(upbeat music) >> Hello, welcome to this CUBE Conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We're here with Tim Everson, CISO at Kalahari Resorts & Conventions. Tim, great to see you. Thanks for coming on theCUBE. >> Thank you for having me. Looking forward to it. >> So, you know, RSA is going on this week. We're talking a lot about security. You've got a lot of conferences. Security is a big scale now across all enterprises, all businesses. You're in the hospitality, you got conventions. You're in the middle of it. You have an interesting environment. You've got a lot of diverse use cases. And you've got a lot of needs. They're always changing. I mean, you talk about change. You've got a network that has to be responsive, robust and support a lot of tough customers who want to have fun or do business. >> Exactly, yeah. We have customers that come in, that we were talking about this before the segment. And we have customers that come in that bring their own Roku Sticks their own Amazon devices. All these different things they bring in. You know, our resort customers need dedicated bandwidth. So they need dedicated network segments stood up at a moment's notice to do the things they're doing and run the shows they're showing. So it's never, never ending. It's constantly changing in our business. And there's just data galore to keep an eye on. So it's really interesting. >> Can you scope the scale of the current cybersecurity challenges these days in the industry? Because they're wide and far, they're deep. You got zero trust on one end, which is essentially don't trust anything. And then you got now on the software supply chain, things like more trust. So you got the conflict between a direction that's more trusted and then zero trust, and everything in between. From, endpoint protection. It's a lot going on. What's the scale of this situation right now in cyber? >> You know, right now everything's very, very up in the air. You talk about zero trust. And zero trust can be defined a lot of ways depending on what security person you talk to today. So, I won't go into my long discussion about zero trust but suffice to say, like I said zero trust can be perceived so many different ways. From a user perspective, from a network perspective, from an end point. I look more broadly at the regulatory side of things and how that affects things too. Because, regulations are changing daily. You've got your GDPRs, your CCPAs, your HIPAA regulations, PCI. All these different things that affect businesses, and affect businesses different ways. I mean, at Kalahari we're vulnerable or we're not vulnerable, but we're subject to a lot of these different regulations, more so than other people. You wouldn't expect a lot of hotels to have HIPAA regulations for instance. We have health people at our resorts. So we actually are subject to HIPAA in a lot of cases. So there's a lot of these broad scenarios that apply and they come into play with all different industries. And again, things you don't expect. So, when you see these threats coming, when you see all the hacks coming. Even today I got an email that the Marriott breach data from a few years ago, or the MGM breach from a few years ago. We've got all these breaches out there in the world, are coming back to the surface and being looked at again. And our users and our guests and our corporate partners, and all these different people see those things and they rely on us to protect them. So it makes that scope just exponentially bigger. >> Yeah, there's so many threads to pull on here. One is, you know we've observed certainly with the pandemic and then now going forward is that if you weren't modern in your infrastructure, in your environment, you are exposed. Even, I'm not talking old and antiquated like in the dark ages IT. We're talking like really state of the art, current. If you're lagging just by a few years, the hackers have an advantage. So, the constant bar raising, leveling up on technology is part of this arms race against the bad guys. >> Absolutely. And you said it, you talked earlier about the supply chain. Supply chain, these attacks that have come through the SolarWinds attacks and some of these other supply chain attacks that are coming out right now. Everybody's doing their best to stay on top of the latest, greatest. And the problem with that is, when you rely on other vendors and other companies to be able to help you do that. And you're relying on all these different tool sets, the supply chain attack is hugely critical. It makes it really, really important that you're watching where you're getting your software from, what they're doing with it, how they secure it. And that when you're dealing with your vendors and your different suppliers, you're making sure that they're securing things as well as you are. And it just, it adds to the complexity, it adds to the footprint and it adds to the headache that a lot of these security teams have. Especially small teams where they don't have the people to manage those kind of contacts. >> It's so interesting, I think zero trust is a knee jerk reaction to the perimeter being gone. It's like, you got to People love the zero trust. Oh it's like, "We're going to protect this that nobody, and then vet them in." But once you're trusted, trust also is coming in to play here. And in your environment, you're a hotel, you're a convention. You have a lot of rotation of guests coming in. Very much high velocity. And spear phishing and phishing, I could be watching and socially engineering someone that could be on your property at any given time. You got to be prepared for that. Or, you got ransomware coming around the corners or heavily. So, you got the ransomware threat and you got potentially spear phishing that could be possible at your place. These are things that are going on, right? That you got to protect for. What's your reaction to that? >> Absolutely. We see all those kind of attacks on a daily basis. I see spear phishing attacks. I see, web links and I chase them down and see what's going on. I see that there's ransomware trying to come in. We see these things every single day. And the problem you have with it is not only, especially in a space where you have a high volume of customers and a high turnover of customers like you're talking about that are in and out of our resorts, in and out of our facilities. Those attacks aren't just coming from our executives and their email. We can have a guest sitting on a guest network, on a wireless network. Or on one of our business center machines, or using our resort network for any one of a number of the conference things that they're doing and the different ports that we have to open and the different bandwidth scenarios that you've got dealing with. All of these things come into play because if any attack comes from any of those channels you have to make sure that segmentation is right, that your tooling is proper and that your team is aware and watching for it. And so it does. It makes it a very challenging environment to be in. >> You know, I don't want to bring up the budget issue but I'll bring up the budget issue. You can have unlimited budget because there's so many tools out there and platforms now. I mean, if you've look at the ecosystem map of the cybersecurity landscape that you have to navigate through as a customer. You've got a lot of people knocking on your door to sell you stuff. So I have to ask you, what is the scale? I mean, you can't have unlimited budget. But the reality is you have to kind of, do the right thing. What's the most helpful kind of tools and platforms for you that you've seen that you've had experience with? Where's this going in terms of the most effective mechanisms and software and platforms that are available out there? >> From the security perspective specifically, the three things that are most important to me are visibility. Whether it's asset visibility or log visibility. You know, being able to see the data, being able to see what's going on. End user. Making sure that the end user has been trained, is aware and that you're watching them. Because the end user, the human is always the weakest link. The human doesn't have digital controls that can be hard set and absolutely followed. The human changes every day. And then our endpoint security solutions. Those are the three biggest things for me. You know, you have your network perimeter, your firewalls. But attackers aren't always looking for those. They're coming from the inside, they're finding a way around those. The biggest three things for me are endpoint, visibility and the end user. >> Yeah, it's awesome. And a lot of companies are really looking at their posture right now. So I would ask you as a CISO, who's in the front end of all this great stuff and protecting your networks and all your environments and the endpoints and assets. What advice would you have for other CISOs who are kind of trying to level up to where you're at, in terms of rethinking their security posture? What advice would you give them? >> The advice I would give you is surround yourself with people that are like-minded on the security side. Make sure that these people are aware but that they're willing to grow. Because security's always changing. If you get a security person that's dead set that they're going to be a network security person and that's all they're going to do. You know, you may have that need and you may fill it. But at the end of the day, you need somebody who's open rounded and ready to change. And then you need to make sure that you can have somebody, and the team that you work with is able to talk to your executives. It never fails, the executives. They understand security from the standpoint of the business, but they don't necessarily understand security from the technical side. So you have to make sure that you can cross those two boundaries. And when you grow your team you have to make sure that that's the biggest focus. >> I have to ask the pandemic question, but I know cybersecurity hasn't changed. In fact, it's gotten more aggressive in the pandemic. How has the post pandemic or kind of like towards the tail end of where we're at now, affect the cybersecurity landscape? Has it increased velocity? Has it changed any kind of threat vectors? Has it changed in any way? Can you share your thoughts on what