>> live from Boston, Massachusetts. It's the Cube covering A W s reinforce 2019. Brought to you by Amazon Web service is and its ecosystem partners. >> Well, welcome back. Everyone's Cube Live coverage here in Boston, Massachusetts, for AWS. Reinforce Amazon Web sources. First inaugural conference around security. It's not Osama. It's a branded event. Big time ecosystem developing. We have returning here. Cube Alumni Bill Jeff for VP of strategy and the partnerships that Iron Net Cyber Security Company. Welcome back. Thanks. General Keith Alexander, who was on a week and 1/2 ago. And it was public sector summit. Good to see you. Good >> to see you. Thanks for >> having my back, but I want to get into some of the Iran cyber communities. We had General Qi 1000. He was the original commander of the division. So important discussions that have around that. But don't get your take on the event. You guys, you're building a business. The minute cyber involved in public sector. This is commercial private partnership. Public relations coming together. Yeah. Your models are sharing so bringing public and private together important. >> Now that's exactly right. And it's really great to be here with eight of us were really close partner of AWS is we'll work with them our entire back in today. Runs on AWS really need opportunity. Get into the ecosystem, meet some of the folks that are working that we might work with my partner but to deliver a great product, right? And you're seeing a lot of people move to cloud, right? And so you know some of the big announcement that are happening here today. We're willing. We're looking to partner up with eight of us and be a first time provider for some key new Proactiv elves. AWS is launching in their own platform here today. So that's a really neat thing for us to be partnered up with this thing. Awesome organization. I'm doing some of >> the focus areas around reinforcing your party with Amazon shares for specifics. >> Yes. So I don't know whether they announced this capability where they're doing the announcement yesterday or today. So I forget which one so I'll leave that leave that leave that once pursued peace out. But the main thing is, they're announcing couple of new technology plays way our launch party with them on the civility place. So we're gonna be able to do what we were only wanted to do on Prem. We're gonna be able to do in the cloud with AWS in the cloud formation so that we'll deliver the same kind of guy that would deliver on prime customers inside their own cloud environments and their hybrid environment. So it's a it's a it's a sea change for us. The company, a sea change for a is delivering that new capability to their customers and really be able to defend a cloud network the way you would nonpregnant game changer >> described that value, if you would. >> Well, so you know, one of the key things about about a non pregnant where you could do you could look at all the flows coming past you. You look at all the data, look at in real time and develop behavior. Lana looks over. That's what we're doing our own prime customers today in the cloud with his world who looked a lox, right? And now, with the weight of your capability, we're gonna be able to integrate that and do a lot Maur the way we would in a in a in a normal sort of on Prem environment. So you really did love that. Really? Capability of scale >> Wagon is always killed. The predictive analytics, our visibility and what you could do. And too late. Exactly. Right. You guys solve that with this. What are some of the challenges that you see in cloud security that are different than on premise? Because that's the sea, So conversation we've been hearing. Sure, I know on premise. I didn't do it on premises for awhile. What's the difference between the challenge sets, the challenges and the opportunities they provide? >> Well, the opportunities air really neat, right? Because you've got that even they have a shared responsibility model, which is a little different than you officially have it. When it's on Prem, it's all yours essential. You own that responsibility and it is what it is in the cloud. Its share responsible to cloud provider the data holder. Right? But what's really cool about the cloud is you could deliver some really interesting Is that scale you do patch updates simultaneously, all your all your back end all your clients systems, even if depending how your provisioning cloud service is, you could deliver that update in real time. You have to worry about. I got to go to individual systems and update them, and some are updated. Summer passed. Some aren't right. Your servers are packed simultaneously. You take him down, you're bringing back up and they're ready to go, right? That's a really capability that for a sigh. So you're delivering this thing at scale. It's awesome now, So the challenge is right. It's a new environment so that you haven't dealt with before. A lot of times you feel the hybrid environment governed both an on Prem in sanitation and class sensation. Those have to talkto one another, right? And you might think about Well, how do I secure those those connections right now? And I think about spending money over here when I got all seduced to spend up here in the cloud. And that's gonna be a hard thing precisely to figure out, too. And so there are some challenges, but the great thing is, you got a whole ecosystem. Providers were one of them here in the AWS ecosystem. There are a lot here today, and you've got eight of us as a part of self who wants to make sure that they're super secure, but so are yours. Because if you have a problem in their cloud, that's a challenge. Them to market this other people. You talk about >> your story because your way interviews A couple weeks ago, you made a comment. I'm a recovering lawyer, kind of. You know, we all laughed, but you really start out in law, right? >> How did you end up here? Yeah, well, the truth is, I grew up sort of a technology or myself. My first computer is a trash 80 a trs 80 color computer. RadioShack four k of RAM on board, right. We only >> a true TRS 80. Only when I know what you're saying. That >> it was a beautiful system, right? Way stored with sword programs on cassette tapes. Right? And when we operated from four Keita 16 k way were the talk of the Rainbow Computer Club in Santa Monica, California Game changer. It was a game here for 16. Warning in with 60 give onboard. Ram. I mean, this is this is what you gonna do. And so you know, I went from that and I in >> trouble or something, you got to go to law school like you're right >> I mean, you know, look, I mean, you know it. So my dad, that was a chemist, right? So he loved computers, love science. But he also had an unrequited political boners body. He grew up in East Africa, Tanzania. It was always thought that he might be a minister in government. The Socialist came to power. They they had to leave you at the end of the day. And he came to the states and doing chemistry, which is course studies. But he still loved politics. So he raised at NPR. So when I went to college, I studied political science. But I paid my way through college doing computer support, life sciences department at the last moment. And I ran 10 based. He came on climate through ceilings and pulled network cable do punch down blocks, a little bit of fibrous placing. So, you know, I was still a murderer >> writing software in the scythe. >> One major, major air. And that was when when the web first came out and we had links. Don't you remember? That was a text based browser, right? And I remember looking to see him like this is terrible. Who would use http slash I'm going back to go for gophers. Awesome. Well, turns out I was totally wrong about Mosaic and Netscape. After that, it was It was it was all hands on >> deck. You got a great career. Been involved a lot in the confluence of policy politics and tech, which is actually perfect skill set for the challenge we're dealing. So I gotta ask you, what are some of the most important conversations that should be on the table right now? Because there's been a lot of conversations going on around from this technology. I has been around for many decades. This has been a policy problem. It's been a societal problem. But now this really focus on acute focus on a lot of key things. What are some of the most important things that you think should be on the table for techies? For policymakers, for business people, for lawmakers? >> One. I think we've got to figure out how to get really technology knowledge into the hands of policymakers. Right. You see, you watch the Facebook hearings on Capitol Hill. I mean, it was a joke. It was concerning right? I mean, anybody with a technology background to be concerned about what they saw there, and it's not the lawmakers fault. I mean, you know, we've got to empower them with that. And so we got to take technologist, threw it out, how to get them to talk policy and get them up on the hill and in the administration talking to folks, right? And one of the big outcomes, I think, has to come out of that conversation. What do we do about national level cybersecurity, Right, because we assume today that it's the rule. The private sector provides cyber security for their own companies, but in no other circumstance to expect that when it's a nation state attacker, wait. We don't expect Target or Wal Mart or any other company. J. P. Morgan have surface to air missiles on the roofs of their warehouses or their buildings to Vegas Russian bear bombers. Why, that's the job of the government. But when it comes to cyberspace, we expect Private Cummings defending us everything from a script kiddie in his basement to the criminal hacker in Eastern Europe to the nation state, whether Russia, China, Iran or North Korea and these nation states have virtually a limited resource. Your armies did >> sophisticated RND technology, and it's powerful exactly like a nuclear weaponry kind of impact for digital. >> Exactly. And how can we expect prices comes to defend themselves? It's not. It's not a fair fight. And so the government has to have some role. The questions? What role? How did that consist with our values, our principles, right? And how do we ensure that the Internet remains free and open, while still is sure that the president is not is not hampered in doing its job out there. And I love this top way talk about >> a lot, sometimes the future of warfare. Yeah, and that's really what we're talking about. You go back to Stuxnet, which opened Pandora's box 2016 election hack where you had, you know, the Russians trying to control the mean control, the narrative. As you pointed out, that that one video we did control the belief system you control population without firing a shot. 20 twenties gonna be really interesting. And now you see the U. S. Retaliate to Iran in cyberspace, right? Allegedly. And I was saying that we had a conversation with Robert Gates a couple years ago and I asked him. I said, Should we be Maur taking more of an offensive posture? And he said, Well, we have more to lose than the other guys Glasshouse problem? Yeah, What are your thoughts on? >> Look, certainly we rely intimately, inherently on the cyber infrastructure that that sort of is at the core of our economy at the core of the world economy. Increasingly, today, that being said, because it's so important to us all the more reason why we can't let attacks go Unresponded to write. And so if you're being attacked in cyberspace, you have to respond at some level because if you don't, you'll just keep getting punched. It's like the kid on the playground, right? If the bully keeps punching him and nobody does anything, not not the not the school administration, not the kid himself. Well, then the boy's gonna keep doing what he's doing. And so it's not surprising that were being tested by Iran by North Korea, by Russia by China, and they're getting more more aggressive because when we don't punch back, that's gonna happen. Now we don't have to punch back in cyberspace, right? A common sort of fetish about Cyrus is a >> response to the issue is gonna respond to the bully in this case, your eggs. Exactly. Playground Exactly. We'll talk about the Iran. >> So So if I If I if I can't Yeah, the response could be Hey, we could do this. Let them know you could Yes. And it's a your move >> ate well, And this is the key is that it's not just responding, right. So Bob Gates or told you we can't we talk about what we're doing. And even in the latest series of alleged responses to Iran, the reason we keep saying alleged is the U. S has not publicly acknowledged it, but the word has gotten out. Well, of course, it's not a particularly effective deterrence if you do something, but nobody knows you did it right. You gotta let it out that you did it. And frankly, you gotta own it and say, Hey, look, that guy punch me, I punch it back in the teeth. So you better not come after me, right? We don't do that in part because these cables grew up in the intelligence community at N S. A and the like, and we're very sensitive about that But the truth is, you have to know about your highest and capabilities. You could talk about your abilities. You could say, Here are my red lines. If you cross him, I'm gonna punch you back. If you do that, then by the way, you've gotta punch back. They'll let red lines be crossed and then not respond. And then you're gonna talk about some level of capabilities. It can't all be secret. Can't all be classified. Where >> are we in this debate? Me first. Well, you're referring to the Thursday online attack against the intelligence Iranian intelligence community for the tanker and the drone strike that they got together. Drone take down for an arm in our surveillance drones. >> But where are we >> in this debate of having this conversation where