>>Hey everyone, and welcome back to Las Vegas. Viva Las Vegas, baby. This is the Cube live at AWS Reinvent 2022 with tens of thousands of people. Lisa Martin here with Dave Valante. Dave, we've had some great conversations. This is day one of four days of wall to wall coverage on the cube. We've been talking data. Every company is a data company. Data protection, data resiliency, absolutely table stakes for organizations to, >>And I think ecosystem is the other big theme. And that really came to life last year. You know, we came out of the pandemic and it was like, wow, we are entering a new era. People no longer was the ecosystem worried about it, AWS competing with them. They were more worried about innovating and building on top of AWS and building their own value. And that's really, I think, the theme of the 2020s within the ecosystem. >>And we're gonna be talking about building on top of aws. Two guests join us, two alumni join us. Stephen Manley is here, the CTO of Druva. Welcome back. Jason crat as well is here. CIO and CTO of Summit Carbon Solutions. Guys, great to have you back on the program. >>Thank you. >>Let's start with you giving the audience an understanding of the company. What do you guys do? What do you deliver value for customers? All that good >>Stuff. Yeah, no, for sure. So Summit Carbon is the world's largest carbon capture and sequestration company capturing close to 15 million tons of carbon every year. So it doesn't go into the atmosphere. >>Wow, fantastic. Steven, the, the risk landscape today is crazy, right? There's, there's been massive changes. We've talked about this many times. What are some of the things, you know, ransomware is a, is, I know as you say, this is a, it's not a, if it's gonna happen, it's when it's how frequent, it's what's gonna be the damage. What are some of the challenges and concerns that you're hearing from customers out there today? >>Yeah, you know, it really comes down to three things. And, and everybody is, is terrified of ransomware and justifiably so. So, so the first thing that comes up is, how do I keep up? Because I have so much data in so many places, and the threats are evolving so quickly. I don't have enough money, I don't have enough people, I don't have enough skilled resources to be able to keep up. The second thing, and this ties in with what Dave said, is, is ecosystem. You know, it used to be that your, your backup was siloed, right? They'd sit in the basement and, and you wouldn't see, see them. But now they're saying, I've gotta work with my security team. So rather than hoping the security team stays away from me, how do I integrate with them? How do I tie together? And then the third one, which is on everybody's mind, is when that attack happens, and like you said, it's win and, and the bell rings and they come to me and they say, all right, it's time for you to recover. It's time for, for all this investment we've put in. Am I gonna be ready? Am I going to be able to execute? Because a ransom or recovery is so different than any other recovery they've ever done. So it's those three things that really are top of mind for >>How, so what is the, what are the key differences, if you could summarize? I mean, I >>Know it's so, so the first one is you can't trust the environment you're restoring into. Even with a disaster, it would finish and you'd say, okay, I'm gonna get my data center set up again and I'm gonna get things working. You know, when I try to recover, I don't know if everything's clean yet. I'm trying to recover while I'm still going through incident response. So that's one big difference. A second big difference is I'm not sure if the thing I'm recovering is good, I've gotta scan it. I've gotta make sure what's inside it is, is, is alright. And then the third thing is what we're seeing is the targets are usually not necessarily the crown jewels because those tend to be more protected. And so they're running into this, I need to recover a massive amount of what we might call tier two, tier three apps that I wasn't ready for because I've always been prepared for that tier one disaster. And so, so those three things they go, it's stuff I'm not prepared or covering. It's a flow. I'm not used to having to check things and I'm not sure where I'm gonna recover too when the, when the time comes. >>Yeah, just go ahead. Yeah, that's right. I mean, I think for me, the biggest concern is the blind spots of where did I actually back it up or not. You know, what did I get it? Cuz you, we always protect our e r p, we always protect these sort of classes of tiers of systems, but then it's like, oh, that user's email box didn't get it. Oh, that, you know, that one drive didn't get it. You know, or, or, or whatever it is. You know, the infrastructure behind it all. I forgot to back that up. That to me the blind spots are the scariest part of a ransomware attack. >>And, and if you think about it, some of the most high profile attacks, you know, on the, on the colonial pipeline, they didn't go after the core assets. They went after billing. That's right. But billing brought everything down so they're smart enough to say, right, I'm not gonna take the, the castle head on. Is there is they're that. Exactly. >>And so how do you, I get, I mean you can air gap and do things like that in terms of protecting the, the, the data, the corrupt data. How do you protect the corrupt environment? Like that's, that's a really challenging issue. Is >>It? I don't know. I mean, I'll, I'll you can go second here. I think that what's interesting to me about is that's what cloud's for. You can build as many environments as you want. You only pay for what you use, right? And so you have an opportunity to just reconstruct it. That's why things, everything is code matters. That's why having a cloud partner like Druva matters. So you can just go restore wherever you need to in a totally clean environment. >>So the answer is you gotta do it in the cloud. Yeah. What if it's on prem? >>So if it's on prem, what we see people do is, and, and, and this is where testing and, and where cloud can still be an asset, is you can look and say a lot of those assets I'm running in the data center, I could still recover in the cloud. And so you can go through DR testing and you can start to define what's in your on-prem so that you could make it, you know, so you can make it cloud recoverable. Now, a lot of the people that do that then say, well actually why am I even running this on prem anymore in the first place? I should just move this to the cloud now. But, but, but there are people in that interim step. But, but, but it's really important because you, you're gonna need a clean environment to play in. And it's so hard to have a clean environment set up in a data center cuz it basically means I'm not touching this, I'm just paying for something to sit idle. Whereas cloud, I can spin that up, right? Get a, a cloud foundation suite and, and just again, infrastructures code, spin things up, test it, spin it down. It doesn't cost me money on a daily basis. >>Jason, talk a little bit about how you are using Druva. Why Druva and give us a kind of a landscape of your IT environment with Druva. >>Yeah. You know, so when we first started, you know, we did have a competitor solution and, and, and it was only backing up, you know, we were a startup. It was only backing up our email. And so as you pointed out, the ecosystem really matters because we grew out of email pretty quick as a startup. And we had to have real use cases to protect and the legacy product just wouldn't support us. And so our whole direction, or my direction to my team is back it up wherever it is, you know, go get it. And so we needed somebody in the field, literally in the middle of Nebraska or Iowa to have their laptop backed up. We needed our infrastructure, our data center backed up and we needed our, our SaaS solutions backed up. We needed it all. And so we needed a partner like Druva to help us go get it wherever it's at. >>Talk about the value in, with Druva being cloud native. >>Yeah. To us it's a big deal, right? There's all sorts of products you could go by to go just do endpoint laptop protection or just do SAS backups. For us, the value is in learning one tool and mastering it and then taking it to wherever the data is. To me, we see a lot of value for that because we can have one team focus on one product, get good at it, and drive the value. >>That consolidation theme is big right now, you know, the economic headwinds and so forth. What was the catalyst for you? Was it, is that something you started, you know, years ago? Just it's good practice to do that? What's, >>Well, no, I mean luckily I'm in a very good position as a startup to do define it, you know, but I've been in those legacy organizations where we've got a lot of tech debt and then how do you consolidate your portfolio so that you can gain more value, right? Cause you only get one budget a year, right? And so I'm lucky in, in the learnings I've had in other enterprises to deal with this head on right now as we grow, don't add tech debt, put it in right. Today. >>Talk to us a little bit about the SaaS applications that you're backing up. You know, we, we talk a lot with customers, the shared, the shared responsibility model that a lot of customers aren't aware of. Where are you using that competing solution to protect SaaS applications before driven and talk about Yeah. The, the value in that going, the data protection is our responsibility and not the SA vendor. >>No, absolutely. I mean, and it is funny to go to, you know, it's like Office 365 applications and go to our, our CFO and a leadership and be like, no, we really gotta back it up to a third party. And they're like, but why? >>It's >>In the cloud, right? And so there's a lot of instruction I have to provide to my peers and, and, and my users to help them understand why these things matter. And, and, and it works out really well because we can show value really quick when anything happens. And now we get, I mean, even in SharePoint, people will come to us to restore things when they're fully empowered to do it. But my team's faster. And so we can just get it done for them. And so it's an extra from me, it's an extra SLA or never service level I can provide to my internal customers that, that gives them more faith and trust in my organization. >>How, how are the SEC op teams and the data protection teams, the backup teams, how are they coming together? Is is, is data protection backup just morphing into security? Is it more of an adjacency? What's that dynamic like? >>So I'd say right now, and, and I'll be curious to hear Jason's organization, but certainly what we see broadly is, you know, the, the teams are starting to work together, but I wouldn't say they're merging, right? Because, you know, you think of it in a couple of ways. The first is you've got a production environment and that needs to be secured. And then you've got a protection environment. And that protection environment also has to be secured. So the first conversation for a lot of backup teams is, alright, I need to actually work with the security team to make sure that, that my, my my backup environment, it's air gapped, it's encrypted, it's secured. Then I think the, the then I think you start to see people come together, especially as they go through, say, tabletop exercises for ransomware recovery, where it's, alright, where, where can the backup team add value here? >>Because certainly recovery, that's the basics. But as there log information you can provide, are there detection pieces that you can offer? So, so I think, you know, you start to see a partnership, but, but the reality is, you know, the, the two are still separate, right? Because, you know, my job as a a protection resiliency company is I wanna make sure that when you need your data, it's gonna be there for you. And I certainly want to, to to follow best secure practices and I wanna offer value to the security team, but there's a whole lot of the security ecosystem that I want to plug into. I'm not trying to replace them again. I want to be part of that broader ecosystem. >>So how, how do you guys approach it? Yeah, >>That's interesting. Yeah. So in my organization, we, we are one team and, and not to be too cheesy or you know, whatever, but as Amazon would say, security is job one. And so we treat it as if this is it. And so we never push something into production until we are ready. And ready to us means it's got a security package on it, it's backed up, the users have tested it, we are ready to go. It's not that we're ready just be to provide the service or the thing. It's that we are actually ready to productionize this. And so it's ready for production data and that slows us down in some cases. But that's where DevOps and this idea of just merging everything together into a central, how do we get this done together, has worked out really well for us. So, >>So it's really the DevOps team's responsibility. It's not a separate data protection function. >>Nope. Nope. We have specialists of course, right? Yeah, yeah. Because you need the extra level, the CISSPs and those people Yeah, yeah. To really know what they're doing, but they're just part of the team. Yeah. >>Talk about some of the business outcomes that you're achieving with Druva so far. >>Yeah. The business outcomes for me are, you know, I meet my SLAs that's promising. I can communicate that I feel more secure in the cloud and, and all of my workloads because I can restore it. And, and that to me helps everybody in my organization sleep well, sleep better. We are, we transport a lot of the carbon in a pipeline like Colonial. And so to us, we are, we are potential victims of, of a pipe, a non pipeline group, right? Attacking us, but it's carbon, you know, we're trying to get it outta atmosphere. And so by protecting it, no matter where it is, as long as we've got internet access, we can back it up. That provides tons of value to my team because we have hundreds of people in the field working for us every day who collect data and generate it. >>What would you say to a customer who's maybe on the fence looking at different technologies, why dva? >>You know, I think, you know, do the research in my mind, it'll win if you just do the research, right? I mean, there might be vendors that'll buy you nice dinners or whatever, and those are, those are nice things, but the, the reality is you have to protect your data no matter where it is. If it's in a SaaS application, if it's in a cloud provider, if it's infrastructure, wherever it is, you need it. And if you just go look at the facts, there it is, right? And so I, I'd say be objective. Look at the facts, it'll prove itself. >>Look at the data. There you go. Steven Druva recently announced a data resiliency guarantee with a big whopping financial sum. Talk to us a little bit about that, the value in it for your customers and for prospects, >>Right? So, so basically there's, there's really two parts to this guarantee. The first is, you know, across five different SLAs, and I'll talk about those, you know, if we violate those, the customers can get a payout of up to 10 million, right? So again, putting, putting our money where our mouth is in a pretty large amount. But, but for me, the exciting part, and this is, this is where Jason went, is it's about the SLAs, right? You know, one of Drew's goals is to say, look, we do the job for you, we do the service for you so you can offer that service to your company. And so the SLAs aren't just about ransomware, some of them certainly are, you know, that, that you're going to be able to recover your data in the event of a ransomware attack, that your data won't get exfiltrated as part of a ransomware attack. >>But also things like backup success rates, because as much as recovery matters a lot more than backup, you do need a backup if you're gonna be able to get that recovery done. There's also an SLA to say that, you know, if 10 years down the road you need to recover your data, it's still recoverable, right? So, so that kind of durability piece. And then of course the availability of the service because what's the point of a service if it's not there for you when you need it? And so, so having that breadth of coverage, I think really reflects who Druva is, which is we're doing this job for you, right? We want to make this this service available so you can focus on offering other value inside your business. And >>The insurance underwriters, if they threw holy water on >>That, they, they, they were okay with it. The legal people blessed it, you know, it, you know, the CEO signed off on it, the board of directors. So, you know, it, and it, it's all there in print, it's all there on the web. If you wanna look, you know, make sure, one of the things we wanted to be very clear on is that this isn't just a marketing gimmick that we're, we're putting, that we're putting substance behind it because a lot of these were already in our contracts anyway, because as a SAS vendor, you're signing up for service level agreements anyway. >>Yeah. But most of the service level agreements and SaaS vendors are crap. They're like, you know, hey, you know, if something bad happens, you know, we'll, we'll give you a credit, >>Right? >>For, you know, for when you were down. I mean, it's not, you never get into business impact. I mean, even aws, sorry, I mean, it's true. We're a customer. I read define print, I know what I'm signing up for. But, so that's, >>We read it a lot and we will not, we don't really care about the credits at all. We care about is it their force? Is it a partner? We trust, we fight that every day in our SLAs with our vendors >>In the end, right? I mean this, we are the last line of defense. We are the thing that keeps the business up and running. So if your business, you know, can't get to his data and can't operate, me coming to you and saying, Dave, I've got some credits for you after you, you know, after you declare bankruptcy, it'll be great. Yeah, that's not a win. >>It's no value, >>Not helpful. The goal's gotta be, your business is up and running cuz that's when we're both successful. So, so, so, you know, we view this as we're in it together, right? We wanna make sure your business succeeds. Again, it's not about slight of hand, it's not about, you know, just, just putting fine print in the contract. It's about standing up and delivering. Because if you can't do that, why are we here? Right? The number one thing we hear from our customers is Dr. Just works. And that's the thing I think I'm most proud of is Druva just works. >>So, speaking of Juva, just working, if there's a billboard in Santa Clara near the new offices about Druva, what's, what's the bumper sticker? What's the tagline? >>I, I, I think, I think that's it. I think Druva just works. Keeps your data safe. Simple as that. Safe and secure. Druva works to keep your data safe and secure. >>Saved me. >>Yeah. >>Truva just works. Guys, thanks so much for joining. David, me on the program. Great to have you back on the cube. Thank you. Talking about how you're working together, what Druva is doing to really putting, its its best foot forward. We appreciate your insights and your time. Thank >>You. Thanks guys. It's great to see you guys. Likewise >>The show for our guests and Dave Ante. I'm Lisa Martin, you're watching the Cube, the leader in enterprise and emerging tech coverage.

(upbeat music) >> Welcome to transforming ideas into insights, presented with theCUBE and made possible by Cloudera. My name is Dave Vellante from theCUBE and I'll be your host for today. In the next hundred minutes, you're going to hear how to turn your best ideas into action using data and we're going to share the real-world examples of 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing efficiencies, better forecast retail demand, transform analytics, improve public sector service and so much more. How we use data is rapidly evolving. That is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to, rather we use terms like, digital transformation and digital business. But you think about it. What is a digital business? How is that different from just a business? Well, a digital business is a data business and it differentiates itself by the way it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such, the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings, but increasingly insights are leading to the development of data products and services that can be monetized. Or as you'll hear in our industry examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. Self-service investing, filing insurance claims on our smart phones and so many examples. IOT systems that communicate and act machine to machine. Real-time pricing actions, these are all examples of products and services that drive revenue, cut costs or create other value and they all rely on data. Now, while many business leaders sometimes express frustration that their investments in data, people and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data transformation and leadership. One thing is certain, the next 10 years of data and digital transformation won't be like the last 10. So let's into it. Please join us in the chat. You can ask questions. You can share your comments. Hit us up on Twitter. Right now, it's my pleasure to welcome Mick Holliston and he's the president of Cloudera. Mick, great to see you. >> Great to see you as well, Dave. >> Hey, so I call it the new abnormal, right? The world is kind of out of whack. Offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations, line cooks at restaurants. Everything that we consumers have missed, but here's the one thing, it seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling, their pricing algorithms, commodity prices, we don't know. Is inflation transitory? Is it a long-term threat, trying to forecast GDP? It seems like we have to reset all of our assumptions and Mick, I feel a quality data is going to be a key here. How do you see the current state of the industry in the role data plays to get us into a more predictable and stable future? >> Well, I can sure tell you this, Dave, out of whack is definitely right. I don't know if you know or not, but I happened to be coming to you live today from Atlanta and as a native of Atlanta, I can tell you there's a lot to be known about the airport here. It's often said that whether you're going to heaven or hell, you got to change planes in Atlanta and after 40 minutes waiting on an algorithm to be right for baggage claim last night, I finally managed to get some bag and to be able to show up, dressed appropriately for you today. Here's one thing that I know for sure though, Dave. Clean, consistent and safe data will be essential to getting the world and businesses as we know it back on track again. Without well-managed data, we're certain to get very inconsistent outcomes. Quality data will be the normalizing factor because one thing really hasn't changed about computing since the dawn of time, back when I was taking computer classes at Georgia Tech here in Atlanta and that's what we used to refer to as garbage in, garbage out. In other words, you'll never get quality data-driven insights from a poor dataset. This is especially important today for machine learning and AI. You can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid. As AI is increasingly used in every business app, you must build a solid data foundation. >> Mick, let's talk about hybrid. Every CXO that I talked to, they're trying to get hybrid right. Whether it's hybrid work, hybrid events, which is our business, hybrid cloud. How are you thinking about the hybrid everything, what's your point of view? >> With all those prescriptions of hybrid and everything, there was one item you might not have quite hit on, Dave and that's hybrid data. >> Oh yeah, you're right, Mick, I did miss that. What do you mean by hybrid data? >> Well, Dave, in Cloudera, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now, every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises, in a private cloud, in public cloud or perhaps even in a new open data exchange. Now, this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud. But either way, security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch or read a recent news story. Data breaches are at an all time high and the ethics of AI applications are being called into question everyday. And understanding lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know, Dave, that's the business Cloudera is in. On a serious note, from Cloudera's perspective, adopting a hybrid data strategy is central to every business' digital transformation. It will enable rapid adoption of new technologies and optimize economic models, while ensuring the security and privacy of every bit of data. >> Okay, Mick, I'm glad you brought in that notion of hybrid data because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You got the economics, the physics, the local laws come into play, so what about the rest of hybrid? >> Yeah, that's a great question, Dave and certainly, Cloudera itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind, the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office ethernet may not be happening quite so fast in somebody's rural home in the middle of Nebraska somewhere. So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, involve us kind of slowly coming back to work, beginning this fall. And we're looking forward to being able to shake hands and see one another again for the first time, in many cases, for more than a year and a half. But yes, hybrid work and hybrid data are playing an increasingly important role for every kind of business. >> Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, here's how I think about it. I mean, some industries have transformed. You think about retail, for example, it's pretty clear. Although, every physical retail brand I know has not only beefed up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence. And reverse, we see Amazon building out physical assets, so there's more hybrid going on. But when you look at healthcare, for example, it's just starting with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control of payment systems. In manufacturing, the pandemic highlighted, America's reliance on China as a manufacturing partner and supply chain. And so my point is, it seems at different industries, they're in different stages of transformation, but two things look really clear. One, you got to put data at the core of the business model, that's compulsory. It seems like embedding AI into the applications, the data, the business process, that's going to become increasingly important. So how do you see that? >> Wow, there's a lot packed into that question there, Dave. But yeah, at Cloudera, I happened to be leading our own digital transformation as a technology company and what I would tell you there that's been an interesting process. The shift from being largely a subscription-based model to a consumption-based model requires a completely different level of instrumentation in our products and data collection that takes place in real-time, both for billing for our customers and to be able to check on the health and wellness, if you will, of their Cloudera implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed the rate and pace of getting vaccines to market or we've been assisting with testing process that's taken place. Because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and healthy and safe outcomes for everyone. And Cloudera has been underneath a great deal of that type of work. And the financial services industry you pointed out, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are helping those kinds of organizations get through those difficult challenges. You also happened to mention public sector and in public sector, we're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. And while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, you can't build great ML apps unless you've got a strong data foundation underneath. It's back to that garbage in, garbage out comment that I made previously. And so, in order to do that, you've got to have a great hybrid data management platform at your disposal to ensure that your data is clean and organized and up to date. Just as importantly from that, that's kind of the freedom side of things. On the security side of things, you've got to ensure that you can see who's touched not just the data itself, Dave, but actually the machine learning models. And organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage in addition to data lineage. In other words, who's had access to the machine learning models? When and where and at what time and what decisions were made perhaps, by the humans, perhaps by the machines that may have led to a particular outcome? So, every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models, just as they can track the lineage of data. So, lots going on there across industries. Lots going on as those various industries think about how AI can be applied to their businesses. >> It's a pretty interesting concept you're bringing into the discussion, the hybrid data, sort of, I think new to a lot of people. And this idea of model lineage is a great point because people want to talk about AI ethics, transparency of AI. When you start putting those models into machines to do real-time inferencing at the edge, it starts to get really complicated. I wonder if we could talk, we're still on that theme of industry transformation. I felt like coming into the pre-pandemic, there was just a lot of complacency. Yeah, digital transformation and a lot of buzz words and then we had this forced march to digital, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? >> There definitely is a lot of a POC limbo or I think some of us internally have referred to as POC purgatory, just getting in that phase, not being able to get from point A to point B in digital transformation. And for every industry, transformation, change in general, is difficult and it takes time and money and thoughtfulness. But like with all things, what we've found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts. To say it another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts, as it relates to the underlying technology here and to bring it home a little bit more practically, I guess I would say. At Cloudera, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, right close to home. In place, they can kind of experiment a little bit more safely and economically and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplished, but kind of starting small and then drawing fast from there on customer's journey to the cloud. >> Well Mick, we've covered a lot of ground. Last question, what do you want people to leave this event, this session with and thinking about sort of the next era of data that we're entering? >> Well, it's a great question, but I think it could be summed up in two words. I want them to think about a hybrid data strategy. So, really hybrid data is a concept that we're bringing forward on this show really, for the first time, arguably. And we really do think that it enables customers to experience what we refer to, Dave, as the power of ANT. That is freedom and security and in a world where we're all still trying to decide whether each day when we walk out, each building we walk into, whether we're free to come in and out with a mask, without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe for ourselves and for others. And the same is true of organization's IT strategies. They want the freedom to choose, to run workloads and applications in the best and most economical place possible, but they also want to do that with certainty that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So, hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole. >> Nick, thanks so much, great conversation. I really appreciate the insights that you're bringing to this event, into the industry, really. Thank you for your time. >> You bet, Dave, pleasure being with you.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, hi everybody John Walls here on theCUBE and we're now welcoming Jeremy Wilmot who is the chief product officer at ACI Worldwide part of the Postgres movement, you might say or certainly benefiting from the great value that Postgres is providing a number of enterprises across the globe. Jeremy good to see you today and first off, congratulations you are the first guest I've talked to maybe in a year and a half in their office. So good for you. >> Thanks (chuckles) John that's very kind of you John and great to see you and thanks for having me here. Yeah, it's great to be in the office, it really is. I'm here in Miami in South Florida and getting some sort of normalcy back is great for all of us and I'm certainly enjoying it. So thank you before (indistinct) has been. >> I'm sure you are, yeah, congratulations on that front. First off, let's talk about ACI Worldwide for the folks in our audience who aren't familiar with the payments, your role in terms of that payment ecosystem. Tell us a little bit about ACI Worldwide. >> Sure, well, primarily we're a software company. That's ACI, we started 1975 in Omaha, Nebraska built the first debit card system and ATM system for first National Bank of Omaha and over the last 45 years, we've globalized ourselves, we have, we are delivering mission-critical real-time payment systems across the world to banks to merchants to billers, we help them meet the payment needs of their consumers and their corporates. So we process, manage digital payments, we power omni-commerce and e-commerce payments, we present and process bill payments, we manage fraud, we manage the risk all within that and as I said on a global basis 13 of the G20 countries with a leading DDA account or current account payment processing software in those countries and have been for many years. >> So, as the CPO then quite obviously in the financial space your plate is quite full these days in terms of providing for your client base. How would you characterize maybe the evolution in terms of product development that you've been through in the financial world here over the past say, three to five years, where were you back then to where you are now and what role has Postgres played in that journey? >> Sure, yeah. So, specific to the Postgres part of the ecosystem, previously five-plus years ago our previous database solution was complex, it was expensive, it was hard to change and maintain and we leveraged multiple pieces of software from multiple vendors as a result of that. So at that time we looked for an alternative that was simpler and better and we went through a very comprehensive due diligence process, we explored both open source and license models of database to support our solution and when we looked at all of the options we determined that 2ndQuadrant Postgres was the one that provided the most comprehensive solution we were looking for. It had the right mix of capabilities and performance at the right total cost of ownership that we were looking for. And in the payments world as you can imagine, you've got to to be 24/7 365. And we also required a lower cost of ownership than we had before. But we also wanted a greater flexibility and time to market that we could pass on to our customers. And then the last thing I'd say that we were looking for was a multi-deployment capability. And what I mean by that is that we would be able to use this new platform, Postgres platform in our own data centers in our own private cloud, but we could also deploy it in the public cloud, whether we would run it or whether our customers would run it. We wanted that ability to mix and match between these different deployment options. >> So you've talked about a lot of key elements here attributes in terms of availability, accessibility reliability, security obviously. Walk us through those in terms of why you think 2ndQuadrant was addressing your needs in those particular areas or any others for that matter but what it was that checked the box specifically about what Postgres was offering you as opposed to what these other possible solutions and services were that you were looking at. >> Yeah, I think, we're very focused on being able to identify what our customers need and when they're offering services to consumers and to their corporates what is it that they require that's going to enable them to win and compete. And payments industry has a lot of cost pressures within it. It has regulation, it has consumer convenience and the whole movement of digitalization that puts a lot of downward pressure on the cost space. And those who are going to win in the payment space need to be able to address that. So, that is relevant for our banks, for our merchants, for the billers. They all come under very similar regulatory pressure and market pressure and as a result, the ability to reduce dramatically in a very significant way, the total cost of ownership upon which the payment software was going to be operating that was one of the key elements that was very important to us as we made that decision. The second one I think was to enable us to be able to do what we are good at and what our customers expect us to do. And that in turn enables them to focus on their core competencies. We're a software company, we own our own IP we manage our own software for the needs of the 24/7 365 payment requirements and therefore the merchant or the biller or the bank can really focus in on the digital experience for their customers, focusing on their core competencies and what they need to do to win. That was a second key factor for us. I think the third one for us was as well speed to market. Speed to market for ourselves and being competitive to the alternative to ACI, but also more importantly a speed to market for our customers. And there are, the payment world is highly regulated requires significant certification in order to launch new services that's often the long pole in the tent. So we want to be able to get to that point as quickly as possible. And being able to have a public cloud deployment open systems capabilities that would really allow us to pass on that speed to market to those customers. So for example, an acquirer, a payment acquirer moving into a new geographical country they want to compete in they can (indistinct) on their competitors by launching minimum viable products in six to nine months that is five years ago, that could have been a 24 to 30 months endeavor for them to take on. So I, those were important considerations for us as we were choosing a longterm partner for the Postgres world and the public cloud world. >> Obviously, so you've talked a lot about your relationship with your clients and I know you have a really keen awareness of the need to ensure that trust, to ensure that reliability to ensure the collaboration. How about your relationship on the other side with EDB and in terms of all those elements so how has that evolved over a period of time and what kind of service and what kind of value do you think are you deriving from that relationship now? >> So with EDB, first of all, our journey started with 2ndQuadrant and now EDB. And we were specifically looking at the, one area was at the Bi-Directional Replication BDR that we were wanting to support with our solutions particularly in the public cloud. And that was going to enable us to replace multiple pieces of software from multiple vendors. And so we were to create that solution that was right for ACI, it was right for our customers from a functionality and agility and a cost perspective. So technologically with the non-functional requirements and the reliability, availability, serviceability aspects that we were looking for that was in partnership with 2ndQuadrant and EDB, that was a key element. I think the second piece of it is we worked really well with 2ndQuadrant EDB in terms of partnering to meet the needs of the market. It's great to have the right technology in place but then you need your partners really to be able to work with you tactically real-time in order to win in the market and make it work. And I found that they'd been a great partner for us to be able to do that and to be able to react quickly, do the right thing and really enable us to be a great partner to our customers as we deliver real-time payments, as we deliver the acquiring capabilities, as we deliver a modernization for the big banks that we work with as well. >> Now, before I let you go, I'm going to give you a two-part question here. That's always one way to squeeze a little more info (laughing) to the guest. First off advice. You've been through this transformation obviously you're very happy with all that has transpired, so your advice to others who are considering this journey. And then secondly, what can they and you do you think expect in terms of future challenges, opportunities how we might want to frame that with Postgres? Like, where are we going from here, basically? So, two parts, advice and then where do you think this is headed? >> So advice, I certainly learnings from us versus advice is number one, be very thorough in the due diligence that you do and be very clear on what you want and what are your goals that you're looking for. So from an AGI perspective, we were clear that total cost of ownership in terms of the stack that we were going to be providing to our customers. That was very important, number one number two, nonfunctional requirements. So I've talked about the mission criticality of payments 24/7 365. That was a key second piece. And then the third one, ease of deployment. I talked about that, multi-cloud deployment that we were looking for. So we were clear what we wanted and we we took our time from a due diligence point of view. It's a multi-year decision being made so it's not something specifically I think we want to rush into. In terms of looking forward and where do we go from here? Performance is critical so further up performance enhancements, ability for rapid failover availability, near 100% availability that we're looking for five-nines and above, working together with Postgres in order to make those failovers more seamless because they will happen, particularly in the real-time payments world, where we're now seeing billions of transactions happening in a week and soon that will be in a day, they will need to be able to deal with. And for all of this to happen in a public cloud environment, we, I think all understand a lot of the benefits of public cloud and we need to be able to provide this failover availability capability in the public cloud but also in a hybrid cloud environments we're in a multi-cloud environment, so we need to keep working that and make that happen that will make Postgres a payment-grade infrastructure that could power the world's real-time payments and we would love to be able to do that into the future. >> Well, Jeremy thanks for the insights, we appreciate that and once again, congratulations on getting back in that office. I know it's probably a pretty welcomed addition to your regimen now. >> Yeah, John, thank you very much and thanks to everyone who's dialed in for this and John I look forward to welcoming you in the office soon. >> Very good sir, I look forward to that as well. I'll take you up on that in Miami for sure. John Walls here on theCUBE talking with Jeremy Wilmot is the chief product officer at ACI Worldwide. part of our Postgres Vision 2021 coverage. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, hi everybody John Walls here on theCUBE and we're now welcoming Jeremy Wilmot who is the chief product officer at ACI Worldwide part of the Postgres movement, you might say or certainly benefiting from the great value that Postgres is providing a number of enterprises across the globe. Jeremy good to see you today and first off, congratulations you are the first guest I've talked to maybe in a year and a half in their office. So good for you. >> Thanks (chuckles) John that's very kind of you John and great to see you and thanks for having me here. Yeah, it's great to be in the office, it really is. I'm here in Miami in South Florida and getting some sort of normalcy back is great for all of us and I'm certainly enjoying it. So thank you before (indistinct) has been. >> I'm sure you are, yeah, congratulations on that front. First off, let's talk about ACI Worldwide for the folks in our audience who aren't familiar with the payments, your role in terms of that payment ecosystem. Tell us a little bit about ACI Worldwide. >> Sure, well, primarily we're a software company. That's ACI, we started 1975 in Omaha, Nebraska built the first debit card system and ATM system for first National Bank of Omaha and over the last 45 years, we've globalized ourselves, we have, we are delivering mission-critical real-time payment systems across the world to banks to merchants to billers, we help them meet the payment needs of their consumers and their corporates. So we process, manage digital payments, we power omni-commerce and e-commerce payments, we present and process bill payments, we manage fraud, we manage the risk all within that and as I said on a global basis 13 of the G20 countries with a leading DDA account or current account payment processing software in those countries and have been for many years. >> So, as the CPO then quite obviously in the financial space your plate is quite full these days in terms of providing for your client base. How would you characterize maybe the evolution in terms of product development that you've been through in the financial world here over the past say, three to five years, where were you back then to where you are now and what role has Postgres played in that journey? >> Sure, yeah. So, specific to the Postgres part of the ecosystem, previously five-plus years ago our previous database solution was complex, it was expensive, it was hard to change and maintain and we leveraged multiple pieces of software from multiple vendors as a result of that. So at that time we looked for an alternative that was simpler and better and we went through a very comprehensive due diligence process, we explored both open source and license models of database to support our solution and when we looked at all of the options we determined that 2ndQuadrant Postgres was the one that provided the most comprehensive solution we were looking for. It had the right mix of capabilities and performance at the right total cost of ownership that we were looking for. And in the payments world as you can imagine, you've got to to be 24/7 365. And we also required a lower cost of ownership than we had before. But we also wanted a greater flexibility and time to market that we could pass on to our customers. And then the last thing I'd say that we were looking for was a multi-deployment capability. And what I mean by that is that we would be able to use this new platform, Postgres platform in our own data centers in our own private cloud, but we could also deploy it in the public cloud, whether we would run it or whether our customers would run it. We wanted that ability to mix and match between these different deployment options. >> So you've talked about a lot of key elements here attributes in terms of availability, accessibility reliability, security obviously. Walk us through those in terms of why you think 2ndQuadrant was addressing your needs in those particular areas or any others for that matter but what it was that checked the box specifically about what Postgres was offering you as opposed to what these other possible solutions and services were that you were looking at. >> Yeah, I think, we're very focused on being able to identify what our customers need and when they're offering services to consumers and to their corporates what is it that they require that's going to enable them to win and compete. And payments industry has a lot of cost pressures within it. It has regulation, it has consumer convenience and the whole movement of digitalization that puts a lot of downward pressure on the cost space. And those who are going to win in the payment space need to be able to address that. So, that is relevant for our banks, for our merchants, for the billers. They all come under very similar regulatory pressure and market pressure and as a result, the ability to reduce dramatically in a very significant way, the total cost of ownership upon which the payment software was going to be operating that was one of the key elements that was very important to us as we made that decision. The second one I think was to enable us to be able to do what we are good at and what our customers expect us to do. And that in turn enables them to focus on their core competencies. We're a software company, we own our own IP we manage our own software for the needs of the 24/7 365 payment requirements and therefore the merchant or the biller or the bank can really focus in on the digital experience for their customers, focusing on their core competencies and what they need to do to win. That was a second key factor for us. I think the third one for us was as well speed to market. Speed to market for ourselves and being competitive to the alternative to ACI, but also more importantly a speed to market for our customers. And there are, the payment world is highly regulated requires significant certification in order to launch new services that's often the long pole in the tent. So we want to be able to get to that point as quickly as possible. And being able to have a public cloud deployment open systems capabilities that would really allow us to pass on that speed to market to those customers. So for example, an acquirer, a payment acquirer moving into a new geographical country they want to compete in they can (indistinct) on their competitors by launching minimum viable products in six to nine months that is five years ago, that could have been a 24 to 30 months endeavor for them to take on. So I, those were important considerations for us as we were choosing a longterm partner for the Postgres world and the public cloud world. >> Obviously, so you've talked a lot about your relationship with your clients and I know you have a really keen awareness of the need to ensure that trust, to ensure that reliability to ensure the collaboration. How about your relationship on the other side with EDB and in terms of all those elements so how has that evolved over a period of time and what kind of service and what kind of value do you think are you deriving from that relationship now? >> So with EDB, first of all, our journey started with 2ndQuadrant and now EDB. And we were specifically looking at the, one area was at the Bi-Directional Replication BDR that we were wanting to support with our solutions particularly in the public cloud. And that was going to enable us to replace multiple pieces of software from multiple vendors. And so we were to create that solution that was right for ACI, it was right for our customers from a functionality and agility and a cost perspective. So technologically with the non-functional requirements and the reliability, availability, serviceability aspects that we were looking for that was in partnership with 2ndQuadrant and EDB, that was a key element. I think the second piece of it is we worked really well with 2ndQuadrant EDB in terms of partnering to meet the needs of the market. It's great to have the right technology in place but then you need your partners really to be able to work with you tactically real-time in order to win in the market and make it work. And I found that they'd been a great partner for us to be able to do that and to be able to react quickly, do the right thing and really enable us to be a great partner to our customers as we deliver real-time payments, as we deliver the acquiring capabilities, as we deliver a modernization for the big banks that we work with as well. >> Now, before I let you go, I'm going to give you a two-part question here. That's always one way to squeeze a little more info (laughing) to the guest. First off advice. You've been through this transformation obviously you're very happy with all that has transpired, so your advice to others who are considering this journey. And then secondly, what can they and you do you think expect in terms of future challenges, opportunities how we might want to frame that with Postgres? Like, where are we going from here, basically? So, two parts, advice and then where do you think this is headed? >> So advice, I certainly learnings from us versus advice is number one, be very thorough in the due diligence that you do and be very clear on what you want and what are your goals that you're looking for. So from an AGI perspective, we were clear that total cost of ownership in terms of the stack that we were going to be providing to our customers. That was very important, number one number two, nonfunctional requirements. So I've talked about the mission criticality of payments 24/7 365. That was a key second piece. And then the third one, ease of deployment. I talked about that, multi-cloud deployment that we were looking for. So we were clear what we wanted and we we took our time from a due diligence point of view. It's a multi-year decision being made so it's not something specifically I think we want to rush into. In terms of looking forward and where do we go from here? Performance is critical so further up performance enhancements, ability for rapid failover availability, near 100% availability that we're looking for five-nines and above, working together with Postgres in order to make those failovers more seamless because they will happen, particularly in the real-time payments world, where we're now seeing billions of transactions happening in a week and soon that will be in a day, they will need to be able to deal with. And for all of this to happen in a public cloud environment, we, I think all understand a lot of the benefits of public cloud and we need to be able to provide this failover availability capability in the public cloud but also in a hybrid cloud environments we're in a multi-cloud environment, so we need to keep working that and make that happen that will make Postgres a payment-grade infrastructure that could power the world's real-time payments and we would love to be able to do that into the future. >> Well, Jeremy thanks for the insights, we appreciate that and once again, congratulations on getting back in that office. I know it's probably a pretty welcomed addition to your regimen now. >> Yeah, John, thank you very much and thanks to everyone who's dialed in for this and John I look forward to welcoming you in the office soon. >> Very good sir, I look forward to that as well. I'll take you up on that in Miami for sure. John Walls here on theCUBE talking with Jeremy Wilmot is the chief product officer at ACI Worldwide. part of our Postgres Vision 2021 coverage. (upbeat music)

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Hey, welcome back everybody Jeff Frick here with the cube. This is a special week it's Grace Hopper week, and Grace Hopper is the best name in tech conferences. The celebration of women in computing, and we've been going there for years we're not there this year, but one of the themes that comes up over and over at Grace Hopper is women and girls need to see women in positions that they can envision themselves being in someday. That is a really important piece of the whole diversity conversation is can I see people that I can role model after and I just want to bring up something from a couple years back from 2016 when we were there, we were there with Mimi Valdez, Christina Deoja and Dr. Jeanette Epps, Dr. Jeanette Epps is the astronaut on the right. They were there talking about "The Hidden Figures" movie. If you remember it came out 2016, it was about Katherine Johnson and all the black women working at NASA. They got no credit for doing all the math that basically keep all the astronauts safe and they made a terrific movie about it. And Janet is going up on the very first Blue Origin Space Mission Next year. This was announced a couple of months ago, so again, phenomenal leadership, black lady astronaut, going to go into space and really provide a face for a lot of young girls that want to get into that and its clearly a great STEM opportunity. So we're excited to have four terrific women today that well also are the leaders that the younger women can look up to and follow their career. So we're excited to have them so we're just going to go around. We got four terrific guests, our first one is Annabel Chang, She is the Head of State Policy and Government Regulations at Waymo. Annabel great to see you, where are you coming in from today? >> from San Francisco >> Jeff: Awesome. Next up is Inamarie Johnson. She is the Chief People and Diversity Officer for Zendesk Inamarie, great to see you. Where are you calling in from today? >> Great to be here. I am calling in from Palos Verdes the state >> Jeff: awesome >> in Southern California. >> Jeff: Some of the benefits of a virtual sometimes we can, we couldn't do that without the power of the internet. And next up is Jennifer Cabalquinto she is the Chief Financial Officer of the Golden State Warriors. Jennifer, great to see you Where are you coming in from today? >> Well, I wish I was coming in from the Chase Center in San Francisco but I'm actually calling in from Santa Cruz California today. >> Jeff: Right, It's good to see you and you can surf a lot better down there. So that's probably not all bad. And finally to round out our panelists, Kate Hogan, she is the COO of North America for Accenture. Kate, great to see you as well. Where are you coming in from today? >> Well, it's good to see you too. I am coming in from the office actually in San Jose. >> Jeff: From the office in San Jose. All right, So let's get into it . You guys are all very senior, you've been doing this for a long time. We're in a kind of a crazy period of time in terms of diversity with all the kind of social unrest that's happening. So let's talk about some of your first your journeys and I want to start with you Annabel. You're a lawyer you got into lawyering. You did lawyering with Diane Feinstein, kind of some politics, and also the city of San Francisco. And then you made this move over to tech. Talk about that decision and what went into that decision and how did you get into tech? 'cause we know part of the problem with diversity is a pipeline problem. You came over from the law side of the house. >> Yes, and to be honest politics and the law are pretty homogenous. So when I made the move to tech, it was still a lot of the same, but what I knew is that I could be an attorney anywhere from Omaha Nebraska to Miami Florida. But what I couldn't do was work for a disruptive company, potentially a unicorn. And I seized that opportunity and (indistinct) Lyft early on before Ride Hailing and Ride Sharing was even a thing. So it was an exciting opportunity. And I joined right at the exact moment that made myself really meaningful in the organization. And I'm hoping that I'm doing the same thing right now at Waymo. >> Great, Inamarie you've come from one of my favorite stories I like to talk about from the old school Clorox great product management. I always like to joke that Silicon Valley needs a pipeline back to Cincinnati and Proctor and Gamble to get good product managers out here. You were in the classic, right? You were there, you were at Honeywell Plantronics, and then you jumped over to tech. Tell us a little bit about that move. Cause I'm sure selling Clorox is a lot different than selling the terrific service that you guys provide at Zendesk. I'm always happy when I see Zendesk in my customer service return email, I know I'm going to get taken care of. >> Oh wow, that's great. We love customers like you., so thank you for that. My journey is you're right from a fortune 50 sort of more portfolio type company into tech. And I think one of the reasons is because when tech is starting out and that's what Zendesk was a few five years back or so very much an early stage growth company, two things are top of mind, one, how do we become more global? And how do we make sure that we can go up market and attract enterprise grade customers? And so my experience having only been in those types of companies was very interesting for a startup. And what was interesting for me is I got to live in a world where there were great growth targets and numbers, things I had never seen. And the agility, the speed, the head plus heart really resonated with my background. So super glad to be in tech, but you're right. It's a little different than a consumer products. >> Right, and then Jennifer, you're in a completely different world, right? So you worked for the Golden State Warriors, which everybody knows is an NBA team, but I don't know that everyone knows really how progressive the Warriors are beyond just basketball in terms of the new Chase Center, all the different events that you guys put on it. And really the leadership there has decided we really want to be an entertainment company of which the Golden State Warrior basketball team has a very, very important piece, you've come from the entertainment industry. So that's probably how they found you, but you're in the financial role. You've always been in the financial role, not traditionally thought about as a lot of women in terms of a proportion of total people in that. So tell us a little bit about your experience being in finance, in entertainment, and then making this kind of hop over to, I guess Uber entertainment. I don't know even how you would classify the warriors. >> Sports entertainment, live entertainment. Yeah, it's interesting when the Warriors opportunity came up, I naturally said well no, I don't have any sports background. And it's something that we women tend to do, right? We self edit and we want to check every box before we think that we're qualified. And the reality is my background is in entertainment and the Warriors were looking to build their own venue, which has been a very large construction project. I was the CFO at Universal Studios Hollywood. And what do we do there? We build large attractions, which are just large construction projects and we're in the entertainment business. And so that sort of B to C was a natural sort of transition for me going from where I was with Universal Studios over to the Warriors. I think a finance career is such a great career for women. And I think we're finding more and more women entering it. It is one that you sort of understand your hills and valleys, you know when you're going to be busy and so you can kind of schedule around that. I think it's really... it provides that you have a seat at the table. And so I think it's a career choice that I think is becoming more and more available to women certainly more now than it was when I first started. >> Yeah, It's interesting cause I think a lot of people think of women naturally in human resources roles. My wife was a head of human resources back in the day, or a lot of marketing, but not necessarily on the finance side. And then Kate go over to you. You're one of the rare birds you've been at Accenture  for over 20 years. So you must like airplanes and travel to stay there that long. But doing a little homework for this, I saw a really interesting piece of you talking about your boss challenging you to ask for more work, to ask for a new opportunity. And I thought that was really insightful that you, you picked up on that like Oh, I guess it's incumbent on me to ask for more, not necessarily wait for that to be given to me, it sounds like a really seminal moment in your career. >> It was important but before I tell you that story, because it was an important moment of my career and probably something that a lot of the women here on the panel here can relate to as well. You mentioned airplanes and it made me think of my dad. My father was in the air force and I remember him telling stories when I was little about his career change from the air force into a career in telecommunications. So technology for me growing up Jeff was, it was kind of part of the dinner table. I mean it was just a conversation that was constantly ongoing in our house. And I also, as a young girl, I loved playing video games. We had a Tandy computer down in the basement and I remember spending too many hours playing video games down there. And so for me my history and my really at a young age, my experience and curiosity around tech was there. And so maybe that's, what's fueling my inspiration to stay at Accenture for as long as I have. And you're right It's been two decades, which feels tremendous, but I've had the chance to work across a bunch of different industries, but you're right. I mean, during that time and I relate with what Jennifer said in terms of self editing, right? Women do this and I'm no exception, I did this. And I do remember I'm a mentor and a sponsor of mine who called me up when I'm kind of I was at a pivotal moment in my career and he said you know Kate, I've been waiting for you to call me and tell me you want this job. And I never even thought about it. I mean I just never thought that I'd be a candidate for the job and let alone somebody waiting for me to kind of make the phone call. I haven't made that mistake again, (laughing) but I like to believe I learned from it, but it was an important lesson. >> It's such a great lesson and women are often accused of being a little bit too passive and not necessarily looking out for in salary negotiations or looking for that promotion or kind of stepping up to take the crappy job because that's another thing we hear over and over from successful people is that some point in their career, they took that job that nobody else wanted. They took that challenge that really enabled them to take a different path and really a different Ascension. And I'm just curious if there's any stories on that or in terms of a leader or a mentor, whether it was in the career, somebody that you either knew or didn't know that was someone that you got kind of strength from kind of climbing through your own, kind of career progression. Will go to you first Annabel. >> I actually would love to talk about the salary negotiations piece because I have a group of friends about that we've been to meeting together once a month for the last six years now. And one of the things that we committed to being very transparent with each other about was salary negotiations and signing bonuses and all of the hard topics that you kind of don't want to talk about as a manager and the women that I'm in this group with span all types of different industries. And I've learned so much from them, from my different job transitions about understanding the signing bonus, understanding equity, which is totally foreign to me coming from law and politics. And that was one of the most impactful tools that I've ever had was a group of people that I could be open with talking about salary negotiations and talking about how to really manage equity. Those are totally foreign to me up until this group of women really connected me to these topics and gave me some of that expertise. So that is something I strongly encourage is that if you haven't openly talked about salary negotiations before you should begin to do so. >> It begs the question, how was the sensitivity between the person that was making a lot of money and the person that wasn't? And how did you kind of work through that as a group for the greater good of everyone? >> Yeah, I think what's really eye opening is that for example, We had friends who were friends who were on tech, we had friends who were actually the entrepreneurs starting their own businesses or law firm, associates, law firm partners, people in PR, so we understood that there was going to be differences within industry and frankly in scale, but it was understanding even the tools, whether I think the most interesting one would be signing bonus, right? Because up until a few years ago, recruiters could ask you what you made and how do you avoid that question? How do you anchor yourself to a lower salary range or avoid that happening? I didn't know this, I didn't know how to do that. And a couple of women that had been in more senior negotiations shared ways to make sure that I was pinning myself to a higher salary range that I wanted to be in. >> That's great. That's a great story and really important to like say pin. it's a lot of logistical details, right? You just need to learn the techniques like any other skill. Inamarie, I wonder if you've got a story to share here. >> Sure. I just want to say, I love the example that you just gave because it's something I'm super passionate about, which is transparency and trust. Then I think that we're building that every day into all of our people processes. So sure, talk about sign on bonuses, talk about pay parody because that is the landscape. But a quick story for me, I would say is all about stepping into uncertainty. And when I coach younger professionals of course women, I often talk about, don't be afraid to step into the role where all of the answers are not vetted down because at the end of the day, you can influence what those answers are. I still remember when Honeywell asked me to leave the comfort of California and to come to the East coast to New Jersey and bring my family. And I was doing well in my career. I didn't feel like I needed to do that, but I was willing after some coaching to step into that uncertainty. And it was one of the best pivotal moment in my career. I didn't always know who I was going to work with. I didn't know the challenges and scope I would take on, but those were some of the biggest learning experiences and opportunities and it made me a better executive. So that's always my coaching, like go where the answers aren't quite vetted down because you can influence that as a leader. >> That's great, I mean, Beth Comstock former vice chair at GE, one of her keynotes I saw had a great line, get comfortable with being uncomfortable. And I think that its a really good kind of message, especially in the time we're living in with accelerated change. But I'm curious, Inamarie was the person that got you to take that commitment. Would you consider that a sponsor, a mentor, was it a boss? Was it maybe somebody not at work, your spouse or a friend that said go for it. What kind of pushed you over the edge to take that? >> It's a great question. It was actually the boss I was going to work for. He was the CHRO, and he said something that was so important to me that I've often said it to others. And he said trust me, he's like I know you don't have all the answers, I know we don't have this role all figured out, I know you're going to move your family, but if you trust me, there is a ton of learning on the other side of this. And sometimes that's the best thing a boss can do is say we will go on this journey together. I will help you figure it out. So it was a boss, but I think it was that trust and that willingness for him to stand and go alongside of me that made me pick up my family and be willing to move across the country. And we stayed five years and really, I am not the same executive because of that experience. >> Right, that's a great story, Jennifer, I want to go to you, you work for two owners that are so progressive and I remember when Joe Lacob came on the floor a few years back and was booed aggressively coming into a franchise that hadn't seen success in a very long time, making really aggressive moves in terms of personnel, both at the coaches and the players level, the GM level. But he had a vision and he stuck to it. And the net net was tremendous success. I wonder if you can share any of the stories, for you coming into that organization and being able to feel kind of that level of potential success and really kind of the vision and also really a focus on execution to make the vision real cause vision without execution doesn't really mean much. If you could share some stories of working for somebody like Joe Lacob, who's so visionary but also executes so very, very effectively. >> Yeah, Joe is, well I have the honor of working for Joe, for Rick Welts to who's our president. Who's living legend with the NBA with Peter Guber. Our leadership at the Warriors are truly visionary and they set audacious targets. And I would say from a story the most recent is, right now what we're living through today. And I will say Joe will not accept that we are not having games with fans. I agree he is so committed to trying to solve for this and he has really put the organization sort of on his back cause we're all like well, what do we do? And he has just refused to settle and is looking down every path as to how do we ensure the safety of our fans, the safety of our players, but how do we get back to live entertainment? And this is like a daily mantra and now the entire organization is so focused on this and it is because of his vision. And I think you need leaders like that who can set audacious goals, who can think beyond what's happening today and really energize the entire organization. And that's really what he's done. And when I talked to my peers and other teams in there they're talking about trying to close out their season or do these things. And they're like well, we're talking about, how do we open the building? And we're going to have fans, we're going to do this. And they look at me and they're like, what are you talking about? And I said, well we are so fortunate. We have leadership that just is not going to settle. Like they are just always looking to get out of whatever it is that's happening and fix it. So Joe is so committed His background, he's an epidemiologist major I think. Can you imagine how unique a background that is and how timely. And so his knowledge of just around the pandemic and how the virus is spread. And I mean it's phenomenal to watch him work and leverage sort of his business acumen, his science acumen and really think through how do we solve this. Its amazing. >> The other thing thing that you had said before is that you basically intentionally told people that they need to rethink their jobs, right? You didn't necessarily want to give them permission to get you told them we need to rethink their jobs. And it's a really interesting approach when the main business is just not happening, right? There's just no people coming through the door and paying for tickets and buying beers and hotdogs. It's a really interesting talk. And I'm curious, kind of what was the reception from the people like hey, you're the boss, you just figure it out or were they like hey, this is terrific that he pressed me to come up with some good ideas. >> Yeah, I think when all of this happened, we were resolved to make sure that our workforce is safe and that they had the tools that they needed to get through their day. But then we really challenged them with re imagining what the next normal is. Because when we come out of this, we want to be ahead of everybody else. And that comes again from the vision that Joe set, that we're going to use this time to make ourselves better internally because we have the time. I mean, we had been racing towards opening Chase Center and not having time to pause. Now let's use this time to really rethink how we're doing business. What can we do better? And I think it's really reinvigorated teams to really think and innovate in their own areas because you can innovate anything, right?. We're innovating how you pay payables, we're all innovating, we're rethinking the fan experience and queuing and lines and all of these things because now we have the time that it's really something that top down we want to come out of this stronger. >> Right, that's great. Kate I'll go to you, Julie Sweet, I'm a big fan of Julie Sweet. we went to the same school so go go Claremont. But she's been super aggressive lately on a lot of these things, there was a get to... I think it's called Getting to 50 50 by 25 initiative, a formal initiative with very specific goals and objectives. And then there was a recent thing in terms of doing some stuff in New York with retraining. And then as you said, military being close to your heart, a real specific military recruiting process, that's formal and in place. And when you see that type of leadership and formal programs put in place not just words, really encouraging, really inspirational, and that's how you actually get stuff done as you get even the consulting businesses, if you can't measure it, you can't improve it. >> Yeah Jeff, you're exactly right. And as Jennifer was talking, Julie is exactly who I was thinking about in my mind as well, because I think it takes strong leadership and courage to set bold bold goals, right? And you talked about a few of those bold goals and Julie has certainly been at the forefront of that. One of the goals we set in 2018 actually was as you said to achieve essentially a gender balance workforce. So 50% men, 50% women by 2025, I mean, that's ambitious for any company, but for us at the time we were 400,000 people. They were 500, 6,000 globally. So when you set a goal like that, it's a bold goal and it's a bold vision. And we have over 40% today, We're well on our path to get to 50%, I think by 2025. And I was really proud to share that goal in front of a group of 200 clients the day that it came out, it's a proud moment. And I think it takes leaders like Julie and many others by the way that are also setting bold goals, not just in my company to turn the dial here on gender equality in the workforce, but it's not just about gender equality. You mentioned something I think it's probably at as, or more important right now. And that's the fact that at least our leadership has taken a Stand, a pretty bold stand against social injustice and racism, >> Right which is... >> And so through that we've made some very transparent goals in North America in terms of the recruitment and retention of our black African American, Hispanic American, Latinex communities. We've set a goal to increase those populations in our workforce by 60% by 2025. And we're requiring mandatory training for all of our people to be able to identify and speak up against racism. Again, it takes courage and it takes a voice. And I think it takes setting bold goals to make a change and these are changes we're committed to. >> Right, that's terrific. I mean, we started the conversation with Grace Hopper, they put out an index for companies that don't have their own kind of internal measure to do surveys again so you can get kind of longitudinal studies over time and see how you're improving Inamarie, I want to go to you on the social justice thing. I mean, you've talked a lot about values and culture. It's a huge part of what you say. And I think that the quote that you use, if I can steal it is " no culture eats strategy for breakfast" and with the social injustice. I mean, you came out with special values just about what Zendesk is doing on social injustice. And I thought I was actually looking up just your regular core mission and value statement. And this is what came up on my Google search. So I wanted to A, you published this in a blog in June, taking a really proactive stand. And I think you mentioned something before that, but then you're kind of stuck in this role as a mind reader. I wonder if you can share a little bit of your thoughts of taking a proactive stand and what Zendesk is doing both you personally, as well as a company in supporting this. And then what did you say as a binder Cause I think these are difficult kind of uncharted waters on one hand, on the other hand, a lot of people say, hello, this has been going on forever. You guys are just now seeing cellphone footage of madness. >> Yeah Wow, there's a lot in there. Let me go to the mind reader comments, cause people are probably like, what is that about? My point was last December, November timing. I've been the Chief People Officer for about two years And I decided that it really was time with support from my CEO that Zendesk have a Chief Diversity Officer sitting in at the top of the company, really putting a face to a lot of the efforts we were doing. And so the mind reader part comes in little did I know how important that stance would become, in the may June Timing? So I joked that, it almost felt like I could have been a mind reader, but as to what have we done, a couple of things I would call out that I think are really aligned with who we are as a company because our culture is highly threaded with the concept of empathy it's been there from our beginning. We have always tried to be a company that walks in the shoes of our customers. So in may with the death of George Floyd and the world kind of snapping and all of the racial injustice, what we said is we wanted to not stay silent. And so most of my postings and points of view were that as a company, we would take a stand both internally and externally and we would also partner with other companies and organizations that are doing the big work. And I think that is the humble part of it, we can't do it all at Zendesk, we can't write all the wrongs, but we can be in partnership and service with other organizations. So we used funding and we supported those organizations and partnerships. The other thing that I would say we did that was super important along that empathy is that we posted space for our employees to come together and talk about the hurt and the pain and the experiences that were going on during those times and we called those empathy circles. And what I loved is initially, it was through our mosaic community, which is what we call our Brown and black