happened during the pandemic and now has we come out of it into the next, well post pandemic? >> Absolutely. It affected hospitality in a kind of unique way. Because, a lot of the different governments, state, federal. I'm in Ohio. I work out of our Ohio resort. A lot of the governments literally shut us down or limited severely how many guests we could have in. So on the one hand you've got less traffic internal over the network. So you've got a little bit of a slow down there. But on the flip side it also meant a lot of our workers were working from home. So now you've got a lot of remote access coming in. You've got people that are trying to get in from home and work machines. You have to transition call centers and call volume and all of the things that come along with that. And you have to make sure that that human element is accounted for. Because, again, you've got people working from home, you no longer know if the person that's calling you today, if it's not somebody you're familiar with you don't know if that person is Joe Blow from the front desk or if that person's a vendor or who they are. And so when you deal with a company with 5,000 ish employees or 10,000 that some of these bigger companies are. 15,000, whatever the case may be. You know, the pandemic really put a shift in there because now you're protecting not only against the technologies, but you're dealing with all of the scams, all of the phishing attempts that are coming through that are COVID related. All of these various things. And it really did. It threw a crazy mix into cybersecurity. >> I can imagine that the brain trust over there is prior thinking, "Hey, we were a hybrid experience." Now, if people who have come and experienced our resorts and conventions can come in remotely, even in a hybrid experience with folks that are there. You've seen a lot of hybrid events for instance go on, where there's shared experience. I can almost imagine your service area is now extending to the homes of those guests. That you got to start thinking differently. Has that been something that you guys are looking at? >> We're looking at it from the standpoint of trying to broaden some of the events. In the case of a lot of our conventions, things of that nature. The conventions that aren't actually Kalahari's run conventions, we host them, we manage them. But it does... When you talk about workers coming from home to attend these conventions. Or these telecommuters that are attending these conventions. It does affect us in the stance that, like I said we have to provision network for these various events. And we have to make sure that the network and the security around the network are tight. So it does. It makes a big deal as far as how Kalahari does its business. Being able to still operate these different meetings and different conventions, and being able to host remotely as well. You know, making sure that telecommunications are available to them. Making sure that network access and room access are available to them. You know for places where we can't gather heavily in meetings. You know, these people still being able to be near each other, still being able to talk, but making sure that that technology is there between them. >> Well, Tim is great to have you on for this CUBE Conversation. CISO from the middle of all the action. You're seeing a lot. There's a lot of surface area you got to watch. There's a lot of data you got to observe. You got to get that visibility. You can only protect what you can see, and the more you see the better it is. The better the machine learning. You brought up the the common area about like-minded individuals. I want to just ask you on the final point here, on hiring and talent coming into the marketplace. I mean, this younger generation coming out of university and college is, or not even going to school. There's no cyber degree. I mean, there are now. But I mean, the world's changing. It's easy to level up. So, skill sets you can't get a degree in certain things. I mean, you got to have a broad set. What do you look for in talent? Is there a trend you see in terms of what makes a good cybersecurity professional, developer, analyst? Is there roles that you see emerging that you think people should pay attention to? What's your take on this as someone who's looking at the future? And- >> You know, it's very interesting that you bring this up. I actually have two of my team members, one directly working for me and another team member at Kalahari that are currently going through college degree programs for cybersecurity. And I wrote recommendations for them. I've worked with them, I'm helping them study. But as you bring people up, you know the other thing I do is I mentor at a couple of the local technical schools as well. I go in, I talk to people, I help them design their programs. And the biggest thing I try to get across to them is, number one, if you're in the learning side of it. Not even talking about the hiring side of it. If you're in the learning side of it, you need to come into it with a kind of an understanding to begin with to where you want to fit into security. You know, do you want to be an attacker, a defender, a manager? Where do you want to be? And then you also need to look at the market and talk to the businesses in the area. You know, I talk to these kids regularly about what their need is. Because if you're in school and you're taking Cisco classes, and focusing on firewalls and what an organization needs as somebody who can read log and do things like that. Or somebody who can do pen testing. You know, that's a huge thing. So I would say if you're on the hiring side of that equation, you know. Like you said, there's no super degrees that I can speak to. There's a lot of certifications. There's a lot of different things like that. The goal for me is finding somebody who can put hands to the ground and feet to the ground, and show me that they know what they know. You know, I'll pull somebody in, I'll ask them to show me a certain specific or I'll ask them for specific information and try to feel that out. Because at the end of the day, there's no degree that's going to protect my network. There's no degree that's a hundred percent going to understand Kalahari, for instance. So I want to make sure that the people I talk to, I get a broad interview scope, I get a number of people to talk to. And really get a feel for what it is they know, and what tools they want to work with and make sure it's going to align with us. >> Well, Tim, that's great that you do that. I think the industry needs that. And I think that's really paying it forward, by getting in and using your time to help shape the young curriculums and the young guns out there. It's interesting you know, like David Vellante and I talk on theCUBE all the time. Cyber is like sports. If you're playing football, you got to know the game. If you're playing football and you come in as a baseball player, the skills might not translate, right? So it's really more of, categorically cyber has a certain pattern to it. Math, open mindedness, connecting dots, seeing things around corners. Maybe it's more holistic views, if you're at the visibility level or getting the weeds with data. A lot of different skill sets needed. The aperture of the job requirements are changing a lot. >> They are. And you know, you touched on that really well. You know, they talk about hacking and the hacker mindset. You know, all the security stuff revolves around hacker. And people mislabel hacker. Hacking in general is making something do something that it wasn't originally designed to do. And when I hire people in security, I want people that have that mindset. I want people that not only are going to work with the tool set we have, and use that mathematical ability and that logic and that reasoning. But I want them to use a reasoning of, "Hey, we have this tool here today. How can this tool do what I want it do but what else can it do for me?" Because like any other industry we have to stretch our dollar. So if I have a tool set that can meet five different needs for me today, rather than investing in 16 different tool sets and spreading that data out and spreading all the control around. Let's focus on those tool sets and let's focus on using that knowledge and that adaptive ability that the human people have on the security side, and put that to use. Make them use the tools that work for them but make 'em develop things, new tools, new methods, new techniques that help us get things across. >> Grow the capabilities, protect, trust all things coming in. And Tim, you're a tech athlete, as we say and you've got a great thing going on over there. And again, congratulations on the work you're doing on the higher ed and the education side and the Kalahari Resorts & Conventions. Thanks for coming on theCUBE. I really appreciate the insight you're sharing. Thank you. >> Thanks for having me. >> Okay. I'm John Furrier here in Palo Alto for theCUBE. Thanks for watching. (somber music)