the government should protect and serve its people? And that's the role. Because if a army rolled in fiscal army dropped on the shores of Manhattan, I don't think Citibank would be sending their people out the fight. Right? Right. So, like, this is really happening. >> Where are we >> on this? Like, is it just sitting there on the >> table? What's happening? What's amazing about it? Hi. This was getting it going well, that that's a Q. What's been amazing? It's been happening since 2012 2011 right? We know about the Las Vegas Sands attack right by Iran. We know about North Korea's. We know about all these. They're going on here in the United States against private sector companies, not against the government. And there's largely been no response. Now we've seen Congress get more active. Congress just last year passed to pass legislation that gave Cyber command the authority on the president's surgery defenses orders to take action against Russia, Iran, North Korea and China. If certain cyber has happened, that's a good thing, right to give it. I'll be giving the clear authority right, and it appears the president willing to make some steps in that direction, So that's a positive step. Now, on the back end, though, you talk about what we do to harden ourselves, if that's gonna happen, right, and the government isn't ready today to defend the nation, even though the Constitution is about providing for the common defense, and we know that the part of defense for long. For a long time since Secretary Panetta has said that it is our mission to defend the nation, right? But we know they're not fully doing that. How do they empower private sector defense and one of keys That has got to be Look, if you're the intelligence community or the U. S. Government, you're Clinton. Tremendous sense of Dad about what you're seeing in foreign space about what the enemy is doing, what they're preparing for. You have got to share that in real time at machine speed with industry. And if you're not doing that and you're still count on industry to be the first line defense, well, then you're not empowered. That defense. And if you're on a pair of the defense, how do you spend them to defend themselves against the nation? State threats? That's a real cry. So >> much tighter public private relationship. >> Absolutely, absolutely. And it doesn't have to be the government stand in the front lines of the U. S. Internet is, though, is that you could even determine the boundaries of the U. S. Internet. Right? Nobody wants an essay or something out there doing that, but you do want is if you're gonna put the private sector in the in the line of first defense. We gotta empower that defense if you're not doing that than the government isn't doing its job. And so we gonna talk about this for a long time. I worked on that first piece of information sharing legislation with the House chairman, intelligence Chairman Mike Rogers and Dutch Ruppersberger from Maryland, right congressman from both sides of the aisle, working together to get a fresh your decision done that got done in 2015. But that's just a first step. The government's got to be willing to share classified information, scaled speed. We're still not seeing that. Yeah, How >> do people get involved? I mean, like, I'm not a political person. I'm a moderate in the middle. But >> how do I How do people get involved? How does the technology industry not not the >> policy budgets and the top that goes on the top tech companies, how to tech workers or people who love Tad and our patriots and or want freedom get involved? What's the best approach? >> Well, that's a great question. I think part of is learning how to talk policy. How do we get in front policymakers? Right. And we're I run. I run a think tank on the side at the National Institute at George Mason University's Anton Scalia Law School Way have a program funded by the Hewlett Foundation who were bringing in technologists about 25 of them. Actually. Our next our second event. This Siri's is gonna be in Chicago this weekend. We're trained these technologies, these air data scientists, engineers and, like talk Paul's right. These are people who said We want to be involved. We just don't know how to get involved And so we're training him up. That's a small program. There's a great program called Tech Congress, also funded by the U. A. Foundation that places technologists in policy positions in Congress. That's really cool. There's a lot of work going on, but those are small things, right. We need to do this, its scale. And so you know, what I would say is that their technology out there want to get involved, reach out to us, let us know well with our partners to help you get your information and dad about what's going on. Get your voice heard there. A lot of organizations to that wanna get technologies involved. That's another opportunity to get in. Get in the building is a >> story that we want to help tell on be involved in David. I feel passion about this. Is a date a problem? So there's some real tech goodness in there. Absolutely. People like to solve hard problems, right? I mean, we got a couple days of them. You've got a big heart problems. It's also for all the people out there who are Dev Ops Cloud people who like to work on solving heart problems. >> We got a lot >> of them. Let's do it. So what's going on? Iron? Give us the update Could plug for the company. Keith Alexander found a great guy great guests having on the Cube. That would give the quick thanks >> so much. So, you know, way have done two rounds of funding about 110,000,000. All in so excited. We have partners like Kleiner Perkins Forge point C five all supporting us. And now it's all about We just got a new co CEO in Bill Welshman. See Scaler and duo. So he grew Z scaler. $1,000,000,000 valuation he came in to do Oh, you know, they always had a great great exit. Also, we got him. We got Sean Foster in from from From Industry also. So Bill and Sean came together. We're now making this business move more rapidly. We're moving to the mid market. We're moving to a cloud platform or aggressively and so exciting times and iron it. We're coming toe big and small companies near you. We've got the capability. We're bringing advanced, persistent defense to bear on his heart problems that were threat analytics. I collected defence. That's the key to our operation. We're excited >> to doing it. I call N S A is a service, but that's not politically correct. But this is the Cube, so >> Well, look, if you're not, if you want to defensive scale, right, you want to do that. You know, ECE knows how to do that key down here at the forefront of that when he was in >> the government. Well, you guys are certainly on the cutting edge, riding that wave of common societal change technology impact for good, for defence, for just betterment, not make making a quick buck. Well, you know, look, it's a good business model by the way to be in that business. >> I mean, It's on our business cards. And John Xander means it. Our business. I'd say the Michigan T knows that he really means that, right? Rather private sector. We're looking to help companies to do the right thing and protect the nation, right? You know, I protect themselves >> better. Well, our missions to turn the lights on. Get those voices out there. Thanks for coming on. Sharing the lights. Keep covers here. Day one of two days of coverage. Eight of us reinforce here in Boston. Stay with us for more Day one after this short break.

>> Narrator: 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 along side John Furrier. We are joined by Jamil Jaffer, he is the VP Strategy and Partnerships at IronNet. Thanks so much for coming on theCUBE. >> Thanks for having me Rebecca. >> Rebecca: I know you've been watching us for a long time so here you are, soon to be a CUBE alumn. >> I've always wanted to be in theCUBE, it's like being in the octagon but for computer journalists. (laughing) I'm pumped about it. >> I love it. Okay, why don't you start by telling our viewers a little bit about IronNet and about what you do there. >> Sure, so IronNet was started about 4 1/2 years ago, 5 years ago, by General Kieth Alexander, the former director of the NSA and founding commander of US Cyber command. And essentially what we do is, we do network traffic analytics and collective defense. Now I think a lot of people know what network traffic analytics are, you're looking for behavioral anomalies and network traffic, trying to identify the bad from the good. Getting past all the false positives, all the big data. What's really cool about what we do is collective defense. It's this idea that one company standing alone can't defend itself, it's got to work with multiple companies, it's got to work across industry sectors. Potentially even with the governments, and potentially across allied governments, really defending one another. And the way that works, the way we think about that, is we share all the anomalies we see across multiple companies to identify threat trends and correlations amongst that data, so you can find things before they happen to you. And so the really cool idea here is, that something may not happen to you, but it may happen to your colleague, you find about it, you're defended against it. And it takes a real commitment by our partners, our companies that we work with, to do this, but increasingly they're realizing the threat is so large, they have no choice but to work together, and we provide that platform that allows that to happen. >> And the premise is that sharing the data gives more observational space to have insights into that offense, correct? >> That's exactly right. It's as though, it's almost like you think about an air traffic control picture, or a radar picture, right? The idea being that if you want to know what's happening in the air space, you got to see all of it in real time at machine speed, and that allows you to get ahead of the threats rather than being reactive and talking about instant response, we're talking about getting ahead of the problems before they happen so you can stop them and prevent the damage ahead of time. >> So you're an expert, they're lucky to have you. Talk about what you've been doing before this. Obviously a lot of experience in security. Talk about some about some of the things you've done in the past. >> So I have to admit to being a recovering lawyer, but you have to forgive me because I did grow up with computers. I had a Tandy TRS-80 Color computer when I first started. 4K of all more RAM, we upgraded to 16K, it was the talk of the rainbow computer club, what are you doing, 16K of RAM? (laughing) I mean, it was-- >> Basic programming language, >> That's right. (laughing) Stored on cassette tapes. I remember when you used to have to punch a hole in the other side of a 5 1/4 floppy disc to make it double sided. >> Right, right. >> John: Glory days. >> Yeah, yeah. I paid my way through college running a network cable, but I'm a recovering lawyer, and so my job in the government, I worked at the House Intelligence Committee, the Senate Foreign Relations Committee and then the Bush administration on the Comprehensive National Cybersecurity Initiative, both the Justice Department and the White House. >> You've seen the arc, you've seen the trajectory, the progress we're making now seems to me slower than it should be, obviously a lot of inertia as Amy Chasity said today about these public sector government agencies, what not. But a real focus has been on it, we've been seeing activity. Where are we with the state of the union around the modernization of cyber and awareness to what's happening? How critical are people taking this threat seriously? >> Well I think I variety of things to say on that front. First, the government itself needs modernize its systems, right? We've seen that talked about in the Obama administration, we've seen President Trump put out an executive order on modernization of federal infrastructure. The need to move to the cloud, the need to move to shared services, make them more defensible, more resilient long-term. That's the right move. We've seen efforts at the Department of Defense and elsewhere. They aren't going as fast as the need to, more needs to happen on that front. IT modernization can really be accelerated by shifting to the cloud, and that's part of why that one of the things that IronNet's done really aggressively is make a move into the cloud space, putting all of our back end in the cloud and AWS. And also, ability, capability to do surveillance and monitoring. When I say surveillance I mean network threat detection not surveillance of the old kind. But network threat detection in the cloud, and in cloud-enabled instances too. So both are important, right? Classic data centers, but also in modern cloud infrastructure. >> Yeah, one of the things people want to know about is what your enemy looks like, and now with the democratization with open source, and democratization of tools, the enemies could be hiding through obscure groups. The states, the bad actors and the state actors can actually run covert activities through other groups, so this is kind of a dynamic that creates confusion. >> No, in fact, it's their actual mode of operating, right? It's exactly what they do, they use proxies, right? So you'll see the Russians operating, looking like a criminal hacker group operating out of the eastern Europe. In part because a lot of those Russian criminal rings, in actuality. You see a lot of patriotic hackers, right? I would tell most people, if you see a patriotic hacker there's probably a government behind that whole operation. And so the question becomes, how do you confront that threat, right? A lot of people say deterrence doesn't work in cyberspace. I don't believe that. I think deterrence can and does work in cyberspace, we just