and persons of color employee resource group. But it grew into something bigger. We ended up doing five of these empathy circles around the globe and as leadership, what we were there to do is to listen and stand as an ally and support. And the stories were life changing. And the stories really talked about a number of injustice and racism aspects that are happening around the world. And so we are committed to that journey, we will continue to support our employees, we will continue to partner and we're doing a number of the things that have been mentioned. But those empathy circles, I think were definitely a turning point for us as an organization. >> That's great, and people need it right? They need a place to talk and they also need a place to listen if it's not their experience and to be empathetic, if you just have no data or no knowledge of something, you need to be educated So that is phenomenal. I want to go to you Jennifer. Cause obviously the NBA has been very, very progressive on this topic both as a league, and then of course the Warriors. We were joking before. I mean, I don't think Steph Curry has ever had a verbal misstep in the history of his time in the NBA, the guy so eloquent and so well-spoken, but I wonder if you can share kind of inside the inner circle in terms of the conversations, that the NBA enabled right. For everything from the jerseys and going out on marches and then also from the team level, how did that kind of come down and what's of the perception inside the building? >> Sure, obviously I'm so proud to be part of a league that is as progressive and has given voice and loud, all the teams, all the athletes to express how they feel, The Warriors have always been committed to creating a diverse and equitable workplace and being part of a diverse and equitable community. I mean that's something that we've always said, but I think the situation really allowed us, over the summer to come up with a real formal response, aligning ourselves with the Black Lives Matter movement in a really meaningful way, but also in a way that allows us to iterate because as you say, it's evolving and we're learning. So we created or discussed four pillars that we wanted to work around. And that was really around wallet, heart, beat, and then tongue or voice. And Wallet is really around putting our money where our mouth is, right? And supporting organizations and groups that aligned with the values that we were trying to move forward. Heart is around engaging our employees and our fan base really, right? And so during this time we actually launched our employee resource groups for the first time and really excited and energized about what that's doing for our workforce. This is about promoting real action, civic engagement, advocacy work in the community and what we've always been really focused in a community, but this really hones it around areas that we can all rally around, right? So registration and we're really focused on supporting the election day results in terms of like having our facilities open to all the electorate. So we're going to have our San Francisco arena be a ballot drop off, our Oakland facilities is a polling site, Santa Cruz site is also a polling location, So really promoting sort of that civic engagement and causing people to really take action. heart is all around being inclusive and developing that culture that we think is really reflective of the community. And voice is really amplifying and celebrating one, the ideas, the (indistinct) want to put forth in the community, but really understanding everybody's culture and really just providing and using the platform really to provide a basis in which as our players, like Steph Curry and the rest want to share their own experiences. we have a platform that can't be matched by any pedigree, right? I mean, it's the Warriors. So I think really getting focused and rallying around these pillars, and then we can iterate and continue to grow as we define the things that we want to get involved in. >> That's terrific. So I have like pages and pages and pages of notes and could probably do this for hours and hours, but unfortunately we don't have that much time we have to wrap. So what I want to do is give you each of you the last word again as we know from this problem, right? It's not necessarily a pipeline problem, it's really a retention problem. We hear that all the time from Girls in Code and Girls in Tech. So what I'd like you to do just to wrap is just a couple of two or three sentences to a 25 year old, a young woman sitting across from you having coffee socially distanced about what you would tell her early in the career, not in college but kind of early on, what would the be the two or three sentences that you would share with that person across the table and Annabel, we'll start with you. >> Yeah, I will have to make a pitch for transportation. So in transportation only 15% of the workforce is made up of women. And so my advice would be that there are these fields, there are these opportunities where you can make a massive impact on the future of how people move or how they consume things or how they interact with the world around them. And my hope is that being at Waymo, with our self driving car technology, that we are going to change the world. And I am one of the initial people in this group to help make that happen. And one thing that I would add is women spend almost an hour a day, shuttling their kids around, and we will give you back that time one day with our self driving cars so that I'm a mom. And I know that that is going to be incredibly powerful on our daily lives. >> Jeff: That's great. Kate, I think I might know what you're already going to say, but well maybe you have something else you wanted to say too. >> I don't know, It'll be interesting. Like if I was sitting across the table from a 25 year old right now I would say a couple of things first I'd say look intentionally for a company that has an inclusive culture. Intentionally seek out the company that has an inclusive culture, because we know that companies that have inclusive cultures retain women in tech longer. And the companies that can build inclusive cultures will retain women in tech, double, double the amount that they are today in the next 10 years. That means we could put another 1.4 million women in tech and keep them in tech by 2030. So I'd really encourage them to look for that. I'd encouraged them to look for companies that have support network and reinforcements for their success, and to obviously find a Waymo car so that they can not have to worry where kids are on for an hour when you're parenting in a few years. >> Jeff: I love the intentional, it's such a great word. Inamarie, >> I'd like to imagine that I'm sitting across from a 25 year old woman of color. And what I would say is be authentically you and know that you belong in the organization that you are seeking and you were there because you have a unique perspective and a voice that needs to be heard. And don't try to be anything that you're not, be who you are and bring that voice and that perspective, because the company will be a better company, the management team will be a better management team, the workforce will be a better workforce when you belong, thrive and share that voice. >> I love that, I love that. That's why you're the Chief People Officer and not Human Resources Officer, cause people are not resources like steel and cars and this and that. All right, Jennifer, will go to you for the wrap. >> Oh my gosh, I can't follow that. But yes, I would say advocate for yourself and know your value. I think really understanding what you're worth and being willing to fight for that is critical. And I think it's something that women need to do more. >> Awesome, well again, I wish we could go all day, but I will let you get back to your very, very busy day jobs. Thank you for participating and sharing your insight. I think it's super helpful. And there and as we said at the beginning, there's no better example for young girls and young women than to see people like you in leadership roles and to hear your voices. So thank you for sharing. >> Thank you. >> All right. >> Thank you. >> Okay thank you. >> Thank you >> All right, so that was our diversity panel. I hope you enjoyed it, I sure did. I'm looking forward to chapter two. We'll get it scheduled as soon as we can. Thanks for watching. We'll see you next time. (upbeat music)

>>live from Boston, Massachusetts. It's the Q covering I. F s World Conference 2019. Brought to you by I. F. S. >>Welcome back to Boston, everybody. You're watching The Cube. The leader in live tech coverage is Day one coverage of the I. F s World Conference. Darren Russo's here is the CEO of F S Darren. Thanks for coming back in the Cube. Great TV again. So last year was your first year. He was kind of laid out your vision at the World Conference. How's progress? >>Yeah, Look, it's going incredibly well. We were really focused on how we go from being a pretty fragment of global business to being, you know, an integrated business where we were able to operate. You know, its scale globally in a very homogenous way, where the customer experience was the same, irrespective where they engaged with us. And, you know, we've made a tremendous amount of progress with it, So you know, the business is growing really strongly. Net revenues up 22% year on year. I lost its revenues up 40% year on year are clouds up in the triple digits, so you know it's tough to be critical of how it's going so far. >>That's great, Great. You're growing faster than your peers. I think the stat was you gave us three Ex factory except in the industry would be awesome. Is that means that your primary benchmark do you want? You want to gain share? You want to go faster than the big whales, I presume. I >>think two things One is customer satisfaction, we believe, is the key indicator of long term success. S O. You know, we're the number one ranked European efforts. Salmon gotten appearance sites. That's that is and always will be my number. One metric. Can we be way the number one from a customer satisfaction perspective? And then I believe the revenue stats will follow and you know that's where we are. So certainly, if you look at our our core peers, the big G R P vendors, all of them are flat on. Dhe were growing 20 ships since >>one of the things you mentioned in your Cube interview last year was one of the things that you wanted to focus on was I'll call regional alignment. Paul and I used to work for I D. G. I worked for I. D. C. You were editor in chief of Computer World. We work for a company, had more offices overseas and IBM, and it was really hard to herd the cats. And that was one of the things that you cited. Have you been able to get people generally poor or at the same time? And how has that affected your business? Yeah. Look, I >>think the big challenge before I arrived was that there wasn't really a strategy of global strategy for the business. My face had a way of working and there was a strong culture, but there wasn't really a strategy. And obviously it's difficult to be critical of people when they not following the strategy when there isn't one s o. You know, Step one was really making sure that we had a strategy on DDE that was really about being focused on the five industries that we focused on, focused on three solutions on dhe focused on the six segments of customer, which is half a 1,000,000,000 to 5 billion. So now, globally, you know, irrespective the office that you go to, um anywhere in the world, they're focused on those five industries they focused on those three solutions and they're focused on their customer segments. So it helps me. P. M >>I said during our preview video video this morning that I've been around this industry as long as I f s has, until last year had never even heard of it. Is that just me being clueless? There's something there >>that we were just saying before we started that we're the definitely the biggest software business you've never heard of. Um, and and and that's common, I think, you know, we were There are a couple of factors. One is that the business was very European centric. Andi didn't really engaged in a tremendous amount of marketing and media prison. So, you know, those are elements that, you know, I think we're doing a better job off now, But we have a long way to go. The challenge that we have is that where we compete, we win when we get in and were able to tell our story, and we're able to show the value we win. We just don't get into as many deals as we need to. And that's the challenge we have. >>Yeah, there was a lot of talk this morning about the importance of those five pillars of those five industries. If you're going to become the next S A P, you're gonna have to branch out beyond that. What is your thinking about diversify >>becoming the next? They say he is definitely not my ambition, You know, I think way remain focused on customer satisfaction. And, you know, I think that there's a there's a difference. Whatever it is leading them, it's not customer satisfaction. You worked >>there for four years. >>I worked there for four years. I know. I think the big thing for me is is that we've got to stay focused on their customer voice. They focused on what delivers value for our customers beyond just the rhetoric and hyperbole. You know, I think when you when you listen to a lot of the complexity that our customers are facing today, any customers are facing. Companies are facing increasingly disruptive times, and the tech industry is making life more difficult for them. The more best of breed solutions get both. The more fragments that potential the landscape is, the more complex it becomes for customers if they have to try and figure out. How do we integrate these things and derive value from this highly fragmented landscape? So you know, we're trying to solve that problem. How do we make it easier for customers to challenge in their industry? And that's where this whole for the challenges has check comes from. How do we help him to be disruptive in their industry? Have competitive advantage? >>That seems to be a sort of a fundamentally different thing about your approach, though. Is this focus on those vertical industry's most e r P companies did not do that. Is that something that is core to your values? >>Look, I >>think what we recognize is that as you move to the cloud, you have to drive to standard. That's just the reality of going to the cloud on what's happening for the horizontal E. R B vendors. So the locks of ASAP and Oracle is that they have one e r P solution that fits every industry. So if it's good for health insurance and it's good for a bank, then it's difficult to really get your head around the fact that it could be good for a defense manufacturer, but the functional requirements is simply vastly different on that means that you have to customize them. If you have to customize that, they can go to the cloud. So what we believe is that you have to have this vertical specialization, the five industries that we serve us all. A lot of commonality in the process is that they use. And that's why that vertical strategy is so key to our success. So you won't see us going into financial service is, or health care or retail worth that core application. We may in time in many years to come branch out. That will be a different solutions. >>So your tailor, that app for that module for that industry, Yes, just go deep, deep functionality. You're known for that, but at the same time you're also messaging. You want your customers to be able to tailor this for their environment. So square that circle for me. >>So I think when we talk about a choice and and I think tailoring is the wrong word, we talk about choice. We're talking about choice of deployments on Prem or in the cloud choice of customer choice of partner, rather who they're going to deploy with on Dhe, then The solution is really an industry solution that comes with that functional death. And we don't we don't advocate their customers customized that all. We really don't want them to customize it. What we explain to them in some detail is that the real value comes from adopting the solution for two standard and staying on a vanilla application. Because that vanilla application, you're going to be able to withstand future upgrades, the total cost of ownership gets lower. The processes that are embedded in that application or best of breed at the box. That's what they're intended to do, and that works when you have a vertical application. When you have a horizontal application and you're trying to have a do things that it shouldn't naturally be doing, that becomes company. >>Well, correct me if I'm wrong, but wasn't that essentially the message ASAP had when it went through? It's hyper growth in the late nineties. I mean, there was a Y two k thing there, too, but ah, lot of the message was around. Do it our way and and then you don't have to get stuck in a rut, >>So I think that when it came out with that generation of application. That certainly was what they had hoped would happen. But what happened in practice is that the system integrators came in and the whole business process reengineering explosion happened on Dhe. That's not how it how it manifested itself. So what you see is, you see, he's very large, monolithic ASAP applications that were customized over in some cases decades, not not. You know, if a customer is deploying for two standard, then they should be able to deploy in a period mission. In weeks, we spoke about our deployment with Racing Point. If one team and going live in 12 weeks, you know, we're a 700 million global business. We deployed a knife s in 24 weeks. You know, if a customer's deploying for two standard, it's measured in weeks. As soon as they start to talk about two years or three years or five years or seven years there, customizing the solution significantly. Yeah, I >>mean, it became just sort of a perpetual upgrade, maintenance and up for the time it had a business impact. But boy, you think a cloud today agility, you know, getting rid of waterfall approaches, Missus. Antithetical to today's Look >>what I don't point fingers here. I think that this just maturity come with experience. The line of business applications you'll see our EMS and your HR solutions have taught people that you can, if you think about this is look at sea. Are Emma's an example? You had Siebel before people would implement stable. They would customize Siebel that would take long implementations. They were highly bespoke applications and then sells. Force came along and just destroyed them, and they destroyed them. Because what people learned very quickly was that there was a really easy to consume, really easy to use application that functionally might be inferior. But the compromises that you'd make from a functionality perspective will weigh, outweighed by their time to value in ease of use. And and the learnings from CR mnh are in procurement. Those line of business applications have now being backed into in the e. R. P >>world. So in terms of capital allocation, you're owned by private equity, which is actually a public company. I'm interested in how you're allocating capital R and D, where you're where your emphasis is. You don't have to you have to do stock buy back, but, you know, describe the P relationship. >>So look, one of my learning's to see survive this is that not all private equity firms or equal they have different strategies are very fortunate to be with Ekiti, who are a growth investor. They're known as a growth investor on dhe, and they buy companies that are strong growth tech firms on dhe. They've been hugely supportive of us investing because they understand that the investment in technology is important. So, you know, just looking at some detail today we invest twice as much in R and D as we did three years ago, just to give you, you know, one data point. So there's a big focus on technology, and the thing is, is that we we have to invest in technology to drive those attributes that are discussed earlier. How do we How do we enable customers to adopt a solution? It's a standard so they can go alive quicker. How do we enable customers to be able to sit down in the front of the application like we do with the mobile phone and intuitively know how to use it? How do we reduce the total cost of ownership through automation. Those are capabilities that you know that they don't come for free. We have to invest in them. So big investments in technology. And >>I think the private equity guys, at least the modern ones, have realized Why should the V. C's have all the fun they realize? Hey, we can actually put some money in tow and the transforming we can have a bigger exit and actually make much better returns than sucking the company drive. Yeah, well, look, I think the other >>thing is is that you know, in public companies, you have the downside off. You know this this courtly metric Ondas quarterly cadence. Andi, you see very compromising decisions being made because you know, people can't afford to miss 1/4. There's no long term planning that's done on dhe. That's fundamentally not the case and the private equity world, you know, not unusual now for four p firms to hold companies for 5678 years on, and that allows you to take a very long term strategic view. If if if a shift from perpetual to subscription is the right thing to happen, they can do that without worrying that, you know, because of the definite earnings are revenue that you're going to get caned by the market next quarter. Andi. I think that that needs to, I think, better decision making for the long term. >>A lot of companies are struggling. >>If you have the right P for because you get bought by the firm of events, you want to go public. But the the you said something this morning that 50% of your customers each year or net knew, How are you pulling that off >>That 50% of our license revenue? Eso way we went about 300 odd new customers a year. Obviously, that's growing, as I said, you know, 40%. But you know, it's ah, I think, having done this for 25 years, there are companies that are or good at extracting revenue from their installed based. One of the analysts here has as a hashtag wallet Fracking is what do you think It's such a great So you know, they're good at Wallick fracking and and I think the customers that that our customers off those vendors know exactly who they are and you know I think that for us to that the fact that we're able to go out and win 50% of our license revenue from net new name customers, I think is a really strong indicator of the health of the business. It's much harder to do than just extracting revenue out of the install base. You know, we don't have a compliance practice. We've never charged a customer for you in direct access. You know, these are principles that we stand by, and it's easier to say that your customer centric on get 80% of your revenue, have your installed base because you're doing compliance rounds. But, you know, we put our money where our mouth is, and that's not that's not how we do it. >>Are these net new customers? Are they? Are they migrating from QuickBooks or they migrating from a Competitors >>know, because of the segment that we're in this half a 1,000,000,000 to 5 billion? I would say the majority of them are what I would call first generation the Rp solution. So you know you're talking about you know, the original generation of Microsoft's acquisitions, the divisions and the eggs actors and the Solomon's and so on on. And then, you know, it's a P R two and our three customers you're talking about customer sitting on, you know, the solutions that in for hoovered up the matrix B picks type customers, ace 400 customers. So they're you know, they're first generation your P solutions that simply don't have the flexibility to deal with the complexity and demands of modern business world. >>From 2009 about 2017 I f. S was pretty inquisitive and then just actually, I was gonna ask you >>when I started, you stopped >>it, right? But then, you know, today you announced an extra small acquisition, But how should we think about M and a >>look? The first year for me was really about trying to build a functional business. You know, we spoke about how fragmented this really hit to Jenna's business. Andi just occurred to me. You know, if we go out and we start to buy things, how do we integrate them into a business that's completely fragments? And you know, it had no identity or culture. So, you know, the last year has been focused on how do we build their common understanding of what it is that we're doing. We now have a very clear strategy. Five industries, three solutions, one segment. And you know, when you when you have that clarity of vision that it's really easy to guard and do him and I because you know what fits and what doesn't fit, you can understand exactly how you're gonna build value for customers on dhe. That's why the S t a deal is so good for us. Because we're now the undisputed leader in field service management, you know, 8000 our customers globally, which is way more than anybody else. Scott, Andi, you know, you should absolutely expect more from us. But it will be in the five industries, three technology segments and one customers. Isaac. >>Well, in the A p I enablement should obviously facility. >>Absolutely. I mean, I was just with a partner of ours now, and they have this amazing augmented reality solution. You know, it will be a combination of off going out there to build market, share a cz well, as finding you know, really innovative solutions that can help us advance the technology that we provide customers. >>You have a new slogan this year for the challengers, which seems to be aimed at companies that that imagine themselves as challenging the Giants, which is great. But if you're not a company that season sees themselves that way. Are the studies level home with I have s Look, >>I I think I was with a group of CEOs from one of the big analyst rooms, and they had the portfolio companies and their private equity firm and analysts that CEOs of the companies are having a conversation with him about digital transformation. And I I made a rather provocative statement which, you know, got unanimous agreement, which is that all of the CEOs there with either in an industry that was being disrupted and we're trying to figure out how they respond to that disruption or they would soon not every job and they all acknowledge that they absolutely fit into that category. In other words, all of them were being disrupted. All of them were facing a challenge. It was kind of like, you know, if it is happening to all of us at a more rapid pace than we have ever had before. So my view is, is that you know if if you're in the room and you're going, you know, if it's might not be for us because we're not a challenger. Yeah, The lights may not be on >>for Long s o double click on that. What role does I s play in terms of digital transformation? >>If I could just hold on there because the thing is, there are leaders in Mama, there challenges. And there are leaders. The leaders typically are gonna go with seif solution. They're gonna go with one of the legacy our peace. So I'm not suggesting that everybody necessarily is a challenger. There are leaders, you know, Nokia was a leader until they weren't because they were complacent. Andi, I think they you know, they didn't run on I office. So, you know, I think there are two segments. There are leaders and there are challenges, and we're there for the ones that are ready to disrupt. Sorry. >>Please clarify that. No. Good. So So get back to it. Sort of digital transformation and disruption. What do you see? Is the role of AARP generally, but specifically I f s. >>Look, I think we digital information. A lot of discussion about it on the stage this morning. I've just touched on it now. I think that it takes very different forms. What most industries are finding is that they're facing a lot of non traditional competition and they're having to innovate around their business models. They can't going to market in the same way as they did before. They're having to innovate because of this non traditional competition. Andi. Understanding your your customer's understanding, your your staff, understanding your supply chain understanding your financials are all critical parts of being able to respond to whatever their changes, and that's where the RP solution comes into it. I think there's an interesting challenge now, which is that as those applications have become more fragmented and you've got more based debris cloud applications Ah, lot of the value often E. R P was that you had this integrated set of applications that you had this one source of the truth andan. Fortunately for many customers today, they don't have that because they've got import all of these best of breed applications and they don't have one source of the truth that multiple invoices made it multiple versions of their customer in the databases. Andi we still stand for a single integrated the r p. So, you know, I think understanding those elements of your businesses key. I was with a customer of ours in Nebraska a short while ago, and they were talking about our existing office customer. They were talking about the steel import duties that were imposed through the trade war with China. And they were saying, Look, that they had been able to respond to that in a way that they had good visibility of the supply chain, who was improved, imposing the tariffs, how they were going to impact them when they were going to impact them. And because they had this integrated Siara AARP. They were able to pass those pricing changes onto their customers, and they survived this. What could have been a cataclysmic event for their business had they not had an integrated your pee? They not being able to have this visibility into the supply chain and the customer base. They may well have gone out of business just because of that one change >>to meet all day and all comes back to the data, putting their putting data at the core of their business. That integrated data pipeline is essentially what they get out of that last question. So thinking about the next 18 to 24 months, what are the milestones that observers should look for? One of the barometers that we should be watching. >>So look, in the next two years, it's it's really about us building incremental scale. We have, ah, four year plan, which I built when I came in. We're halfway through that plan. We've hit all of the metrics and exceeded most the metrics that we had on their plan. It's really continue to focus on the strategy. As I said, we focus on those five industries, continue to build market share, continue to focus on those three solution types and build market share and market dominance on those three solutions. Andi in that segment that I defined before, so no change from a strategy perspective. I think there's really value in the consistency that we bring on on their talk track and, you know, along the way we passed the $1,000,000,000 mark, which we will do, I think, in 2021 organically if we accelerate, some of the money will pass the 1,000,000,000 before, but you know business. The margins continue to expand. We focus on customer satisfaction and, you know, it's a It's a pretty straight, you know, traditional prey book that we have to execute on now. >>Well, congratulations. It's a great playbook, and you're growing very nicely. So love that. Look, we really an honor to the last couple of years. Learn a little bit about the company in your industry. So appreciate meeting you guys. Thank you. All right. And thank you for watching over right back with our next guest. Ready for this short break day Volonte with Paul Gill in. You're watching the Cube from I f s World Conference from Boston 2019 right back.

>> Live from Washington, DC, it's theCUBE, covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of the AWS Public Sector Summit, here in our nation's capital. I'm your host, Rebecca Knight, co-hosting with John Furrier. We have two guests for this segment, we have George Gagne, he is the Chief Information Officer at Defense POW/MIA Accounting Agency. Welcome, George. And we have Christopher McDermott, who is the CDO of the POW/MIA Accounting Agency. Welcome, Chris. >> Thank you. >> Thank you both so much for coming on the show. >> Thank you. >> So, I want to start with you George, why don't you tell our viewers a little bit about the POW/MIA Accounting Agency. >> Sure, so the mission has been around for decades actually. In 2015, Secretary of Defense, Hagel, looked at the accounting community as a whole and for efficiency gains made decision to consolidate some of the accounting community into a single organization. And they took the former JPAC, which was a direct reporting unit to PACOM out of Hawaii, which was the operational arm of the accounting community, responsible for research, investigation, recovery and identification. They took that organization, they looked at the policy portion of the organization, which is here in Crystal City, DPMO and then they took another part of the organization, our Life Sciences Support Equipment laboratory in Dayton, Ohio, and consolidated that to make the defense POW/MIA Accounting Agency, Under the Office of Secretary Defense for Policy. So that was step one. Our mission is the fullest possible accounting of missing U.S. personnel to their families and to our nation. That's our mission, we have approximately 82,000 Americans missing from our past conflicts, our service members from World War II, Korea War, Korea, Vietnam and the Cold War. When you look at the demographics of that, we have approximately 1,600 still missing from the Vietnam conflict. We have just over a 100 still missing from the Cold War conflict. We have approximately 7,700 still missing from the Korean War and the remainder of are from World War II. So, you know, one of the challenges when our organization was first formed, was we had three different organizations all had different reporting chains, they had their own cultures, disparate cultures, disparate systems, disparate processes, and step one of that was to get everybody on the same backbone and the same network. Step two to that, was to look at all those on-prem legacy systems that we had across our environment and look at the consolidation of that. And because our organization is so geographically dispersed, I just mentioned three, we also have a laboratory in Offutt, Nebraska. We have detachments in Southeast Asia, Thailand, Vietnam, Laos, and we have a detachment in Germany. And we're highly mobile. We conduct about, this year we're planned to do 84 missions around the world, 34 countries. And those missions last 30 to 45 day increments. So highly mobile, very globally diverse organization. So when we looked at that environment obviously we knew the first step after we got everybody on one network was to look to cloud architectures and models in order to be able to communicate, coordinate, and collaborate, so we developed a case management system that consist of a business intelligence software along with some enterprise content software coupled with some forensics software for our laboratory staff that make up what we call our case management system that cloud hosted. >> So business challenges, the consolidation, the reset or set-up for the mission, but then the data types, it's a different kind of data problem to work, to achieve the outcomes you're looking for. Christopher, talk about that dynamic because, >> Sure. >> You know, there are historical different types of data. >> That's right. And a lot of our data started as IBM punchcards or it started from, you know, paper files. When I started the work, we were still looking things up on microfiche and microfilm, so we've been working on an aggressive program to get all that kind of data digitized, but then we have to make it accessible. And we had, you know as George was saying, multiple different organizations doing similar work. So you had a lot of duplication of the same information, but kept in different structures, searchable in different pathways. So we have to bring all of that together and make and make it accessible, so that the government can all be on the same page. Because again, as George said, there's a large number of cases that we potentially can work on, but we have to be able to triage that down to the ones that have the best opportunity for us to use our current methods to solve. So rather than look for all 82,000 at once, we want to be able to navigate through that data and find the cases that have the most likelihood of success. >> So where do you even begin? What's the data that you're looking at? What have you seen has had the best indicators for success, of finding those people who are prisoners of war or missing in action? >> Well, you know, for some degrees as George was saying, our missions has been going on for decades. So, you know, a lot of the files that we're working from today were created at the time of the incidents. For the Vietnam cases, we have a lot of continuity. So we're still working on the leads that the strongest out of that set. And we still send multiple teams a year into Vietnam and Laos, Cambodia. And that's where, you know, you try to build upon the previous investigations, but that's also where if those investigations were done in the '70s or the '80s we have to then surface what's actionable out of that information, which pathways have we trod that didn't pay off. So a lot of it is, What can we reanalyze today? What new techniques can we bring? Can we bring in, you know, remote sensing data? Can we bring GIS applications to analyze where's the best scenario for resolving these cases after all this time? >> I mean, it's interesting one of the things we hear from the Amazon, we've done so many interviews with Amazon executives, we've kind of know their messaging. So here's one of them, "Eliminate the undifferentiated heavy lifting." You hear that a lot right. So there might be a lot of that here and then Teresa had a slide up today talking about COBOL and mainframe, talk about punch cards >> Absolutely. >> So you have a lot of data that's different types older data. So it's a true digitization project that you got to enable as well as other complexity. >> Absolutely, when the agency was formed in 2015 we really begin the process of an information modernization effort across the organization. Because like I said, these were legacy on-prem systems that were their systems' of record that had specific ways and didn't really have the ability to share the data, collaborate, coordinate, and communicate. So, it was a heavy lift across the board getting everyone on one backbone. But then going through an agency information modernization evolution, if you will, that we're still working our way through, because we're so mobilely diversified as well, our field communications capability and reach back and into the cloud and being able to access that data from geographical locations around the world, whether it's in the Himalayas, whether it's in Vietnam, whether it's in Papua New Guinea, wherever we may be. Not just our fixed locations. >> George and Christopher, if you each could comment for our audience, I would love to get this on record as you guys are really doing a great modernization project. Talk about, if you each could talk about key learnings and it could be from scar tissue. It could be from pain and suffering to an epiphany or some breakthrough. What was some of the key learnings as you when through the modernization? Could you share some from a CIO perspective and from a CDO perspective? >> Well, I'll give you a couple takeaways of what I thought I think we did well and some areas I thought that we could have done better. And for us as we looked at building our case management system, I think step one of defining our problem statement, it was years in planning before we actually took steps to actually start building out our infrastructure in the Amazon Cloud, or our applications. But building and defining that problem statement, we took some time to really take a look at that, because of the different in cultures from the disparate organizations and our processes and so on and so forth. Defining that problem statement was critical to our success and moving forward. I'd say one of the areas that I say that we could have done better is probably associated with communication and stakeholder buy-in. Because we are so geographically dispersed and highly mobile, getting the word out to everybody and all those geographically locations and all those time zones with our workforce that's out in the field a lot at 30 to 45 days at a time, three or four missions a year, sometimes more. It certainly made it difficult to get part of that get that messaging out with some of that stakeholder buy-in. And I