>>Hello, everyone. This is not appropriate to lapse of America. I'm going to talk about the motivation. For zero knowledge goes back to the heart off, winding down identity, ownership, community and control. Much of photography exists today to support control communications among individuals in the one world. We also consider devices as extensions of individuals and corporations as communities. Here's hoping you're not fit in this picture. What defines the boundary off an individual is the ability to hold a secret with maybe, it says, attached to the ownership. Off some ethic, we want the ability to use the secret to prove ownership of this asset. However, giving up the secret itself essentially announced ownership since then, anybody else can do the same. Dear Knowledge gives us tools to prove ownership without revealing the secret. The notion of proving ownership off a digital object without revealing it sounds very paradoxical outside the model off. So it gives us a surprise when this motion was formalized and constructed by Goldwasser Miccoli and back off in the late eighties, we'll focus on the non interactive >>version of Siri, a knowledge our music in the >>stock, which was first developed by blow Tillman and Peggy, where the general it can span multiple rounds of communications music only allows a single message to be trusted. No, let's get into some technical details for musics. The objective of for music is to show that an object X, which you can think off as the public footprint, often asset, belonging clan and the language without revealing its witness. W, which you can think off as the Future Analytics team consists off three algorithms, video proof and very. The key generation process is executed by a trusted third party and the very opposite, resulting in a common >>random string, or steers, which is made public. The >>true vendor produces a proof by based on the CIA's X and the very fine with the checks. The proof against X and accepts or rejects music off course has to satisfy some properties. We needed to be correct, which basically says that when everyone follows the protocol correctly on, so we can expect, we need to be thought, which says that a false statement cannot be proven. The channel is a trickier properly to form this. How do we capture the intuition behind saying that the proof there is no knowledge of the witness. One way to capture that is to imagine their tools is the real world where the proof is calculated. Using the witness on there's a simulation worth where the proof is calculated without a witness. To make this possible, the simulator may have some extra information about the CIA's, which is independent off the objectives. The property then requires that it is not possible to effectively distinguish these words Now. It is especially challenging to construct music's compared to encryption signature schemes, in particular in signature schemes. The analog off the Hoover can use a secret, and in any case, the analog off the very fire can use a secret. But in is it's none of the crew layer and the verifier can hold a secret. Yeah, in this talk, I'm going to focus on linear subspace languages. This class is the basis of hardness. >>Assumptions like GH and deliver >>on has proved extremely useful in crypto constructions. This is how we express DD it and dealing as linear software. We will use additive notation on express the spirit logs as the near group actions on coop elements. You think the syntax we can write down Deitch on dealing Jupiter's very naturally a zoo witness sector times a constant electric so we can view the language as being penetrated by a constant language. Metrics really was hard by many groups in our instructions. What does it mean? S while uh, Standard group allows traditions and explain it off by in your group also allows one modification In such groups, we can state various in yourself facing elections. The DDN is the simplest one. It assumes that sampling a one dimensional space is indistinguishable from something full professional. The decisional linear assumption assumes the theme from tours is three dimensional spaces generalizing the sequence of Presumptions. The scaling the resumption asks to distinguish between gay damaged examples and full it and >>examples from a K plus one national space. >>Right, So I came up with a breakthrough. Is the construction in Europe 2008 in particular? There? Music for many years Off Spaces was the first efficient >>construction based on idiots and gear. Structurally, >>it consisted of two parts Our commitment to the witness Andre question proof part and going how the witness actually corresponds to the object. The number of elements in the proof is linear in the number >>of witnesses on the number of elements in the object. >>The question remains to build even shorter visits. The Sierras itself seemed to provide some scoop Rosa Russo fix. See how that works for an entire class of languages? Maybe there's a way to increase proof efficiency on the cost of having had Taylor Sierra's for each year. This is what motivates quality and after six, where we let the solace depend on the language itself. In particular, we didn't require the discrete logs of the language constants to generate this, Yes, but we did require this constant student generated from witness sample distributions. This still turns out to be sufficient for many applications. The construction achieved a perfect knowledge, which was universally in the sense that the simulator was independent. However, soundness is competition. So here's how the construction differed from roots high at a very high level, the language constants are embedded into the CIA s in such a way that the object functions as it's only so we end up not needing any separate commitment in the perfect sense. Our particular construction also needed fewer elements in the question proof, as there On the flip side, the CIA's blows up quadratic instead of constant. Let's get into the detail construction, which is actually present with this script. Let the language apparently trace by Giovanni tricks with the witness changing over time, we sat down and matrices >>D and B with appropriate damages. >>Then we construct the public series into what C. S. D is meant to be used. By the way. On it is constructed by >>multiplying the language matrix with D and being worse, Sierra's V is the part that is meant to be used by the very fair, and it is constructed using details be on be embedded in teaching. >>Now let's say you're asked to computer proof for a candidate X with fitness number we computed simply as a product of the witness with CSP. The verification of the truth is simply taking with the pairing off the candidate and the proof with the Sierras. Seeming threats is equal to zero. If you look carefully. Sierra's V essentially embedded in G to the kernel of the Matrix, owned by the language metrics here and so to speak. This is what is responsible for the correctness. The zero knowledge property is also straightforward, >>given the trapdoor matrices, D and B. Now, >>when corrected journalism relatively simple to prove proving illnesses strictly The central observation is that, given CSP, there is still enough entropy. >>India and me to >>random I seriously in particular Sierra's we Can we expand it to have an additional component with a random sample from the kernel allows it. This transformation is purely statistical. No, we essentially invented idiots are killing their talent in the era of kernel part in this transform sitting within show that an alleged proof on a bad candidate and we used to distinguish whether a subspace sample was used for a full space >>sample was used at the challenge. The need >>to have the kernel of the language in this city. That's the technical >>reason why we need the language to come from a witness. Sample. >>Uh, let's give a simple illustration >>of the system on a standard Diffie Hellman, which g one with the hardness assumption being idiot. >>So the language is defined by G one elements small D, E and F, with pupils off the phone due to the W. After that ugly, the CIA is is generated as follows example D and >>B from random on Compute Sierra speak as due to the day after the being verse and Sierra's V as G to do to do the big on day two of the video. The >>proof of the pupil >>detail that I do after the bill is computed using W. As Sierra Speed race to the party. I know that this is just a single element in the group. The verification is done by bearing the Cooper and the proof with the Sierras VMS and then checking in quality. The >>similar can easily compute the proof using trapdoors demand without knowing that what we are expecting. People leave a Peter's die and reduce the roof size, the constant under a given independent of the number of witnesses and object dimensions. Finally, at Cryptocurrency 14 we optimize the proof toe, one group >>element under the idiots. In both the works, the theorists was reduced to linear sites. The >>number of bearings needed for ratification was also industry in years. This is the crypto Ford in construction in action, the construction skeleton remains more or less the famous VR turkey. But the core observation was that many of the Sierras elements could were anomaly. Comite. While still >>maintaining some of this, these extra random items are depicted in red in this side. >>This round of combination of the Sierras elements resulted in a reduction of boat, Bruce says, as also the number of clearings required for education in Europe in 2015 kills, and we came up with a beautiful >>interpretation of skill sets based on the concept of small predictive hash functions. >>This slide is oversimplified but illustrated, wanting, uh, this system has four collecting >>puzzle pieces. The goodness of the language metrics okay again and a key Haider when >>the hidden version of the key is given publicly in the Sears. Now, when we have a good object, the pieces fit together nicely into detectable. However, when we have a bad object, the pieces no longer fit and it becomes >>infeasible to come up with convincing. Zero knowledge is demonstrable by giving the key to the simulator on observing that the key is independent of the language metrics. >>Through the years, we have extended >>enhanced not mind to be six system, especially with our collaborators, Masayuki Abby Koko Jr. Born on U. >>N. Based on your visits, we were able to construct very efficient, identity based encryption structure, resulting signatures >>public verifiable CCS, secure encryption, nine signatures, group signatures, authorities, key extremes and so on. >>It has also been gratifying to see the community make leaps and bounces ideas and also use queuing visits in practical limits. Before finishing off, I wanted to talk to you a little bit about >>some exciting activities going on Hyper ledger, which is relevant for photographers. Hyper >>Leisure is an open source community for enterprise. Great. It's hosted by the minute formation on enjoys participation from numerous industry groups. Uh, so difficult funded to efforts in Africa, we have versa, which is poised to be the crypto home for all. Blocking it and practice a platform for prospecting transactions are part of the legs on the slide here, >>we would love participation from entity inference. So >>that was a brief history of your analytics. Thanks for giving me the opportunity. And thanks for listening