don't practice it. We don't talk about our capabilities, we don't talk our red lines, we don't talk about what'll happen if you cross our red lines, and when we do establish red lines and they're crossed, we don't really enforce them. So it's no surprise that our enemies, or advisories, are hitting us in cyberspace, are testing our boundaries. It's cause we haven't really give them a sense of where those lines are and what we're going to do if they cross them. >> Are we making an progress on doing anything here? What's the state of the market there? >> Well the government appears to have gotten more aggressive, right? We've seen efforts in congress to give the Department of Defense and the US Intelligence Committee more authorities. You can see the stand up of US Cyber Command. And we've seen more of a public discussion of these issues, right? So that's happening. Now, is it working? That's a harder question to know. But the real hard question is, what do you do on private sector defense? Because our tradition has been, in this country, that if it's a nation-state threat, the government defends you against it. We don't expect Target or Walmart or Amazon to have service to air missiles on the roof of your buildings to defend against Russian Bear bombers. We expect the government to do that. But in cyberspace, the idea's flipped on its head. We expect Amazon and every company in America, from a mom and pop shop, all the way up to the big players, to defend themselves against script kiddies, criminal hacker gangs, and nation-states. >> John: And randomware's been taking down cities, Baltimore, recent example, >> Exactly. >> John: multiple times. Hit that well many times. >> That's right, that's right. >> Talk about where the US compares. I mean, here as you said, the US, we are starting to have these conversations, there's more of an awareness of these cyber threats. But modernization has been slow, it does not quite have the momentum. How do we rate with other countries? >> Well I think in a lot of ways we have the best capabilities when it comes to identifying threats, identifying the adversary, the enemy, and taking action to respond, right? If we're not the top one, we're in the top two or three, right? And the question, though, becomes one of, how do you work with industry to help industry become that good? Now our industry is at the top of that game also, but when you're talking about a nation-state, which has virtually unlimited resources, virtually unlimited man-power to throw at a problem, it's not realistic to expect a single company to defend itself, and at the same time, we as a nation are prepared to say, "Oh, the Department of Defense should be sitting on "the boundaries of the US internet." As if you could identify them even, right? And we don't want that. So the question becomes, how does the government empower the private sector to do better defense for itself? What can the government do working with industry, and how can industry work with one another, to defend each other? We really got to do collective defense, not because it makes sense, which it does, but because there is no other option if you're going to confront nation-state or nation-state enabled actors. And that's another threat, we've seen the leakage of nation-state capabilities out to a lot broader of an audience now. That's a problem, even though that may be 2013 called and wants it's hack back, those things still work, right? What we saw in Baltimore was stuff that has been known for a long time. Microsoft has released patches long ago for that, and yet, still vulnerable. >> And the evolution of just cyber essential command, and Cyber Command, seems to be going slow, at least from my frame. Maybe I'm not in the know, but what is the imperative? I mean, there's a lot of problems to solve. How does the public sector, how does the government, solve these problems? Is cloud the answer? What are some of the things that people of this, the top minds, discussing? >> Well and I think cloud is clearly one part of the solution, right? There's no question that when you move to a cloud infrastructure, you have sort of a more bounded perimeter, right? And that provides that ability to also rapidly update, you could update systems in real time, and in mass. There's not going around and bringing your floppy disc and loading software, and it sounds like that's sort of a joke about an older era, but you look at what happened with NotPetya and you read this great Wired article about what happened with NotPetya, and you look at Maersk. And the way that Maersk brought its systems back up, was they had domain controller in Africa that had gone down due to a power surge, where they were able to recover the physical hard drive and re-image all their world-wide domain controls off of that one hard drive. You think about a major company that runs a huge percentage of the world's ports, right? And this is how they recovered, right? So we really are in that, take your disc and go to computers. In a cloud infrastructure you think about how you can do that in real time, or rapidly refresh, rapidly install patches, so there's a lot of that, that's like a huge part of it. It's not a complete solution, but it's an important part. >> Yeah, one of the things we talk about, a lot of tech guys, is that this debate's around complexity, versus simplicity. So if you store your data in one spot, it's easy to audit and better for governing compliance, but yet easier for hackers to penetrate. From an IQ standpoint, the more complex it is, distributed, harder. >> Yeah I think that's right. >> John: But what's the trade off there? How are people thinking about that kind of direction? >> No that's a great question, right? There's a lot of benefits to diversity of systems, there's a lot of benefit to spreading out your crown jewels, the heart of your enterprise. At the same time, there's real resilience in putting it in one place, having it well defended. Particularly when it's a shared responsibility and you have partial responsibility for the defense, but the provider to, I mean, Amazon, and all the other cloud providers, Microsoft and Google, all have it in their own self interest to really defend their cloud really well. Because whether or not you call it shared responsibility, it's your stock price that matters if you get hit, right? And so, instead of you, Amazon, and all the other cloud players have an incentive to do the right thing and do it really well. And so this shared responsibility can work to both side's benefits. That being said, there's an ongoing debate. A lot of folks want to do there stuff on-prem in a lot of ways. You know, a lot of us are old school, right? When you touch it, you feel it, you know it's there. And we're working through that conversation with folks, and I think that at the end of the day, the real efficiency gains and the power of having super computing power at your fingertips for analytics, for consumer purposes and the like. I really think there's no way to avoid moving to a cloud infrastructure in the long run. >> I know you said you were a recovering lawyer, but you are the founding director of the National Security Institute at the Antonin Scalia School of Law. How are you thinking about educating the next generation of lawyers who could indeed become policy makers or at least work on these committees, to think about these threats that we don't even know about yet? >> That's a great question. So one of the things we're doing, is we're working through the process with the state commission on establishing a new LLM and cyber intelligence national security law. That'll be a great opportunity for lawyers to actually get an advanced degree in these issues. But we're also training non-lawyers. One of the interesting things is, you know, One of the challenges DC has, is we make a lot of tech policy, a lot of it not great, because it's not informed by technologists, so we've got a great partnership with the Hewlett Foundation where we're bringing technologists from around the country, mid-career folks, anywhere from the age of 24 to 38. We're bringing them to DC and we're educating them on how to talk to policy makers. These are technologists, these are coders, data scientists, all the like, and it's a real opportunity for them to be able to be influential in the process of making laws, and know how to involve themselves and talk that speak. Cause, DC speak is a certain thing, right? (laughing) And it's not typically consistent with tech speak, so we're trying to bridge that gap and the Hewlett Foundation's been a great partner in that effort. >> On that point about this collaboration, Silicon Valley's been taking a lot of heat lately, obviously Zuckerberg and Facebook in the news again today, more issues around irresponsibility, but they were growing a rocket ship, I mean, company's only 15 years old roughly. So the impact's been significant, but tech has moved so fast. Tech companies usually hire policy folks in DC to speak the language, educate, a little bit different playbook. But now it's a forcing function between two worlds colliding. You got Washington DC, the Silicon Valley cultures have to blend now. What are some of the top minds thinking about this? What are some of the discussions happening? What's the topic of conversations? >> Well look, I mean, you've see it in the press, it's no surprise you're hearing this talk about breaking up big tech companies. I mean, it's astounding. We used to live in world in which being successful was the American way, right? And now, it seems like at least, without any evidence of anti-trust concerns, that we're talking about breaking up companies that have otherwise hugely successful, wildly innovative. It's sort of interesting to hear that conversation, it's not just one party, you're hearing this in a bipartisan fashion. And so it's a concern, and I think what it reveals to tech companies is, man, we haven't be paying a lot of attention to these guys in DC and they can cause real trouble. We need to get over there and starting talking to these folks and educating them on what we do. >> And the imperative for them is to do the right thing, because, I mean, the United States interest, breaking up, say, Facebook, and Google, and Apple, and Amazon, might look good on paper but China's not breaking up Alibaba anytime soon. >> To the contrary. They're giving them low-interest loans and helping them all to excel. It's crazy. >> Yeah, and they have no R&D by the way, so that's been- >> Jamil: Right, because they stole all of our IP. >> So the US invests in R&D that is easily moving out through theft, that's one issue. You have digital troops on our shores from foreign nations, some will argue, I would say yes. >> Jamil: Inside the border. >> Inside the border, inside the interior, with access to the power grids, our critical infrastructure, this is happening now. So is the government now aware of the bigger picture around what we have as capabilities and criticalities that were needed now for digital military? What is that conversation like? >> Well I think they're having this conversation, right? I think the government knows it's a problem, they know that actually in a lot of ways a partnership with tech is better than an adversary relationship. That doesn't change the fact that, for some reason, in the last three, four years, we really have seen what some people are calling a "techlash", right? A backlash against technology. It kind of strikes me as odd, because of course, the modern economy that we've so benefited from is literally built on the back of the innovations coming out of the Silicon Valley, out of the west coast, and out of the DC metro area, where a lot these tech companies are developing some of the most innovative new ideas. Now they're, frankly, helping government innovate. So Amazon's a key part of that effort, right? Here in the public sector. And so I'm hoping that education will help, I know that the arrival of tech companies here to really have that conversation in an open and sensible way, I hope will sort of waft back some of this. But I worry that for too long the tech and the policies have ignored on another. And now they're starting to intersect as you say, and it has the possibility of going wrong fast, and I'm hoping that doesn't happen. >> You know, one of the things that Rebecca and I were talking about was this talent gap between public sector and private sector. These agencies aren't going to go public anytime soon, so maybe they should get equity deals and get a financial incentive. (laughing) You know what I mean? Shrink down the cost, increase the value. But as you get the collaboration between the two parties, the cloud is attracting smart people, because it gives you an accelerant of value. So people can see some entry points to land, some value out of the gate, verus giving up and abandoning it through red tape, or in other processes. So you starting to see smart people get attracted to cloud as a tool for making change. How is that working? And how is that going to work? Cause this could be coming to the partnership side of it. People might not want to work for the government, but could work with the government. This is a dynamic that we see as real. What's your thoughts? >> I think that's exactly right. Having these cloud infrastructures gives the ability to one, leverage huge amounts of computing power, but also to leverage insights and knowledge from the private sector in ways that you never could have imagined. So I really do think the cloud is an opportunity to bring real benefits from private sector innovation into the public sector very rapidly, right? So, broad-clouded option. And that's part of why John Alexander, my boss, and I have been talking a lot about the need for broad-clouded option. It's not just innovative in technology, it's benefits to the war fighter, Right? I mean, these are real, tangible benefits pushing data in real time, the war fighter, You know John Alexander had one of the biggest innovations in modern war fighting, where he's able to take civil intelligence down from weeks and months, down to minutes and seconds, that the naval and our war fighters in Iraq and Afghanistan to really take the fight to the enemy. The cloud brings that power scaled up to a huge degree, right? By orders of magnitude. And so the government recognizes this and yet today we don't see them yet moving rapidly in that direction. So I think the EO was a good move, a good first step in that direction, now we got to see it implemented by the various agencies down below. >> Well we'll kep in touch, great to have you on. I know we're wrapping up the day here, they're breaking down, we're going to pull the plug literally. (laughing) We'll keep in touch and we'll keep progress on you. >> Thank you so much, I appreciate it. >> Rebecca: Jamil, you are now a CUBE alumn, >> I love it, thank you. >> Rebecca: So congrats, you've joined the club. >> I love it. >> I'm Rebecca Knight for John Furrier you have been watching theCUBE's live coverage of the AWS Public Sector Summit. (electronic music)