think probably moving forward and we still deal regarding challenges is data hygiene. And that's for us, something else we did really well was we established this CDO role within our organization, because it's no longer about the systems that are used to process and store the data. It's really about the data. And who better to know the data but our data owners, not custodians and our chief data officer and our data governance council that was established. >> Christopher you're learnings, takeaways? >> What we're trying to build upon is, you define your problem statement, but the pathway there is you have to get results in front of the end users. You have get them to the people who are doing the work, so you can keep guiding it toward the solution actually meets all the needs, as well as build something that can innovate continuously over time. Because the technology space is changing so quickly and dynamically that the more we can surface our problem set, the more help we can to help find ways to navigate through that. >> So one of the things you said is that you're using data to look at the past. Whereas, so many of the guests we're talking today and so many of the people here at this summit are talking about using data to predict the future. Are you able to look your data sets from the past and then also sort of say, And then this is how we can prevent more POW. Are you using, are you thinking at all, are you looking at the future at all with you data? >> I mean, certainly especially from our laboratory science perspective, we have have probably the most advanced human identification capability in the world. >> Right. >> And recovery. And so all of those lessons really go a long ways to what what information needs to be accessible and actionable for us to be able to, recover individuals in those circumstances and make those identifications as quickly as possible. At the same time the cases that we're working on are the hardest ones. >> Right. >> The ones that are still left. But each success that we have teaches us something that can then be applied going forward. >> What is the human side of your job? Because here you are, these two wonky data number crunchers and yet, you are these are people who died fighting for their country. How do you manage those two, really two important parts of your job and how do you think about that? >> Yeah, I will say that it does amp up the emotional quotient of our agency and everybody really feels passionately about all the work that they do. About 10 times a year our agency meets with family members of the missing at different locations around the country. And those are really powerful reminders of why we're doing this. And you do get a lot of gratitude, but at the same time each case that's waiting still that's the one that matters to them. And you see that in the passion our agency brings to the data questions and quickly they want us to progress. It's never fast enough. There's always another case to pursue. So that definitely adds a lot to it, but it is very meaningful when we can help tell that story. And even for a case where we may never have the answers, being able to say, "This is what the government knows about your case and these are efforts that have been undertaken to this point." >> The fact there's an effort going on is really a wonderful thing for everybody involved. Good outcomes coming out from that. But interesting angle as a techy, IT, former IT techy back in the day in the '80s, '90s, I can't help but marvel at your perspective on your project because you're historians in a way too. You've got type punch cards, you know you got, I never used punch cards. >> Put them in a museum. >> I was the first generation post punch cards, but you have a historical view of IT state of the art at the time of the data you're working with. You have to make that data actionable in an outcome scenario workload work-stream for today. >> Yeah, another example we have is we're reclaiming chest X-rays that they did for induction when guys were which would screen for tuberculosis when they came into service. We're able to use those X-rays now for comparison with the remains that are recovered from the field. >> So you guys are really digging into history of IT. >> Yeah. >> So I'd love to get your perspective. To me, I marvel and I've always been critical of Washington's slowness with respect to cloud, but seeing you catch up now with the tailwinds here with cloud and Amazon and now Microsoft coming in with AI. You kind of see the visibility that leads to value. As you look back at the industry of federal, state, and local governments in public over the years, what's your view of the current state of union of modernization, because it seems to be a renaissance? >> Yeah, I would say the analogy I would give you it's same as that of the industrial revolutions went through in the early 20th century, but it's more about the technology revolution that we're going through now. That's how I'd probably characterize it. If I were to look back and tell my children's children about, hey, the advent of technology and that progression of where we're at. Cloud architecture certainly take down geographical barriers that before were problems for us. Now we're able to overcome those. We can't overcome the timezone barriers, but certainly the geographical barriers of separation of an organization with cloud computing has certainly changed. >> Do you see your peers within the government sector, other agencies, kind of catching wind of this going, Wow, I could really change the game. And will it be a step function into your kind of mind as you kind of have to project kind of forward where we are. Is it going to a small improvement, a step function? What do you guys see? What's the sentiment around town? >> I'm from Hawaii, so Chris probably has a better perspective of that with some of our sister organizations here in town. But, I would say there's more and more organizations that are adopting cloud architectures. It's my understanding very few organizations now are co-located in one facility and one location, right. Take a look at telework today, cost of doing business, remote accessibility regardless of where you're at. So, I'd say it's a force multiplier by far for any line of business, whether it's public sector, federal government or whatever. It's certainly enhanced our capabilities and it's a force multiplier for us. >> And I think that's where the expectation increasingly is that the data should be available and I should be able to act on it wherever I am whenever the the opportunity arises. And that's where the more we can democratize our ability to get that data out to our partners to our teams in the field, the faster those answers can come through. And the faster we can make decisions based upon the information we have, not just the process that we follow. >> And it feeds the creativity and the work product of the actors involved. Getting the data out there versus hoarding it, wall guarding it, asylumming it. >> Right, yeah. You know, becoming the lone expert on this sack of paper in the filing cabinet, doesn't have as much power as getting that data accessible to a much broader squad and everyone can contribute. >> We're doing our part. >> That's right, it's open sourcing it right here. >> To your point, death by PowerPoint. I'm sure you've heard that before. Well business intelligence software now by the click of a button reduces the level of effort for man-power and resources to put together slide decks. Where in business intelligence software can reach out to those structured data platforms and pull out the data that you want at the click of a button and build those presentations for you on the fly. Think about, I mean, if that's our force multiplier in advances in technology of. I think the biggest thing is we understand as humans how to exploit and leverage the technologies and the capabilities. Because I still don't think we fully grasp the potential of technology and how it can be leveraged to empower us. >> That's great insight and really respect what you guys do. Love your mission. Thanks for sharing. >> Yeah, thanks so much for coming on the show. >> Thank you for having us. >> I'm Rebecca Knight for John Ferrer. We will have much more coming up tomorrow on the AWS Public Sector Summit here in Washington, DC. (upbeat music)

>> [Narrator] From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. (mellow electronic music) Now here's your host, Stu Miniman. >> Hi, I'm Stu Miniman, and welcome to theCUBE's Boston area studio. Gonna be having a different conversation today. We often talk about cloud and data and all the various technologies, and we're gonna talk about a different application of them in the customer experience base. And to help me to do that, thought leader in the space, Steve Papas, who's the senior vice president and chief marketing officer of Panviva. Steve, thanks so much for joining us. >> Thanks for having me, this is great. >> I go back in my roots, and my first job out of school, the company I started with, put everybody into customer support. There's no better way to kinda understand how something works and how people interact with technology as well as the product than taking those phone calls when something goes wrong in customer support. So I have a little bit of experience in the CX space, as I believe you call it these days. You know, watch from the technology space, the call centers, and all those kind, but, maybe start us out, when you say CX here in 2019, what's the scope, what are we talking about that, and we'll go from there. >> That's a great place to start, Stu, 'cause really when we're talking about customer experience, or CX as it's being known, we're really talking about what is the customer's experience when they're interacting with our organization or they're even transacting with our organization. So if you think about it, there's probably the three things that they could do with a company. They can either interact with them and get some information, maybe they're checking on a rate for a mortgage or looking for a car loan or getting claim information from their health insurer, or they're transacting, they're buying something, they're conveying some kind of a transaction together. Or there may be more of a back office approach to it, so that someone's operating on behalf of the customer. So when we think about all of those three dimensions, it's really about, was it frictionless, was it easy to do, did they get to the point where they felt delighted and they're willing to provide a reference or a testimonial because they're gushing because the experience was so good. They got what they needed and they're willing to tell people about it. >> Yeah, that's great. You see friction lists, it reminds me of what we talked for years about with cloud computing, talked about bringing joy and having authentic conversations. We've been talking for years about how social media and engagement should be. I have to think that the balance and interaction between people and machines and technology have to be a hot-button topic there. One of my favorite events that we did a few years ago was with MIT, talking about automation, are the robots going to take over everything? And what we know tends to work best is that there needs to be a balance of the robots, chatbots, whatever they are, and people. It can't be all of one, or even all of the other because it either get too costly, or the experience might not be optimal. >> Yeah, I think you're exactly right. I think all of those different things have their place. And if you think about it, it's kind of like the pie. You're adding pieces to the pie. So you're adding the chatbot as another method, or another medium that someone can interact with the organization, but it's not the be-all and end-all. There has to be a level of human aspect to a lot of things. I'll give you an example. You're not gonna call your hospital when you're feeling some chest pains, and want the chatbot to be on the other end. >> [Stu] Right. >> So there has to be, we have to temper what types of technology we use with what areas, and we have to be thinking about the customer. I always advocate, you always think about the customer at the center of the universe, and make sure the customer has a seat at every decision table. So when we're thinking about bringing technology into organizations, we have to think about, well, how does this make the customer's experience better? Does it help them? Does it make their interaction with us better? And overall, does that technology make the types of customers and lifetimes value increase for us as organizations? >> You hear a lot of organizations, I'm customer focused, you go read Jeff Bezos talks about, I need to be paranoid about my customer, I need to think about everything they're doing, because if they change and they leave us, what are we left with? Bring us into customer experience, what does that matter, how do we get beyond lip service, talking, yeah, it's great to listen to the customers but, I've gotta worry about my bottom line and my employees and stockholders and things like that. >> Sure, well today, if you think about customer service, good customer service, every company in the world is talking about it. That's the baseline now, right? That is where we begin, and we're moving up from there to a level of customer service. So if we're thinking about customer service as, it has to be good, but how do you get from that good to great scenario, it's how do we train our people, how do we make sure they're empowered to provide the customer with all they need, and give them a little bit of decision making power when it makes the difference of keeping that customer for life, and maybe their children and friends and relatives, or potentially losing them at that single interaction. So, when we're thinking about the bottom line, we always have to think that every interaction could be the last interaction. But also, every interaction's an opportunity to make that relationship better. So we have to think about that in terms of how we do things, as well as what technology surrounds that. And obviously, the negative side of customer experience is if we do it wrong, we're certainly losing, but if we do it right, it's exponentially better. >> I'm curious Steve, what your thoughts are, how do I measure that? In the B to B world we talk about the net promoter score, NPS, and we love it, and it's great when you see a high net promoter score, but when you understand the details and what goes under it, that's only part of the picture. And boy do I agree with you about, if you have that opportunity to talk to a customer and turn it around, uh, you know. If you spend any time in the space, it's great when somebody comes back and has something good to say, but if somebody comes and says something bad, it's usually only the tip of the iceberg. There's usually other people that can have it, and you have to take that opportunity to turn it into something good. So, metrics and, how do we measure whether we're doing good or bad in the space? >> Absolutely, well, the contact center itself is metriced to the nth degree anyway. Net promoter score is one dimension of how we have to looks at things. I'll tell you a story, that I recommend to every C-suite person that I interact with, and I'm a member of a lot of associations, that the best thing that they can do is spend time in the contact center. Double check into those calls. Not only is it the best focus group you can ever pay for, that you already have, but also it allows for a C-suite, whether it's a CEO or the Chief Operating Officer or the CFO it allows them to understand really how the interactions are happening between the customer as well as the organization. But it goes a step further. Not only do you measure the customer satisfaction levels, but you also need to measure your employee satisfaction levels that way too. Because having employees that have the tools necessary to provide the best service possible, as well as make sure that they have the training, they have the empowerment to do it. Once you have those things in place, I always say that the CEO and others in the C-suite should be listening to those calls to understand, does the employee have all the right tools to make that customer interaction better. And to extend that lifetime value or not. And that's one way, which is much more of a qualitative versus the metrics, but it's one that's missed all the time. And I have CEOs tell me time and time again, after they've done it, it was absolutely enlightening for them to say, I never saw that part of the business, from that vantage point. >> Steve, bring us inside those call centers a little bit. I've got a little bit of background, but it was often overworked, underappreciated, very much metrics-driven. There's the big thing on the wall, saying how long the average call's been waiting. Have you hit the number that you needed to do? Has it gotten better? What's it like in these environments today? Outsourcing was a big push for a number of years, what's it like in those call centers? >> Outsourcing is still a big thing. A lot of U.S. companies have started bringing some of the things back in-house too. When they found that the metrics might not have been there. But they're also holding their outsources to a higher standard, now. So they're providing not only the training, but what I'm seeing as far as trends, is that they're providing the how-to much better. They're realizing that having a single source of truth that your employees are using, your customers can access via self-service, as well as the outsourcer, is really the key to making all of this work so you have the portability of process much better. Now the call centers are getting much better because they're starting to move more onto the knowledge side as well as the process side. They're looking internal. It's not good enough for them to say, well, it's been working fine, right? It's now to the point with, how much better can we get it to work? How do we get to the last mile? How do we get to the point where these customers are willing and call back to say, hey, I had a great experience. So, we're finding that one of the keys was making sure the employees, the people on the front lines, have what they need the second that they need it. Not to pop their head over the cube, not to escalate to a help desk, right? Because that just increases the overall cost of a contact center. Not to be shuffling through papers, or flipping through the pages of a binder every few minutes. But giving them the tools that they need so that A. They know exactly what the process is, they can remain compliant with the process, they can navigate the myriad of applications that are open on the desktop, as well as know how to say the right things, they avoid saying the wrong things, and they don't come across as robotic. And that's one of the keys that is happening now. And we see that trend happening more and more in contact centers, and I probably walk in and out of 150 of them in a year, and see them from the inside. You know the one thing that I always look around in a contact center is, if there's lots of sticky notes around the monitors, if there's lots of binders on the desk and papers up on the cubes, there are process problems. There are opportunities to make that organization run a lot smoother on behalf of the customer. >> Steve, related to CX, one of the topics you've written about is Omnichannel. Maybe you can explain what that is, and what you're finding. >> Sure, so Omnichannel is really geared around how do we communicate with our customers, our partners, our dealers, our distributors, etc. So how do we communicate properly on any channel necessary that the customer wants? We always say that it used to be multichannel, right? We would have the telephone, we would have maybe the IVR is giving them directions and allowing them some information when they call in. But now customers want to be communicated with on Skype, or Slack, or Facebook Messenger, or Twitter or Instagram, or various other methods that are accessible to the consumer. The consumer has a lot of information as well as a lot of power at their fingertips now, that they probably didn't have, 10, 15 years ago. Now, the Omnichannel is really geared around creating a universal way of, of communicating with the customer where they want to be communicated with, and we say that's probably the best channel, is, what does the customer want, right? Where are they, so how do we get to them where they are? And to make that work there's technology involved. And also if we want to say, well how do we take care of our customers at 2:00 AM, maybe with a chatbot, so they can get some of the information that they need when they need it. It's all about time, right? The thing that we're trying to solve now is the problem of time. How do we make sure that we get the information into the hands of the person that needs it, whether it's our employee or our customer, or maybe our third-party dealers, distributors, etc. How do we get that information in a timely manner so that they can do something of action, of value? And that's really the key. So Omnichannel really is gearing around, how do we maintain all of those? But, some of the keys to it, and I wanna put those out there, is we have to curate content better. We have to look at the fact that, you don't write a procedure for the employee to speak over the phone the same way you're gonna write for Alexa as a virtual assistant, to be speaking out into the air. So we have to think about content curation as, what are the multiple versions of the same thing that need to be housed in one place? And then how do we orchestrate them at the moment of need? When Alexa does call in and says, I need information about your hours, that information and the version of that content has to be pushed in a sub-second method to go to the right channel at the right time, in the right format. >> That machine-to-machine discussion added a whole new dimension for a lot of companies. >> [Steve] Absolutely. To try to solve that. Great, give us, we're here towards the beginning of the year still, at 2019, give us a little bit look forward, what are the challenges, what are the things that are exciting you, as we look throughout this year. >> Sure. I think we're really looking forward to more companies understanding the customer. And by that I don't mean that they have to go through an entire customer journey mapping, but that is a good place to start. But at the end of the day, you have to make sure the operator 24 in Omaha, Nebraska knows the result of all that journey mapping. So there has to be a third dimension if you will, after you've done your analysis and your mapping, is how do they execute? On all of the stuff we've found in the customer journey mapping, how do they execute at that point, at that cold face of business happening, for the benefit of the customer, as well as for the employee satisfaction. So we're seeing that customer-centric conversations are increasing. By that I mean that companies are looking for, what are all the methods, the simple methods that we can incorporate today, which doesn't necessarily mean bringing in all kinds of technology, what are the methods that we can start bringing in to make our employees feel empowered around the whole customer experience paradigm. So, that I'm seeing, is happening. The other one is, as you referred to Jeff Bezos, whenever you have a decision in your company, and you've got the conference room table, put one chair over there and just put the name Customer on the chair, and allow the customer to have a decision. Allow the customer to have a seat at the decision table. And by that I mean that, always think, as you're making your moves in 2019 and 2020 and beyond, what does it mean to the customer? How is that going to affect the customer, and will it be positive for their experience? Those are the types of things that are getting real exciting, that companies are finally starting to look at those and they're not saying good enough is good enough anymore, and they're not looking at, well the whole operation is factored into the cost of doing business. They're all starting to say, how can we do better? And mostly the thing that's driving that is they have to get better at customer experience. Because if you think about it, price, everybody knows the price now, they can search for everything that they're shopping for, and they know who's got the same price, and pretty much there's an equilibrium on that. So, if price is one thing, and size and color and all of those things are similar, and all of the components of that are similar across the board, well what are companies starting to compete on? Companies in 2019 and 2020 are gonna start competing on the experience. So if you think about one of the best competitive advantages moving forward? Is, what is the experience that we give, over and above our competition. And that is so important, we're seeing the trends moving to that and honestly, that's what's really starts to excite me as companies are moving down this path. >> Steve, one of the things I know is that you've written a number of things on this topic. If people want to learn more about CX what are some of the resources they can go to? Which, not trying to pitch product from Panviva, but really thought leadership interface. >> We also work with a lot of thought leaders, and we only approach it from an educational perspective. Matter of fact, we just published a new e-book on customer experience. All the tips from ten industry leaders in customer experience, and that's available on our website, at Panviva.com. They can connect with me at Twitter @SXP01, or by email at spapas@panviva.com. And I'm happy to point them in the direction of any of these resources that fundamentally will help them start a workshop inside, and start the thought process of, how can we get better on behalf of the customer? >> Alright well, Steve, really appreciate you helping to educate our community a little bit more about the CX base and definitely do check out, either reach out to Steve directly, or check out the Panviva.com website to learn more. And be sure to check out thecube.net for all the upcoming shows as well as the archive of everything we have. If you go into the search box you can search on topic, company, or person, we've got the database of thousands of interviews we've done in the past. So, once again, I'm Stu Miniman, and thank you for watching The Cube. (electronic music)

>> From San Francisco, it's theCUBE covering Sumo Logic Illuminate 2018. (techy music) Now here's Jeff Frick. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate, we're at the San Francisco Hyatt Regency by the airport. 600 people, three times bigger than last year. They got one of the coolest things I've ever seen. They got like the silent disco in the expo area. Everyone's listening to their session, they all got headphones on. Ton a people, you can't hear a thing. Pretty innovative, I've never seen anything like that. We're excited to have our next guest, John Visneski, he's a director of information security and data protection officer for the Pokémon company, John, great to see you. >> Yeah, happy to be here, and there's free coffee, which is why I showed up. >> The free coffee. >> Absolutely. >> And they're not taking it away, that's-- >> And they're not taking it away. >> No, you can tell a good conference from a bad conference, the bad ones wheel it out and take it away and the good ones just leave it out all day. >> I like so much free coffee at some point I'll probably have a heart attack half way through and you'll have to resuscitate me. >> Don't do that. >> So, I apologize in advance. >> Don't do that, don't do that. (laughs) So, tell us a little a little bit about what you do. Everyone knows Pokémon, right? >> Yeah. >> It's a great brand, great global brand. >> Absolutely. >> What are some of the projects you're working on behind the scenes that most people probably aren't thinking about when they think about Pokémon? >> Yeah, well absolutely, I think in this day and age the first thing people think about when they think about our brand is Pokémon Go, right, and with that sort of explosion of user base what comes with that is this giant lake of data, right, and so my job primarily, my team's job is to protect our customers, right? One of our core values is child safety, so we take security and privacy very seriously, and so what we're working on right now is trying to figure out how do we wrap our arms around that data, and as a security team, how do we enable the business to move as fast as they want to move while keeping that data secure. We have a whole lot of awesome products that are coming up in the next two years, and while most security teams have a hard time keeping pace with that sort of thing-- >> Right. >> I like to think that we're sort of on the cutting edge of leveraging our security tools, like Sumo Logic, to operationalize our security team and make sure we're a business enabler-- >> Right >> Not just a return on investment. >> So, was the Pokémon Go explosive growth, had you seen anything like that? Was that kind of a seminal moment in terms of what you guys had to manage-- >> Yeah. >> On the backend. I mean, the numbers are giant. I saw something, 750 million users-- >> Yeah. >> Most of whom, or a lot of whom, are kids, so you've got the whole kid factor, under 18. >> Yeah. >> I mean, that was quite a phenomenon. >> You know, I don't think anyone ever plans for 750 million downloads, and when it happens the scalability issues that come with that are phenomenal. You know, one of the advantages we have as an organization is that we take child online privacy protection very seriously, so we're really well-postured from a policy perspective to understand as we scale, you know, what are the controls we need to put in place to ensure that our customers are kept safe. >> Right. >> But all the policy in the world doesn't make up for the fact that you still need a lot of horsepower to accommodate all that and make sure that people can go to gyms and all those sorts of things, and so it's been an interesting ride in that respect. >> So, where is it deployed? You guys on a cloud-based infrastructure or do you have on-prem? Kind of what's your backend look like? >> Absolutely, so we're AWS customer, so our customer-facing platforms are almost entirely in AWS, and we've been pretty happy. >> Good, so you could scale, you could scale to the 750. (laughs) >> You sure can, you sure can, the meter goes up, though, the meter goes up, for sure. >> Yes, the meter does go up. >> I mean, and so one of the things that that's presented to us is, you know, how do we think about security and how do we think about devops and how do we join those two things together to make sure that as we scale we're scaling in a way that is smart, right? >> Right, right. >> You can't just keep throwing instances at things because eventually your break your own cost curve, so how are we building smarter, not bigger-- >> Right. >> And not harder, if that makes sense. >> So, what are some the unique challenges because of the kids that are involved in your marketplace that you guys have to do that maybe someone... We had a guest on the other day who was involved in bedding, right, just by rule hopefully there's no kids on the bedding application-- >> Sure. >> But what are some of the special things you guys have to think about when you're dealing with minors? >> Yeah, absolutely, so there's the Child Online Privacy Protection Act, which kinds of governs how we're supposed to be handling data for children that are under 13, and then that gap in between 13 and 18, and so when we start thinking about user controls, particularly in this new environment with GDPR and some of the privacy standards that are coming out in the United States, you know, as we're building applications, or as we're building out the platform, design decisions need to be taken into account as far as, you know, what kind of a user is what age and how are we telling that people are telling that truthfully and how do we give them right to their data, or how do we give parents rights to their children's data in a way that's scalable, easy to understand, and really takes privacy to the forefront of us as a brand. >> Right, were there, I was wondering if you can share some of the stories of some of the trickier things that you guys had to work through that kind of give you an advantage because you've had to think thing. You know, like the whole parent, the whole parent-child relationship-- >> Yeah. >> Adds a completely different layer to just what is a user and what is a user ID. >> Yeah, I think one of the fascinating stories is with GDPR. It's kind of enabled us to really think through a lot of these tricky use cases, right? So, the Child Online Privacy Protection Act says that, you know, there's certain rules for children that are under 13. Well, so for GDPR you're able to make a subject access request for your own personal data. Well, at what point does a parent not have access to their child's data, is it at 13, is it at 18, and so thinking through those particular problem sets that as one of our customers ages up, because we'd like them to be lifelong customers-- >> Right, right. >> You know, how does their account change and how does their relationship with their parent account change along that journey. >> Right, so you got an interesting title, because you're an information security and data protection. >> Yeah. >> So, you've got both this explosion of data-- >> Yeah. >> That's coming in everyday that you do have to protect-- >> Absolutely. >> And make sure you got to keep on top of your AWS bill. >> Yep. >> At the same time you've got to bake the security in throughout the whole gamut. So, what are some of the things you're thinking about as you kind of plan for the future, other big roll-outs like Pokémon Go, that will make sure you're in a position to keep the data, mine the data, but not break the bank? >> Well, I think the first is this understanding that I think the future of information security is security and privacy, right? I think more and more people that are in my position are also going to be looked at in their organizations to make really due-diligent efforts at understanding what kind of data are we taking in, why are we taking in, what's the business justification, how long do we keep it, and really starting to think through and catalog that so that when our customers ask us the question, you know, "What kind of data do you have on me "and why are you keeping it for so long?" >> Right. >> We have a realistic answer, so that when a parent goes to let their child download one of our applications they know that they're downloading a safe space for their child to enjoy our brand. >> Right, it was GDPR for you guys just, "Oh, we've been there already." (laughs) You know, "We've been dealing with 13 year-olds "and kids and all these other kinds of regulations," or was that any type of a, kind of a game changer in the way you architect stuff, or is it more kind of compliance and regulation, and I guess the thing that I always crack up is the turn off, right? >> Right. >> Like if things are in a cloud, by rule they're nowhere, they're everywhere, right? >> Right. >> That great movie that came out years ago. >> Well, I mean, I think, you know, we had a headstart because we were already focused on child safety and protecting our data, but I think with a lot of companies, you know, you're still, there's so many policies you need to put in place and there are so many, you know, new ways you need to think about how that data's harvested and where it's going to live and visibility in all of your systems into that data. You know, honestly I think we were more 80% policy and 20% technical implementation because we kind of had that headstart, but 80% of policy is still a whole lot of policy. >> Right, right. >> But the way we think about it is GDPR wasn't a line in the sand, GDPR's just a new way of living, and that needs to be our privacy standard for our entire customer base, not just our European Union customers. >> Right, right. >> Because at the end of the day, it doesn't matter if you live in Berlin or you live in Nebraska, you want to make sure that your data's safe and your child's data's safe and you have that ownership. >> Right. >> And I think at the Pokémon Company we take that pride and ownership in letting our customers own their own data very seriously. At the end of the day, privacy is just as much of a product as one of our new applications. >> Interesting way to think about it. So, we're at Sumo Logic Illuminate. >> Yep. >> Tell us a little bit about your relationship with Sumo Logic, why did you choose to go with them, give us a little background there. >> Absolutely, you know, I think the day and age where a vendor-customer relationship is about the customer, you know, presenting their budget and then saying, "Give me stuff"-- >> Right. >> Is over, right? So, just as much as I want to make sure that we are in business with vendors that have a vested interest in seeing us be successful, you know, I think vendors now have a vested interest in making sure that they're doing business with customers that have that same in mind, so that means that, you know, my team needs to show up on time. My team needs to be prepared for meetings, and all those sorts of things, and to that end Sumo has been phenomenal, right? Everything from their engineers to their sales teams to their executive staff, you know, you really get the feeling that they are concerned with making sure that you're going to be successful as an organization-- >> Yeah. >> And that's why they're foundational to what we're going to be doing moving forward. >> You know, I'm just curious from your perspective as a buyer, since you used the word vendor-buyer relationship. You know, it's so interesting how the world has changed. Back in the old days, right, there was asynchronous information, the vendors had all the information. >> Yeah. >> And you had limited sources of information. Now you've got probably more sources of information and types of information than you can deal with-- >> Yeah. >> And by the time you actually talk to a vendor you probably have a pretty good idea of what they have and why it's going to be a fit. I'm just curious from your perspective, on the other hand you have a, just a flood, a sea, a tsunami of new things happening all the time. >> Yeah. >> New technologies, IoTs coming, 5G, how do you kind of sort it out, and I know what you're going to say. You know, how do you figure out who you want to work with tomorrow? >> Right, right, well, so because we're so invested in the cloud, you know, a big thing for us in ensuring that the companies that we do business with either are very much already doing cloud services or they have a plan in the very near future. What a lot of people don't realize is that a lot of these companies, they've been doing business for quite some time on-prem, and they might not have had a lot of customers yet that have been really progressive and moved all of their business into the cloud, and so the trick is finding the companies that have sort of that robust idea of, you know, customers are all going to be in the cloud someday-- >> Right. >> So, what are they doing right now to ensure that I'm going to be successful three years from now, and understanding our problems in terms of scale and all those sorts of things-- >> Yeah. >> And Sumo's been phenomenal in that respect. >> Well, I think such an underrated piece of a subscription-based economy is it forces you to have an ongoing relationship. >> Yep. >> It forces you to deliver value each and every month because you didn't just take the down payment-- >> Yeah. >> With a maintenance fee, you know. You're engaged and you want to grow that business together. >> Yeah, and I think transparency's key in that, right? So, they need to understand what our roadmap looks like just as much as I want to understand what their roadmap looks like. >> Right, all right. >> I think there's this tendency to try to keep everything secret because we are security professionals, but at the end of the day that's a losing battle. >> Right, right, all right, John. Well, thanks for taking a few minutes. I was going to ask you if you can share any secrets, but you probably can't share any secrets with us. (laughs) >> Just a lot of neat stuff coming on the horizon, absolutely. >> All right, all right, very good, and all packaged in small, yellow, furry bodies. >> For sure, for sure. (laughs) >> All right, all right, John. Well, thanks again, appreciate it. >> Yeah, it was a pleasure, thanks. >> All right, he's John, I'm Jeff, you're watching theCUBE. We're at Sumo Logic Illuminate 2018, thanks for watching.

