different kinds of data together While activity is in motion Gives you the power to change the outcome maybe serving up Kansas City Royals information as opposed to Camelot or something like that I think she meant the British Royal Opposed to come all right, I got it. I got it Okay Lynn and Ben you know one of the things that's that's become clear Is that as businesses? Digitized they're essentially going through a different channel and then it's almost like they have to reverse engineer their entire business The business changes At that at that level. Can you tell us for instance take for example the New York Times? It's like their newsroom has to change, you know because they're not on a daily cycle or whatever So the the whole notion of well, what are we going to decide for everyone? It's on the front page Changes, can you talk about how your business changed once you realize the delivery channel was new? So, I mean not for the time being thing but like for us One of the things that's been a big challenge and a big change for us is Moving to what I like to call sort of an analyst driven technology investment culture The power of the big data platform allows us to get data in front of our analyst community much faster It gives them the opportunity to go and do experiments and test things and many of those things Won't work right some do and those things that do are able to be thrown back over the wall to IT in our previous life We would build everything up front So the business would come to us and say hey We need we need these reports we need this analytics and we need to do it exactly this way And so we would spend a lot of time together in requirements We spend a lot of time building something at the end of the day We would test it and then we'd hand it off to the business and probably would be half of what they wanted in the first place Now what we get to be in a world of is we provide you with data We just plumb that into a big system We give you the tools to go off and do the job yourself, which is a big challenge It's a big change from an analyst community perspective But they're starting to get that and they see the power of being able to operate Atomously and do their own work right and then they turn back around to us and say this is a product We want to go build this it works and by the way I've built it in this tool and I can show you how to go operationalize it We turn that back around into something for them and much tighter time frame because there's much less You know requirements gathering up front it's much easier for us to figure out exactly what to build And then we can turn around and give the community back something very quickly So that's been a huge change in the way that we think about data and how we use it So we have 25 plus brands here in the United States And I think we look at each of them a little bit differently people here may not realize that time incorporated Publishes people magazine and sports illustrated and many others rather than you know, not just time And so we've needed to adapt a little bit her brand Based upon the needs so if you look at time ink for example time magazine for example You know we want to catch running headlines So what we've done with a lot of our teams is we put the engineers right in with the riders and the content creators And we've created tools that enable our content creators to quickly make changes on the website And if they get into trouble, they've got an engineer right there And then at the same time the two of them together working on these agile scrum lists, right? What's the next most important thing we need and how do we get it to market quickly? And then looking at some bigger pictures one thing I think we did that was really cool this year is We are a big presence on the red carpet, especially at the Oscars, right? And so one of the challenges we have is how do we quickly get the pictures out there people want to know You know what a J-Lo wear on the red carpet, right? And we get you know, we've got photographers there are thousands of pictures being shot a minute So we developed a tool that does images and could pull out of the pictures as they're feeding into us Everything J-Lo right by looking at the face and the dress and then we can quickly grab the ones that we think are best And the editorial team can can get them out there, right? I Just said to George I think there's an interesting technical point to make here You're looking at one large continuous stream of information and you're going to deliver it to several different constituencies based on their different set of preferences which you expect to be able to monetize in different ways and That's really an interesting analogy for the whole pivot that this conference is about from data at rest to data in motion Because because those decisions have to be made while it's happening I need Entertainment Weekly to get this shot and talk about who she was wearing I also need however to feed it over to time Which is doing a story about that particular couture house and how their finances are running right now and use the picture to illustrate that story That's a great metaphor for what we're doing with this technology right now Right it really is about learning to build the platform capabilities that can be leveraged quickly via API's right So that we have one digital asset management system that has all those digital assets tagged and other groups can get to them quickly through their UI tools and many curators well I'd say I think stream that you bring up a really good topic and stream processing because that's been a huge Differentiator for us recently right so over the past few years Altar trader and Kelly blue book both have provided back to our what we call our OEMs or original equipment manufacturers the Fords and the Chevy's of the world feedback on the ads that they run during the biggest sporting event of the year at Super Bowl and What we've done in the past is we've What we've done in the past is that we've we've taken that data overnight We processed it and we give feedback