>> Live from Toronto, Canada, it's theCUBE! Covering Blockchain Futurist Conference 2018. Brought to you by theCUBE! >> Hey, welcome back, everyone, we're live here in Toronto for the Blockchain Futurist Conference put on by Untraceable, Tracy and her team doing a fantastic job, so shout out to the team at Untraceable for another great event. I'm John Furrier with theCUBE, my cohost's Dave Vellante, and we're here with CUBE's friend, CUBE alumni, from the CryptoChicks, Nataliya Hearn, director, good to see you, great to have you back. >> Thank you. (laughs) >> Okay, good to see you, we're laughing, we've got some great funny stories we've been telling, since PolyCon, but really, some great things going on, so give us the update, you had a hackathon recently, you got new things happening here in your organization, take a quick minute to explain what it is for the folks that don't know, what do you guys do, and what's going on? >> Good, well, CryptoChicks is a organization focused on educating women in blockchain and cryptospace. We started because at meetups there would be one or two women out of hundreds of men, who would be afraid to ask stupid questions, so we said, Oh, okay, there's no stupid questions, come and join us, and we'll show you how to open a wallet, what blockchain is all about, so we've been doing that. We've actually grew quite a bit, we are now have chapters in all over the world, in Pakistan, in Bahamas, in Moscow, we just teamed up with She Codes in Israel, which is 50,000 women, so, we're doing really well. >> Congratulations, a great mission, we totally support it, and, you know, I'm proud to say that I love my shirt that says, Satoshi is Female, thanks to Nyla Rodgers, who gave it to me, at Consensus in Blockchain Week in New York, but this is really beyond women in tech, it's beyond that, it's a really, you're doing some innovative things around onboarding, new talent and education, this is a really important, because the Internet is bounded on discovery, learning. >> Absolutely. >> What's the new thing? >> Well, you know when you hear, when you go to the blockchain conference and events, and we hear again and again about the chasm. How do we bridge the chasm, right? That's just the, like, big word that you hear like every third presentation, because the blockchain community needs it. But I think globally, blockchain represents something that's quite unique, and it's an opportunity not just to make money and speculate, or to develop new technology, it's technology that can liberate. But how do we get that message across? And I think we have to start with kids. Kids are our future, but they're also the ones who spend most of their time on social media, so that's a good thing, but if you ask their parents, that's not such a good thing necessarily. So how do we convert them, some of their time from social media to learning? So we've put, we're putting together this program that focuses on children to earn to learn. >> Earn to learn, like they earn coins or money, or? >> That's right, basically they can earn swag, so basically we're creating the marketplace that rewards children for learning. >> All kids, right? >> All kids, well we're focusing on -- >> On girls. >> No, not on girls, we're going to high schools, so immediate next generation. >> So girls, boys, everybody's welcome? >> Absolutely. Yep. >> Awesome. >> Next generation, and they're the next generation that has to solve the problems that we, and opportunities that can be captured, that's coming right to their front door. >> Absolutely, we have a lot of question marks in the blockchain community. Which blockchain, how do we do it, there is going to be multi-chain tokens, we're talking about, next generation is the one who's going to provide solutions for us. So we got to open their minds, and to show that blockchain is a tool like potentially calculus is a tool. To create something that hasn't been there before. >> You know, I have a lot of conversations in Silicon Valley and Nataliya, recently at the Google Cloud event, Google's been very much a great change agent, especially with women in tech and underrepresented minorities, but Aparna Sinha, who's one of the senior people there, dual degrees from Stanford, she's got a PhD, she said we're losing the girls early, and what came out of it was a conversation that, when you have these new market movements like blockchain, AI, these are new skills that you can level up, so the ability to come from behind and level up is an opportunity for people who have traditionally been behind, whether it's women or other minorities, to level up. So it's a huge opportunity now to put the naysayers down to rest, and saying, Screw you, we're going to level up and learn. >> Absolutely, and it's global, the thing is -- >> There's nothing stopping anyone from learning. >> Absolutely, and trust, and the borderless system that blockchain potentially can provide is at a global advantage. As long as you have a cell phone, you can be in a village, an old village, like at our last hackathon, we actually were streaming women hackers from Zimbabwe. So there you go, it's doable. >> So how are you, how are you scaling your message globally? >> So we're starting, one thing is that education today, is basically the bill is being paid either by the government or by parents. The reason I would call that a marketplace, I would like companies to be involved. And it could be local companies, or it could be global. What about creating ARVR classrooms, and providing the information to kids, via a completely new way that they would actually move away from swiping or just looking on some random YouTube videos, to something that they can get a phone, some shoes, mascara, focusing on girls, right? And to understand what that borderless economy really means by experiencing, what does it mean to have tokens that you can trade globally? You are used to your parents giving you some dollars, you go to a corner store. What about if you learn something, you go to a bakery, in Kenya, and for the work that you've done, you get a bun, right, or a meal? >> So this democratizing access, it's bringing education to the masses? >> And it's also uniting the blockchain community, 'cause we would be building this governance platform on blockchain, we would tokenize it, and there will be many elements of it, reward programs, smart contracts that reward content, some level of AI in terms of analysis of what we're doing, so I think this is why I was looking at multi-chain tokens. Maybe that would be a solution to kind of, to deal with -- >> Explain that, what does that mean? >> Well, we've got different chains right now, right? You've got Hyperledger, you've got Ethereum, and all this good stuff. How do you bridge all this, right, instead of having to choose one, you're now saying, I can work in all of them, because each one potentially can offer something unique. Maybe you don't have to choose one. We don't know. Only time will tell, as this, this is such a young industry, and this is why it's so exciting. >> Well, Nataliya -- >> It -- >> Oh, go ahead. >> No, I was going to say, and you're giving the kids examples, so a lot of times kids ask me, Well, what's the difference between crypto and Venmo? I'm like, okay, you know, let's talk about the different things you can do with crypto that you can't do, but they're closer than the older generations are to transferring, you know, money, at least, so now you're applying different use cases and expanding their minds in ways that, perhaps -- >> Absolutely, and I'll give you my example. I mean, I got into blockchain early before Ethereum was launched, and partly I was into public markets, and then I kind of stopped because that project ended, or I stopped and I actually reentered it, because my fifteen-year-old who started mining. But he started mining because I was in that field already, so there you go, it kind of, you know, what comes around. >> Good job. I hope he gets all his Bitcoin. >> Yeah, he did. (laughs) >> So, I want you to tell a story, of what you've seen that's been high impact from your work you've done. You had, again, that whole Pakistan thing going on, you've got all these hackathons, what is a good story you could share? >> You know, the good story we can share, I think the part that we were able to do, the hackathons that we are doing are local, but they're also global, it really is, there's this sense of empowerment, and you know what I think the best story, this is the best story: best story was, at the hackathon that we ran, it was women, over 100 women, that participated. But all our mentors were young, geeky programming guys. Sorry guys. But you really knew they really knew their stuff, so there was technology transfer, and we had a 48 hour hackathon, these guys stayed 48 hours, they didn't go to sleep, they didn't have to as mentors, and there was this amazing technology transfer that happened, and I think some relationships were formed too. >> Yeah, some serious bonding went on, right? >> Yeah, absolutely. >> It's actually a good thing that you're including people. It's not just a certain thing, you got this inclusion. >> Absolutely, and actually all it is is about inclusion, all it is is we are giving a platform for women not to be afraid, I mean, I'm an engineer, so I've been working with men all my life, so for me to ask difficult questions, or stupid questions, it's like natural now, because it's been what my life, but for women, for many, it isn't. So we just wanted to kind of cross that divide, it's not a chasm, it's just a little divide that we're bridged. >> So when you say stupid questions, do you mean like, Why do you do it that way? (laughs) Why don't you do it this way? >> Or, what's a wallet? Like, what's a private key? What's a public key? And asking that not once, but twenty times until you got it. That's okay too. >> That's called learning. >> Yeah. >> Last question, okay I got to ask you, the most important question is, how do someone get a CryptoChicks shirt? >> I think you can order it on our website, sizes are a problem, I know we've discussed this, so we need to -- >> Extra-large. >> Well, CryptoChicks is a not-for-profit organization so there are, we'll have to order this in bunches, so I'll figure this out, but what I wanted to say is that we have another hackathon that's coming up. And the hackathon is in New York, October 5th to 8th, and we have three streams, so if you're a developer, and this is for women, so if you're a developer, we have a stream. If you're not a developer, or you've never coded in your life, but you have a business mind, and you think you have a really good idea that you can put on blockchain, you're welcome to join as well, and now with all the news and regulations, we also have a regulatory stream. >> So for entrepreneurs and for business-minded people, that want to get involved, that they can come too? >> Absolutely. >> Okay, and their website is cryptochicks.ca, that's where you can get access to the information, that's great. >> October 5th to 8th, you said, right? >> That's right. >> And anybody can go? >> Anybody can register. >> And where in New York? >> It's going to be at University of New York, and at their School of Law. >> Great. >> Blockchain Educational Fun Hub. That's what it says on the website, love your website. Looking forward to getting some shirts, and putting it out there, and promoting your mission. Great job, good to see you again. >> You guys are awesome. Thank you so much. >> Thank you. >> Thank you, Nataliya. >> Thank you. >> This is crypto for good, a lot of education, and this opportunity, and our role is to share that, as a community, and I think this is a great example of the kind of community that crypto is. Education people can level up and move fast through and get proficiency, and change their lives. This is what this is all about, glad to bring us this CUBE coverage live, stay with us! Day One continues, I'm John Furrier with Dave Vellante, we'll be right back from Toronto Blockchain Futurist Summit. Thank you. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2018. Brought to you by Dell EMC, and it's ecosystem partners. >> And welcome back to Las Vegas, as thCUBE continues our coverage here of Dell Technologies World 2018. So glad to have you along here for our Day Three coverage. Along with Stu Miniman, I'm John Walls. It's now a pleasure to welcome David Comroe with us. David is the Senior Director of Client Technology Services at the Wharton School of Business, at the University of Pennsylvania. David, thanks for being with us. >> No problem. Glad to be here. >> Thank for sharing your time with us. First off let's just talk about, about the scope of your work. Again, you take care of all the obviously IT needs for the largest business school faculty in the world. Right? No pressure on you there. But talk about day to day, those responsibilities. >> As you mentioned my title is Senior Director for Client Technology Services. I'm essentially responsible for providing the support and services to four very distinct user groups that we happen to have at a university. That's of course our wonderful faculty, our staff that make everything happen, our incredible students, and of course our alumni group, which is about 100,000 people strong at this point. Just Wharton alums that are again, very important. Give back to the school. Provide mentorship and job opportunities for our graduates. Again very distinct needs for each of those four groups. We provide a high quality, and all the buzzwords. You know, secure, safe, efficient, highly available services to these groups. That's kind of what I do all day. >> One of the cool things, I love acronyms. Not that this industry doesn't have a few, as you know Stu. But WHOOPPEE. I absolutely love making whoopie. But not what you might think. But walk us through that and what it stands for, and what you did in it. It really was groundbreaking. >> You're putting me on the spot with this one. So WHOOPPEE is the Wharton, let's see if I can get this, Online Ordinal Peer Performance Evaluation Engine. One of our incredible faculty, Pete Fader, came up with this idea. It's no secret that grading is kind of bad. Faculty grading students. There's all kinds of challenges. >> It's tedious. >> Well it's tedious. There's inherit biases when you're, the larger the class. And when you have to grade 80 papers, or 100 papers or 200 papers. It's really hard to keep consistency across when your grading paper one through paper 100 through paper 200. Plus when you start divvying up the work between TA's and different faculty teaching the same class. Again fraught with bias. A number of people, again Pet Fader's idea, to come up with basically an algorithm that helps the grading process. And basically what happens is, is students are grading themselves. What we'll do is we'll give them five papers or five projects to grade. And they don't actually grade. All they have to do is rank it. You know, this is the best one. This is number one. This is the worst one. This is number five. And then there's this magic behind the scenes that that runs in our local infrastructure, in our cloud infrastructure. That basically runs an algorithm. And that algorithm is the secret sauce that some of our statistical geniuses at the Wharton school, of which we have many, came up with. And it has all kinds of cool features. You can say, well this batch of five papers might be harder. I might have the five best papers in the class. That's not fair. They still have to rank one the worst. You know, five. You can't say these two are the best. And this one's third. You actually, the students have to read the paper, and just rank it. I like this one the best. I like second, third, fourth, fifth. The algorithm takes into account difficulty of batches of papers. You could literally have the five best or the five worst papers in the class. And that's still going to provide meaningful data to the algorithm. So when you have 50, 100, 500 batches of five. They all start to figure it out. And the algorithm will actually figure out what the best paper is in the class. And what the maybe again at the Wharton. But not so great, greatest paper in the class. >> But not the worst. Just not so great. Again cause our students are brilliant. It basically goes on the fact that if you do a quality paper. If the algorithm says you're the best. Your weight means more than someone who might not have done such a good job on the paper. And you're considered a better grader. And it's weighted towards the better graders. There's all kinds of really cool stuff in there that we think is going to change... Get rid of some of that bias that I spoke about before. And help provide. And the data we've seen is, frankly the students like doing it. They don't like the additional work involved with it. We're seeing some empirical evidence, and some in person interviews. That they're learning more. They're reading five other student's papers. They're getting five other perspectives. They're saying, hey I didn't think about that. Or even, hey they're all wrong here. My paper was much better than theirs. But again that doesn't necessarily matter when we start running the ranks. And we're getting much better, much better grading, which is hard to quantify, but the folks that are on the academic team that are doing that, have some really great data. With the data. Yup, mm-hm. >> David, one of the themes we keep hearing in this show is about transformation. Is change happening? You're talking about IT, how it's working with the business more and more. Bring us inside university life in general and specifically. You work with one of the ancient eight. How does cutting edge technology fit in with - >> That's really interesting. I do have a couple thoughts on that. My boss has a picture in his office, of a Penn classroom from I think it's like 1908 or 1910. And there's literally a bunch of students sitting around. There's a faculty member standing up. And there's a candle-powered projector, which I didn't know is a thing but it's in the picture, projecting an image onto the wall. From over 100 years ago. What's different about our classrooms today? Everything's the same, except the projector's now in LED. Or a L3D projector. We still got people sitting around the room, standing up. I think what we're seeing now in probably the previous ten years from now and to the next ten years is education's probably going to change more in those 20 years than it has in 2,000 years since Socrates was standing around with a stone tablet or whatever they were doing. Things like globalization, online courses, the MOOC space, where Wharton is huge in the MOOC space. Wharton online programs. Where students can take, not even students, anybody! If you're in China or Africa or South America. You can take an introduction to Wharton, introduction to marketing class from a Wharton professor for free. I mean we're a business school. We sell some of that content as well. But you can get verified certificates. We're seeing a lot of stuff change. The students today expect more. We can get into, we won't though, we can get into the whole millennial issue and short attention span and all that kind of stuff. Students today expect their faculty to be technology savvy. They expect content to be online. They expect to use devices. The expect to use... We got tablets, and laptops and phones. They want to be able to consume this content on multiple devices. We're seeing significant transformations in education. Which is, hasn't necessarily changed much in 2,000 years. Or even 200 years, right? So there's that. Speaking specifically about Wharton, one of the things I really thought is interesting, is I've been there 13 years now. When I first started working there, I'm going to make some generalizations here, a lot of our student wanted to go work in iBanking. They wanted to go work for the big banks. They wanted to go work for Goldman Sachs and things like that. In the last five, seven, ten years ago. They wanted to create their own company. Start up their own company. Be entrepreneurial. Have their app. Have their their big idea. Start the next whatever dot com. And be successful that way. Now in the last two or three, four years. We're seeing a lot of our students analytics. We're putting analytics with everything. Companies, businesses, organizations, no matter what you are, we have huge amounts of data available. How can we make meaningful decisions based on that data? Our dean. I guess I can't call him our new dean. He's been there three or four years at this point. Really wants to position Wharton as the analytics school. Every company in the world is trying to hire these kinds of people. There just frankly aren't enough of them out there. The thing we're trying to teach our students is, or one of the many things, is how to analyze data. How to make meaningful decisions based on that data. And of course when you have more data, you need more storage. You need more infrastructure. You need more processing. All the stuff that you know, Dell and Nutanix are providing us, with their hyper convergence infrastructure. Their cloud offerings. Whether private cloud, public cloud, hybrid cloud. All that kind of stuff is... Positioning us as the analytics school requires a significant amount of technology on the backend. And again working with our trusted partners like Dell and Nutanix we can provide that seamlessly in the backend. They don't necessarily know, is it in our data center? Is it in the cloud? And they don't care. They shouldn't care. But as they're collecting huge amounts of data, running these reports, and creating it, and going back to creating these algorithms that do incredible things. And these secret sauces. We need the infrastructure to run that kind of stuff. That's I think one of the greatest things that Wharton Computing provides the Wharton School of Business, and their business, which is creating and disseminating knowledge. >> David, I think you've encapsulated something that I've been hearing from lot's of users over the last year or so. The vendors sometimes, it's private, it's hybrid, it's public. From the user standpoint it's like, no well we have a cloud strategy that we're working on. Can you bring us inside a little bit? How did you get to where you are today? How do you choose who you're partnering with? What leads to some of those decisions? >> I love the word partner. I hate the word vendor. One of the great things about working at Wharton is, is we get to have these awesome partners. I want someone... When we're going to make an IT spend, we want someone who cares about our business. We don't want somebody who just, will come in, give you a dog and pony show, write us a check. And when you want more stuff call us. We want folks that are going to provide the support. You know, pre-sales during installation. Post-sales when they're coming out with new features. We want them to be invested in what we do. I can truly say that Nutanix is a fantastic partner of ours. Dell-Nutanix are great partners. Dell is a great partner of Wharton and Penn as well. That's what we really look for, is someone who is willing to invest their time, their smart people. Tell us about the new features and functionality that are coming out. Call on us and say, hey how are thing going? It's not just the little things. But those little things really mean a lot to us as we're picking an IT partner. Because when you're working for the best business school in the world. Having the best students, the brightest faculty, the best, hardest working staff. We want to provide them a very, very high quality IT support. We need high quality partners. And not just vendors who care about the transaction. That's really the bottom line for us. When we're choosing our partners. >> When you were talking about analytics, and Wharton being the school of data analytics. What are your measuring sticks? In terms of what are you looking at? You're talking about four very separate groups of constituencies. What are you doing to evaluate your performance? And what's critical? >> I think it all comes down to, what do our business units think about us? We're a service organization. Almost all IT shops are. If the business units aren't successful, they don't need an IT department. If we're not providing them high quality IT services, we're not going to get the best faculty. We're not going to get the brightest students. We're not going to get the alumni engagement. They want to be wowed by their IT support. That's a big part of my job, is providing that quality of support. Helping train. Technology breaks, right? How do you deal with the problem? Nobody runs at rock solid 100% infrastructure. Murphy's Law always comes into play. Problems always happen. How do you deal with the cracks in the armor as they come off? I think that's what our business units want. I think we're fortunate that we're computing. Our team, our staff, our CIO. My colleagues, my peers, my team. Our team, right? They're very well thought of, hopefully, by our clients. And that's how we're measured is by their success. We want to help them, empower them to do their job at the highest level. We are playing in pretty rare air, when it comes to the faculty, staff, students and alumni, that we attract to Penn and Wharton. We want to keep doing that. One of the things I love best, and I tell our wonderful faculty when we meet with them, is don't tell me we did a great job. Here's what I want you to tell me. I want you to say, three years ago I was at, I'm not going to name drop schools, but I was at this school and I asked them to do this thing, that you said, sure, no problem to. And they couldn't do it, wouldn't do it, didn't have the ability, the infrastructure in place to do that. But you guys with a smile on your face just made it happen. Stuff like WHOOPPEE. Stuff like the analytics stuff. All the, tying it back to why we're here today, is our partners and our technology partners that help us provide scalable, flexible solutions. That's how we're measured. >> Higher learning. >> Higher learning, absolutely. >> David, thanks for being with us. >> No problem, it was great. >> David Comroe from the Wharton School of Business, University of Pennsylvania. Back with more live coverage here from Dell Technologies World 2018. Right after this break. You're watching theCUBE.