live from San Francisco it's the cube covering micron insight 2018 brought to you by micron welcome back to the San Francisco Bay everybody we saw the Sun rise in the bay this morning of an hour so we're gonna see the Sun set this gorgeous setting here at Pier 27 Nob Hills up there the Golden Gate Bridge over there and of course we have this gorgeous view of the bay you're watching the cube the leader in live tech coverage we're covering micron insight 2018 ai accelerating intelligence a lot of talk on on on memory and storage but a lot more talk around the future of AI so we got a great discussion here on the auto business and how AI is powering that business Jeff Bader is here is the corporate vice president and general manager of the embedded business unit at micron good to see you again Jeff thanks for coming on and Simon and rigor is the vice president BMW and he's also joined by Vijay Nadkarni who was the global head of AI and augmented reality at Visteon which is a supplier to Automobile Manufacturers gentlemen welcome to the cube thanks so much for coming on thank you so you guys had a panel earlier today which was pretty extensive and just a lot of talk about AI how AI will be a platform for interacting with the vehicle the consumer the driver interacting with the vehicle also talked a lot about autonomous vehicles but Simon watch you kick it off your role at BMW let's let's just start there it will do the same for Vijay and then get into it research portion that we do globally in which is represented here in North America and so obviously we're working on autonomous vehicles as well as integrating assistance into the car and basically what we're trying to do is to get use AI as much as possible in all of the behavioral parts of the vehicle that uses have an expectations towards being more personalized and having a personalized experience whereas we have a solid portion of the vehicle is going to be as a deterministic anesthetic as we have it before like all of the safety aspects for example and that is what we're working on here right now Vijay Visteon is a supplier to BMW and other auto manufacturers yes we are a tier 1 supplier so we basically don't make cars but we supply auto manufacturers of which BMW is one and my role is essentially AI technology adversity on and also augmented reality so in AI there are basically two segments that we cater to and one of them is that almost driving which is fully our biggest segment and the second one is infotainment and in that the whole idea is to give the driver a better experience in the car by way of recommendations or productivity improvements and such so that is so my team basically develops the technology and then we centrally integrate that into our products so so not necessarily self-driving it's really more about the experience inside the vehicle that is the and then on the autonomous driving side we of course very much are involved with the autonomous driving technology which is tested with detecting objects are also making the proper maneuvers for the Waker and we're definitely going to talk about that now Jeff you sell to the embedded industry of fooding automobile manufacturers we hear that cars have I forget the number of microprocessors but there's also a lot of memory and storage associate yeah I mean if you follow the chain you have our simon representing the OEMs Vijay represented the Tier one suppliers were supplier to those Tier one suppliers in essence right so so we're providing memory and storage that then goes in to the car in as you said across all of the different sort of control and engine drone and computing units within the car in particular into that infotainment application and increasingly into the a TAS or advanced driver assistance systems that are leading toward autonomous driving so there's a lot of AI or some AI anyway in vehicles today right presumably yeah affected David who did a wonderful job on the panel he was outstanding but he kind of got caught up in having multiple systems like a like an apple carplay your own system I actually have a bit about kind of a BMW have a mini because I'm afraid it's gonna be self-driving cars and I just want to drive a drive on car for this take it away from me though but but you push a button if you want to talk to a Syrian yeah push another button if you want to talk to the mini I mean it's it's gonna use it for different use cases right exactly may I is also about adaption and is also about integrating so AI is is is coming with you with the devices that you have with you anyway right so your might be an Alexa user rather than a Google assistant user and you would have that expectation to be able to ask to chat with your Alexa in your car as well that's why we have them in the vehicle also we have an own voice assistant that we recently launched in Paris Motorshow which augments the experience that you have with your own assistants because it factors in all of the things you can do with the car so you can say there is a solid portion of AI already in the vehicle it's mainly visible in the infotainment section right and of course I remember the first time I'm sure you guys experienced to that the the car braked on my behalf and then kind of freaked me out but then I kind of liked it too and that's another form of machine intelligence well that out well that counts for you that had not that has not necessarily been done by AI because in in in let's say self-driving there is a portion of pretty deterministic rule based behavior and exactly that one like hitting an object at parking you don't need AI to determine to hit the right there is no portion or of AI necessary in order to improve that behavior whereas predicting the best driving strategy for your 20-mile ride on the highway this is where AI is really beneficial in fact I was at a conference last week in Orlando it's the Splunk show and it was a speaker from BMW talking about what you're doing in that regard yeah it's all about the data right learning about it and and in turning data into insights into better behavior yes into better expected behavior from whatever the customer wants so Vijay you were saying before that you actually provide technology for autonomous vehicles all right I got a question for you could it autonomous - could today's state of autonomous vehicles pass a driver's test no no would you let it take one no it depends I mean there are certain companies like way mo for example that do a lot but I still don't think way mo can take a proper driver's test as of today but it is of course trying to get there but what we are essentially doing is taking baby steps first and I think you may be aware of the SAE levels so level 1 level 2 level 3 level 4 SF and a 5 so we and most of the companies in the industry right now are really focusing more on the level 2 through level 4 and a few companies like Google or WAV or other and uber and such are focusing on the level 5 we actually believe that the level 2 through 4 is the market would be ready for that essentially in the shorter term whereas the level 5 will take a little while to get that so everybody Christmas and everyone we're gonna have autonomous because I'm not gonna ask you that question because there's such a spectrum of self-driving but I want to ask you the question differently and I ask each of you when do you think that driving your own car will become the exception rather than than the rule well I'd rather prefer actually to rephrase the question maybe to where not when because we're on a highway setting this question can be answered precisely in roughly two to three years the the functionality will kick in and then it's going to be the renewal of the vehicles so if you answer if you if you ask where then there is an answer within the next five years definitely if we talk about an urban downtown scenario the question when is hard to answer yeah well so my question is more of a social question it is a technology question because I'm not giving up my stick shift high example getting my 17 year old to get his permit was like kicking a bird out of the nest I did drive his permanent driver on staff basically with me right so why but I mean when I was a kid that was freedom 16 years old you racing out and there is a large generational group growing up right now that doesn't necessarily see it as a necessity right so not driving your own car I think car share services right share who bore the so and so forth are absolutely going to solve a large portion of the technology of the transportation challenge for a large portion of the population I think but I agree with the the earlier answers of it's gonna be where you're not driving as opposed to necessarily win and I think we heard today of course the you know talking about I think the number is 40,000 fatalities on the roadways in the u.s. in the u.s. yeah everybody talks about how autonomous vehicles are going to help attack that problem um but it strikes me talk about autonomous cars it why don't we have autonomous carts like in a hospital or even autonomous robots that aren't relying on lines or stripes or beacons you one would think that that would come before in our autonomous vehicle am I missing something are there are there there there systems out there that that I just haven't seen well I don't know if you've ever seen videos of Amazon distribution centers yeah but they're there they're going to school on lines and beacons and they are they're not really autonomous yeah that's fair that's fair yeah so will we see autonomous carts before we see autonomous cars I think it's a question what problem that solves necessarily yeah it's just as easy for them to know where something is yeah you think about microns fabs every one of our fabs is is completely automated as a material handling system that runs up and down around the ceilings handling all the wafers and all the cartridges the wafers moving it from one tool to the next tool to the next tool there's not people anymore carrying that around or even robots on the floor right but it's a guided track system that only can go to certain you know certain places well the last speaker today ii was talking about it I remember when robots couldn't climb stairs and now they can do backflips and you know you think about the list of things that humans can do that computers can't do it let's get smaller and smaller every year so it's kind of scary to think about one hand is that does the does the concept of Byzantine fault-tolerance you guys familiar with that does that does that come into play here you guys know what that's about I don't know what it is exactly so that's