(upbeat Techno music) >> Live from Las Vegas, it's theCUBE, covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE, we are live day two of VMworld in Las Vegas, Mandalay Bay. It's apparently very hot outside but we're in here getting all the exciting scoop. I'm Lisa Martin with my esteemed co-host John Furrier. Hey, John. >> Great to see you, welcome back to the set. >> Thank you so much. John and I are pleased to be joined by a Fortinet customer, Ken Busby, Keith Busby, excuse me, the executive director of information technology and security at the school district of Philadelphia. Keith, welcome to theCUBE. >> Thank you, thanks for having me. >> So, the school district of Philadelphia, eight largest public school district in the United States. You've got over 134,000 students. >> Yes. >> Over 18,000 staff. If only your IT budget was enormous, right? >> Yes. (laughing) >> So you guys, something also interesting, this morning Malala Yousafzai was speaking with Sanjay Poonen. Very intriguing, on the whole spirit of education, let's talk about that. You guys gave Chromebooks to over maybe half the students, about 50, 60 thousand? >> Well it's not one to one, so they're shared resources, they have carts throughout the school. We have between 50 or 60 thousand Chromebooks on our network right now. >> So I imagine great for the students and the education, the firewall security maybe a bit challenged? >> As we started transitioning to the Chromebooks, it overwhelmed our legacy internet firewalls so we had to go out and do proof of concepts and test multiple vendors. >> Talk about the security, we had Pat Gelsinger sit in theCUBE, I think four years ago, Dave Vellante, co-host, asked him, "Is security a do over?" And he's like, "Yes, it's a do over, "we need to do a do over." I said mulligan, used all kinds of terms, resetting. How have you guys set up your security architecture because I've heard stories of fishing attacks just to get the bandwidth to do Bitcoin mining, to crazy things on the security front. How are you guys laying out your network security? >> Honestly, it changes on a day to day basis, right? Because as new vulnerabilities come out, you always have to adjust your posture. Over the last year and a half we redesigned to wear we're not, we were routing through web proxies, we're required to do web filtering for the students by the CIPA, Children's Internet Protection Act. When we replaced our legacy firewalls, we were able to transition everything over to that and just use the Fortinet firewall to do web filtering, intrusion prevention, anti-virus and traditional firewalling. >> How virtualized are you guys? >> Pretty much completely virtual. We still have a few legacy physical servers but pretty much all. >> One of the things that came up in keynote, today was Sanjay Poonen but yesterday Pat Gelsinger, referred it to, was the bridging of the ways, connecting computers together but he mentioned BYOD, bring your own device as one of the ways and that was really the iPhone kind of generation. Obviously kids got Instagrams and they're on all kind of devices these days, how is that impacting your IT? Is it up and running, is it solid? What are some of the details? >> We don't have a traditional BYOD policy. It's more teachers get devices and they bring them in and we just have to find ways to support it so it stretches us, we're a small staff so we can't always help the end user with their devices so if they bring their own device, we have issues, they're trying to use applications that we can't support for whatever reason so it's an issue. >> Obviously all the devices that come in to the school in addition to the 60,000 Chromebooks, needing to rethink your security architecture, what were some of the technical requirements that you were looking for that made Fortinet the obvious choice? >> Performance and cost, right? As we spoke about, we have budget constraints. They have an extremely high performing firewall at a reasonable price. After we did proof of concept with five different vendors, and theirs just out performed them all. >> How about automation? A big talk in cloud is automation. How are you guys handling automation? Are you micro segmenting? >> We're transitioning to the NSX and Fortinet VMX for our server firewall. That's going to allow us, since we're short staff, if our server team stands up a new server my policies automatically take effect, just through the use of their security tags. >> That's the Fortigate product, right? The VMX? >> Yes. >> How is that working for you guys? >> We just did the proof of concept, we haven't transitioned our live systems over to it. But so far all our tests have shown that it does what we expect it to do. >> What's it like working in such a huge school district? I mean it's basically like, it's probably like a case study in campus wide networking. (laughing) >> We look at it as we're an ISP, right? Every school comes through us. We always say that we're protecting the internet from our students. We have smart kids and they-- >> They're digitally native. >> Yeah. They find ways to do things and then next thing you know I'm getting a report by a website saying, "Hey, we got students coming and throwing attacks at us." >> I was talking to a guy in higher ed about the bandwidth, they have huge bandwidth so obviously people game, including gaming centers, have all kinds of IP management issues. Fortnite's pretty hot, I'm sure how many people are playing Fortnite on your-- >> Luckily we don't allow that, right? (laughing) >> But this is what kids want to do. They're like born hackers. >> It is. >> They're curious. >> Yes. >> And it's good thing but you also want to basically make sure they're safe. >> Yes, that's pretty much what my job is. I want them to learn but at the same time, don't use it for malicious purposes. >> Yeah, its' true. One of the things I liked about public sector is cloud really makes things more efficient. >> It does. >> What are some of the things that you've seen with virtualization and with cloud kind of on the horizon, how has tech helped you guys be efficient and be lean and mean, kind of the 10X IT kind of guy thing? >> Like you said, lean and mean, right? We have a very small staff. The school district's budget is 3.2 billion dollars and IT's operating budget is 20.8 million dollars so as you can see, we really have to be cost effective and that's where virtualization comes into play. >> What's some cool tech that you like on the horizon? We hear a lot about SDWAN, sure that might be something that's cool for you guys? >> I like the VPCs, right? AWS, virtual private clouds, where you can set up your own network out there in Amazon's world, attach it to your vSphere so you can have on premise virtualization and out in the cloud, I think that. >> One of things that Pat Gelsinger talked about yesterday we hear this a lot John, is tech for good. I liked how he described it as it's essentially neutral, it's up to us, VMware, everybody else, to shape it for good. I imagine that's challenging? We talked about the Fortnite explosion, which I have only heard of but you've got so many devices, I imagine there's some amount of security gaps that are probably acceptable. In terms of reducing the maliciousness of some of the things that happen in there, tell us about some of the things that you're achieving there, leveraging such things as the automation, how is that helping you guys to enable the Chromebooks and the BYOD for good? >> Well the automation frees up our time so that we can focus on the policies, the education, the different procedures for the district. This way we're not spending time hitting the keyboard, trying to review our traffic logs. >> You had a session yesterday which you were talking, a breakout session, and you were saying that there were some folks that were so interested in what you we had to say, you had limited time in your session. Give a little bit of an idea of some of the feedback or maybe even people that might be in your similar situation that want to learn from, hey, how did you guys tackle this huge problem? >> They were from a school district in Nebraska and they wanted to see how we were handling and they just became a Fortinet customer and they wanted to see what trials and tribulations we had implementing their equipment, any lessons learned and kind of, we just had a conversation about where we see our programs going. It was nice. >> What about compliance? One of the things that's come up is managing the laws of the land. >> Luckily, I don't have much compliance, right? So we're not PCI, CIPA's pretty much, and FERPA but the only reports that we really have to provide are for CIPA, we'll have to prove that we're doing web filtering. That's where the Fortinet analyzer comes into play. I'm able to just schedule the reports through there. Shows that I'm blocking based on categorization, and we're good. >> What's the biggest thing you've learned over the past couple years in tech and IT to be effective and to do your job, what's the learnings? (laughing) >> It's going to sound weird coming from a security guy but I think it's important to take the risk, right? Accept the risk. Most organizations won't try a piece of equipment live, right? I was the exact opposite, I put every firewall that we were going to try live and pushed our entire network through it. I mean, if it breaks some things, we figured it out but I think that's the only way to get a true test of whether or not it's going to fit your needs. >> One of the things that came up yesterday, I interviewed Andy Bechtolsheim, you know, legend, been called the Rembrandt of chips, Pat Gelsinger called him that down to Arista and other companies. He talked about how NSX has the security wrapped around the application, more around NSX, that's freed up his security teams from handling a lot of the network security which kind of like has been intertwined in the past. Are you seeing that same picture emerge? >> That's why I'm transitioning to that, to get out of the traditional IP base firewall rules. It's not really what it was designed for, it was more for a transport layer. So switching over to the NSX and the BMX, now we're basing it on the application, what it's purpose is. >> What's the impact to you guys? What's that mean for your operations and your benefits for staff, what's the impact? >> It frees us up. During the winter months when we're going to have a snow storm, our server team might have to deploy some more web servers to handle the traffic that's going to come in. Before they would have to reach out to my team, to get us to modify a policy because they have new device coming online, well now they just tag it as a web server and it's automatically in the roles. >> You know I love talking about this topic. I have four kids, two of them are still in high school, two are in college, so it's so funny how they all hacked their report cards because the sandbox was out there for testing the new curriculum so they all get it and they all share it and the school sends out a note, "Well, that's not actually officially updated yet." So the kids are smart, like you said, they're going to get what a sandbox is. They don't know why it's there, they know how to get to it, so you got student elections, all kinds of things that go on in the academic world that have been digitized that are vulnerable, you have to handle that. How do you stay on top, does Fortinet help you there? Or what's the main way to keep the secure access? >> I mean that's why we're going with the VMX, NSX, the micro segmentation, it really takes the effort off of us and allows the appliances to do what they're intended to do. >> That's awesome, well it's a great case study. Any advice for practitioners out there who are in your seat in their world who might be looking at, okay I got to reset, I got to start rethinking things, I got to do more with less, I got to be lean and mean? It's kind of command and control but you got to manage it, you got a lot going on, it's the battlefield of IT is changing. >> Yes. >> So what's your advice? >> Take the risk. (laughing) Try it out. I just recently hired another engineer and on his first day I pretty much told him, "Go ahead and break something, it's alright, "we'll figure it out, we'll fix it." He has his own little lab and I'm like, "Just go mess around and figure it out." >> Play, do some R and D. >> Yeah. >> Kick the tires, yeah, it's the best way to do it. Keith, thanks so much for coming on theCUBE, really appreciate it. It's theCUBE live here in Las Vegas, stick with us for more coverage after this short break. (upbeat techno music)

(inspirational music) - So GDPR, the General Data Protection Regulation was passed by the EU in 2016, in May of 2016. It is, as Ronald was saying it's four base things. The right to privacy, the right to be forgotten, privacy built into systems by default, and the right to data transfer. - [Panelist] Takes effect next year. - It is already in effect. GDPR took effect in May of 2016. The enforcement penalties take place the 25th of May 2018. Now here's where there's two things on the penalty side that are important for everyone to know. Number one. GDPR is extra territorial. Which means that any EU citizen anywhere on the planet has GDPR goes with them. So say you are a pizza shop in Nebraska. An EU citizen walks in, orders a pizza, gives the credit card, stuff like that. If you for some reason destroy that data, GDPR now applies to you Mr. Pizza Shop, whether or not you do business in the EU, because an EU citizens data is with you. It's true, the penalties are much different than they ever have been. In the old days companies could simply write off penalties as saying that's cost of doing business. With GDPR the penalties are up to 4% of your annual revenue or 20 million euros, which ever is greater, and there may be criminal sanctions against, charges against key company executives. So there's a lot of questions about how this is going to be implemented. But one of the first impacts you will see from a marketing perspective is, all the advertising we do, targeting people by their age, by their personal identifiable information, by their demographics, between now and May 25th 2018 a good chunk of that may have to go away because we may not, there's no way for you to say well this person's an EU citizen this person's not. People give false information all the time online. So how do you differentiate every company regardless whether they are in the EU or not will have to adapt to it. Or deal with the penalties. - When you think about the principles that GDPR gives you, I look at that and think that's just, to me that's just good data management practices and principles. It happens to be around personal data for GDPR right now, but those principles are just valley for probably kind of any kind of data. So if you're on the digital transformation journey, with all the change and all the opportunity that brings, these practices and principles for GDPR, they should be helping drive things like your digital transformation. For a lot of our customers, change is the only constant they've got, especially managing all this whilst everything is changing around you. It's tough for a lot of them. - How are people thinking about the data layer, where it lives, on prem, in the cloud, think about GDPR compliance, you know all that sort of good stuff. How are you and Red Hat, how are you asking people to think about that? - So, you know, data management is a big question. We build storage tooling. We understand how to put the bytes on disk, and persist and maintain the storage. It's a different question what are the data services and what is the data governance or policy around placement. And, I think it's a really interesting part of the ecosystem today. We've been working with some research partners in the Massachusets open cloud at Boston University on a project called Cloud Dataverse. And it has a whole policy question around data. It's there, scientists want to share data sets, to control and understand who you're sharing your data sets with. So its definitely a space that we are interested in. Understand that there's a lot of work to be done there, and GDPR just kind of shines the light right on it. Says, policy and governance around where data is placed is actually fundamental and important. And I think it's an important part because you have seen some of the data issues recently in the news. And, we got to get a handle on where data goes, and ultimately I'd love to see a place where I'm in control of how my data is shared with the rest of the world. - GDPR provides for two types of things that a business must do. It must provide insight into the data that it's captured, about business or an individual, legal entity. And it must also then provide the processes for mediating or taking action against that data according to whatever the customers virtues are. Tell us a little bit about that. - So these are two important features because of GDPR. First thing GDPR has 99 articles and 173 articles and 99 like term technological ways. There are other ways, legal ways to do it, but technologically what they want. Like if Peter decides, that I need to know from this bank or from this social media company how much information you have about me, and what are you doing with it. They have to provide that information in 30 days. That is called right to access. And the second thing is you can come and say, well I'm not using these five things which you sold me earlier I don't want you to use that information, or even have information on that for me or my son or my kid. So you can tell them delete that information or mask that. - And that's call the right to? - Right to erasure, right to remove the data. And these two things are very important. This gives customer, they make customer the king. They make the individual the king. He can say tell me what you have on me, and delete what you have on me. - Now the laws have been in the books in, at least in the EU for GDPR for a while. But the fines start getting leveled in May. - May 5th. - Now we've heard that... - So GDPR is a big thing for us and our customers and prospects as well. So we are actively working on getting GDPR compliant. Today our platform is FIPS compliance, so that's already a big stepping stone to getting there. So we look at GDPR in one of, in two ways again, right? One is the solution that we provide to our customers, the data platform and the data protect as we call it. Being GDPR complaint. Meaning the data that lands on that system. The ability to delete the data, the ability to say who has access to the data, rules based taxes, things like that. The second aspect is, our support and the fact that we have access to a lot of customer information ourselves, right? The fact that we can look at their systems and make sure that, everything we do internally is also GDPR compliant, so that the customers and our support systems and our sales force database is all GDPR as well. So both those elements come into play and we are actively working on all of them. (inspirational music)

>> Hello and welcome to a special CUBE Conversation. I'm John Furrier, the co-founder of SiliconANGLE on theCUBE. We're here in Sundance 2018 at the Intel Tech Lounge for a panel discussion with experts on the topic of The New Creative. We believe a new creative renaissance is coming in application development and also artistry. The role of craft and the role of technology and software coming together at the intersection. You're seeing results in the gaming industry. Virtual reality, augmented reality, mixed reality. A new wave is coming and it's really inspiring, but also there's a few thought leaders at the front end of this big wave setting the trends and they're here with us in this special panel for The New Creative. Here with us is Brooks Browne, Global Director of VR at Starbreeze Studios, a lot to share there, welcome to the panel. Lisa Watt, VR Marketing Strategist at Intel, Intel powering a lot of these VR games here. And Winslow Porter, co-founder and director of The New Reality Company. Many submissions at Sundance. Not this year, but a ton of experience talk about the role of Sundance and artistry. And then we have Gary Radburn who's a director of commercial VR and AR from media within Dell, Dell Technologies. Guys, welcome to this panel. Lisa, I want to start off with you at Intel. Obviously the Tech Lounge here, phenomenal location on Main Street in Sundance. Really drawing a massive crowd. Yesterday it was packed. This is a new generation here and you're seeing a younger demographic. You're seeing savvier consumers. They love tech, but interesting Sundance is turning into kind of an artistry tech show and the game is changing, your thoughts on this new creative. >> Yeah, it's been amazing to watch. I've been here for, this is my third year coming back with VR experiences. And it's really just been incredible to see. Sundance has been on the leading edge of exploring new technologies for a long time and I think this is, I feel like you know this feels like the break out year really. I mean, it's been successful the last few years, but something about this year feels a little bit different. And I think maybe it's the people are getting more familiar with the technology. I think the artists are getting more comfortable with how to push the boundaries. And then we certainly are getting a lot out of seeing what they're doing and how we can improve our products in the future. >> We were talking yesterday, Lisa, about the dynamic at Sundance. And you were mentioning that you see a few trends popping out. What is the most important story this year for the folks who couldn't make it, who might be watching this video that you see at Sundance? Obviously it's a great day today, it's snowing, it's a white day, it's beautiful powder, greatest snow on Earth. But there's some trends that are emerging. We had a march this morning, the Women's March. You're seeing interesting signals. What's your view? >> I think there's a lot less desire to put up with subpar experiences. I mean I think everyone is really starting to push the boundaries, I mean, we saw a lot of 360 video which we love for a linear narrative. But they're really breaking out and really exploring what does it mean to have autonomy especially in the virtual reality experiences, a lot more social is coming to the forefront. And then a lot more exploration of haptics and the new ways of extending into more 4D effects, etc. So I think it's very very exciting. We're really excited to see all the new innovations. >> Winslow, I want to ask you, if you can comment, you've been an active participant in the community with submissions here at Sundance. This year you're kind of chilling out, hanging out. You've been on the front lines, what is your take on the vibe? What's the sentiment out there? Because you're seeing the wave coming, we're feeling it. It feels early. I don't know how early it is, and the impact to people doing great creative work. What's that take? >> Well yeah, it's kind of like VR years are like dog years, you know. Like a lot can happen in a month in the VR space. So I had a piece here in 2014 called Clouds. It was an interactive documentary about Creative Code, but that was back when there was only two other VR pieces. It's interesting to see how the landscape has changed. Because CCP Games had a piece there. An early version of E Valkyrie. And unfortunately in the last three months, they had to close their VR wing. So, and then Chris Milk also had a Lincoln piece with Beck. Which was a multi camera 360, actually it was a flash video that they recorded to the DK1. And so that was, seeing that everyone was, saw the potential. The technology was still pretty rudimentary or crude even, we should say. Before any tracking cameras. But every year people learned from previous Sundances and other festivals. And we're seeing that Sundance kind of raises the bar every year. It's nice that it's in January because then there's all these other festivals that sort of follow through with either similar content, newer versions of content that's here, or people have just sort of learned from what is here. >> So I got to ask you. You know, obviously Sundance is known for pushing the boundaries. You see a lot of creative range. You see a lot of different stuff. And also you mentioned the VR. We've seen some failures, you've seen some successes, but that's growth. This market has to have some failures. Failures create opportunities to folks who are reiterating in that. What are some of the things that you can point to that are a positive? Things that have happened whether they're failures and/or successes, that folks can learn from? >> Well, I think that this year there's a lot more social VR. We're connecting people. Even though they're in the same space, they're able to be in this new virtual world together. There's something amazing about being able to interact with people in real life. But as soon as you have sort of a hyper reality where people are able to be experiencing a Sufi ritual together. Things that you wouldn't normally... That they're not possible in the real world. And also, I think that there's issues with lines too. Obviously every year, but the more that we can have larger experiences with multiple people, the more people we can get through. And then more impact we can make on the audience. It's really... We were in claim jumper last year. And we could only get one person in every 10 minutes. And that makes things pretty tricky. >> And what are you doing at Sundance this year? You've obviously got some stuff going on with some of the work you've done. What's your focus? >> So yeah we have a company called New Reality Company where we produce Giant and Tree. It's part of a trilogy where Breathe is going to be the third part. We're going to be completing that by the end of this year. And right now, I would say the best thing about Sundance is the projects, but also the people. Being able to come here, check in, meet new people, see partners that we've been working with in the past. Also new collaborations, everywhere you turn, there's amazing possibilities abound. >> I want to talk about empathy and social. I mentioned social's interesting in these trends. I want to go to Brooks Brown, who's got some really interesting work with Starbreeze and the Hero project. You know, being a pioneer, you've got to take a few arrows in your back, you've got to blow peoples' minds. You're doing some pretty amazing work. You're in the front lines as well. What's the experience that you're seeing? Talk about your project and its impact. >> Well for us, we set out with our partner's ink stories, Navid Khonsari, a wonderful creative, and his entire team to try to create that intensely personal experience kind of moving the opposite direction of these very much social things. The goal, ultimately being to try to put a person inside of an event rather than a game style situation where you have objective A, B, or C. Or a film that's a very, very hyper linear narrative. What is that sort of middle ground that VR itself has as unique medium? So we built out our entire piece. Deep 4D effects, everything is actually physically built out so you have that tactility as you walk around. Things react to you. We have smell, temperature, air movement, the audio provided by our partners at DTS is exceptional. And the goal is ultimately to see if we put you in a situation... I'm doing my best not to talk about what that situation is. It's pretty important to that. But to watch people react. And the core concept is would you be a hero? All over the world, every day people are going through horrific stuff. We're fortunate because we're the kind of people who, in order to experience, say a tragedy in Syria, we're fortunate that we have to go to Park City, Utah and go in virtual reality to experience something that is tragic, real, and deeply emotional. And so our goal is to put people through that and come out of it changed. Traumatized actually. So that way you have a little bit more empathy into the real world into the actual experiences they went through. >> And what's the goal? This is interesting because most of the some stuff you see, the sizzle out there is look at the beautiful vistas and the beaches and the peaks and you can almost be there. Now you're taking a different approach of putting people in situations that probe some emotional responses. >> Yeah. It's a big deal to us. The way Navid like to put it, and I'm going to steal this from him, is you see a great deal of people prototyping on hardware and all of these things, and it's great cause we need that. We need to be able to stand on the shoulders of those giants to be able to do these things. But you see very few people really prototyping what is the concept of story as per VR? We've been doing, at Starbreeze, we've been doing location based for some time now and I've been getting thousands upon thousands of pitches. And whenever you get a pitch, you can pretty much identify, oh you come from a film background, you come from a games background. There's very few people who come down that middle line and go, well this is what VR is supposed to be. This is that interesting thing that makes it very deeply unique. >> What's the confluence and what's the trend in your mind as this changes? Cause you mentioned that gamers have affinity towards VR. We were talking about that before we came on the panel. You know, pump someone in mainstream USA or around the world who does email, does work, may not be there, you're seeing this confluence. How is that culture shifting? How do you see that? Cause you're bringing a whole nother dimension. >> We're trying to go back to a little bit, something about this Sundance being a little bit different. I think in general in VR, you're seeing this sort of shift from a few years ago it was all potentiality. And I think a lot of us, the projects were great, but a lot of us who work in VR were like oh I see what they're trying to do. And people like my dad would be like I don't. I don't see what they're trying to do. But that is shifting. And you're seeing a larger shift into that actuality where we're not quite there yet where we can talk about the experiences every day Americans are going to have. What is the real ready player one that we're actually going to have existing. We're not there yet, but we're much closer every time. And we're starting to see a lot of these things that are pushing towards that. Final question before I go to some of the speeds and feeds questions I want to get with Intel and Dell on is what is the biggest impact that you're seeing with your project and VR in general that will have the most important consequences for societal impact? >> Well, we were fortunate yesterday we had a number of people come through Hero. And a number of them simply actually couldn't handle it. Had to come out. We had to pull people out. The moment we took the headset off, they were, tears were streaming down their face. There's a level of emotional impact VR is extremely able to cut through. It's not that you're playing a character. It's not that you're in a separate world. You are you inside of that space. And that is a dangerous but very promising ability of VR. >> Winslow, could you take a stab at that, I'd like to get your reaction to that because people are trying to figure out the societal impact in a positive way and potentially negative. >> Yeah I mean, so with that, whenever you traumatize somebody else or have the ability to possibly re-traumatize somebody... In Giant, we made sure that we gave them a trigger warning because yeah these things can be intensely intimate or personal for somebody who already has that sort of baggage with them or could be living in a similar experience. In Giant, we witnessed the last moments of a family. As they're convincing their daughter that the approaching bomb blast is a giant that actually wants to play with her. And so we put haptics in the chair so the audience was also surprised. But we let them know that it was going to be taking place in a conflict zone. So if that was something that they didn't want to participate in, that they could opt out. But again, like we didn't know... We had to go and buy tissues like right off the bat because people were crying in the headset. And that's kind of a... It's an interesting problem to have for the sake of what are sort of the rules around that? But also it makes it more difficult to get people through the experience in a timely fashion as well. But yeah, but we're seeing that as things become more real then there's also a chance to possibly impact people. It's the... >> So it's social for you? You see it as a social impact? >> Well, I mean if everyone's experiencing the same thing that can be social, but again if it's a one on one experience, it's sort of like up to the filmmaker to make sure that they have the scruples that they are playing by the rules. Cause there's right now most every piece of content is being released through Oculus, Steam, or Viveport. But there will be... It's heavily regulated right now, but as soon as there's other means of distributing the content, it could take a different sort of face. >> Certainly some exciting things to grab on, great stuff. I want to get to the commercial angle. Then we're going to talk more about the craft and the role of artistry in the creating side of it. Gary, you're the commercial VR expert at Dell. You're commercializing this. You're making the faster machines. We want faster everything. I mean everyone... Anyone who's in VR knows that all the graphics cards. They know the speeds and feeds. They're totally hardware nerds. What's going on? Where's the action? >> Okay, that's such a large question. I mean we've had some great stuff here that I also want to comment on as well. But inside the commercial side, then yeah everybody wants bigger, stronger, better, faster. And to Winslow's comment about the dog years, that really puts the pressure on us to continue that innovation and working with partners like Intel to get those faster processors in there. Get faster graphics cards in there so that we can get people more emotionally bought in. We can do better textures, we can get more immersion inside the content itself. We're working a lot around VR in terms of opening peoples' eyes for societal impact. So VR for good for instance. Where we're taking people to far flung corners of the Earth. We work with Nat Geo explorer Mike Libecki to show the plight of polar bears in Greenland and how they're gradually becoming extinct for an edutainment and a learning tool. The boundaries are really being pushed in entertainment and film. That's always been the case. Consumer has always really pushed that technology. Commercial's always been a bit of a lagger. They want stability in what's going on. But the creation that's going on here is absolutely fantastic. It's taken what is essentially a prosumer headset and then taking it into that commercial world and lit it up. 360 video, its very inception, people are using it for training inside of their businesses and so that's now going out into businesses now. We're starting to see advances in 360 video with more compute power needed. Where, to the point about immersion and getting people emotionally bought in. Then you can start doing volumetric, getting them in there. And then we're also working with people like Dr. Skip Rizzo who was on our panel yesterday where we're starting to go into, okay, we can treat PTSD. Help people with autism, through the medium of VR. So again, that buys into... >> These are disruptive use cases that are legit? >> Yeah. >> These are big time, market moving, helping people... >> Absolutely. And that where it becomes really, really powerful. Yes, we want our companies to embrace it. Companies are embracing it for training. But when you start seeing the healthcare implications and people crying inside of headsets. That's effecting you deeply, emotionally. If you can make that for good, and change somebody's trigger points inside of PTSD, and the autism side of helping somebody in interview techniques to be able to be more self sufficient, it's absolutely awesome. >> This is the new creative. So what's your take on the new creative? What's your definition? Cause you're talking about a big range of use cases beyond just film making and digital artistry. >> Yeah, absolutely so the new creative is like with all the great work that's here, people are looking at film and entertainment. Now the world really is the oyster for all the creatives out there. People are clamoring out for modelers, artists, story tellers, story experiencers to be able to use that inside their commercial environments to make their businesses more effective. But they're not going to have a 360 video production company inside of their commercial organization. And it's then leveraging all of the creative here and all of the great stuff here. Which is really going to help the whole world a lot. >> Lisa, I want to get your thoughts on this cause you guys at Intel here at the Tech Lounge have a variety of demos, but there's a range of pro and entry level tools that can get someone up and running quickly to pro. And so there's a creative range not only just for digital artistry, but also business we're hearing. So what's the... Cause AI's involved in a lot of this too though. It's not just AI, it's a lot of these things. What's the Intel take on this. >> Well I think it's really an interesting time for us at Intel because one of the things that we have that I think probably nobody else has. We have this amazing slate of products that really cover the end to end process. Both from the creation side of the house all the way to the consumption side. And we talk a lot about our processors. We worked on an amazing project, a couple of huge scenes inside of the Sansar environment. Which is a great tool for really democratizing the creation of spaces. It's a cloud hosted service but it utilizes this amazing client-server architecture. We created four huge spaces in a matter of eight weeks to launch at CES. And some of the technologies that Gary was referring to just in pure processing power like two generations old processors were taking three hours to render just a small portion of a model where our newest generation Core i9s with our opting technology took that time to 15 minutes. So when we think about what we can do now, and those technologies are going to be available in even portable laptop form factors. We've got the piece where we were working here SPHERES. They were able to actually make some corrections and some tweaks basically immediately without having to send them off to some render farm. They were able to do those things. And I know Winslow has talked about that as well. What does it mean to you to be able to react real time. And be able to do your creative craft where you are and then be able to share that so readily. And then you know... I just think that's kind of an amazing equalizer. It's really democratizing the creation process. >> Okay the next question that begs for everyone to address is where are we in this progression? Early? What work needs to get done? Where are we holding back? Is it speeds and feeds? Is it the software? Is it the routines, libraries, art? Where's the bottleneck? Why isn't it going faster? Or is it going faster? >> I would, and I'm sure the team would agree here, I would say that one of the key things is the creator tools themselves, right. They are still somewhat cumbersome. We were talking to another filmmaker. He was like I can't even, I have to play the whole piece from the beginning, I can't just go in and edit, you know change control, being able to collaborate on these pieces with other people. I mean, if you can collaborate in a real world space, you should be able to also collaborate in VR and have change control and all those sorts of things that are necessary to the iteration of a project. So we're trying to work with our software partners. They're all doing a really great job of trying to iterate that, but it's going to take some time. I mean I think that's probably the bigger thing that's holding everything back. We're going to be right there with the processing power and the other technologies that we bring to the table. OEM partners are going to be right there with the best devices. I really think it's something we've all got to push for as far as those tools getting better. >> Brooks, comment on anything? You're in the... >> So for me, the thing that's holding back VR in general is actually the art form itself. One of the great challenges, if you look back, at say the history of film... We're at Sundance, so it's probably fairly apropo. Very early on in the early movies, aside from penny arcade machines that you'd actually stare at, they were 10 minute almost like plays that people would go to almost a playhouse and they'd watch this thing. There were not cuts, there were no angles. It was a single wide shot. Great Train Robbery came around and there was this crazy thing they did called an edit. Where they spliced film together. And if you go back and you read, and they did these dolly shots. People will have no idea what they're watching. There's no way people will be able to follow that. Like people were not happy with it at the time. Now it's stuff that children do on their iMacs at home. They do iMacs all the time, they do it on their iPhones, on their Android devices. These are normal languages of film that we have. VR doesn't have that yet. And there's not a great deal of effort being made in that direction. There's people here doing that. So I'm kind of speaking in the middle of the group, but outside of these people, there's only a handful who are really doing that and it's a significant challenge. When people who are the mainstream consumer put on a VR headset, it needs to be more than just a magic trick where they go oh that's cool. And that tends to be the vast majority of experiences. So what is the thing that is going to make someone go oh I get why we have VR as a medium. And we're not there yet. We're in the direction, but that's >> So you mentioned earlier the point where you can tell if someone's from film or gaming or whatever when you talk to them about VR. Who is the future VR developer? Is it a filmmaker? Is it a gamer? Is it a digital artist? What is this evolving? >> It's a kid in his basement who no one knows and is screwing around with it and is going to do something that everyone thinks is stupid. Like, it's going to be that. Basically every major leap in gaming is kind of the same thing. It's when we understand how ludonarrative dissonance works inside of telling how people move around a space. It's about how we do Dutch angle suddenly in film. And these things get invented. It's going to be some kid who's just screwing around who doesn't have the baggage of the language of film. A lot of the people I know in VR have been fortunate to work in film, in games and interactive or web dev. So you come from a lot of places but someone's going to come along who has none of that baggage. And they're going to be... >> Well you guys are pioneers and you're