>> Announcer: Live from Austin, Texas it's the Cube. Covering South by Southwest 2017. Brought to you by Intel. Now here's John Furrier. Okay we're back live here at the South by Southwest Intel AI Lounge, this is The Cube's special coverage of South by Southwest with Intel, #IntelAI where amazing starts with Intel. Our next guest is Dr. Dawn Nafus who's with Intel and you are a senior research scientist. Welcome to The Cube. >> Thank you. >> So you've got a panel coming up and you also have a book AI For Everything. And looking at a democratization of AI we had a quote yesterday that, "AI is the bulldozer for data." What bulldozers were in the real world, AI will be that bulldozer for data, surfacing new experiences. >> Right. >> This is the subject of your book, kind of. What's your take on this and what's your premise? >> Right well the book actually takes a step way back, it's actually called Self Tracking, the panel is AI For Everyone. But the book is on self tracking. And it's really about actually getting some meaning out of data before we start talking about bulldozers. So right now we've got this situation where there's a lot of talk about AI's going to sort of solve all of our problems in health and there's a lot that can get accomplished, whoops. But the fact of the matter is is that people are still struggling with gees, like, "What does my Fitbit actually mean, right?" So there's this, there's a real big gap. And I think probably part of what the industry has to do is not just sort of build new great technologies which we've got to do but also start to fill that gap in sort of data education, data literacy, all that sort of stuff. >> So we're kind of in this first generation of AI data you mentioned wearable, Fitbits. >> Dawn: Yup. >> So people are now getting used to this, so that it sounds this integration into lifestyle becomes kind of a dynamic. >> Yeah. >> Why are people grappling >> John: with this, what's your research say about that? >> Well right now with wearables frankly we're in the classic trough of disillusionment. (laughs) You know for those of you listening I don't know if you have sort of wearables in drawers right now, right? But a lot of people do. And it turns out that folks tend to use it, you know maybe about three or four weeks and either they've learned something really interesting and helpful or they haven't. And so there's actually a lot of people who do really interesting stuff to kind of combine it with symptoms tracking, location, right other sorts of things to actually really reveal the sorts of triggers for medical issues that you can't find in a clinical setting. It's all about being out in the real world and figuring out what's going on with you. Right, so then when we start to think about adding more complexity into that, which is the thing that AI's good at, we've got this problem of there's only so many data sets that AI's any actually any good at handling. And so I think there's going to have to be a moment where sort of people themselves actually start to say, "Okay you know what? "This is how I define my problem. "This is what I'm going to choose to keep track of." And some of that's going to be on a sensor and some of it isn't. Right and sort of being really intervening a little bit more strongly in what this stuff's actually doing. >> You mentioned the Fitbit and you were seeing a lot of disruption in the areas, innovation and disruption, same thing good and bad potentially. But I'll see autonomous vehicles is pretty clear, and knows what Tesla's tracking with their hot trend. But you mentioned Fitbit, that's a healthcare kind of thing. AIs might seem to be a perfect fit into healthcare because there's always alarms going off and all this data flying around. Is that a low hanging fruit for AI? Healthcare? >> Well I don't know if there's any such thing as low hanging fruit (John laughs) in this space. (laughs) But certainly if you're talking about like actual human benefit, right? That absolutely comes the top of the list. And we can see that in both formal healthcare in clinical settings and sort of imaging for diagnosis. Again I think there's areas to be cautious about, right? You know making sure that there's also an appropriate human check and there's also mechanisms for transparency, right? So that doctors, when there is a discrepancy between what the doctor believes and what the machine says you can actually go back and figure out what's actually going on. The other thing I'm particularly excited about is, and this is why I'm so interested in democratization is that health is not just about, you know, what goes on in clinical care. There are right now environmental health groups who are looking at slew of air quality data that they don't know what to do with, right? And a certain amount of machine assistance to sort of figure out you know signatures of sort of point source polluters, for example, is a really great use of AI. It's not going to make anybody any money anytime soon, but that's the kind of society that we want to live in right? >> You are the social good angle for sure, but I'd like to get your thoughts 'cause you mentioned democratization and it's kind of a nuance depending upon what you're looking at. Democratization with news and media is what you saw with social media now you got healthcare. So how do you define democratization in your context and you're excited about.? Is that more of freedom of information and data is it getting around gatekeepers and siloed stacks? I mean how do you look at democratization? >> All of the above. (laughs) (John laughs) I'd say there are two real elements to that. The first is making sure that you know, people are going to use this for more than just business, have the ability to actually do it and have access to the right sorts of infrastructures to, whether it's the environmental health case or there are actually artists now who use natural language processing to create art work. And people ask them, "Why are you using deblurting?" I said, "Well there's a real access issue frankly." It's also on the side of if you're not the person who's going to be directly using data a kind of a sense of, you know... Democratization to me means being able to ask questions of how the stuff's actually behaving. So that means building in mechanisms for transparency, building in mechanisms to allow journalists to do the work that they do. >> Sharing potentially? >> I'm sorry? >> And sharing as well more data? >> Very, very good. Right absolutely, I mean frankly we still have a problem right now in the wearable base of people even getting access to their own data. There's a guy I work with named Hugo Campos who has an arterial defibrillator and he's still fighting to get access to the very data that's coming out of his heart. Right? (laughs) >> Is it on SSD, in the cloud? I mean where is it? >> It is in the cloud. It's going back to the manufacturer. And there are very robust conversations about where it should be. >> That's super sad. So this brings up the whole thing that we've been talking about yesterday when we had a mini segment on The Cube is that there are all these new societal use cases that are just springing up that we've never seen before. Self-driving cars with transportation, healthcare access to data, all these things. What are some of the things that you see emerging on that tools or approaches that could help either scientists or practitioners or citizens deal with these new critical problem solving that needs to apply technology to. I was talking just last week at Stanford with folks that are looking at gender bias and algorithms. >> Right, uh-huh it's real. >> Something I would never have thought of that's an outlier. Like hey, what? >> Oh no, it's happened. >> But it's one of those things were okay, let's put that on the table. There's all this new stuff coming on the table. >> Yeah, yeah absolutely. >> What do you see? >> So they're-- >> How do we solve that >> John: what approaches? >> Yeah there are a couple of mechanisms and I would encourage listeners and folks in the audience to have a look at a really great report that just came out from the Obama Administration and NYU School of Law. It's called AI Now and they actually propose a couple of pathways to sort of making sure we get this right. So you know a couple of things. You know one is frankly making sure that women and people of color are in the room when the stuff's getting built, right? That helps. You know as I said earlier you know making sure that you know things will go awry. Like it just will we can't predict how these things are going to work and catching it after the fact and building in mechanisms to be able to do that really matter. So there was a great effort by ProPublica to look at a system that was predicting criminal recidivism. And what they did was they said, "Look you know "it is true that "the thing has the same failure rate "for both blacks and whites." But some hefty data journalism and data scraping and all the rest of it actually revealed that it was producing false positives for blacks and false negatives for whites. Meaning that black people were predicted to create more crime than white people right? So you know, we can catch that, right? And when we build in more system of people who had the skills to do it, then we can build stuff that we can live with. >> This is exactly to your point of democratization I think that fascinates me that I get so excited about. It's almost intoxicating when you think about it technically and also societal that there's all these new things that are emerging and the community has to work together. Because it's one of those things where there's no, there may be a board of governors out there. I mean who is the board of governors for this stuff? It really has to be community driven. >> Yeah, yeah. >> And NYU's got one, any other examples of communities that are out there that people can participate in or? >> Yup, absolutely. So I think that you know, they're certainly collaborating on projects that you actually care about and sort of asking good questions about, is this appropriate for AI or not, right? Is a great place to start of reaching out to people who have those technical skills. There are also the Engineering Professional Association actually just came out a couple months ago with a set of guidelines for developers to be able to... The kinds of things you have to think about if you're going to build an ethical AI system. So they came out with some very high level principles. Operationalizing those principles is going to be a real tough job and we're all going to have to pitch in. And I'm certainly involved in that. But yeah, there are actually systems of governance that are cohering, but it's early days. >> It's great way to get involved. So I got to ask you the personal question. In your efforts with the research and the book and all of your travels, what's some of the most amazing things that you've seen with AI that are out there that people may know about or may not know about that they should know about? >> Oh gosh. I'm going to reserve judgment, I don't know yet. I think we're too early on the curve to be able to talk about, you know, sort of the magic of it. What I can say is that there is real power when ordinary people who have no coding skills whatsoever and frankly don't even know what the heck machine learning is, get their heads around data that is collected about them personally. That opens up, you can teach five year olds statistical concepts that are learned in college with a wearable because the data applies to them. So they know how it's been collected. >> It's personal. >> Yeah they know what it is already. You don't have to tell them what a outlier effect is because they know because they wear that outlier. You know what I mean. >> They're immersed in the data. >> Absolutely and I think that's where the real social change is going to come from. >> I love immersion as a great way to teach kids. But the data's key. So I got to ask you with the big pillars of change going on and at Mobile World Congress I saw you, Intel in particular, talking about autonomous vehicles heavily, smart cities, media entertainment and the smart home. I'm just trying to get a peg a comparable of how big this shift will be. These will be, I mean the '60s revolution when chips started coming out, the PC revolution and server revolution and now we're kind of in this new wave. How big is it? I mean in order of magnitude, is it super huge with all of the other ships combined? Are we going to see radical >> I don't know. >> configuration changes? >> You know. You know I'm an anthropologist, right? (John laughs) You know everything changes and nothing changes at the same time, right? We're still going to wake up, we're still going to put on our shoes in the morning, right? We're still going to have a lot of the same values and social structures and all the rest of it that we've always had, right. So I don't think in terms of plonk, here's a bunch of technology now. Now that's a revolution. There's like a dialogue. And we are just at the very, very baby steps of having that dialogue. But when we do people in my field call it domestication, right? These