to the to these OEMs about how they're performing in their market after they run commercials Right and we're able to sort of see that You know we can see in this hour. You had some lift You know it's interesting and it definitely gives them external validation that their spend was worthwhile But I think now as of this past year what we were able to do is actually that sparked streaming on top of that data Flow as it's coming through and we were and we actually had an operations team in having a Super Bowl party there In the you know in the ops room there while this was going on and we had screens that I know right so Well, I didn't get to be at home with my wife while watching but anyway So so so we're watching the streams go and right so it's it's interesting to see right a commercial runs And then this huge hockey stick and it's compelling I mean I missed several key plays in the game because I was busy watching those those meters as they were going So that's not possible without this kind of technology So there's an example Extending what we just said where that single stream is not only being viewed multiple times by one organization But that same stream of data is being looked at by several other Organizations are they sharing that data who's providing that data who's brokering it and curating it and delivering it to multiple organizations not just yours There's where we get to monetize Okay, and that's where what's the value of all this starts to get answered and let's keep it there because in the call You said we got to talk about security, but I don't know sure we have time but That and two really interesting examples and as George whispered in my ear Let me you do basically redefining the concept of a magazine and building a you know proprietary System to make your writers more productive. I mean it's a huge competitive advantage. So hypothetical So you've got an executive who comes to you and says we need to do something that's completely changed the game Give us competitive advantage drive value Linda you speak wallet then you speak geek nerve. You're the bilingual translator, okay? So, okay, so where do I start within an organization? Maybe think about some of the you know examples without divulging, you know the big secrets But some of the folks in the audience who might want to get started on something like this Where do you start? Who do you bring in to that discussion? What capabilities do I need? How do you decide what you can even take on? Well, so let's start with the where do you start I spent my day-to-day at an off-site with executives from consumer marketing And I think this is probably the first year. They've had a technologist attend their strategy Session but this year it was important because the understanding is a lot of the strategies that need to be built are going to require Tech and so you want to understand right up front. Are we biting off something? That's so big. We won't get value this year Where can it fit into that stream? And so I think the starting is engaging in the conversation and really recognizing that there's a deeper partnership I think several years back there was an executive from Microsoft I don't remember the name that wrote a book about you know bringing IT into the business I think that's even more important now The other piece is hiring not just IT professionals. You talked about this I and I think you would ask the question I do have some folks who have very strong IT background and these are these are the core and backbone of my analytics practice But they want to become more technologists people who invent and so giving them that opportunity while also bringing in people Who have that backbone and that experience which is you know partly why Colin brought me in from Microsoft and Amazon was to bring that Capability into the company. So, you know, I don't believe you do anything great without standing on the shoulders of the people Who got you to where you are so it's having that respect for the people that are there that understand You know the the holes and the potholes that they've hit before and bringing in some new folks And then getting the two to work together and watching for the magic and then from a platform perspective Yeah, yeah, okay. I've got I've got your translation for you. What she just said. Where do you start everywhere? Seriously, seriously, everybody's involved in this get the ideas wherever they come from. That's that's my answer So it's from a platform My perspective there were when we first started down this path there were two options we could take we had two forks in the road One is leverage the analyst community work directly with them find out from them What it is they can't do today and help them do that, right? And that's that's key to adoption and success and the other was a strictly IT play Let me go after cost reduction and savings Let me offload some of the expensive overnight processing we do and move it into a platform where it's more suited And it's and it's certainly more cost-effective and as the late great yogi bearer said when you see a fork in the road take it So we went both paths at the same time, right? So so so in that respect, I think we're solving for two problems simultaneously Questions from the audience Got these Three practitioners Experts. Oh great. Thank you Give us some exercise in yourself Hello everyone, thank you for the panel Fatima Balani from UBS This is something that Dave touched on The topic of security and I'm wondering if you can talk about your your Challenges and pain points with respect to you know, anything from role-based access to metadata management as it relates to deployment That's in production. Yeah, so I'll say this when we first started down this path our initial Our initial thoughts around building this enterprise hub was that we would build a platform that was democratized and leveraged by everyone we're going to put data in this that everyone can leverage and you know, I mean No, strictly no PII included Intentionally right and that's still our motto, but we realized very