doing it. So for the first person out there that's in their basement, that inspirational soundbite or comment. How can you guys talk to that person or that group? Because this is the democratization, this is what's happening. It's not the gatekeepers. It's real creatives out there that could come from anywhere. YouTube generation, Twitch generation, gaming. What would you say to that person to motivate them and to give them that passion? >> Well it's only going to get easier, faster, cheaper, all these things are happening. But again, yeah I totally agree with what Brooks said. It's really about the culture and about educating the audience and getting them up to speed. There are some VR experiences that as soon as they put on the headset, like somebody who's never done it before, immediately will take it off cause they'll get nauseated. And then there's people, like kids who are like jet fighters. They've seen everything. You could throw like a 30 frames per second experience at them and that doesn't even phase them. They can be, all of a sudden their worlds are changing and they're like bring it because they're ready for that. So I think it's sort of about raising the bar for what the audience is comfortable with, familiar with, educating the community. There's a lot of tools right now, you know with Unreal and Unity that allow people who have very little... They don't need to know C# or C++, they can get started in a lot of like visual. What you see is what you get. Being able to drag things into a virtual room. And the windows headsets that are out. They refer to them as mixed reality, but just even having the ability to flip up the screen and transition from the virtual world to the real world in milliseconds, it allows you to be able to create things more at the speed of thought instead of coming up with an idea, coding it, and making sure it works, and then eventually putting on the headset. The sooner that we can actually be ideating inside this virtual environment is when things will get really interesting. >> So the next question is to take to the next level is what's the playbook? How does someone get involved? How does someone ingratiate into a community? If I'm an artist, I want to get, and I'm proficient with technology, or maybe not, how do they get involved? Is it community driven? Is it social? You guys mentioned seeing social's a big trend here. How do people get involved? What's the track? >> Well yeah you don't just need to go to a grad school or... There's a lot of programs out there that are popping up. Almost every single major state school has like an interactive art program now. And that wasn't the case like two or three years ago. So we're seeing that that's a big shift in the culture. But again, VR is still... It's expensive and it's you know, like VR, I refer to it's in the stage of it's almost like in the neo geo phase, maybe a little before that. But it's the really expensive thing that your friend's neighbor has. Or his older brother or something. You get to play it a little bit, you're like that's great but there's no way in hell I'm going to... You know, I can't afford that or like that just doesn't really work with my lifestyle right now so it needs to incorporate itself into our everyday, our habits. And it needs to be something that... If we're all doing it then it makes sense for us to do it together not just somebody in their basement doing it by themselves. >> Yeah feel free to comment, this is a good topic. >> Oh yeah, absolutely. So what we're doing is sort of about democratization and accessibility. So for people to get into the then they're going to need a rig, they're going to need a headset and previously it's actually been quite expensive to actually take that first plunge into it. So now by democratizing and bringing price points down, it makes it more accessible. That helps content creators because there's now more of an audience that can now consume that content. And the people that can then play with the medium and consume it now have a better reason to do it. So we're working on that. We're also working on the education pieces like Key. It's actually going out there to schools and actually letting them experience VR and play with VR. Because it is a whole new different medium. We've seen film directors and filmmakers go into the VR space and things that worked in 2D film like fast pans and whatever else so the points have already been made don't really translate into VR without somebody losing their lunch. So it is going to be somebody who's coming up who hasn't got the baggage of previous skill sets inside of 2D doing it inside of VR. So we're going to see that. And in terms of the technology, everybody's wanting things to progress. That shows the level of excitement out there. And everybody wants to get into it. Everybody wants to see it go further. And I'm reminded of the mobile phone. Mobile phone, 30 years ago? Two suitcases for batteries, a large brick on the ear and a car antennae. Okay, so where we are now, if you had a time machine and you went back in time to talk to the inventor of the mobile phone, well, I'd be a lot richer because I know sports results and all, but that aside, but you go back and talk to them and you said do you know in 30 years time, everybody is going to be carrying that device? Everybody's going to be dependent on that device? They're going to get social anxiety and separation anxiety if they lose it. And they will probably laugh in your face. >> Alright so since you brought up the phone analogy, since I love that example, are we in the Blackberry moment of VR and no one yet has built the iPhone? Because the iPhone was the seminal moment for smartphones. And you see what happened there. Is VR needing that kind of break? Or is it there? >> I think we're on the cusp. Where we are at the moment with technology, we've had the headsets, which I say have been more in the consumer space, they've been designed to hit a certain price point. We had CES the other week where we've had advancements now in the resolutions of headset that are now coming out. One of the issues was well I can't see texts, I can't read texts. So from a working environment, if you're actually using tools that you would normally use on a 2D screen, you can now translate that and read that text. However, in terms of the tools that people use, why are we trying to put 2D screens into a VR headset? We've got a whole new way of interacting with data. We've got a whole new way of doing things that are going to be more intuitive than the mouse and keyboard interaction that we're used to. Why just translate that. Let's push that envelope and those are the developments that we're pushing our partners and our ISVs to really embrace. >> So it's an evoution. >> It's absolutely an evolution. >> You guys have any thoughts on that comment. That we have that inflection point, are we hitting that, will we see it soon, is it here? >> Well I think it's a very interesting symbiotic relationship between multiple factors. So you know, we hear the cost factor, we hear the technology factor, then we have the content factor. You know I saw an interesting evolution at CES we had created this virtual booth experience so that you could still come to the CES Intel booth without actually having to be there. And I met a guy in there and I was like hey where are you? He goes I've been in here like all week. (laughter) And I was like oh yeah, where do you live? He goes oh I'm in my basement in Nebraska. But he had just, this was Friday when I met him. He'd been in there all week, but in 2D mode. And he had gone out the night before and bought a headset just so he could come back and go in VR mode. And I think, yes, all these factors have to kind of line up, but I do think that content, those experiences that are going to keep people coming back for more. Like these guys literally kept coming back to our booth. Right, to see... >> Content gain. >> To see who was there. And to them at that point, it wasn't really a barrier of cost. It was like there is something that I want to consume therefore I am going to go get what I need to consume it. And I use the analogy of HDTV, right. When we kind of moved over that hump where there was enough content people didn't really care how much that television cost. >> Sports was great. Sports really highlighted HD. >> Yeah. >> But this is a good point. This is a good question to ask. Brooks, I'd love to get your thoughts. Content drives experiences, amazing experiences, but we're building the scaffolding of everything at the same time. So where are we, what's your opinion? >> So here on the Starbreeze side, we're fortunate because we have our own headset. We have the StarVR headset we've been building with Acer. 5K all of that stuff and we're upgrading it over the next year. Our focus has been, we skipped the consumer market very much. We went straight to location based and enterprise. And the reason we did that is because there's a promise of VR at a basic, I don't want to say technology stand point, but from an experience perspective, when it comes to that resolution, when it comes to that field of view, when it comes to these things people expect. Average consumers who go to a movie and they see these giant screens. They want that translated. They don't have the understanding like we do of well, LED panels are actually a pain in the ass to build and it takes a little bit and they flip at their own speeds. Time to photon is not a thing my dad will ever see in his life. But there's a reality that people have a need for that. And it is extremely expensive. It's again the reason we went straight to LBE. But for us it's about marrying the two and consistently trying to match what's happening. So when we're talking about, as I mentioned earlier the technology and how we're standing on the shoulders of giants very very quickly, someone who's doing technology is going to see what we're doing content wise and go well I can do that better technology wise. And then we're just going to keep leap frogging. And it's very similar to the phone in the same way that we're not at the final stage of the phone. Like we're at our stage of the phone and no doubt in 30 years people will laugh at us for carrying anything. The same way we laugh about the briefcases and the giant batteries in the cars we had to pull with us. So it's one of those things that's continually transitional. And VR's in an odd, amazing place. >> Well you know, it was a lot of waves that we've all seen. You mentioned the mobile phone, that's a good one to point to. It feels like the PC revolution to me because the same culture of entrepreneurs and pioneers come from a bunch of different backgrounds. So I'd like to get Brooks perspective and Winslow's perspective on this because I think there's an entrepreneurial culture out there right now that's just emerging very fast. It's not like your classic entrepreneur software developer. So in this movement, in this wave, the entrepreneur is the filmmaker, it could be the kid in the basement, could be the gamer. Those entrepreneurs are trying to find a path. >> Yeah, it's a weird mix. VR is at this odd point where not only is it the people who are wanting to be cutting edge in terms of content or technology, but also that first mover strategy from the business side of things. And so everyone wants to be those guys who are charging ahead because in reality, if you look at the financials around all of this, VR is one of those things that you don't want to finance. It's not nearly as safe as say Marvel Avengers or the next Call of Duty. >> You've got to be, you've got to hustle. >> Yeah you've got to hustle. You've got to make... >> What's your advice? >> Start doing it. That's really it. It's the same advice I used to give to game makers when people would be like well I want to learn how to make games. It's like go to YouTube, download a thing and go do it. There's literally no reason why you can't. >> Are there meetups or like the Homebrew Computer Club that spawned the Mac. >> There are, there are infinite groups of VR people who are more than happy to give you all the terrible and wonderful opinions that come with that. There's no shortage of people. There's no shortage and it's an amazingly helpful group. Because everyone wants someone else to figure out something so they can steal that and then figure out something else. >> Winslow, your advice to entrepreneurs out there that are young and/or 14 to 50, what should they do? Jump right in obviously is a good one. >> Well yeah, experiment, break things, that's really the only way to learn. I would say watch as much VR as you can because sometimes bad VR is the best VR. Because you can learn don't do that. And if you learn, if you put all that together, you can really... It's like this lexicon that you can really follow. Also, I think we... As people in tech, we kind of get obsessed with things like resolution, frame rate, and these are very important, but it's also good to remember, or at least for me, I watch some of the best experiences from storytelling when I was a kid, eight years old on a 12 inch screen that was 640 by 480. You know, like scan lines on the VHS. But for me the story still resonated and it's important to think of story first, but obviously it's a dance between the story and the technology. They kind of have to both organically work together. And if they don't, one thing in the story that doesn't work because the tech isn't supporting it, can throw you out of the experience. >> Other concern entrepreneurs might have is financing. How do I get someone to help me build it? And then doing relationships. Finding relationships that could... One plus one equals more than two, right. So how do you? >> You have to get really creative when it comes to funding right now. Unless you're doing location based, which also requires a certain amount of investment to get it up to a bar where you want to be showing it to people with all the haptic effects when it's heat, smell, vibration, stuff like that. You know, it's not cheap to develop. But as far as like working with film foundations, we're fortunate enough to be sponsored by Fledgling Fund and Chicken and Egg. But we also were able to get partnerships with people like Intel and NVidia. And also work with people who come from a traditional film background. There's not one way to successfully fund a project. There's a million. And that's why it's interesting that the technology's innovating, but also the market place is as well. >> One of the things I want to ask is as any new industry gets building, is cultures form early. DNA forms in the entrepreneurs, in the pioneers. And one of the big hottest topics in the creative world is inclusion and diversity. So what's the makeup of the culture of this new generation? Because democratization means everyone can participate, everyone's involved. What's the state of the community vis a vis diversity, inclusion, and the role of the actors in the community. >> Well I think it's important to understand that VR has a profound ability to place you in somebody else's shoes. The trick though is to make sure that those feel like they're your shoes. But I think that we're learning a lot more about story telling techniques and we're able to empower people that their voices you know were previously not heard. The tricky thing is being able to yeah, educate all different groups of people how to use the technology, but once they're enabled and empowered to do it, it's amazing what you can experience inside the headset. >> So VR can be an enabler for education, outreach, a variety of things? >> Yes, I mean the term empathy, empathy machine gets thrown around a lot. You could do a drinking game around it. For panels when people are talking about it. But it's important to know there is a truth to that. And it's, yeah the perspective shift from looking at a screen, a 16 by 9 screen where you can look away, then dissolving the screen and becoming that person. Becoming the director, the actor, the camera person, the editor. When you're in the first person perspective, there's so much more... It feels more personal and that's a really interesting angle that we're going to continue to explore. >> So you could walk in someone's shoes, literally? >> Yes, you literally can. You just have to make sure that you got a... The tracking system's proper or else you'll look like there's... It can be come a horror movie pretty quickly if your leg is behind your head. >> Lisa, your thoughts on this, I know it's important to you. >> Yeah, I mean I think it's fascinating because I've been in tech for a really long time. And seen many, many trends. I mean the first job I had at Intel I was a PC tech and as you can imagine as a female, I think there was one other tech female in the department at the time and I would get funny looks when I would show up with my bag. They were like hi can I help you? I'm like I'm not here to deliver coffee, I'm here to fix your computer, you know. So I've seen a lot of trends and it's super exciting to me to see so much diversity cross culture, cross country, I mean we're having... We had guys come in from all over the world. From even war torn, they've escaped their country just several years ago and they're coming and they're bringing all that creativity to the market. We're seeing very, very strong female contingent from the filmmaker perspective so it's this wonderful, wonderful just primordial soup of people that I think are growing their own voice and their own power. They're breaking molds as far as how you actually get content produced. Distribution is kind of crazy right now. I mean, how do you get it distributed? There's like so many different ways. But all of those things are so important to the evolutionary and biological process of this. Yes, we need to let it go and sometimes we're frustrated. We're like where's the standards? Where's the one ring to rule them all? Where there's not going to be one. And it's good for us that there's not right now. It's frustrating from a business perspective sometimes. You're like, I can't peanut butter myself around all of these places, but I think it's just a very unique time where so many people are... The technology is accessible, that means that so many creators can now bring their fresh voice to this space and it's just going to be fascinating to continue to watch. >> That's awesome. Well two more questions and I'll give you some time to think about the last one which is your perspective on Sundance, what's happening this year, your personal view of what you think's happening, what might happen during this year. But the question I have for you now is to go down the line. We'll start with Brooks here, and talk about the coolest thing that you're involved in right now. >> It actually has to be Hero. We're debuting it here at Sundance. We've been working on it and not talking about it for about nine months. And it's been very difficult. Again it's sacrosanct to the experience that you don't know literally what you're getting in to. And the emotional response has been essentially our goal, trying to find out how far can we take that. You actually being in a space, moving around, having that interactivity, doing what you would do. But it being your story and how deeply we can absolutely effect a human being. And again, watching people come out, it's one of those things, I've been doing game development, I've worked on films, I've done all kinds of stuff. And you usually get a chance when someone experiences something you've made, you walk up to them and you go so what'd you think? And that's not at all what we can do with ours. >> How has it impacted you, that reaction? >> Well, I personally suffer significant PTSD and I've had some traumas in my life. And so it's been incredibly powerful to be able to share these things with people. Share this emotion in a deeply profound, yet amazingly personal way. Which I'm amazingly fortunate to be able to be a part of it. >> Alright thanks for sharing. Coolest thing that's going on with you right now here at Sundance. >> Just the fact that I'm here at all. I mean, it's incredible right? Personally was able to be an advisor on the SPHERES project that is premiering here with Eliza McNitt. She's someone who was an Intel Science Fair winner back in high school and kind of came back to us. So just to see the evolution of an artist really from the beginning to the point where they've been able to come here to Sundance. I'm also very passionate about the work that we're doing with Sansar. I kind of consider myself one of the chief storytellers at Intel around Virtual reality and this new move into social where people are like well what's this game. I'm like, it's not a game. It's you are the game, you are the interactivity. You become the person that makes the space interesting. We're just really setting the scene for you. And there's so many... You know there's a lot of different people kind of chasing this be togetherness. But what we've been able to produce there. And just to be able to explore some of my own personal ideas has just been such a gift. Then to be working with guys like these on the panels and see what they're doing and just be in touch is really just an exciting time. >> John: Awesome. >> Probably what, other than the people on the projects, or the projects that are being shown here, we're working on our new project, which we would have loved to premiere here, but we did... Basically when you get in, you have two months to create a piece, so you have a demo and you have to finish it, so we're taking a little bit more time. This one's going to be about a year development cycle. It's called Breathe where we take you from where Giant left off, where, in Giant, the ceiling collapses on a family. They're in front of you. In this experience, we use a breathing apparatus to basically bring yourself back to life. And then you realize you're trapped under rubble and you remove the... We actually want to have physical objects on top of you that are going to be tracked. So you're moving rubble from you and you realize that you're a six year old girl. You're the survivor from Giant. And you get to witness what it's like to be a future refugee sort of in different key moments of her life that use breath. Whether it's a flirtatious moment, blowing a dandelion, seeing your own breath in snow as a drone shows you a message that your parents pre-recorded on your 18th birthday. This is all in the future, obviously, but every time you walk around an object, you actually grow 10 to 15 years older in the experience. As you get older, the world becomes smaller. And then we witness what's like for her last breath. From being six years old to being 90 years old. But it's a profound personal experience. >> John: That sounds cool, cool. Gary, coolest thing that you're involved in right now at Sundance. >> Wow. I could say it's all cool that would be a bit trite. They say if you enjoy what you do, is it really a job? And I'm lucky enough to be in that position. Because working with all these guys here and like people around the place, they're doing such great things that every day I wake up and I'm astounded of where the industry's going. In terms of what we're doing here at Sundance, then we're really starting to push those envelopes as well. I've been lucky enough to be involved with Dunkirk and Spider-Man: Homecoming. Like last year, so some great pieces there. And moving out into this year, we've got some other developments which I can't mention at this point, but we're showing things like AR and VR mashup. So we haven't talked much about augmented reality here. It's an evolutionary, it's not a replacement. Both can be used and we've started to really start to blend those two technologies now. So you can still see the outside world. Just touching on the commercial side, and health care's very big for me. That's where I think the really cool stuff is happening. Entertainment is great and that's really pushing the envelope and allowing us to then take it for the good of human kind. >> It happens everywhere, it's not just entertainment. >> Yeah absolutely. You start looking at MRI scans inside of VR or AR. Talking a patient through it so they can actually see exactly what you're talking about. You're now no longer pointing at flat things on a screen. You're now actually taking them through it. If you're using AR, you can actually judge the responses of the patient as for how they're reacting to the news. And effectively, inside of the VR, and what's really cool for me is seeing people's reaction to that content and to the entertainment content. >> That's awesome. Okay final question. This is a little bit of self serving because I'd like you to help me do my job at SiliconANGLE. If you were a reporter and you were going to report the most important stories happening this year at Sundance or really kind of what's really happening versus what's kind of being billed to be happening here. What's the story? What is the story this year at Sundance 2018 in your personal perspective? We'll go down the line and share your observations. >> Well, mine here, I'm a Sundance newbie. This is my first year of being here. I'm absolutely astounded by the community spirit that's around. I go to a lot of technical trade shows and technical presentations. People coming here with a willingness to learn. Wanting to learn from other people. It's been touched on already. It's the pool of knowledge that's available inside of Sundance that everybody that comes here can actually tap into to create better content, to learn not what to do as well as learn what to do. And I just think that's brilliant because in that community spirit, that's really going to help enable this industry quickly. >> John: Winslow, you've got some experience, what's your thoughts? >> Obviously, this Intel house, just a little plug for you Lisa. (laughter) Tech Lounge. We got that? Okay good. I mean, yeah, the people that's here. Every year we come here and see where the high water mark is. All these people are... Some of these teams first started with two people and then they grew to six and then by the end of it, there's 100 people working around the clock, pulling all-nighters to be able to give the latest and greatest of what's available with these current tools. So it's amazing because the work itself doesn't really mean anything until people get to experience it. So that's nice that they make a big splash. The people here are very attentive to it. It's a very nice audience and this will continue the momentum for future festivals throughout the year, but also will excite people that have never done VR before. People who have never been to Sundance before. We're seeing that there's a lot of new people. And that will continue to influence many years to come. >> John: So you think VR is the top story here being told? >> As far as like just to generalize, I would say last year kind of the big VR year. This is kind of the big AR year. Next year's going to be the AI year. Then after that we're going to start putting them all together. >> John: Great, great feedback. >> I think it's just exciting for Intel just to be back here. I think Intel hasn't been here in quite some time. Dell coming in here probably one of the breakout years for us to come back and really talk to creators what we're doing from the Intel Studios all the way through to the stuff you can take home and do at home. And I think coming in, we're coming back here with a purpose really, not just to be here to be seen. We're really here with real things and want to have real conversations on how tech can enable what people are doing. Not just from a brand perspective, but from a real hands on point of view. >> John: Yeah, some great demos too, phenomenal tech. >> Really just, yeah everything from the AI stuff we have to the social to the great new pieces that have been submitted here like we mentioned with SPHERES. So I think, yeah, it doesn't feel gratuitous to me you know that Dell or Intel is here this year. We've really come with a purpose. >> You guys are moving the needle, it's really awesome. We need more horsepower. >> Brooks, your thoughts on Sundance this year. Observation, the vibe, what would you tell your friend back home when you get back? >> If, for me, I think it's almost the non-story. It's like the opposite of a story. It's just the deep integration of VR into the normal Sundance flow I think has been interesting. Some people have been here for a few years. And back in the day when it was one or two, it was a lot of oh, you do VR? What's that then? Whereas now, you see a lot more people who are crossing over. Going to see documentaries, then they come to see a VR piece and it's just a part of the normal flow. And the team at New Frontier has done exceptional work to kind of make sure that they have this ridiculous high level of broad content for all kinds of people. All kinds of experiences, all high end things. But it's not that VR's here. Oh good, we have a VR section. It's a lot more of an integrated set up. And it's been really encouraging to see. >> Well you guys have been great. It's been very inspirational. Great information. You guys are reimagining the future and building it at the same time so entrepreneurially and also with content and technology. So thanks so much for sharing on this panel The New Creative. This is SiliconANGLE's coverage of Sundance 2018 here at the Intel Tech Lounge at the Sundance Film Festival. I'm John Furrier thanks for watching. (upbeat music)

>> Narrator: Live, from Munich, Germany, it's the CUBE. Covering IBM, Fast Track Your Data. Brought to you by IBM. >> Welcome to Munich everybody. This is a special presentation of the CUBE, Fast Track Your Data, brought to you by IBM. My name is Dave Vellante. And I'm here with my cohost, Jim Kobielus. Jim, good to see you. Really good to see you in Munich. >> Jim: I'm glad I made it. >> Thanks for being here. So last year Jim and I hosted a panel at New York City on the CUBE. And it was quite an experience. We had, I think it was nine or 10 data scientists and we felt like that was a lot of people to organize and talk about data science. Well today, we're going to do a repeat of that. With a little bit of twist on topics. And we've got five data scientists. We're here live, in Munich. And we're going to kick off the Fast Track Your Data event with this data science panel. So I'm going to now introduce some of the panelists, or all of the panelists. Then we'll get into the discussions. I'm going to start with Lillian Pierson. Lillian thanks very much for being on the panel. You are in data science. You focus on training executives, students, and you're really a coach but with a lot of data science expertise based in Thailand, so welcome. >> Thank you, thank you so much for having me. >> Dave: You're very welcome. And so, I want to start with sort of when you focus on training people, data science, where do you start? >> Well it depends on the course that I'm teaching. But I try and start at the beginning so for my Big Data course, I actually start back at the fundamental concepts and definitions they would even need to understand in order to understand the basics of what Big Data is, data engineering. So, terms like data governance. Going into the vocabulary that makes up the very introduction of the course, so that later on the students can really grasp the concepts I present to them. You know I'm teaching a deep learning course as well, so in that case I start at a lot more advanced concepts. So it just really depends on the level of the course. >> Great, and we're going to come back to this topic of women in tech. But you know, we looked at some CUBE data the other day. About 17% of the technology industry comprises women. And so we're a little bit over that on our data science panel, we're about 20% today. So we'll come back to that topic. But I don't know if there's anything you would add? >> I'm really passionate about women in tech and women who code, in particular. And I'm connected with a lot of female programmers through Instagram. And we're supporting each other. So I'd love to take any questions you have on what we're doing in that space. At least as far as what's happening across the Instagram platform. >> Great, we'll circle back to that. All right, let me introduce Chris Penn. Chris, Boston based, all right, SMI. Chris is a marketing expert. Really trying to help people understand how to get, turn data into value from a marketing perspective. It's a very important topic. Not only because we get people to buy stuff but also understanding some of the risks associated with things like GDPR, which is coming up. So Chris, tell us a little bit about your background and your practice. >> So I actually started in IT and worked at a start up. And that's where I made the transition to marketing. Because marketing has much better parties. But what's really interesting about the way data science is infiltrating marketing is the technology came in first. You know, everything went digital. And now we're at a point where there's so much data. And most marketers, they kind of got into marketing as sort of the arts and crafts field. And are realizing now, they need a very strong, mathematical, statistical background. So one of the things, Adam, the reason why we're here and IBM is helping out tremendously is, making a lot of the data more accessible to people who do not have a data science background and probably never will. >> Great, okay thank you. I'm going to introduce Ronald Van Loon. Ronald, your practice is really all about helping people extract value out of data, driving competitive advantage, business advantage, or organizational excellence. Tell us a little bit about yourself, your background, and your practice. >> Basically, I've three different backgrounds. On one hand, I'm a director at a data consultancy firm called Adversitement. Where we help companies to become data driven. Mainly large companies. I'm an advisory board member at Simply Learn, which is an e-learning platform, especially also for big data analytics. And on the other hand I'm a blogger and I host a series of webinars. >> Okay, great, now Dez, Dez Blanchfield, I met you on Twitter, you know, probably a couple of years ago. We first really started to collaborate last year. We've spend a fair amount of time together. You are a data scientist, but you're also a jack of all trades. You've got a technology background. You sit on a number of boards. You work very active with public policy. So tell us a little bit more about what you're doing these days, a little bit more about your background. >> Sure, I think my primary challenge these days is communication. Trying to join the dots between my technical background and deeply technical pedigree, to just plain English, every day language, and business speak. So bridging that technical world with what's happening in the boardroom. Toe to toe with the geeks to plain English to execs in boards. And just hand hold them and steward them through the journey of the challenges they're facing. Whether it's the enormous rapid of change and the pace of change, that's just almost exhaustive and causing them to sprint. But not just sprint in one race but in multiple lanes at the same time. As well as some of the really big things that are coming up, that we've seen like GDPR. So it's that communication challenge and just hand holding people through that journey and that mix of technical and commercial experience. >> Great, thank you, and finally Joe Caserta. Founder and president of Caserta Concepts. Joe you're a practitioner. You're in the front lines, helping organizations, similar to Ronald. Extracting value from data. Translate that into competitive advantage. Tell us a little bit about what you're doing these days in Caserta Concepts. >> Thanks Dave, thanks for having me. Yeah, so Caserta's been around. I've been doing this for 30 years now. And natural progressions have been just getting more from application development, to data warehousing, to big data analytics, to data science. Very, very organically, that's just because it's where businesses need the help the most, over the years. And right now, the big focus is governance. At least in my world. Trying to govern when you have a bunch of disparate data coming from a bunch of systems that you have no control over, right? Like social media, and third party data systems. Bringing it in and how to you organize it? How do you ingest it? How do you govern it? How do you keep it safe? And also help to define ownership of the data within an organization within an enterprise? That's also a very hot topic. Which ties back into GDPR. >> Great, okay, so we're going to be unpacking a lot of topics associated with the expertise that these individuals have. I'm going to bring in Jim Kobielus, to the conversation. Jim, the newest Wikibon analyst. And newest member of the SiliconANGLE Media Team. Jim, get us started off. >> Yeah, so we're at an event, at an IBM event where machine learning and data science are at the heart of it. There are really three core themes here. Machine learning and data science, on the one hand. Unified governance on the other. And hybrid data management. I want to circle back or focus on machine learning. Machine learning is the coin of the realm, right now in all things data. Machine learning is the heart of AI. Machine learning, everybody is going, hiring, data scientists to do machine learning. I want to get a sense from our panel, who are experts in this area, what are the chief innovations and trends right now on machine learning. Not deep learning, the core of machine learning. What's super hot? What's in terms of new techniques, new technologies, new ways of organizing teams to build and to train machine learning models? I'd like to open it up. Let's just start with Lillian. What are your thoughts about trends in machine learning? What's really hot? >> It's funny that you excluded deep learning from the response for this, because I think the hottest space in machine learning is deep learning. And deep learning is machine learning. I see a lot of collaborative platforms coming out, where people, data scientists are able to work together with other sorts of data professionals to reduce redundancies in workflows. And create more efficient data science systems. >> Is there much uptake of these crowd sourcing environments for training machine learning wells. Like CrowdFlower, or Amazon Mechanical Turk, or Mighty AI? Is that a huge trend in terms of the workflow of data science or machine learning, a lot of that? >> I don't see that crowdsourcing is like, okay maybe I've been out of the crowdsourcing space for a while. But I was working with Standby Task Force back in 2013. And we were doing a lot of crowdsourcing. And I haven't seen the industry has been increasing, but I could be wrong. I mean, because there's no, if you're building automation models, most of the, a lot of the work that's being crowdsourced could actually be automated if someone took the time to just build the scripts and build the models. And so I don't imagine that, that's going to be a trend that's increasing. >> Well, automation machine learning pipeline is fairly hot, in terms of I'm seeing more and more research. Google's doing a fair amount of automated machine learning. The panel, what do you think about automation, in terms of the core modeling tasks involved in machine learning. Is that coming along? Are data scientists in danger of automating themselves out of a job? >> I don't think there's a risk of data scientist's being put out of a job. Let's just put that on the thing. I do think we need to get a bit clearer about this meme of the mythical unicorn. But to your call point about machine learning, I think what you'll see, we saw the cloud become baked into products, just as a given. I think machine learning is already crossed this threshold. We just haven't necessarily noticed or caught up. And if we look at, we're at an IBM event, so let's just do a call out for them. The data science experience platform, for example. Machine learning's built into a whole range of things around algorithm and data classification. And there's an assisted, guided model for how you get to certain steps, where you don't actually have to understand how machine learning works. You don't have to understand how the algorithms work. It shows you the different options you've got and you can choose them. So you might choose regression. And it'll give you different options on how to do that. So I think we've already crossed this threshold of baking in machine learning and baking in the data science tools. And we've seen that with Cloud and other technologies where, you know, the Office 365 is not, you can't get a non Cloud Office 365 account, right? I think that's already happened in machine learning. What we're seeing though, is organizations even as large as the Googles still in catch up mode, in my view, on some of the shift that's taken place. So we've seen them write little games and apps where people do doodles and then it runs through the ML library and says, "Well that's a cow, or a unicorn, or a duck." And you get awards, and gold coins, and whatnot. But you know, as far as 12 years ago I was working on a project, where we had full size airplanes acting as drones. And we mapped with two and 3-D imagery. With 2-D high res imagery and LiDAR for 3-D point Clouds. We were finding poles and wires for utility companies, using ML before it even became a trend. And baking it right into the tools. And used to store on our web page and clicked and pointed on. >> To counter Lillian's point, it's not crowdsourcing but crowd sharing that's really powering a lot of the rapid leaps forward. If you look at, you know, DSX from IBM. Or you look at Node-RED, huge number of free workflows that someone has probably already done the thing that you are trying to do. Go out and find in the libraries, through Jupyter and R Notebooks, there's an ability-- >> Chris can you define before you go-- >> Chris: Sure. >> This is great, crowdsourcing versus crowd sharing. What's the distinction? >> Well, so crowdsourcing, kind of, where in the context of the question you ask is like I'm looking for stuff that other people, getting people to do stuff that, for me. It's like asking people to mine classifieds. Whereas crowd sharing, someone has done the thing already, it already exists. You're not purpose built, saying, "Jim, help me build this thing." It's like, "Oh Jim, you already "built this thing, cool. "So can I fork it and make my own from it?" >> Okay, I see what you mean, keep going. >> And then, again, going back to earlier. In terms of the advancements. Really deep learning, it probably is a good idea to just sort of define these things. Machine learning is how machines do things without being explicitly programmed to do them. Deep learning's like if you can imagine a stack of pancakes, right? Each pancake is a type of machine learning algorithm. And your data is the syrup. You pour the data on it. It goes from layer, to layer, to layer, to layer, and what you end up with at the end is breakfast. That's the easiest analogy for what deep learning is. Now