become tame, they become part of our lives, we shape them and they shape us. And that's not radical change, that's the change we always have. >> That's evolution. So I got to ask you a question because I have four kids and I have this conversation with my wife and friends all the time because we have kids, digital natives are growing up. And we see a lot of also work place domestication, people kind of getting domesticated with the new technologies. What's your advice whether it's parents to their kids, kids to growing up in this world, whether it's education? How should people approach the technology that's coming at them so heavily? In the age of social media where all our voices are equal right now, getting more filters are coming out. It's pretty intense. >> Yeah, yeah. I think it's an occasion where people have to think a lot more deliberately than they ever have about the sources of information that they want exposure to. The kinds of interaction, the mechanisms that actual do and don't matter. And thinking very clearly about what's noise and what's not is a fine thing to do. (laughs) (John laughs) so yeah, probably the filtering mechanisms has to get a bit stronger. I would say too there's a whole set of practices, there are ways that you can scrutinize new devices for, you know, where the data goes. And often, kind of the higher bar companies will give you access back, right? So if you can't get your data out again, I would start asking questions. >> All right final two questions for you. What's your experiences like so far at South by Southwest? >> Yup. >> And where is the world going to take you next in terms of your research and your focus? >> Well this is my second year at South by Southwest. It's hugely fun, I am so pleased to see just a rip roaring crowd here at the Intel facility which is just amazing. I think this is our first time as in Dell proper. I'm having a really good time. The Self Tracking book is in the book shelf over in the convention center if you're interested. And what's next is we are going to get real about how to make, how to make these ethical principles actually work at an engineering level. >> Computer science meets social science, happening right now. >> Absolutely. >> Intel powering amazing here at South by Southwest. I'm John Furrier you're watching The Cube. We've got a great set of people here on The Cube. Also great AI Lounge experience, great demos, great technologists all about AI for social change with Dr. Dawn Nafus with Intel. We'll be right back with more coverage after this short break. (upbeat digital beats)

>> Announcer: From the Silicon Valley Media Office in Boston, Massachusetts, it's The Cube! Now, here's your host, Dave Vellante. >> Hi, everybody, welcome to a special Silicon Angle, The Cube on the ground. We're going to be talking about data capital with Paul Sonderegger, who is a big data strategist at Oracle, and he leads Oracle's data capital initiative. Paul, thanks for coming in, welcome to The Cube. >> Thank you, Dave, it's good to be here. >> So data capital, it's a topic that's gaining a lot of momentum, people talking about data value, they've talked about that for years, but what is data capital? >> Well, what we're saying with data capital, is that data fulfills the literal economic textbook definition of capital. Capital is a produced good, as opposed to a natural resource that you have to invest to create it, and it is then an necessary input into some other good or service. So when we define data capital, we say that data capital is the recorded information necessary to produce a good or service. Which is really boring, so let me give you an example. So imagine, picture a retailer. A retailer wants to go into a new market. To do that, the retailer has to expand its inventory, it has to extend its supply chain, it has to buy property, all of these kinds of investments. If it lacks the financial capital to make all of those investments, it can't go, cannot go into that new region. By the same token, if this retailer wants to create a new dynamic pricing algorithm, or a new recommendation engine, but lacks the data to feed those algorithms, it cannot create that ability. It cannot provide that service. Data is now a kind of capital. >> And for years, data was viewed by a lot of organizations, particularly general counsel, as a liability, and then the big data meme sort of took off and all of a sudden, data becomes an asset. Are organizations viewing data as an asset? >> A lot of organizations are starting to view data as an asset, even though they can't account for it that way. So by current accounting standards, companies are not allowed to treat the money that they spend on developing information, on capturing data, as an asset. However, what you see with these online consumer services, the ones that we know, Uber, Airbnb, Netflix, Linkedin, these companies absolutely treat data as an asset. They treat it, not just as a record of what happened, but as a raw material for creating new digital products and services. >> You too, you tweeted out an article recently on Uber, and Uber lost about, what is it? 1.2 billion- >> At least. >> Over six months, at least. >> At least. >> And then the article calculated how much it was actually paid, I mean basically, the conclusion was it paid 1.2 billion for data. >> Yeah. >> It was about $1.20 per data for ride record, which actually is not a bad deal, when you think about it that way. >> Well, that's the thing, it's not a bad deal when you consider that the big picture they have in view is the global market for personal transportation, which The Economist estimates is about 10 trillion dollars annually. Well, to go after a 10 trillion dollar market, if you can build up a unique stock of data capital, of a billion records at about a billion dollars per record, that's probably a pretty good deal, yeah. >> So, money obviously is fungible, it's currency. Data is not a currency, but digital data is fungible, right, I mean, you can use data in a lot of different ways, can't you? >> No, no, it's, and this actually is a really important point, it's a really important point. Data is actually not fungible. This is part of data's curious economic identity. So data, contrary to popular wisdom, data is not abundant. Data consists of countless unique observations, and one of the issues here is that, two pieces of data are usually not fungible. You can't replace one with the other because they carry different information. They carry different semantics. So just to make it very, very concrete, one of the things that we see now, a huge use of data capital is in fraud detection. And one of our customers handles the fraud detection for person-to-person mobile payments. So say you go away for a weekend with a friend, you come back, you want to split the tab, and you just want to make a payment directly to the other person. You do this through your phone. Those transactions, that account to account transfer, gets checked for possible fraudulent activity in the moment, as it happens, and there is a scoring algorithm that sniffs those transactions and gives it a score to indicate whether or not it may be fraudulent or if it's legitimate. Well, this company, they use the information they capture about whether their algorithm captured, caught, all of the fraudulent transactions or missed some, and whether that algorithm mistakenly flagged legitimate transactions as fraudulent. They capture all of those false positives and false negatives, feed it back into the system, and improve the performance of the algorithm for the next go around. Here's why this matters: the data created by that algorithm about its own performance, is a proprietary asset. It is unique. And no other data with substitute for it. And in that way, it becomes the basis for a sustainable competitive advantage. >> It's a great example. So the algorithm maybe is free, you can grab an algorithm, it's how you apply it that is proprietary, and now, okay, so we've established that the data is not fungible. But digital data doesn't necessarily have high asset specificity. Do you agree with that? In other words, I can use data in different ways, if it's digital. Yeah, absolutely, as a matter of fact, this is one of the other characteristics of data. It is non-rivalrous, is what economists would call it. And this means that two parties can use the same piece of data at the same time. Which is not the case with, say, a tractor. One guy on a tractor means that none of the other people can ride that tractor. Data's not like that. So data can be put to multiple uses simultaneously. And what becomes very interesting is that different uses of data can command different prices. There's actually a project going on right now where Harvard Law School is scanning and digitizing the entire collection of US case law. Now this is The Law, the law that we all as Americans are bound to. Yet, it is locked up in a way, in just, in all of these 43,000 books. Well, Harvard and a startup called Ravel Law, they are working on scanning and digitizing this data, which can then be searched, for free, all of these, you can search this entire body of case law, for free, so you can go in and search "privacy," for example, and see all of the judgements that mention privacy over the entire history of US case law. But, if you want, for example, to analyze how different judges, current sitting judges, rule on cases related to privacy, well, that's a service that you would pay for from Ravel. The exact same data, their algorithms are working on the same body of data. You can search it for free, but the analysis that you might want on that same data, you can only get for a fee. So different uses of data can command different prices. >> So, some excellent examples there. What are the implications of all of this for competitive strategies, what should companies, how should they apply this for competitive strategies? >> Well, when we think about competitive strategy with data capital, we think in terms of three principles of data capital, is what we call them. The first one is that data comes from activity. The second one is, data tends to make more data, and the third is that platforms tend to win. So these three principles, even if we just run through them in their turn, the first one, data comes from activity, this means that, in order to capture data, your company has to be part of the activity that produces it at the time that activity happens. And the competitive strategy implication here is that, if your company is not part of that activity when it happens, your chance to capture its data is lost, forever. And so this means that interactions with customers are critical targets to digitize and datify before the competition gets in there and shuts you out. The second principle, data tends to make more data, this is what we were talking about with algorithms. Analytics are great, they're very important, analytics provide information to people so that they can make better choices, but the real action is in algorithms. And here is where you're feeding your unique stock of data capital to algorithms, that not only act on that data, but create data about their own performance, that then improve their future performance, and that data capital flywheel becomes a competitive advantage that's very hard to catch. The third principle is that platforms tend to win. So platforms are common in information-intensive industries, we see them with a credit card, for example, we see them in financial services. A credit card is a payment platform between consumers on the one side, merchants on the other. A video game console is a platform between developers on the one side and gamers on the other. The thing about platform competition is that it tends to lead toward a winner-take-all outcome. Not always, but that's how it tends to go. And with the digitization and datification of more activities, platform competition is coming for industries that have never seen it before. >> So platform beats product, but it's winner-take-all, or number two maybe breaks even, right? >> That tends to be the way it goes. >> And number three loses money, okay. The first point you were making about, you've got to be there when the transaction occurs, you've got to show up. The second one's interesting, data tends to make more data. So, and you talked about algorithms and improving and fine-tuning in that feedback loop. I would imagine customers are challenged in terms of investments, do they spend money on acquiring more data, or do they spend money on improving their algorithms, and then the answer is got to do both, but budgets are limited. How are customers dealing with that challenge? >> Well, prioritization becomes really critical here. So not all data is created equal, but it's very difficult to know which data will be more valuable in the future. However, there are ways to improve your guess. And one of the best ways is to, go after data that your competition could get as well. So this is data that comes from activities with customers. Data from activities with suppliers, with partners. Those are all places where the competition could also try to digitize and datify those