quickly that not all data is created equal and Not all data can be globally accessible, right? There's data that's sometimes sensitive like financial data sales data. There's also data that contractually isn't available for everyone to access So we had to go tackle this and we spent a lot of time on security a whole lot of time on security You know in the in the Hadoop world when you sort of look at this there's a there's a Kerberos thing that comes up a lot when we start talking about this and While it's a technology spent around since the 80s I wasn't able to find anyone the organization that had real skill in this right so we had to invent this Wasn't going to hire anybody either because it's about as impossible as finding a big data architect so So we had to challenge we had a challenge to go fix this We worked with our partners at cloud era and it read hat to go solve for it But it took an enormous amount of time and it's still something that we're working through if you ask me about the things That keep me up at night security resource management or two at the top of my list and how we actually provide those Entitlements is really important some of the tools help us with it But at the end of the day, it's got to be at the base level right we've got to have Restrictions and we've got to have compliance And I'm not lying to you when I say that it has been a real challenge to do that We too have spent a lot of time in security and I would echo a lot of the same things He said it you know I always tell my team the most secure system is one that nobody can access That doesn't help us right but you know looking at every vector goes back to your everything and saying What is it that we need to do to protect in this vector and one of the things I've really pushed my team on and had a Difficult time finding a good partner to help us with was I really only want somebody to be able to log into my system for that session Right, I don't want their credentials to last longer than the session that they're sitting at because I think at the end That's my one of my greatest protections if I got my firewall down really tight And I've got you know my PII and everything so people can't penetrate in then I need to protect it at the admin level And we're been using working with Z data and we're putting that in place John Furrier and I asked Pat Gelsinger in the Cube a couple years ago is security a do-over and he just said yes Would you agree with that? security is Too often a disabler We talk about a gardener. We talk about bimodal IT a lot where there's a place where you get agile and you throw the Rules out and you you invent and you create and you and you imagine Security can enable that if it's applied correctly if there is some data that I need to make sure is not exposed I redacted I mask it I give people a sandbox where they can play with all the rest of it Now I may squeeze a few pieces out in that process that might turn out to have been valuable But I'm probably going to be busy for a while if I can provide the sandbox with some guardrails I can probably still get a lot of work done inside it security in that environment is actually an enabler because it gives Me a place where it is safe to experiment and to your point safe to fail You know if it needs me because failure won't mean exposure failure would just mean the project didn't work That's a very different value proposition Oh, please So I think part of what I heard from you that that I really that I really Believe in and we are doing is try to use your technology as much as you can as a protector Right and masking data is a big one because then you weren't inhibiting your data lake and in access in in the deeper ways Other questions we got a wrap shortly, but I want to make sure that you guys have a chance to chime in all right good We've kept you for a while here. Oh last question Gotta be a good one Hi, I'm Gokula missile from Oracle. I hear a lot of speakers talking about Collect all forms of data and everything your company creates and just keep collecting and you know put in this data lake Who knows maybe you know you'll find some value out of it and someday right? Who is going to fund this? Yeah Storage guys love that What about that you certainly do you can't be a complete pack rat with this data right? I mean it costs something and that's that's certainly a challenge I mean, I think the only way that happens is that you know You have engaged business partners that understand the value of the data and drive that Otherwise you can't just keep data for the sake of keeping it right so I think for us Joe rip really understands the value of data and we're able to make it real We were last year able to make a really good business case on the backward looking But on the forward looking he took a leap of faith with us And you know we're building tools now to demonstrate and show what can be done And I think there is a piece of that predictive that you don't know what you don't know until you get into the data And but I don't think you're going to be funded for a lot of years if you can't show that value Yeah, I go close question It's kind of the yin and the yang of value and liability You know so I would say keep it as long as you can but no longer, you know But then there's the value equation. All right, we're out of time Linda and Ben Thank you so much as practitioners for sharing your insights You know how busy you guys are and Merv at the say on behalf of the whole cube and silicon angle wikibon community We just love the collaboration with you. We appreciate your time and thank you very much All right John Furrier is here and I want to turn the mic over to John. How about a round of applause for that great customer panel great content? Merv customers great job. Okay, so we have raffle gifts. So put this over here so we have three giveaways we have Actually, I think this is the best gift because I love GoPro GoPro hero with a selfie stick kind of a GoPro stick I won't call it a selfie stick because It's one of the anti-selfie stick, but I think that's ridiculous