imagine a stack of pancakes, 500 or 1,000 high, that's where deep learning's going now. >> Sure, multi layered machine learning models, essentially, that have the ability to do higher levels of abstraction. Like image analysis, Lillian? >> I had a comment to add about automation and data science. Because there are a lot of tools that are able to, or applications that are able to use data science algorithms and output results. But the reason that data scientists aren't in risk of losing their jobs, is because just because you can get the result, you also have to be able to interpret it. Which means you have to understand it. And that involves deep math and statistical understanding. Plus domain expertise. So, okay, great, you took out the coding element but that doesn't mean you can codify a person's ability to understand and apply that insight. >> Dave: Joe, you have something to add? >> I could just add that I see the trend. Really, the reason we're talking about it today is machine learning is not necessarily, it's not new, like Dez was saying. But what's different is the accessibility of it now. It's just so easily accessible. All of the tools that are coming out, for data, have machine learning built into it. So the machine learning algorithms, which used to be a black art, you know, years ago, now is just very easily accessible. That you can get, it's part of everyone's toolbox. And the other reason that we're talking about it more, is that data science is starting to become a core curriculum in higher education. Which is something that's new, right? That didn't exist 10 years ago? But over the past five years, I'd say, you know, it's becoming more and more easily accessible for education. So now, people understand it. And now we have it accessible in our tool sets. So now we can apply it. And I think that's, those two things coming together is really making it becoming part of the standard of doing analytics. And I guess the last part is, once we can train the machines to start doing the analytics, right? And get smarter as it ingests more data. And then we can actually take that and embed it in our applications. That's the part that you still need data scientists to create that. But once we can have standalone appliances that are intelligent, that's when we're going to start seeing, really, machine learning and artificial intelligence really start to take off even more. >> Dave: So I'd like to switch gears a little bit and bring Ronald on. >> Okay, yes. >> Here you go, there. >> Ronald, the bromide in this sort of big data world we live in is, the data is the new oil. You got to be a data driven company and many other cliches. But when you talk to organizations and you start to peel the onion. You find that most companies really don't have a good way to connect data with business impact and business value. What are you seeing with your clients and just generally in the community, with how companies are doing that? How should they do that? I mean, is that something that is a viable approach? You don't see accountants, for example, quantifying the value of data on a balance sheet. There's no standards for doing that. And so it's sort of this fuzzy concept. How are and how should organizations take advantage of data and turn it into value. >> So, I think in general, if you look how companies look at data. They have departments and within the departments they have tools specific for this department. And what you see is that there's no central, let's say, data collection. There's no central management of governance. There's no central management of quality. There's no central management of security. Each department is manages their data on their own. So if you didn't ask, on one hand, "Okay, how should they do it?" It's basically go back to the drawing table and say, "Okay, how should we do it?" We should collect centrally, the data. And we should take care for central governance. We should take care for central data quality. We should take care for centrally managing this data. And look from a company perspective and not from a department perspective what the value of data is. So, look at the perspective from your whole company. And this means that it has to be brought on one end to, whether it's from C level, where most of them still fail to understand what it really means. And what the impact can be for that company. >> It's a hard problem. Because data by its' very nature is now so decentralized. But Chris you have a-- >> The thing I want to add to that is, think about in terms of valuing data. Look at what it would cost you for data breach. Like what is the expensive of having your data compromised. If you don't have governance. If you don't have policy in place. Look at the major breaches of the last couple years. And how many billions of dollars those companies lost in market value, and trust, and all that stuff. That's one way you can value data very easily. "What will it cost us if we mess this up?" >> So a lot of CEOs will hear that and say, "Okay, I get it. "I have to spend to protect myself, "but I'd like to make a little money off of this data thing. "How do I do that?" >> Well, I like to think of it, you know, I think data's definitely an asset within an organization. And is becoming more and more of an asset as the years go by. But data is still a raw material. And that's the way I think about it. In order to actually get the value, just like if you're creating any product, you start with raw materials and then you refine it. And then it becomes a product. For data, data is a raw material. You need to refine it. And then the insight is the product. And that's really where the value is. And the insight is absolutely, you can monetize your insight. >> So data is, abundant insights are scarce. >> Well, you know, actually you could say that intermediate between insights and the data are the models themselves. The statistical, predictive, machine learning models. That are a crystallization of insights that have been gained by people called data scientists. What are your thoughts on that? Are statistical, predictive, machine learning models something, an asset, that companies, organizations, should manage governance of on a centralized basis or not? >> Well the models are essentially the refinery system, right? So as you're refining your data, you need to have process around how you exactly do that. Just like refining anything else. It needs to be controlled and it needs to be governed. And I think that data is no different from that. And I think that it's very undisciplined right now, in the market or in the industry. And I think maturing that discipline around data science, I think is something that's going to be a very high focus in this year and next. >> You were mentioning, "How do you make money from data?" Because there's all this risk associated with security breaches. But at the risk of sounding simplistic, you can generate revenue from system optimization, or from developing products and services. Using data to develop products and services that better meet the demands and requirements of your markets. So that you can sell more. So either you are using data to earn more money. Or you're using data to optimize your system so you have less cost. And that's a simple answer for how you're going to be making money from the data. But yes, there is always the counter to that, which is the security risks. >> Well, and my question really relates to, you know, when you think of talking to C level executives, they kind of think about running the business, growing the business, and transforming the business. And a lot of times they can't fund these transformations. And so I would agree, there's many, many opportunities to monetize data, cut costs, increase revenue. But organizations seem to struggle to either make a business case. And actually implement that transformation. >> Dave, I'd love to have a crack at that. I think this conversation epitomizes the type of things that are happening in board rooms and C suites already. So we've really quickly dived into the detail of data. And the detail of machine learning. And the detail of data science, without actually stopping and taking a breath and saying, "Well, we've "got lots of it, but what have we got? "Where is it? "What's the value of it? "Is there any value in it at all?" And, "How much time and money should we invest in it?" For example, we talk of being about a resource. I look at data as a utility. When I turn the tap on to get a drink of water, it's there as a utility. I counted it being there but I don't always sample the quality of the water and I probably should. It could have Giardia in it, right? But what's interesting is I trust the water at home, in Sydney. Because we have a fairly good experience with good quality water. If I were to go to some other nation. I probably wouldn't trust that water. And I think, when you think about it, what's happening in organizations. It's almost the same as what we're seeing here today. We're having a lot of fun, diving into the detail. But what we've forgotten to do is ask the question, "Well why is data even important? "What's the reasoning to the business? "Why are we in business? "What are we doing as an organization? "And where does data fit into that?" As opposed to becoming so fixated on data because it's a media hyped topic. I think once you can wind that back a bit and say, "Well, we have lot's of data, "but is it good data? "Is it quality data? "Where's it coming from? "Is it ours? "Are we allowed to have it? "What treatment are we allowed to give that data?" As you said, "Are we controlling it? "And where are we controlling it? "Who owns it?" There's so many questions to be asked. But the first question I like to ask people in plain English is, "Well is there any value "in data in the first place? "What decisions are you making that data can help drive? "What things are in your organizations, "KPIs and milestones you're trying to meet "that data might be a support?" So then instead of becoming fixated with data as a thing in itself, it becomes part of your DNA. Does that make sense? >> Think about what money means. The Economists' Rhyme, "Money is a measure for, "a systems for, a medium, a measure, and exchange." So it's a medium of exchange. A measure of value, a way to exchange something. And a way to store value. Data, good clean data, well governed, fits all four of those. So if you're trying to figure out, "How do we make money out of stuff." Figure out how money works. And then figure out how you map data to it. >> So if we approach and we start with a company, we always start with business case, which is quite clear. And defined use case, basically, start with a team on one hand, marketing people, sales people, operational people, and also the whole data science team. So start with this case. It's like, defining, basically a movie. If you want to create the movie, You know where you're going to. You know what you want to achieve to create the customer experience. And this is basically the same with a business case. Where you define, "This is the case. "And this is how we're going to derive value, "start with it and deliver value within a month." And after the month, you check, "Okay, where are we and how can we move forward? "And what's the value that we've brought?" >> Now I as well, start with business case. I've done thousands of business cases in my life, with organizations. And unless that organization was kind of a data broker, the business case rarely has a discreet component around data. Is that changing, in your experience? >> Yes, so we guide companies into be data driven. So initially, indeed, they don't like to use the data. They don't like to use the analysis. So that's why, how we help. And is it changing? Yes, they understand that they need to change. But changing people is not always easy. So, you see, it's hard if you're not involved and you're not guiding it, they fall back in doing the daily tasks. So it's changing, but it's a hard change. >> Well and that's where this common parlance comes in. And Lillian, you, sort of, this is what you do for a living, is helping people understand these things, as you've been sort of evangelizing that common parlance. But do you have anything to add? >> I wanted to add that for organizational implementations, another key component to success is to start small. Start in one small line of business. And then when you've mastered that area and made it successful, then try and deploy it in more areas of the business. And as far as initializing big data implementation, that's generally how to do it successfully. >> There's the whole issue of putting a value on data as a discreet asset. Then there's the issue, how do you put a value on a data lake? Because a data lake, is essentially an asset you build on spec. It's an exploratory archive, essentially, of all kinds of data that might yield some insights, but you have to have a team of data scientists doing exploration and modeling. But it's all on spec. How do you put a value on a data lake? And at what point does the data lake itself become a burden? Because you got to store that data and manage it. At what point do you drain that lake? At what point, do the costs of maintaining that lake outweigh the opportunity costs of not holding onto it? >> So each Hadoop note is approximately $20,000 per year cost for storage. So I think that there needs to be a test and a diagnostic, before even inputting, ingesting the data and storing it. "Is this actually going to be useful? "What value do we plan to create from this?" Because really, you can't store all the data. And it's a lot cheaper to store data in Hadoop then it was in traditional systems but it's definitely not free. So people need to be applying this test before even ingesting the data. Why do we need this? What business value? >> I think the question we need to also ask around this is, "Why are we building data lakes "in the first place? "So what's the function it's going to perform for you?" There's been a huge drive to this idea. "We need a data lake. "We need to put it all somewhere." But invariably they become data swamps. And we only half jokingly say that because I've seen 90 day projects turn from a great idea, to a really bad nightmare. And as Lillian said, it is cheaper in some ways to put it into a HDFS platform, in a technical sense. But when we look at all the fully burdened components, it's actually more expensive to find Hadoop specialists and Spark specialists to maintain that cluster. And invariably I'm finding that big data, quote unquote, is not actually so much lots of data, it's complex data. And as Lillian said, "You don't always "need to store it all." So I think if we go back to the question of, "What's the function of a data lake in the first place? "Why are we building one?" And then start to build some fully burdened cost components around that. We'll quickly find that we don't actually need a data lake, per se. We just need an interim data store. So we might take last years' data and tokenize it, and analyze it, and do some analytics on it, and just keep the meta data. So I think there is this rush, for a whole range of reasons, particularly vendor driven. To build data lakes because we think they're a necessity, when in reality they may just be an interim requirement and we don't need to keep them for a long term. >> I'm going to attempt to, the last few questions, put them all together. And I think, they all belong together because one of the reasons why there's such hesitation about progress within the data world is because there's just so much accumulated tech debt already. Where there's a new idea. We go out and we build it. And six months, three years, it really depends on how big the idea is, millions of dollars is spent. And then by the time things are built the idea is pretty much obsolete, no one really cares anymore. And I think what's exciting now is that the speed to value is just so much faster than it's ever been before. And I think that, you know, what makes that possible is this concept of, I don't think of a data lake as a thing. I think of a data lake as an ecosystem. And that ecosystem has evolved so much more, probably in the last three years than it has in the past 30 years. And it's exciting times, because now once we have this ecosystem in place, if we have a new idea, we can actually do it in minutes not years. And that's really the exciting part. And I think, you know, data lake versus a data swamp, comes back to just traditional data architecture. And if you architect your data lake right, you're going to have something that's substantial, that's you're going to be able to harness and grow. If you don't do it right. If you just throw data. If you buy Hadoop cluster or a Cloud platform and just throw your data out there and say, "We have a lake now." yeah, you're going to create a mess. And I think taking the time to really understand, you know, the new paradigm of data architecture and modern data engineering, and actually doing it in a very disciplined way. If you think about it, what we're doing is we're building laboratories. And if you have a shabby, poorly built laboratory, the best scientist in the world isn't going to be able to prove his theories. So if you have a well built laboratory and a clean room, then, you know a scientist can get what he needs done very, very, very efficiently. And that's the goal, I think, of data management today. >> I'd like to just quickly add that I totally agree with the challenge between on premise and Cloud mode. And I think one of the strong themes of today is going to be the hybrid data management challenge. And I think organizations, some organizations, have rushed to adopt Cloud. And thinking it's a really good place to dump the data and someone else has to manage the problem. And then they've ended up with a very expensive death by 1,000 cuts in some senses. And then others have been very reluctant as a result of not gotten access to rapid moving and disruptive technology. So I think there's a really big challenge to get a basic conversation going around what's the value using Cloud technology as in adopting it, versus what are the risks? And when's the right time to move? For example, should we Cloud Burst for workloads? Do we move whole data sets in there? You know, moving half a petabyte of data into a Cloud platform back is a non-trivial exercise. But moving a terabyte isn't actually that big a deal anymore. So, you know, should we keep stuff behind the firewalls? I'd be interested in seeing this week where 80% of the data, supposedly is. And just push out for Cloud tools, machine learning, data science tools, whatever they might be, cognitive analytics, et cetera. And keep the bulk of the data on premise. Or should we just move whole spools into the Cloud? There is no one size fits all. There's no silver bullet. Every organization has it's own quirks and own nuances they need to think through and make a decision themselves. >> Very often, Dez, organizations have zonal architectures so you'll have a data lake that consists of a no sequel platform that might be used for say, mobile applications. A Hadoop platform that might be used for unstructured data refinement, so forth. A streaming platform, so forth and so on. And then you'll have machine learning models that are built and optimized for those different platforms. So, you know, think of it in terms of then, your data lake, is a set of zones that-- >> It gets even more complex just playing on that theme, when you think about what Cisco started, called Folk Computing. I don't really like that term. But edge analytics, or computing at the edge. We've seen with the internet coming along where we couldn't deliver everything with a central data center. So we started creating this concept of content delivery networks, right? I think the same thing, I know the same thing has happened in data analysis and data processing. Where we've been pulling social media out of the Cloud, per se, and bringing it back to a central source. And doing analytics on it. But when you think of something like, say for example, when the Dreamliner 787 from Boeing came out, this airplane created 1/2 a terabyte of data per flight. Now let's just do some quick, back of the envelope math. There's 87,400 fights a day, just in the domestic airspace in the USA alone, per day. Now 87,400 by 1/2 a terabyte, that's 43 point five petabytes a day. You physically can't copy that from quote unquote in the Cloud, if you'll pardon the pun, back to the data center. So now we've got the challenge, a lot of our Enterprise data's behind a firewall, supposedly 80% of it. But what's out at the edge of the network. Where's the value in that data? So there are zonal challenges. Now what do I do with my Enterprise versus the open data, the mobile data, the machine data. >> Yeah, we've seen some recent data from IDC that says, "About 43% of the data "is going to stay at the edge." We think that, that's way understated, just given the examples. We think it's closer to 90% is going to stay at the edge. >> Just on the airplane topic, right? So Airbus wasn't going to be outdone. Boeing put 4,000 sensors or something in their 787 Dreamliner six years ago. Airbus just announced an 83, 81,000 with 10,000 sensors in it. Do the same math. Now the FAA in the US said that all aircraft and all carriers have to be, by early next year, I think it's like March or April next year, have to be at the same level of BIOS. Or the same capability of data collection and so forth. It's kind of like a mini GDPR for airlines. So with the 83, 81,000 with 10,000 sensors, that becomes two point five terabytes per flight. If you do the math, it's 220 petabytes of data just in one day's traffic, domestically in the US. Now, it's just so mind boggling that we're going to have to completely turn our thinking on its' head, on what do we do behind the firewall? What do we do in the Cloud versus what we might have to do in the airplane? I mean, think about edge analytics in the airplane processing data, as you said, Jim, streaming analytics in flight. >> Yeah that's a big topic within Wikibon, so, within the team. Me and David Floyer, and my other colleagues. They're talking about the whole notion of edge architecture. Not only will most of the data be persisted at the edge, most of the deep learning models like TensorFlow will be executed at the edge. To some degree, the training of those models will happen in the Cloud. But much of that will be pushed in a federated fashion to the edge, or at least I'm predicting. We're already seeing some industry moves in that direction, in terms of architectures. Google has a federated training, project or initiative. >> Chris: Look at TensorFlow Lite. >> Which is really fascinating for it's geared to IOT, I'm sorry, go ahead. >> Look at TensorFlow Lite. I mean in the announcement of having every Android device having ML capabilities, is Google's essential acknowledgment, "We can't do it all." So we need to essentially, sort of like a setting at home. Everyone's smartphone top TV box just to help with the processing. >> Now we're talking about this, this sort of leads to this IOT discussion but I want to underscore the operating model. As you were saying, "You can't just "lift and shift to the Cloud." You're not going to, CEOs aren't going to get the billion dollar hit by just doing that. So you got to change the operating model. And that leads to, this discussion of IOT. And an entirely new operating model. >> Well, there are companies that are like Sisense who have worked with Intel. And they've taken this concept. They've taken the business logic and not just putting it in the chip, but actually putting it in memory, in the chip. So as data's going through the chip it's not just actually being processed but it's actually being baked in memory. So level one, two, and three cache. Now this is a game changer. Because as Chris was saying, even if we were to get the data back to a central location, the compute load, I saw a real interesting thing from I think it was Google the other day, one of the guys was doing a talk. And he spoke about what it meant to add cognitive and voice processing into just the Android platform. And they used some number, like that had, double the amount of compute they had, just to add voice for free, to the Android platform. Now even for Google, that's a nontrivial exercise. So as Chris was saying, I think we have to again, flip it on its' head and say, "How much can we put "at the edge of the network?" Because think about these phones. I mean, even your fridge and microwave, right? We put a man on the moon with something that these days, we make for $89 at home, on the Raspberry Pie computer, right? And even that was 1,000 times more powerful. When we start looking at what's going into the chips, we've seen people build new, not even GPUs, but deep learning and stream analytics capable chips. Like Google, for example. That's going to make its' way into consumer products. So that, now the compute capacity in phones, is going to, I think transmogrify in some ways because there is some magic in there. To the point where, as Chris was saying, "We're going to have the smarts in our phone." And a lot of that workload is going to move closer to us. And only the metadata that we need to move is going to go centrally. >> Well here's the thing. The edge isn't the technology. The edge is actually the people. When you look at, for example, the MIT language Scratch. This is kids programming language. It's drag and drop. You know, kids can assemble really fun animations and make little movies. We're training them to build for IOT. Because if you look at a system like Node-RED, it's an IBM interface that is drag and drop. Your workflow is for IOT. And you can push that to a device. Scratch has a converter for doing those. So the edge is what those thousands and millions of kids who are learning how to code, learning how to think architecturally and algorithmically. What they're going to create that is beyond what any of us can possibly imagine. >> I'd like to add one other thing, as well. I think there's a topic we've got to start tabling. And that is what I refer to as the gravity of data. So when you think about how planets are formed, right? Particles of dust accrete. They form into planets. Planets develop gravity. And the reason we're not flying into space right now is that there's gravitational force. Even though it's one of the weakest forces, it keeps us on our feet. Oftentimes in organizations, I ask them to start thinking about, "Where is the center "of your universe with regard to the gravity of data." Because if you can follow the center of your universe and the gravity of your data, you can often, as Chris is saying, find where the business logic needs to be. And it could be that you got to think about a storage problem. You can think about a compute problem. You can think about a streaming analytics problem. But if you can find where the center of your universe and the center of your gravity for your data is, often you can get a really good insight into where you can start focusing on where the workloads are going to be where the smarts are going to be. Whether it's small, medium, or large. >> So this brings up the topic of data governance. One of the themes here at Fast Track Your Data is GDPR. What it means. It's one of the reasons, I think IBM selected Europe, generally, Munich specifically. So let's talk about GDPR. We had a really interesting discussion last night. So let's kind of recreate some of that. I'd like somebody in the panel to start with, what is GDPR? And why does it matter, Ronald? >> Yeah, maybe I can start. Maybe a little bit more in general unified governance. So if i talk to companies and I need to explain to them what's governance, I basically compare it with a crime scene. So in a crime scene if something happens, they start with securing all the evidence. So they start sealing the environment. And take care that all the evidence is collected. And on the other hand, you see that they need to protect this evidence. There are all kinds of policies. There are all kinds of procedures. There are all kinds of rules, that need to be followed. To take care that the whole evidence is secured well. And once you start, basically, investigating. So you have the crime scene investigators. You have the research lab. You have all different kind of people. They need to have consent before they can use all this evidence. And the whole reason why they're doing this is in order to collect the villain, the crook. To catch him and on the other hand, once he's there, to convict him. And we do this to have trust in the materials. Or trust in basically, the analytics. And on the other hand to, the public have trust in everything what's happened with the data. So if you look to a company, where data is basically the evidence, this is the value of your data. It's similar to like the evidence within a crime scene. But most companies don't treat it like this. So if we then look to GDPR, GDPR basically shifts the power and the ownership of the data from the company to the person that created it. Which is often, let's say the consumer. And there's a lot of paradox in this. Because all the companies say, "We need to have this customer data. "Because we need to improve the customer experience." So if you make it concrete and let's say it's 1st of June, so GDPR is active. And it's first of June 2018. And I go to iTunes, so I use iTunes. Let's go to iTunes said, "Okay, Apple please "give me access to my data." I want to see which kind of personal information you have stored for me. On the other end, I want to have the right to rectify all this data. I want to be able to change it and give them a different level of how they can use my data. So I ask this to iTunes. And then I say to them, okay, "I basically don't like you anymore. "I want to go to Spotify. "So please transfer all my personal data to Spotify." So that's possible once it's June 18. Then I go back to iTunes and say, "Okay, I don't like it anymore. "Please reduce my consent. "I withdraw my consent. "And I want you to remove all my "personal data for everything that you use." And I go to Spotify and I give them, let's say, consent for using my data. So this is a shift where you can, as a person be the owner of the data. And this has a lot of consequences, of course, for organizations, how to manage this. So it's quite simple for the consumer. They get the power, it's maturing the whole law system. But it's a big consequence of course for organizations. >> This is going to be a nightmare for marketers. But fill in some of the gaps there. >> Let's go back, so GDPR, the General Data Protection Regulation, was passed by the EU in 2016, in May of 2016. It is, as Ronald was saying, it's four basic things. The right to privacy. The right to be forgotten. Privacy built into systems by default. And the right to data transfer. >> Joe: It takes effect next year. >> It is already in effect. GDPR took effect in May of 2016. The enforcement penalties take place the 25th of May 2018. Now here's where, there's two things on the penalty side that are important for everyone to know. Now number one, GDPR is extra territorial. Which means that an EU citizen, anywhere on the planet has GDPR, goes with them. So say you're a pizza shop in Nebraska. And an EU citizen walks in, orders a pizza. Gives her the credit card and stuff like that. If you for some reason, store that data, GDPR now applies to you, Mr. Pizza shop, whether or not you do business in the EU. Because an EU citizen's data is with you. Two, the penalties are much stiffer then they ever have been. In the old days companies could simply write off penalties as saying, "That's the cost of doing business." With GDPR the penalties are up to 4% of your annual revenue or 20 million Euros, whichever is greater. And there may be criminal sanctions, charges, against key company executives. So there's a lot of questions about how this is going to be implemented. But one of the first impacts you'll see from a marketing perspective is all the advertising we do, targeting people by their age, by their personally identifiable information, by their demographics. Between now and May 25th 2018, a good chunk of that may have to go away because there's no way for you to say, "Well this person's an EU citizen, this person's not." People give false information all the time online. So how do you differentiate it? Every company, regardless of whether they're in the EU or not will have to adapt to it, or deal with the penalties. >> So Lillian, as a consumer this is designed to protect you. But you had a very negative perception of this regulation. >> I've looked over the GDPR and to me it actually looks like a socialist agenda. It looks like (panel laughs) no, it looks like a full assault on free enterprise and capitalism. And on its' face from a legal perspective, its' completely and wholly unenforceable. Because they're assigning jurisdictional rights to the citizen. But what are they going to do? They're going to go to Nebraska and they're going to call in the guy from the pizza shop? And call him into what court? The EU court? It's unenforceable from a legal perspective. And if you write a law that's unenforceable, you know, it's got to be enforceable in every element. It can't be just, "Oh, we're only "going to enforce it for Facebook and for Google. "But it's not enforceable for," it needs to be written so that it's a complete and actionable law. And it's not written in that way. And from a technological perspective it's not implementable. I think you said something like 652 EU regulators or political people voted for this and 10 voted against it. But what do they know about actually implementing it? Is it possible? There's all sorts of regulations out there that aren't possible to implement. I come from an environmental engineering background. And it's absolutely ridiculous because these agencies will pass laws that actually, it's not possible to implement those in practice. The cost would be too great. And it's not even needed. So I don't know, I just saw this and I thought, "You know, if the EU wants to," what they're essentially trying to do is regulate what the rest of the world does on the internet. And if they want to build their own internet like China has and police it the way that they want to. But Ronald here, made an analogy between data, and free enterprise, and a crime scene. Now to me, that's absolutely ridiculous. What does data and someone signing up for an email list have to do with a crime scene? And if EU wants to make it that way they can police their own internet. But they can't go across the world. They can't go to Singapore and tell Singapore, or go to the pizza shop in Nebraska and tell them how to run their business. >> You know, EU overreach in the post Brexit era, of what you're saying has a lot of validity. How far can the tentacles of the EU reach into other sovereign nations. >> What court are they going to call them into? >> Yeah. >> I'd like to weigh in on this. There are lots of unknowns, right? So I'd like us to focus on the things we do know. We've already dealt with similar situations before. In Australia, we introduced a goods and sales tax. Completely foreign concept. Everything you bought had 10% on it. No one knew how to deal with this. It was a completely new practice in accounting. There's a whole bunch of new software that had to be written. MYRB had to have new capability, but we coped. No one actually went to jail yet. It's decades later, for not complying with GST. So what it was, was a framework on how to shift from non sales tax related revenue collection. To sales tax related revenue collection. I agree that there are some egregious things built into this. I don't disagree with that at all. But I think if I put my slightly broader view of the world hat on, we have well and truly gone past the point in my mind, where data was respected, data was treated in a sensible way. I mean I get emails from companies I've never done business with. And when I follow it up, it's because I did business with a credit card company, that gave it to a service provider, that thought that I was going to, when I bought a holiday to come to Europe, that I might want travel insurance. Now some might say there's value in that. And other's say there's not, there's the debate. But let's just focus on what we're talking about. We're talking about a framework for governance of the treatment of data. If we remove all the emotive component, what we are talking about is a series of guidelines, backed by laws, that say, "We would like you to do this," in an ideal world. But I don't think anyone's going to go to jail, on day one. They may go to jail on day 180. If they continue to do nothing about it. So they're asking you to sort of sit up and pay attention. Do something about it. There's a whole bunch of relief around how you approach it. The big thing for me, is there's no get out of jail card, right? There is no get out of jail card for not complying. But there's plenty of support. I mean, we're going to have ambulance chasers everywhere. We're going to have class actions. We're going to have individual suits. The greatest thing to do right now is get into GDPR law. Because you seem to think data scientists are unicorn? >> What kind of life is that if there's ambulance chasers everywhere? You want to live like that? >> Well I think we've seen ad blocking. I use ad blocking as an example, right? A lot of organizations with advertising broke the internet by just throwing too much content on pages, to the point where they're just unusable. And so we had this response with ad blocking. I think in many ways, GDPR is a regional response to a situation where I don't think it's the exact right answer. But it's the next evolutional step. We'll see things evolve over time. >> It's funny you mentioned it because in the United States one of the things that has happened, is that with the change in political administrations, the regulations on what companies can do with your data have actually been laxened, to the point where, for example, your internet service provider can resell your browsing history, with or without your consent. Or your consent's probably buried in there, on page 47. And so, GDPR is kind of a response to saying, "You know what? "You guys over there across the Atlantic "are kind of doing some fairly "irresponsible things with what you allow companies to do." Now, to Lillian's point, no one's probably going to go after the pizza shop in Nebraska because they don't do business in the EU. They don't have an EU presence. And it's unlikely that an EU regulator's going to get on a plane from Brussels and fly to Topeka and say, or Omaha, sorry, "Come on Joe, let's get the pizza shop in order here." But for companies, particularly Cloud companies, that have offices and operations within the EU, they have to sit up and pay attention. So if you have any kind of EU operations, or any kind of fiscal presence in the EU, you need to get on board. >> But to Lillian's point it becomes a boondoggle for lawyers in the EU who want to go after deep pocketed companies like Facebook and Google. >> What's the value in that? It seems like regulators are just trying to create work for themselves. >> What about the things that say advertisers can do, not so much with the data that they have? With the data that they don't have. In other words, they have people called data scientists who build models that can do inferences on sparse data. And do amazing things in terms of personalization. What do you do about all those gray areas? Where you got machine learning models and so forth? >> But it applies-- >> It applies to personally identifiable information. But if you have a talented enough data scientist, you don't need the PII or even the inferred characteristics. If a certain type of behavior happens on your website, for example. And this path of 17 pages almost always leads to a conversion, it doesn't matter who you are or where you're coming from. If you're a good enough data scientist, you can build a model that will track that. >> Like you know, target, infer some young woman was pregnant. And they inferred correctly even though that was never divulged. I mean, there's all those gray areas that, how can you stop that slippery slope? >> Well I'm going to weigh in really quickly. A really interesting experiment for people to do. When people get very emotional about it I say to them, "Go to Google.com, "view source, put it in seven point Courier "font in Word and count how many pages it is." I guess you can't guess how many pages? It's 52 pages of seven point Courier font, HTML to render one logo, and a search field, and a click button. Now why do we need 52 pages of HTML source code and Java script just to take a search query. Think about what's being done in that. It's effectively a mini operating system, to figure out who you are, and what you're doing, and where you been. Now is that a good or bad thing? I don't know, I'm not going to make a judgment call. But what I'm saying is we need to stop and take a deep breath and say, "Does anybody need a 52 page, "home page to take a search query?" Because that's just the tip of the iceberg. >> To that point, I like the results that Google gives me. That's why I use Google and not Bing. Because I get better search results. So, yeah, I don't mind if you mine my personal data and give me, our Facebook ads, those are the only ads, I saw in your article that GDPR is going to take out targeted advertising. The only ads in the entire world, that I like are Facebook ads. Because I actually see products I'm interested in. And I'm happy to learn about that. I think, "Oh I want to research that. "I want to see this new line of products "and what are their competitors?" And I like the targeted advertising. I like the targeted search results because it's giving me more of the information that I'm actually interested in. >> And that's exactly what it's about. You can still decide, yourself, if you want to have this targeted advertising. If not, then you don't give consent. If you like it, you give consent. So if a company gives you value, you give consent back. So it's not that it's restricting everything. It's giving consent. And I think it's similar to what happened and the same type of response, what happened, we had the Mad Cow Disease here in Europe, where you had the whole food chain that needed to be tracked. And everybody said, "No, it's not required." But now it's implemented. Everybody in Europe does it. So it's the same, what probably going to happen over here as well. >> So what does GDPR mean for data scientists? >> I think GDPR is, I think it is needed. I think one of the things that may be slowing data science down is fear. People are afraid to share their data. Because they don't know what's going to be done with it. If there are some guidelines around it that should be enforced and I think, you know, I think it's been said but as long as a company could prove that it's doing due diligence to protect your data, I think no one is going to go to jail. I think when there's, you know, we reference a crime