a problem and I first read about it with it's the Byzantine general problem if you have nine generals for one Oh attack for one retreat and the ninth sends a message to half to retreat or not and then you don't have the full force of the attack so the concept is if you're in a self-driving boat within the vehicle and within the ecosystem around the city then you're collectively solving the problem so there these are challenging math that need to be worked out and and I'm not saying I'm a skeptic but I just wanted more I read about it the more hurdles we have there's some isolated examples of where AI I think fits really well and is gonna solve problems today but this singularity of vehicle seems to be we have a highly regulated environment obviously public transportation or public roads right are a highly regulated environment so it's like it's different than curating playlists or whatever right this is not so much regulated traffic and legislation isn't there yet so especially and it's it's designed for humans right traffic cars roads are designed for human to use them and so the adoption to they the design of any legislation any public infrastructure would be completely different if we didn't drive as humans but we have it we have machines drive them so why are robots and carts not coming because the infrastructure really is designed for humans and so I think that's what's going to be the ultimate slow down is how fast we as a society that comes up with legislation with acceptance of behavioral aspects that are driven by AI on how fast we adopt it technically I think it can happen faster than yeah yeah it's not a technology problem as much as it is the public policy insurance companies think about one of the eventually you can think of from from let's say even level four capable car on a highway is platooning yeah right instead of having X number of car lengths to the turn fryer you just stack them up and they're all going on in a row that sounds great until Joe Blow with their 20 year old Honda you know starts to pull into that Lane right so you either say this Lane is not allowed for that or you create special infrastructure essentially that isn't designed for humans there is more designed specifically for the for the machine driven car right how big is this market it's it feels like it's enormous I don't know how do you look at the tan we can talk to the memory I can talk the memory storage part of it right but today memory and storage all of memory storage for automotive is about a two and a half billion dollar market that is gonna triple in the next three years and probably beyond that my visibility is not so good maybe yours is better for sure but it then really driven by adoption rate and how fast that starts to penetrate through the car of OAM lines and across the different car in vijay your firm is when were you formed how long you've been around or vistas be around basically since around 2001 okay we were part of relatively old spun out whiskey on that at work right okay so so alright so that's been around forever yeah for this Greenfield for you for your your group right where's the aw this is transitional right so is it is it is it you try not to get disrupted or you trying to be the disrupter or is it just all sort of incremental as a 101 year old company obviously people think about you as being ripe for disruption and I think we do quite well in terms of renewing ourselves coming from aeroplane business to a motorcycle business to garbage and so I think the answer is are we fast enough I'll be fast enough in adoption and on the other hand it's fair to say that BMW with all of its brands is part of a premium thing and so it's not into the mass transportation so everything that's going to be eaten up by something like multi occupancy vehicle mass transportation in a smaller effort right this is probably not going to hurt the premium brand so much as a typical econo type of boxy car exciting time so thanks so much for coming on the cube you got a run appreciate thank you so much okay thanks for watching everybody we are out from San Francisco you've watched the cube micron inside 2018 check out Silicon angle comm for all the published research the cube dotnet as well you'll find these videos will keep on calm for all the research thanks for watching everybody we'll see you next time you

>> Hey welcome back everybody, Jeff Frick here with theCUBE we're at the data privacy day at Twitter's world headquarters in downtown San Fransciso and we're really excited to get into it with our next guest Dr. Andreas Weigend, he is now at the Social Data Lab, used to be at Amazon, recently published author. Welcome. >> Good to be here, morning. >> Absolutely, so give us a little about what is Social Data Lab for people who aren't that familiar with it and what are you doing over at Berkeley? >> Alright, so let's start with what is social data? Social data is a data people create and share whether they know it or not and what that means is Twitter is explicit but also a geo location or maybe even just having photos about you. I was in Russia all day during the election day in the United States with Putin, and I have to say that people now share on Facebook what the KGB wouldn't have gotten out of them under torture. >> So did you ever see the Saturday Night Live sketch where they had a congressional hearing and the guy the CIA guy says, Facebook is the most successful project that we've ever launched, people tell us where they are who they're with and what they're going to do, share pictures, location, it's a pretty interesting sketch. >> Only be taught by Black Mirror, some of these episodes are absolutely amazing. >> People can't even watch is it what I have not seen I have to see but they're like that's just too crazy. Too real, too close to home. >> Yeah, so what was the question? >> So let's talk about your new book. >> Oh that was social data. >> Yeah social data >> Yeah, and so I call it actually social data revolution. Because if you think back, 10, 20 years ago we absolutely we doesn't mean just you and me, it means a billion people. They think about who they are, differently from 20 years ago, think Facebook as you mentioned. How we buy things, we buy things based on social data we buy things based on what other people say. Not on what some marketing department says. And even you know, the way we think about information I mean could you do a day without Google? >> No >> No. >> Could you go an hour without Google? >> An hour, yes, when I sleep. But some people actually they Google in their sleep. >> Well and they have their health tracker turned on while they sleep to tell them if they slept well. >> I actually find this super interesting. How dependent I am to know in the morning when I wake up before I can push a smiley face or the okay face or the frowny face, to first see how did I sleep? And if the cycles were nice up and down, then it must have been a good night. >> So it's interesting because the concept from all of these kind of biometric feedback loops is if you have the data, you can change your behavior based on the data, but on the other hand there is so much data and do we really change our behaivor based on the data? >> I think the question is a different one. The question is alright, we have all this data but how can we make sure that this data is used for us, not against us. Within a few hundred meters of here there's a company where employees were asked to wear a fit bit or tracking devices which retain more generally. And then one morning one employee came in after you know not having had an exactly solid night of sleep shall we say and his boss said I'm sorry but I just looked at your fit bit you know this is an important meeting, we can't have you at that meeting. Sorry about that. >> True story? >> Yeah >> Now that's interesting. So I think the fit bit angle is interesting when that is a requirement to have company issued health insurance and they see you've been sitting on your couch too much. Now how does that then run into the HIPPA regulations. >> You know, they have dog walkers here. I'm not sure where you live in San Francisco. But in the area many people have dogs. And I know that a couple of my neighbors they give when the dog walker comes to take the dog, they also give their phone to the dog walker so now it looks like they are taking regular walks and they're waiting for the discount from health insurance. >> Yeah, it's interesting. Works great for the person that does walk or gives their phone to the dog walker. But what about the person that doesn't, what about the person that doesn't stop at stop signs. What happens in a world on business models based on aggregated risk pooling when you can segment the individual? >> That is a very very very biased question. It's a question of fairness. So if we know everything about everybody what would it mean to be fair? As you said, insurance is built on pooling risk and that means by nature that there are things that we don't know about people. So maybe, we should propose lbotomy data lobotomy. So people actually have some part chopped off out of the data chopped off. So now we can pool again. >> Interesting >> Of course not, the answer is that we as society should come up with ways of coming up with objective functions, how do we weigh the person you know taking a walk and then it's easy to agree on the function then get the data and rank whatever insurance premium whatever you're talking about here rank that accordingly. So I really think it's a really important concept which actually goes back to my time at Amazon. Where we came up with fitness functions as we call it. And it takes a lot of work to have probably spent 50 hours on that with me going through groups and groups and groups figuring out, what do we want the fitness function to be like? You have to have the buy in of the groups you know it they just think you know that is some random management thing imposed on us, it's not going to happen. But if they understand that's the output they're managing for, then not bad. >> So I want to follow up on the Amazon piece because we're big fans of Jeff Hamilton and Jeff Bezzos who we go to AWS and it's interesting excuse me, James Hamilton when he talks about the resources that EWS can bring to bear around privacy and security and networking and all this