activities. So companies should really look outside their own four walls. But the next part, you know, figuring out, what do you do with it? This is where companies really need to take a page out of actual science as they approach data science, and science is all about argument. It's all about experimentation, testing, and keeping the hypotheses that are proven and discarding the ones that are disproven. What this means is that companies need a data lab environment, where they can cut the time, the cost, the effort, of forming and testing new hypotheses, getting new answers to new questions from their data. >> Okay, so, data has value, you've got to prioritize. How do you actually value the data so that I can prioritize and figure out what I should be focusing on in the lab and in production? >> Yeah, well, the basic answer is to go where the money is. So there are a couple things you can do with data. One is that you can improve your operational effectiveness, and so here, you should go look at your big cost areas, and focus your limited data science and managerial resources on trying to figure out, hey, can we become more efficient in whatever your big cost driver is? If it's shipping and logistics, if it's inventory management, if it's customer acquisition, if it's marketing and advertising, so that's one way to go. The next big thing that you can do with data is try to create a new product or service, a new ... create new value in a way that generates revenue. Here, there is a little caveat, which is that, companies may also want to consider creating new capabilities, maybe enriching the customer experience, making connections across multiple channels, that they can't actually charge for, not today. But, what they get, is data that no one else has. What they get from, let's say, making an investment into, bring together the in-store shopping experience with the, with the targeted emails, with, with communication through social feeds and through Twitter. Let's say that they invest in trying to tie that data together, to get a richer picture of their consumers' behavior. They might not be able to charge for that today. But, they may get insight into the way that shopping experience works that no one else can see, which then leads to a value-added service tomorrow. And I know it all sounds very speculative, but this is basically the nature of prototyping, of new product creation. >> Well, Uber's overused as an example, but this is a good application of Uber because they, essentially they pay for driver acquisition, which doesn't scale well. >> Yeah. >> But they get data. >> That's right. >> Because they're there at the point of the transaction and the activity and they've got data that nobody else has. >> Yeah, yeah, that's exactly right, and, you know, one of the ways to think about that is that, you're like a blackjack player, counting cards, and every time you play a hand as a company, you get data, information that may help you improve your future bets. This is why Vegas kicks out card counters, because it's an advantage for the future. But what we're talking about here, in digitizing activity with customers, every time you capture data about your interaction with those customers, you gain something simply for having carried out that activity. >> And so, thinking about, back to value for a minute, I mean I can envision some kind of value flow methodology where you assess the data intensity of the activity, and then assign some kind of, I don't know, score or a value to that activity, and then you can then look at that in relation to other activities. Is that a viable approach? >> It absolutely is. What companies need here is a new way to measure how much data they've got, how much they use, and then ascribe ... value created, you know, by that data. So the, how much they've got, you know, we can think about this, we always talk in terms of gigabytes and petabytes. But really we need some finer measurements. Data is an observation about something in the real world. And so, companies should start to think about measuring their data in terms of observations, in terms of attribute-value pairs. So even thinking about the record captured per activity, that's not enough. Companies should start thinking in terms of, how many columns are in that record? How many attributes are captured in these observations we make from that activity? The next issue, you know, how much do they use? Well, now, companies need to look at, how many of these observations are being touched, are being tapped by queries? Whether they're automatically generated, whether they are generated ad hoc by some data scientist, rooting around for some new understanding. So there's a set of questions there about, what percentage of these observations we possess are we actually using in queries of some kind? And then the third piece, how much value do we create from it? This is where ... This is a tough one, and it's really an estimation. It's, most likely what we need here is a new method for attributing the, profitabilty of a particular business unit to its use of that data. And I realize this is an estimation, but this is, there's a precedent for this in brand valuation, this is the coin of the realm when you're talking about putting a value to intangible assets. >> Well, as long as you're consistently applying that methodology across your portfolio, then, then at least you've got a relative measure and you can get back to prioritization, which is a key factor here. Is there an underlying technical architecture that has to be in place to take advantage of all this data capital momentum? >> There is, there is, companies are moving toward a hybrid cloud, big data architecture. >> What does that mean? >> It means that almost all the buzzwords are used, and we're going to need new ones. No, what it means is that, companies are going to find themselves in a situation where some of their computing activities, storage, processing, application execution, analytics, some of those activities will take place in a public cloud environment, some of it will take place within their own data centers, reconfigured to act as private clouds. And there are lots of potential reasons for this. There could be, companies have to deal with, not only existing regulations, which sometimes will prevent them from putting data up into a cloud, but they are also going to have to deal with regulatory arbitrage, maybe the regulations will change, or maybe they've got agreements with partners that are embodied in service level agreements that again require them to keep the data under their own observation. Even in that case, even in that case, the business still wants to consume all of those computing resources inside the data center as if they were services. The business doesn't care where they come from. And so this is one of the things that Oracle is providing, is an architecture for Oracle public cloud, and private cloud in the data center. It is the same on both sides of the wire. And in fact, can even be purchased in the same way so that even these, this Oracle cloud at customer, these machines, they are purchased on a subscription basis, just as public cloud capabilities are. And the reason this is good is because it allows IT leaders to provide to the business, computing capabilities, storage capabilities, you know, as needed, that can be consumed as services, regardless of where they come from. >> Yeah, so you've got the data locality issue, which is speed of light problems, you don't want to move data, then you've got compliance and governance, and you're saying, that hybrid approach allows you to have the cake and eat it, too. >> Yeah. >> Essentially. Are there other sort of benefits to taking this approach? >> Well, one of the, you know, the, one of the other pieces that we should talk about here is the big data aspect, and really what that means is, that, relational, Hadoop, NoSQL, graph database, repositories, they're all going to, they're all peers. They're all peers now, and, you know, this is Oracle's perspective, and as I'm sure you know, Oracle makes a relational database, it's very popular. Yeah, we've been doing it for a while, we're pretty good at it. Oracle's perspective on the future of data management is that Hadoop, NoSQL, graph, relational, all of these methods of data management will be peers and act together in a single high-performance enterprise system. And here's why. The reason is that, as our customers digitize and datify more of their activities, more of the world, they're creating data that's born in shapes and formats that don't necessarily lend themselves to a relational representation. It's more convenient to hold them in a Hadoop file system, and it's more convenient to hold them in just a great big key value store like NoSQL. And yet, they would like to use these data sources as if they were in the same system and not really have to worry about where they are. And we see this with, we see this with telecom providers who want to combine call data records with customer, warehouse, you know, customer data in the data warehouse. We see it with financial services companies who want to do a similar thing of combining research with portfolio investments records of what their high net worth customers have invested, with transaction data from the equities markets. So we see this polyglot future, the future of all of these different data management technologies, and their applications in the analytics built on top, working together, and existing in this hybrid cloud environment. >> So that's different than the historical Oracle, at least perceived messaging, where a lot of people believe that Oracle sees its Oracle database as a hammer, and every opportunity is a nail. You're telling a completely different story now. >> Well, it turns out there are many nails. So, you know, the hammer's still a good thing, but it turns out that, you know, there are also brads and tacks and Philips and flathead screwdrivers too. And this is just one of the consequences of our customers creating more kinds of data. Images, audio, JSON, XML, you know, spectrographic images from drones that are analyzing how much green is in a photograph because that indicates the chlorophyll content. We know, we know that our customers' ability to compete is based on how they create value from data capital. And so Oracle is in the business of making the things that make data more valuable, and we want to reinvent enterprise computing as a set of services that are easier to buy and use. >> And SQL is the lowest common denominator there, because of the skill sets that are available, is that right or? >> Well, it's funny, it's not necessarily a lowest common denominator, it turns out it's just incredibly useful. (laughs) Sequel is not just a technology standard, it's actually, in a manner of speaking, it's sort of a thinking standard. SQL is based on literally hundreds of years of hard thinking about how to think straight. You can trace SQL back to predicate logic, which was one of the critical ideas in the renaissance of mathematics and logic in the 1800s. So SQL embodies this way to think about, to think logically, to think about the attributes of things and their values and to reason about them in an automated fashion. And that is not going away, that in fact is going to become more powerful, more useful. >> Business processes are wired to that way of thinking, is what you're saying. >> That's exactly right. If you want to improve your operational effectiveness as a company, you're going to have to standardize some of your procedures and automate them, and that means you're going to standardize the information component of those activities. You can automate them better. And you're going to want to ask questions about, how's it going? And SQL is incredibly useful for doing that. >> So we went way over our time, this is very interesting discussion, but I have to ask you, what is it you do at Oracle? Do you work with customers to help them understand data strategies and catalyze new thinking? What's your day-to-day like? >> Yeah, I do a lot of this, a lot of telling the story, because we're in a huge time of change. Every 20 years or so, the IT industry goes through an architectural shift, and that changes, not just the technologies used to create value from data, but it changes the very value created from data itself. It changes what you can do with information. So, I spend a lot of time explaining these ideas of data capital, and sitting down with executives at our customers, helping them understand how to look out at the world and see the data that is not there yet, and what that means for the way that they compete, and then we talk through the competitive strategies that follow from that, and the technical architecture required to execute those strategies. >> Excellent. Well, Paul, thanks very much for sharing your knowledge with our Cube audience and coming into the Silicon Angle Media Studios here at Marlborough. >> Well, it's my pleasure. Thanks for having me. >> All right, you're welcome. Okay, thanks for watching, everybody. This is The Cube, Silicon Angle Media's special on the ground production. We'll see you next time. (peppy synth music)