scene, if there's a heinous crime being committed, all right, then it's going to become obvious. And then you do go directly to jail. But I think having guidelines and even laws around privacy and protection of data is not necessarily a bad thing. You can do a lot of data, really meaningful data science, without understanding that it's Joe Caserta. All of the demographics about me. All of the characteristics about me as a human being, I think are still on the table. All that they're saying is that you can't go after Joe, himself, directly. And I think that's okay. You know, there's still a lot of things. We could still cure diseases without knowing that I'm Joe Caserta, right? As long as you know everything else about me. And I think that's really at the core, that's what we're trying to do. We're trying to protect the individual and the individual's data about themselves. But I think as far as how it affects data science, you know, a lot of our clients, they're afraid to implement things because they don't exactly understand what the guideline is. And they don't want to go to jail. So they wind up doing nothing. So now that we have something in writing that, at least, it's something that we can work towards, I think is a good thing. >> In many ways, organizations are suffering from the deer in the headlight problem. They don't understand it. And so they just end up frozen in the headlights. But I just want to go back one step if I could. We could get really excited about what it is and is not. But for me, the most critical thing there is to remember though, data breaches are happening. There are over 1,400 data breaches, on average, per day. And most of them are not trivial. And when we saw 1/2 a billion from Yahoo. And then one point one billion and then one point five billion. I mean, think about what that actually means. There were 47,500 Mongodbs breached in an 18 hour window, after an automated upgrade. And they were airlines, they were banks, they were police stations. They were hospitals. So when I think about frameworks like GDPR, I'm less worried about whether I'm going to see ads and be sold stuff. I'm more worried about, and I'll give you one example. My 12 year old son has an account at a platform called Edmodo. Now I'm not going to pick on that brand for any reason but it's a current issue. Something like, I think it was like 19 million children in the world had their username, password, email address, home address, and all this social interaction on this Facebook for kids platform called Edmodo, breached in one night. Now I got my hands on a copy. And everything about my son is there. Now I have a major issue with that. Because I can't do anything to undo that, nothing. The fact that I was able to get a copy, within hours on a dark website, for free. The fact that his first name, last name, email, mobile phone number, all these personal messages from friends. Nobody has the right to allow that to breach on my son. Or your children, or our children. For me, GDPR, is a framework for us to try and behave better about really big issues. Whether it's a socialist issue. Whether someone's got an issue with advertising. I'm actually not interested in that at all. What I'm interested in is companies need to behave much better about the treatment of data when it's the type of data that's being breached. And I get really emotional when it's my son, or someone else's child. Because I don't care if my bank account gets hacked. Because they hedge that. They underwrite and insure themselves and the money arrives back to my bank. But when it's my wife who donated blood and a blood donor website got breached and her details got lost. Even things like sexual preferences. That they ask questions on, is out there. My 12 year old son is out there. Nobody has the right to allow that to happen. For me, GDPR is the framework for us to focus on that. >> Dave: Lillian, is there a comment you have? >> Yeah, I think that, I think that security concerns are 100% and definitely a serious issue. Security needs to be addressed. And I think a lot of the stuff that's happening is due to, I think we need better security personnel. I think we need better people working in the security area where they're actually looking and securing. Because I don't think you can regulate I was just, I wanted to take the microphone back when you were talking about taking someone to jail. Okay, I have a background in law. And if you look at this, you guys are calling it a framework. But it's not a framework. What they're trying to do is take 4% of your business revenues per infraction. They want to say, "If a person signs up "on your email list and you didn't "like, necessarily give whatever "disclaimer that the EU said you need to give. "Per infraction, we're going to take "4% of your business revenue." That's a law, that they're trying to put into place. And you guys are talking about taking people to jail. What jail are you? EU is not a country. What jurisdiction do they have? Like, you're going to take pizza man Joe and put him in the EU jail? Is there an EU jail? Are you going to take them to a UN jail? I mean, it's just on its' face it doesn't hold up to legal tests. I don't understand how they could enforce this. >> I'd like to just answer the question on-- >> Security is a serious issue. I would be extremely upset if I were you. >> I personally know, people who work for companies who've had data breaches. And I respect them all. They're really smart people. They've got 25 plus years in security. And they are shocked that they've allowed a breach to take place. What they've invariably all agreed on is that a whole range of drivers have caused them to get to a bad practice. So then, for example, the donate blood website. The young person who was assist admin with all the right skills and all the right experience just made a basic mistake. They took a db dump of a mysql database before they upgraded their Wordpress website for the business. And they happened to leave it in a folder that was indexable by Google. And so somebody wrote a radio expression to search in Google to find sql backups. Now this person, I personally respect them. I think they're an amazing practitioner. They just made a mistake. So what does that bring us back to? It brings us back to the point that we need a safety net or a framework or whatever you want to call it. Where organizations have checks and balances no matter what they do. Whether it's an upgrade, a backup, a modification, you know. And they all think they do, but invariably we've seen from the hundreds of thousands of breaches, they don't. Now on the point of law, we could debate that all day. I mean the EU does have a remit. If I was caught speeding in Germany, as an Australian, I would be thrown into a German jail. If I got caught as an organization in France, breaching GDPR, I would be held accountable to the law in that region, by the organization pursuing me. So I think it's a bit of a misnomer saying I can't go to an EU jail. I don't disagree with you, totally, but I think it's regional. If I get a speeding fine and break the law of driving fast in EU, it's in the country, in the region, that I'm caught. And I think GDPR's going to be enforced in that same approach. >> All right folks, unfortunately the 60 minutes flew right by. And it does when you have great guests like yourselves. So thank you very much for joining this panel today. And we have an action packed day here. So we're going to cut over. The CUBE is going to have its' interview format starting in about 1/2 hour. And then we cut over to the main tent. Who's on the main tent? Dez, you're doing a main stage presentation today. Data Science is a Team Sport. Hillary Mason, has a breakout session. We also have a breakout session on GDPR and what it means for you. Are you ready for GDPR? Check out ibmgo.com. It's all free content, it's all open. You do have to sign in to see the Hillary Mason and the GDPR sessions. And we'll be back in about 1/2 hour with the CUBE. We'll be running replays all day on SiliconAngle.tv and also ibmgo.com. So thanks for watching everybody. Keep it right there, we'll be back in about 1/2 hour with the CUBE interviews. We're live from Munich, Germany, at Fast Track Your Data. This is Dave Vellante with Jim Kobielus, we'll see you shortly. (electronic music)

prepare for the extraction point we've been briefed on all the important stories and events in the world of emerging information now it's time to extract the data and turn it into action live from the silicon angle studios in the heart of Silicon Valley this is extraction point with John furrier okay we're live back in the palo alto studios i'm john furrier for the extraction point we extract the signal from the noise and my special guest today i'm excited to have here is Paul Martino who is the founder of aggregate knowledge and also storied entrepreneur in Silicon Valley who now lives in Philly with his family comes out here Paul is known for among other things being a great entrepreneur tech geek loves tech loves to build build startups started one of the first social networks with Mark Pincus called tribe started his own company funded by Kleiner Perkins with his partner Chris law called aggregate knowledge which is booming and doing great and now more famous for being the first round investor in zynga company that is exploding with revenue as Kleiner Perkins said is the of all their portfolio comes in the history more than Google's made more money faster than anybody Paul Martino welcome to the extraction point great to see you John as always awesome to see you first I got to start with your now I forgot to mention that you're actually running a venture firm so in addition to being famous with Zynga you're running bullpen capital so first give the folks out there an update and first confirm or deny you were in the first round of Zynga or not yes the the first round of Zynga there were several institutional investors and several individual investors Morocco me Reid Hoffman were individual investors Avalon Union Square accelerator ventures and foundry where the institutional investors in that first round Peter was Peter Thiel yeah Peter was also an individual investor in the first round so that's officially the first round investors of Zynga we have clarified that and that is now hot on the books but now you're you've been successfully founded aggregate knowledge you know have a CEO running that what's the update with aggregate knowledge yeah so great guy runs that company as a guy you need to meet and have on this show Dave jakubowski aggregate knowledge really went in a direction where all of the focus was on providing data and analytics to the major ad agencies and John John Nelson who started organic one of the first agencies is now the CEO of Omnicom digital joined the board and I said look we got to get a guy who's an ad heavy in here and jakubowski was previously the GM of microsoft adcenter and had a senior position at specific media and we brought him in and he's just been kickin butt our greek knowledge has really really made a significant significant contribution in the area of data and analytics for these major agencies and he was very able to bring in a crew of people know exactly how to run that business so you're a big fan of big data then mm-hmm oh yeah we just had a big special yesterday on Big Data mentioned about it so that's cool we're going to get into a lobbyist I was just kind of get the small talk out of the way here your current role is the founder of bullpen capital right so bullpen to me I'm a baseball not I love baseball bullpen means you go the bullpen for relief right yep thank God close the game out hopefully or mid-innings relief so tell us about what bullpen is it's a special fund as I know from reading talk to you to target an expansion of this new seed and explosive new funding environment Bryce plain force right I'll tell you how we got the name at the end too so here's what happened I've been investing with a lot of the so-called super angels and that's kind of a misnomer because they really are actually in some cases actual small venture firms to I've been investing with a lot of them since they got off the ground Josh Kopelman from first round is one of the first investors in aggregate knowledge mike maples was an early advisor to the company I've known Jeff claw be a who run soft tech since he was at Reuters and with the late 90s and so I've worked with these guys done a lot of investing and we were me and my buddies Duncan Davidson rich Melman were sitting around over summer of 09 doing a little bit data analysis right another big data assignment we realized that as more and more these seed funds got created they were creating an inventory of companies that weren't quite ready to go to the traditional venture guy but we're also difficult to bridge from just the seed guys because the see guys at that time didn't have really big funds so wait a minute you've got some really good companies here is to clarify the for the folks out there seed funds don't traditionally have follow-on big funds like a VC firm right that's what you're referring to yeah they tend not to have as bigger reserve so if a big fun writes you a five-million-dollar check and you stub your toe you can probably get some more money to get through the hardships but a lot of the the new super angel funds or smaller funds and you get a five hundred thousand dollar check and if you need another five hundred thousand dollars it can frequently be very difficult because they make so many investments with smaller reserves yeah and so you've got dave McClure clavey a maples first round capital true ventures made the first round truevision more traditional VC then say dave McClure and mike maples and claw VA they're out doing some really good work out their funding really good company spending a lot of time I know I've seen them working their butt off yeah they need some air support right they need some cover the little bullpen is that that's you come in and say hey for your stars they're going to rise up yep and so that's exactly right so what happens is here's what the analysis we did turned out of their portfolio thirty percent of their portfolios in aggregate quickly are really exciting companies you know and they quickly go up to a venture auction and the guys and sandhill rotor excited about it about twenty percent of their deals you know that they don't like too much it's kind of just floating there yeah that you know the entrepreneur wasn't a fit that team didn't execute that left fifty percent of their deals in the middle which they kind of were too early to tell as Mike maple sometimes says they were in an extended learning and discovery phase they hadn't quite figured out what their models yeah and this de pivoting stuff's going on right now the Marcus changes turbulence so these guys are right and so you look you look at some examples and you go well wait a minute for every zynga that goes up into the right immediately go look at the stories of chegg and modcloth and etsy and quite frankly the in-between round on twitter and for everyone Zynga that you find that just hits it out of the park the right way there were four to five companies that went through that hard intermediate round that it was difficult in the environment where you have only a potentially thinly capitalized seed fund in front of you go get through that difficult point I said guys you need a bull pen and way we came up with the name is I'm involved in a deal with Chad Durbin who used to pitch for the Phillies and now as a relief pitcher for the cleveland indians and he was in our office and we were talking about this idea and Chad said yeah it's kind of like you're building a bullpen for the seed guys I'm like that's exactly right that's the name we got to go with and so fortunately I was involved in in this company called showcase you which is actually cool cited suppose for recruiting for college scholarships for a collegiate athletes right you're a high school student you throw 80 miles an hour left hand it and you're in 10th grade how do you figure out where the right scholarships are so Durbin and some of the Phillies where the original investors in this company called showcase you it's actually a cool company as the combine work out online basically fries for the high school kids and because the high school kids sometimes are in tough geographies to get to you're in you're in a small rural area in Nebraska how do they find out that you're the guy who can throw 89 miles an hour great so I mean this VC market so basically you're referring to with bullpen right now is an innie and you've been in our sprayer so you live through classic you know classic financing your last company financed by kleiner perkins and a tribe i forget who financed tribe yet Mayfield was the lead investor may feel again another traditional VC firm all tier 1 VCS although may feel people are you now is slipped a little bit that's some of their key partners who have slipped away but they've all moved on what you're really referring to is there's a new dynamic of entrepreneurship going on now we're now there are some break outcomes that just need a little bit more time to mature in the old model they just be kind of closed down the VC guy would be on the Bora has just a pain in the ass and you know really not growing and do another round it's they get kind of lazy in a way if they got 10 10 boards are on so with the super angels and the fact that does take a lot of cash to start a company you've got more deals getting done so the the Y Combinator the Dave McClure's and chef claw va's in the mike maples and sometimes SiliconANGLE labs which we're doing here is telling you about right we're funding companies the more [ __ ] is funded a better will you come in as you keep them alive longer just wreck the pivot possibly that's right and so what happens is right now the venture industry is being disrupted the same way the venture industry has funded companies that have rupted other industries they are being disrupted in the exact same way and the disruption happened from below as always happens it started in seed stage now in order for the disruption to go all the way through there need to be companies that come after seed stage investors that have the same philosophy and mentality pro entrepreneur easy terms operating people who get their hands dirty to get deals done you need that in the B stage and in the sea stage and here's what our prediction is John our prediction is a few years from now there'll be a company that comes after bullpen that does series c and series d financing or mezzanine financing but the same philosophy is bullpen and then DST s at the end of that chain and you can imagine building companies that go all the way to liquidity that you got money from maples first bullpen second this unnamed company third and you went quasi-public with DST and you've bypassed the entire venture scheme entirely and the entire institutional public markets complete liquidity wealth creation companies creating jobs I mean this is new paradigm I mean this isn't amazing I mean this is a potentially amazing point in the history of us finance the idea that you could go two billion dollar outcomes by passing not only the public markets on the back side but the traditional venture ecosystem on the front side I mean that is a disruption if ever there was one amen I mean hi and with you a hundred percent the other some people who will argue regulation is if market forces first of all I'm a big believer in market forces so I think what you're doing is clearly identifying an opportunity that dynamics are all lying lining up entrepreneurs are validating it and so but the questions are regulations I mean first of all I'm anti-regulation but as you start to get to that liquidity and some are arguing I even wrote a blog post about saying hey you know basically Facebook's public merry go buddy what do you say to those guys this is the change in the history of this financial asustor we want the government regulating this yeah so my co-founder of both i started bullpen with two really good guys Duncan Davison who was the founder covad was advantage point for years asking them to buy government regulation would go bad i mean what happened then because of the I lack warsi like Wars but only that the some extent covet doesn't exist unless the telco 1994 happens through in some ways a creation of the government to good point it's social right but but think about it the arbitrariness of government as opposed to a well-thought-out centralized plan so anyway so Duncan sometimes uses that phrase you know he talks a lot about the way in which the government you know that the worst thing you can ever hear is I'm with the government I'm here to help right i mean that's about the way it goes but his point around the the the new quasi public markets is money we'll find a way yeah and when sarbanes-oxley happens and it's tough to go public and you're a CEO like Pincus who's running one of the great all-time companies in Silicon Valley at Zynga he says you know going public is not an entrance is not an exit it's an entrance that's that's this quote what why would I why do I need that headache I mean I was just talking with Charles beeler who sold for the hell dorado he sold to compel in one of his investments to dell for over a billion dollars and and 3 para nother firm he wasn't on that one that was sold to HP during storage wars he's talking about the lawsuits literally this shakedown of immediately filed lawsuits you know you could have got more money so this is this public markets brutal no doubt no doubt i think what you're doing is a revolution I'm all excited about this new environment again anything with his liquidity wealth creation with the engine of innovation can be powered that's fantastic look back the startups okay get back to where you're playing yeah the history of Silicon Valley was built on the notion of value add some have said over the past 10 years venture capital has not been truly value add and some were arguing value subtract and then just money so what you're talking about here is getting in and helping me stay alive what's the value added side of the equation mean I know that a lot of these folks like like like ourselves here it's looking angle McClure Xavier and maples and true ventures they roll their sleeves up first round capital right before we can only provide so much it kind of expands right you guys are filling in the capital market side right how are you guys helping out on the value add because a lot of those companies may be the next Twitter right you've got a bridge to finance that's right allow them to do the pivot or get the creative energy to grow and they hit that market if they hit that hit it going vertical you got it kind of sometimes nurture it you guys have a strategy for that talk about the so let me let me give you my perspective on that so I think 10 years ago when you're starting a company the name of the venture firm was more important than potentially the partner on your board ten years later the name of the firm matters much less and it's the name of the partner and it's the operating experience that that partner partner brought to bear and you go talk to the 24 year old entrepreneur verse the 34 year old entrepreneur the 24 entrepreneur 24 year old entrepreneur wants a guy like you or a guy like me on his board he wants have been there done that started a company was a CEO exited it got fired hired people fired other people scar tissue scars knowledge experience exactly and if a good friend of mine who's in the traditional business I'll leave his name out of it he sometimes says the following phrase the era of the gentleman VC is over and what he means by the era of the gentleman VC is over is you know if your background is you were a junior associate who came in with a finance degree in an MBA and it never started a company you're not going to get picked by the entrepreneur anymore in 10 years from now almost everyone in the business is going to have a resume that looks more like a Cristal Paul Martino a mark pincus that you name all the people who we've started our companies with if there's a lot more hochberg with track record certainly with with the kind of big companies in the valley just in our generation yet started with netscape google paypal right now i want to see facebook is and then now's inga either the ecosystem is just entered intertwined I mean for every failure that spawns more success right so that's right that's a Silicon Valley way yeah well a tribe was tribe was a perfect example of a successful failure tribe was not a successful outcome but it was in many ways a very successful way to actually pioneer what became social networking you know investments got made into Facebook as a result of that Zynga in aggregate knowledge were both the outcrops of what was learned to some extent the original business case of Zynga was remarkably simple there is a ton of time being spent on social networks and after you get done finding your buddies and looking at photos what do you do and Pincus is original vision to some extent was let's have games to play and that insight doesn't happen that way unless you don't do tribe and go into the trenches and get the scars on your back and your in your your second venture of our adventure right at the tribe was aggregate knowledge was similar concept people are connected I mean you got to be excited though I mean you know you were involved in tribes very early on all the stuff that you dealt with activity streams newsfeed connections the social science you know the one that one of the nicest pieces of validation of this recently was over in q4 of 2010 seven of the patents that me Chris law Elliot low and Brian Waller wrote got issued now they're all owned by Cisco Cisco bought tribe in the end they bought the assets in the and the patent filings but there are patent filings that go back to 2002 on the corner stones and hallmarks of what social networking really is that we wrote back then that have now issued order granted or sitting in the cisco portfolio and well that's kind of like a consolation prize and that there wasn't a big outcome for tribe it is very validating to see that those original claims on really cutting-edge stuff have been had been issued and I'm excited about that you should be proud i'm proud to know your great guy you have great integrity you're going to do well as a venture capitalist i think you people will trust you and you're fair and there's two types of people in this world people who help people people who screw people so you know you really on one side of the other you're you're not in between you're truly on the on the good side I really enjoy you know having chatting with you but let's talk about entrepreneurship from that perspective about patents you know I'm try was an outcome that we all can relate to the peplum with Facebook of what Zuckerberg and and those guys are doing over there that's entrepreneurship so talk to the entrepreneurs out there yeah hey you know what you do some good work it all comes back to you talk about the the Karma of entrepreneurship a failure is not a bad thing it's kind of a punch line these days I'll failures are stepping stone to the next thing but talk about your experience and lets you and i talk about how to deal with faith for those first-time entrepreneurs out there in their 20s what just give them a sense of how to approach their venture and if it fails or succeeds what advice would you give them yeah well like winning and losing is important part of the game I mean certain companies are going to be successful in certain ones art and if you go and start ten unsuccessful companies maybe this isn't exactly the business for you but that said how you the game is important as well and if you're a high integrity guy who gets good investors and you make quality decisions and let's say the market wasn't a fit you're going to get the money the second time because people said you know I work with that guy that guy really did a good job you know they never got it quite right but this is a guy learn the right lessons so when I'm coaching a first-time CEO and i'm the CEO coach of a couple guys now you know i'm looking for someone who's sitting there going hey i not only want to do this to win and be successful but i want to learn i I want to do this better than no one no one walks in and says I learn from my failure I hope I'm successful I mean you let it go and say hey I'm gonna be successful I want to win failure is not an option but failure happens right i mean you know it's bad breaks that mean but but here is the key less I tell this to all of the entrepreneurs I work with you will not be successful if you're making mistakes that were made by those before you if you make novel mistakes you're in good company right and so only ever make a novel mistake I made a good example this is one claw and I started Chris law and I started aggregate knowledge aggregate knowledge was the original business model was around recommendations and there were dead bodies in front of us there was net perceptions there was fire fly and she was in the office this morning with Yazdi one of the founders of [ __ ] cast with it man yeah so predictive analytics residi what did we do we went out and we I flew out and met John riedle University of Minnesota who was the founder of net perceptions I dug up yes d i got these guys on my advisory board and while aggregate knowledge was not successful in the recommendation business and pivoted into the data management thing we made novel mistakes we did not repeat the mistakes of met perceptions and firefly and so i think that's an important important lesson to an entrepreneur if you're going into an area that has dead bodies in front of you you better research them you better know who they are you better know what happened and you better make sure that if you screw it up you at least screw it up in a way which none of us could have predicted yeah that's the only way you're going to get a hall pass on that well let's talk about talk about some of the hot Renisha of activity saw so you're in that sector where you're feeding the seed the super angels in the first rounds early stage guys and it's a good fit what about some of the philosophies on like the firms out there there's of this to this two philosophies I just taught us to an entrepreneur here you met on the way out a street speaker text and there at seven you know under a million dollars in financing hmm series a yeah and then you got in the news yesterday color 41 million dollars building to win magnin flipboard a hundred million dollars i got this is these guys that we know i mean there are yep our generation and a little bit around the same time and certainly they have pedigree so remember the old days the arms race mentality right when the sector at all costs right that's kind of what's going on here i mean some of the command that kind of money there's actually an auction going on what do you make of that I mean bubble is an arms race so so rich Melman inside a bullpen de tu fascinating analysis he looked at the full portfolio of 28 took about 20 of the best super angels by the way the super angles are all different some are micro vc summer buying options etc so so first off super angel is a weird word but it's everybody from Union Square and foundry on one side first round and flooding but any take the top 20 or so of these guys and look at their portfolios what's amazing about their portfolios is the unlike 10 and 20 years ago in prior tech bubbles there are not 20 companies doing the same thing when you categorize them yeah ten percent are in ad tech ten percent our direct-to-consumer consider but like forty percent are one-offs that is this is I think one of the first times in the history of venture that forty percent of the deal flow is a one-off unique business idea that there aren't 30 guys going to do and I think that the importance of that to what happens in this next stage of the tech boom we don't know what that means yet because back in the day well we need to just we're venture firm we need to disk drive company okay so your venture firm you've got your disk drive companies and I'll 20 venture friend knows if drive out and created the herd mentality everyone talks about with venture yep mean I was an opponent on a talk on here in the cube and I don't think I actually put in a blog post but I called the era of entrepreneurship like with open sores and low cost of entry with cloud computing and now mobility the manure of innovation where you know in the manure that's being out in the mark place mushrooms are growing out of it right and these you don't know what's going to be all look the same in a way so how do you tell the good ones from the bad ones so it's hard right so you have a lot of one you have a lot more activity hence angel list hence the super in rice so so the economics and the deal flow are all there the question is how do you get them from being just a one-off looked good on paper flame out the reality yeah well look in my opinion seed stage investing is about investing in people and I think when big firms trying to seed stage investing there's an impedance mismatch a lot of times because they want more evidence they want to know did the market work to the management then this is this is an early stage venture and am I going to want to go in a foxhole with this person and in many ways the good super angels are instinctive investors who are betting on people that they want to be in the foxhole with and yeah did they do it before do they know how to hire people is the market reasonably interesting but guess what they're probably gonna pivot three times so wait a minute at the end of the day you got to invest in people later stage venture is not you can look at discounted cash flows you can look at mezzanine financing you can do traditional measures but if you're going to invest in two people who have a prototype and need five hundred thousand dollars you're investing in people at that point what do you think about the OC angel is I'm a big fan of and recently was added thanks to maybe out there but even though i'm not i don't really co-invest with anyone else other than myself maybe you guys would bullpen but but if that's a phenomenon you don't have angel list which is opening up doors for deal flow companies are getting funded navales getting yeah a ton of activity nivea doing great job with venture hacks i get y combinator which I called the community college of startups they bring in like they open the door and I mean that an actually good way don't mean that negatively I mean they're giving access to entrepreneurs that never had access to the market right and now you have Paul Graham kind of giving the halo effect or thrown the holy water on certain stars and they get magically funded but yesterday at an event and they're they're packed right I've heard from VC saying I'm not invited because I didn't wasn't part of the original investment class so it seems that Y comma day is getting full yeah so do you see that you agree is there will be an over lo y combinator you know kind of like I've TED Conference has you know Ted they'll be you know y combinator Boston little franchises will be like barcamp for sure I mean look and look at techstars they franchise they'd I was over there with Dave Tisch in New York there's TechStars New York after those TechStars older in techstars seattle there is no doubt in my mind that right now there is an over investment in the seed stage meaning that there is a little bit of a seed bubble going on that's not necessarily bad though because in terms of raw dollars there's not a bubble yet Rory who's over at rafi it smells like a bubble it looks like a bubble but when you look at the mechanic when you look at the actual total dollars it's not a bubble rory who has a hinge recent Horowitz been said that that it's a boom not a bubble yeah so don't be confused it looks like bubbles and booms kind of look together the same right I actually I'm not quite sure I had the exact data right but here's the quick summary if you take a look at venture capital investment as a percent of GDP historically it's been something like point one percent of GDP in the bubble back in 99 it went to one percent something like it went 10x higher right now we're still at point one percent but since it's very much centered around the seed stage investing you see this frothiness in the sea but until that number goes from point 1 percent of GDP back up to one percent there's no real bubble because the tonnage of money hasn't come in yet and so so it's starting but this is what a tech boom feels like the early stages are excitement and lots of ideas and lots of flowers blooming and then the big money comes in because John I'll bet you're your brother and your sister and your mom haven't invested in a tech startup back in 99 video there's no public market that supports seven in a way that's a good and bad star basement yeah there's no fraud going on and most of the companies that are out there whether their lifestyle business or seed or bullpen funded are actually generating income the entrepreneur he has any earlier Mike was saying that he could a business deal so people are kind of like saw the old bubble and said shoot I don't want to do that again I gotta have at least revenue right and so companies didn't seem to start out with cash so you know that because you invested it but you know Pincus was getting some cash flow in the door from day one that's right that company was company was profitable the first day it started basically so talk about you know so I'm with Paul Martino by the way with bullpen capital entrepreneur wrote the patents on social networking which he sold the cisco when they sold the company now with bullpen capital huge dynamic you're a company out there this is exactly the positive dynamic you want to see because mainly you know dave mcclure jeff clavier mike maples have been kind of getting their butts handed to them in the press about super angels not having the juice to kind of go anywhere and it's been kind of a negative press there so you know this is the kind of void that's been filled by you guys to show the market that look at this there's a road map here so even though that the McClure's and clubs don't have big funds that there's a path to follow on financing so that the vc's can't shut them down and i've heard some pc say that so a lot of traditional venture guys would like to say that you know this little disruption we nipped it in the butt and it stopped after the seed stage but that's not the history of disruptions the history of disruptions are they start from the bottom then they get ecosystem support and then they grow and they disrupt the incumbents and I think we're halfway there so so the Angel gate thing that Arrington reported on was interesting because you know essentially what happened there it was a lot of him fighting Ron Conway I was not happy you can't be happy about competition I mean this is competition that increases prices right so you know in the short term prices have been inflated on valuations true or false that's true but but but I think I think the whole way angel gate was reported was absurd the most Pro entrepreneurial venture people perhaps in the history of the business are the guys who were supposedly at those tables I mean mike maples Jeff claw VA josh cop and Ron Conway fired his guy that was there I I understand suppose again suppose a key are right these are the most Pro entrepreneurial venture guys in the history of the business so I think that turned into something that it never was yeah well I mean that's the thing you know good for content producers who want page views I got to create some drama and you know as you know SiliconANGLE doesn't have any banner ads on our site quick plug for us we are motivated by content not page views so thanks for coming in today no but seriously I mean there's a there's a black cloud over the super angels has been since Angel gate I've heard privately from VCS that super angels it's been kind of a scuttlebutt they're misaligned just rumors I completely overblown and you know their business model threatens the incumbents and you know someone needed someone needed a piece of fodder to start a you know start a techcrunch discussion right there's no doubt that the market is need in need of a new ecosystem for the early stage because individual angels traditionally were wealthy individuals but now you have people with more experience like yourselves and entrepreneurs from google and facebook etc coming out and doing some things okay so next topic more on a personal kind of professional note k last final question is I know you got to run appreciate your time you're a technologist a lot of folks don't know that you're hardcore computer science guy and our model southern angles computer science meet social science right in your wheelhouse so with that just kind of final parting question what gets you excited technically right now I mean I'll see you have roots in both comps I and social Iran Zynga's early investor roster you got a bullpen capital you're looking at a lot of deals outside of that you as a computer scientist geek mm-hmm what gets you jazz what do you see in the horizon that's not yet on the mega trend roster that kind of you can't put your finger on it truly we might really get a good feeling well so I think you'll be disappointed with this answer because I think it's now cross the chasm to start being one of those mega trends it's called consumerization of enterprise and that's now the buzz word for it but what is it really mean and why do I think it's for real look you've got cool self-service applications for everything you can go do home banking by logging into a portal you can go to an ATM you can go do these things but you know go bring a new laptop into your big stodgy fortune 500 company and you know it's like getting a rectal exam right you know we got to install this we got to give you this private key yet that's TSA it writes like going through TSA exact idea that IT inside of big fortune 500 companies is going to stop being this gatekeeper to new technology I think look how long do you think it'll be until pick your favorite fortune 500 company the IT people know how to deal with the ipad 2 but how many people bought an ipad 2 into the off already everyone and so this to me is going to be the big next deck the next decade are going to be self service offerings for the enterprise getting around a very frustrating gatekeepers inside of you know the IT department etc and that's going to lead to an awesome boom of everything from security to auditing to compliance etc that's the convergence question Paul Martino my friend entrepreneur great guy venture capitals now on the good side helping the seed Super Angel micro VCS great to have you consumerization of IT that hits the cloud mobile social it's everything so that I was buzzword compliant on that great job great to have you know you're busy got to have you in again thanks so much for time that's a wrap thank you very much great thank you John