massive infrastructure being built in terms of being able to protect privacy once you're in the quote un-quote public cloud versus people trying to execute that at the individual company level and you know RSA is in a couple of weeks the amount of crazy scary stuff that is coming in for people that want interviews around some of this crazy security stuff. When you look at kind of public cloud versus private cloud and privacy you know supported by a big heavy infrastructure like what EWS has versus a Joe Blow company you know trying to implement them themselves, how do you see that challenge. I mean I don't know how the person can compete with having the resourses again the aggregated resources pool that James Hamilton has to bring to barrel this problem. >> So I think we really need to distinguish two things. Which is security versus privacy. So for security there's no question in my mind that Joe Blow, with this little PC has not a chance against our Chinese or Russian friends. Is no question for me that Amazon or Google have way better security teams than anybody else can afford. Because it is really their bread and butter. And if there's a breach on that level then I think it is terrible for them. Just think about the Sony breach on a much smaller scale. That's a very different point from the point of privacy. And from the point about companies deliberately giving the data about you for targeting purposes for instance. And targeting purposes to other companies So I think for the cloud there I trust, I trust Google, I trust Amazon that they are doing hopefully a better job than the Russian hackers. I am more interested in the discussion on the value of data. Over the privacy discussion after all this is the world privacy day and there the question is what do people understand as the trade off they have, what they give in order to get something. People have talked about Google having this impossible irresistible value proposition that for all of those little data you get for instance I took Google Maps to get here, of course Google needs to know where I am to tell me to turn left at the intersection. And of course Google has to know where I want to be going. And Google knows that a bunch of other people are going there today, and you probably figure out that something interesting is happening here. >> Right >> And so those are the interesting questions from me. What do we do with data? What is the value of data? >> But A I don't really think people understand the amount of data that they're giving over and B I really don't think that they understand I mean now maybe they're starting to understand the value because of the value of companies like Google and Facebook that have the data. But do you see a shifting in A the awareness, and I think it's even worse with younger kids who just have lived on their mobile phones since the day they were conscious practically these days. Or will there be a value to >> Or will they even mobile before they were born? Children now come pre-loaded, because the parents take pictures of their children before they are born >> That's true. And you're right and the sonogram et cetera. But and then how has mobile changed this whole conversation because when I was on Facebook on my PC at home very different set of information than when it's connected to all the sensors in my mobile phone when Facebook is on my mobile phone really changes where I am how fast I'm moving, who I'm in proximity to it completely changed the privacy game. >> Yes so geo location and the ACLU here in Northern California chapter has a very good quote on that. "Geo location is really extremely powerful variable" Now what was the question? >> How has this whole privacy thing changed now with the proliferation of the mobile, and the other thing I would say, when you have kids that grew up with mobile and sharing on the young ones don't use Facebook anymore, Instagram, Snap Chat just kind of the notion of sharing and privacy relative to folks that you know wouldn't even give their credit card over the telephone not that long ago, much less type it into a keyboard, um do they really know the value do they really understand the value do they really get the implications when that's the world in which they've lived in. Most of them, you know they're just starting to enter the work force and haven't really felt the implications of that. >> So for me the value of data is how much the data impacts a decision. So for the side of the individual, if I have data about the restaurant, and that makes me decide whether to go there or to not go there. That is having an impact on my decision thus the data is valuable. For a company a decision whether to show me this offer or that offer that is how data is valued from the company. So that kind of should be quantified The value of the picture of my dog when I was a child. That is you know so valuable, I'm not talking about this. I'm very sort of rational here in terms of value of data as the impact is has on decisions. >> Do you see companies giving back more of that value to the providers of that data? Instead of you know just simple access to useful applications but obviously the value exceeds the value of the application they're giving you. >> So you use the term giving back and before you talked about kids giving up data. So I don't think that it is quite the right metaphor. So I know that metaphor come from the physical world. That sometimes has been data is in your oil and that indeed is a good metaphor when it comes to it needs to be refined to have value. But there are other elements where data is very different from oil and that is that I don't really give up data when I share and the company doesn't really give something back to me but it is much interesting exchange like a refinery that I put things in and now I get something not necessarily back I typically get something which is very different from what I gave because it has been combined with the data of a billion other people. And that is where the value lies, that my data gets combined with other peoples data in some cases it's impossible to actually take it out it's like a drop of ink, a drop in the ocean and it spreads out and you cannot say, oh I want my ink back. No, it's too late for that. But it's now spread out and that is a metaphor I think I have for data. So people say, you know I want to be in control of my data. I often think they don't have deep enough thought of what they mean by that. I want to change the conversation of people saying You what can I get by giving you the data? How can you help me make better decisions? How can I be empowered by the data which you are grabbing or which you are listening to that I produce. That is a conversation which I want to ask here at the Privacy Day. >> And that's happening with like Google Maps obviously you're exchanging the information, you're walking down the street, you're headed here they're telling you that there's a Starbucks on the corner if you want to pick up a coffee on the way. So that is already kind of happening right and that's why obviously Google has been so successful. Because they're giving you enough and you're giving them more and you get in this kind of virtuous cycle in terms of the information flow but clearly they're getting a lot more value than you are in terms of their you know based on their market capitalization you know, it's a very valuable thing in the aggregation. So it's almost like a one plus one makes three >> Yes. >> On their side. >> Yes, but it's a one trick pony ultimately. All of the money we make is rats. >> Right, right that's true. But in-- >> It's a good one to point out-- >> But then it begs the question too when we no longer ask but are just delivered that information. >> Yes, I have a friend Gam Dias and he runs a company called First Retail, and he makes the point that there will be no search anymore in a couple of years from now. What are you talking about? I search every day, but is it. Yes. But You know, you will get the things before you even think about it and with Google now a few years ago when other things, I think he is quite right. >> We're starting to see that, right where the cards come to you with a guess as to-- >> And it's not so complicated If let's see you go to the symphony you know, my phone knows that I'm at the symphony even if I turn it off, it know where I turned it off. And it knows when the symphony ends because there are like a thousand other people, so why not get Ubers, Lyfts closer there and amaze people by wow, your car is there already. You know that is always a joke what we have in Germany. In Germany we have a joke that says, Hey go for vacation in Poland your car is there already. But maybe I shouldn't tell those jokes. >> Let's talk about your book. So you've got a new book that came out >> Yeah >> Just recently released, it's called Data for the People. What's in it what should people expect, what motivated you to write the book? >> Well, I'm actually excited yesterday I got my first free copies not from the publisher and not from Amazon. Because they are going by the embargo by which is out next week. But Barnes and Noble-- >> They broke the embargo-- Barnes and Noble. Breaking news >> But three years of work and basically it is about trying to get people to embrace the data they create and to be empowered by the data they create. Lots of stories from companies I've worked with Lots of stories also from China, I have a house in China I spend a month or two months there every year for the last 15 years and the Chinese ecosystem is quite different from the US ecosystem and you of course know that the EU regulations are quite different from the US regulations. So, I wrote on what I think is interesting and I'm looking forward to actually rereading it because they told me I should reread it before I talk about it. >> Because when did you submit it? You probably submitted it-- >> Half a year >> Half a year ago, so yeah. Yeah. So it's available at Barnes and Noble and now Amazon >> It is available. I mean if you order it now, you'll get it by Monday. >> Alright, well Dr. Andreas Weigin thanks for taking a few minutes, we could go forever and ever but I think we've got to let you go back to the rest of the sessions. >> Thank you for having me. >> Alright, pleasure Jeff Frick, you're watching theCUBE see you next time.

>>Live from Seattle, Washington. It's the queue at Tableau conference 2014 brought to you by headline sponsor Tableau.. >>Here are your hosts, John furrier and Jeff Kelly. >>Okay, welcome back. And when we hear live in Seattle, Washington for the cube, this is our flagship program. We go out to the events, expect to see with the noise. I'm John furrier, my coach Jeff Kelly, analysts that we bond.org and we'd love to go talk to the senior leaders of the companies that are hosting the event, the Tablo data 14 conference and Kelly, right EVP of sales for Tableau software. Welcome to the cube. >>Thank you. Thank you for having me. >>So, uh, you're under the, you're in the pressure cooker seat. So sales is everything, right? You know, you guys are a public company and you have to perform. Performance is happy customers, they pay you money, you collect the cash, you put it in the bank and invested into your business and do it again and again. Um, you've done very well as a company. You guys have been great. So I got to ask you, um, about where Chad blow is today. Share with the folks a little bit of the history. Um, you know, we've been big fans of the company actually. We are, uh, you know, me personally being an entrepreneur, I love when companies get built by the founders and don't have to raise money to start the company. They get critical mass and take the extra growth capital. And you guys have done that. You've been in real big success story is an entrepreneurial venture. So share the culture and kind of where you guys are now and with the customer base, the culture. >>Oh, that's a lot of questions all in one. Uh, well thank you for having me. It's a pleasure being here. You know, you asked about what it's been like on this whole journey and a lot of the people that were here at the beginning, we're all still here, right? So I was the first salesperson at Tableau. I joined a month before we started version one. And I've seen how things have changed and evolved. And the truth of the matter is we have a lot more people. We have more customers, but the culture of the company has stayed really sound from the beginning. We were a bunch of people who were very, very passionate about this mission to help people see and understand data. And that's still our mission today. So from the day I started to now, it's all been focused on empowering people to answer their questions more. And so the culture of the people that started were very passionate, really excited about the mission, really a group of company builders who wanted to roll up their sleeves and go make things happen. And yes, we're a bigger company now. Now we're a public company, but we're still just barely, barely scratching the surface. I mean, they're 55 million companies out there in the world. We have 20,000 customers. So we have a long, long way to go. >>I love that you're a senior lead as a company. You've been there as the first is awesome. So I've got to ask you, I mean there's always a moment in time where you go, Oh, will we make it? Or that moment where you going? We've the flywheels going. Could you share just some color around because startups are very hard. Think they're easy all yet. Anyone can do that. So share with a moment where you go, Oh my God, it's gonna be tough shipping where they're shipping a product or hiring or personnel or, and an aha moment where you said, Oh my God, we're doing it. Well, >>when, when you're in this company building mode, it's just you put your head down and you go and you're just go, go, go. And it's always about going and finding the next customer, making sure that customer is excited, ecstatic, hiring more people on the team, making sure that culture is still vibing. And we really just took the focus of doing things one day at a time and treating each customer like their goals. And that's still what we do. Our customers are our lifeblood, right? And that's what's keeping us going. So there were certain times at during during the whole journey, I mean, I remember 2009 when the economy was slowing down. Tableau actually still grew at a really healthy clip, but it was harder. But there was really no time that I felt, Oh, this is a huge uphill battle. I, it was an uphill battle all the time. >>We're still kind of the underdogs, right, where there's tons of customers to help. We haven't helped tons of them yet. And it's just doing things to make sure that we're building good products, empowering people to you go, wow, we're really doing this well. Did you take a break and pause and say, Hey, we're doing it, we're making it. Well, you know, I think one of the moments that really resonated for me is we worked so long to say is Tao, is Tablo gonna make it just keep doing what we're doing and believe in what we're doing. Believe in that mission. And for a long time it was, can we make it to be a public company? Can we ever get to that moment? And I remember the day, it was May 17th last year, 2013 when we were on the floor of the New York stock exchange. And we had brought tons of customers. I mean not customers. We had a lot of employees. So we had over a hundred employees filling out the floor. And in that moment when we had the management team and Christian was ringing the bell, just looking out at all these people who had helped us build Tableau and get to that day. I think that was a moment of real. A lot of pride. And it's funny talking about it right now because where I just came from is gesturing in the bell again at the, at the closing bell. So >>cause that's a lot of those steps are very hard. I mean Jeff and I talked to special all the time. We'll get a big pile of money from the VCs. Four or five guys. >>Well we didn't get a big pile of, >>I know, I just, why I was thinking why it's such a great story because the pilot money could complicate it. Being hungry actually is motivating. So, and then having that customer product successes is a great testimony. So we, I mean I think you guys are a great testimonial to successful startups. Thank you. So let's dig into the sales strategy a little bit. So as you've grown up Tableau, when you started off you really, this is you know, this very nimble underdog. You were kind of going in there with really disrupting the old guard BI players. A lot of, more of a kind of I think a desktop focus, a single user kind of focus. You've expanded, you've got enterprise licenses, now you've got cloud, now you've got mobile. How has the sales strategy evolved over that time period to, to adopt or to adjust to these new, uh, Kevin, the new ways of reaching your customer? >>Well, you know, our model is actually really quite simple. I'll go back to what I had talked about before. We help people see and understand data. So everything about what we're trying to do is to help people to be able to answer their own questions and to empower them with flexibility and agility and self service. And as we add additional products, it's really just extending the number of people that we can help. Some people want to work in the cloud, so Tableau online's better. Some people want to do it on their desktop so they're doing it more with tablet, desktop, some people out in the server and so as long as our salespeople are are looking for what is the best way that I can help this customer to be able to be more self sufficient in answering their own question and then we really hear what's the customer's use case. >>Then to answer that we have different products that actually fit that in. So in terms of how our sales strategy is working, the sales strategy is the same as it always is so we don't really focus on what to do with this product line versus that product line or this product line or small customers versus big customers. It's really all in this landed expand, let the customer buy as big or as little as they want to get started. We'll work with them very closely to make them successful and then as they're successful, they'll come back to buy more. And we have all these different ways that they can buy software and types of software that they can buy to be able to address their needs of self service agility and answering their own questions. >>The buyer, the profile of the buyer changed at all. So I know obviously Tableau is all about the end user, the person who's interacting with the software interact with the data as you'd like to focus on. But as you move to larger accounts, larger enterprises, are you still dealing directly with that user when you sell? Are you dealing with essential it more often? Right, right. >>And I guess that was kind of my question. You evolve to that, you know, I think that's a great, it's a great question because if I were to roll back the clock to almost 10 years ago when I was starting, we were, we were actually interacting mostly with the business user. So the end user and over time we're interacting with the C level, the C suite, we're interacting with the VP of it, we're interacting with the business users. And actually we're, we're working with both groups a lot. So what happened early on was we'd start with the business and over time as they bought more and more and more, they would bring us into it. And now actually we're seeing a shift that sometimes it's the it and the C suite that's coming to us and they're saying, Hey, we want to be able to empower our user community answered their own questions, but we need to be able to do that in a more secure governed control type of way. >>And is there a way that we can balance with Tableau? So we see it happening in both. I think one of the interesting changes that we're seeing is there is a cultural shift that's going on right now and companies are now starting to realize that the way that the past is very different than the wave of the future. So the wave of the past was if you had a question, you threw it over the fence to this central group that was report writers and these report writers knew how to code and they were very, very specialized. And the user that had the question, they had absolutely no idea how to operate those systems well. Now that companies are saying as data's coming in at such a fast clip, it just takes too long. They have to empower people to be able to answer their own questions, otherwise they end up being at a standstill. And so as we start having more discussions with the enterprise in the C suite, those folks who are in it and the CIO who realize, Hey, there's a shift that's going on and we need to be doing things in the way of where the world is going, not the way that we've done it in the past. It makes that conversation quite a bit easier. And so now we're seeing more and more conversations that are along those lines of how are we going to keep our organization to be competitive going into the. >>So I've got to ask you about the international expansion. We were talking earlier with your colleague Dave Martin, um, and also move at the HP big data event. And I had also had a conversation with Dave, CEO firearm, huge international. He says, John, my big growth happened. He's public company. You got you guys, he says international huge growth opportunity for us. So you have a Tam, then you have 55 million customers. You have one of those unique products at all customers need. So that's good. Check growth is on the horizon. How are you going to attack that new territory? I mean international and to grow, I mean channel strategy, indirect big part of it. I mean you guys are enabling people to create value. That seems to be the formula for a great indirect strategy. You've built a successful direct sales force graduations, but that's can take time. >>Yeah. Well you know, our model for international international is a huge opportunity for us. So we are putting a lot of resources and time into expanding internationally. We have our headquarters over in AMEA, we have headquarters over an APAC. We're now just w we opened up offices in Japan and in Germany we opened up operations in India. We are opening up another, a bigger office in, in Australia and even in Latin America, Brazil and Mexico. There's a fair amount going on now as we're going to market. It actually is pretty similar, so we're building direct sales force in all of those regions. But international, as you start doing more international, the channel becomes even increasingly important and it is, we're focusing a lot of time and energy on the channel here in the States. But in places like AMEA and certain locations over an APAC and and certainly in Latin America there is just the way of doing business tends to be more around the channel. >>Equalization has always been a nice thing of having in country operations. So that's always been kind of the international playbook. But with data I can be complicated. So having people in country, in a channel delivering value, is that the preferred way you guys, is that what you're saying? Is that, is that kind of? >>You know what I th th well the interesting part about Tableau is as we talked about, it's agnostic. Anyone can use it. And so when we go into a new country, there's two ways that we can go in. We can go on with our directing and we can go in with empowering our channel. And we actually have customers in over a hundred countries throughout the world, right? And we have partners operating in a large number of those. So our partners often are the ones that are the local feet on the street. They're going and they're having the conversations and, and they're providing the local support in the language and in the culture that it is now. When we actually open up offices in those different regions, we try to be very aligned, not only just putting our salespeople in, but having our entire company all lined up behind it. So we have our sales team, we have our marketing, we have our product. So when we go into Japan, for instance, we want to be able to have the website in Japanese. We want to be able to have the product localized in Japanese, we want to be able to have support staff that can help. And, and then of course having the partner ecosystem where the partners are able to help us make those customers all realistic. >>Flip yet in the U S I mean, as you guys get the channel going, has there been some channel conflict on order orders and who owns the accounts? >>Yeah, well you know what, our channel, we were developing a lot in the channel, but we're still pretty early in the, in our channel development and we're spending a lot of time to make sure that our channel is really successful as well as our, as well as our customers being successful. And the truth of the matter is we can't, we can't go and help all the people that we want to help without embracing the channel. And they're system integrators that they're in there and they're doing huge multi-year projects and we're working closely with them. And when we talk about the channel, we're working with resellers but also OEM and technology partners and system integrators. So lots and lots of channel activity going on. >>Yeah, I think you just touched on, well I think is one of the going to be one of the challenges for Tableau is that you can't, as you expand so fast, you can't keep your finger or your pulse on the customer quite as quite as closely as maybe you'd like. You've got to, you've got to count on the channel to do some of that. So that, and Tableau is of course known for being very customer focused. I mean the show here, you know, the crowds are cheering and Christian as he's giving his keynote and different visualizations are being demoed on stage and the crowds standing on their feet, you know, to keep that kind of customer focus as you expand. I think it's a challenge. It sounds like you really got to focus on those relationships with your partners and your OEM partners, et cetera. So they kind of understand that the Tableau approach is that, yeah, >>I I, I totally agree. Actually. I think you can even see at the show today, if you go down to that partner expo hall, there are so many partners, you're way more partners than we've ever had before. And when I was checking in with them, even yesterday where the show hadn't even started, they're getting a huge number of leads that are coming in and they're, there's so many opportunities for us to work together with our partners. In fact, this year, not only did we build of being really growing our partner sales team, but we had a whole series of partner summits this year and we traveled around the world. We had one in AMEA, one in APAC, one here in the States of being able to really train and enable our partners not only how to sell Tableau, but to work with them in a conversation of what's the best way that we can engage with them and make them really successful. So when we think about our ecosystem, it's not just about our customers, it's now about our customers and about our partners. And we're all part of the Tableau >>here. So obviously one of the things that you guys have done, you do a great job because you're such walking testimonials as customers. Um, what channel partners do you have as customers and that are top references now that you're showcasing and what end users are you showcasing here at this event? Can you name names and? >>Yeah, well I think you can, you can actually go downstairs and look in the partners of who we are and we're doing Watson, lots of, uh, partner with, with whether it's Vertica or with Alteryx or with data, uh, where we're doing joint sales and a lot of those, a lot of the that you'll see here, they're using Tableau internally in a pretty big way. And then in terms of customers, and we have showcases all over the place. I think we have a hundred customer speakers that are here. So there are there hospitals, we have Barnes, Jewish and Seattle children's who are talking about how they're using Tableau actually in the operating rooms and with nurses. And to be able to help save lives. We have education institutions who are using Tableau for how they can teach better in school, how the teachers can have their administration going. Uh, and we also have a number of corporate customers who are helping with that as well. >>So one of the things that we always talk about when we talk about startups, you guys want to start certainly, but company building is a great team. You guys are on that next generation of building out. Um, you always get the question, um, high touch sales, indirect low cost, our automated self-service if you're, you know, kind of a platform, um, inside sales is a great strategy for expanding out growth. Um, but it's hard. Um, do you guys have an inside sales organization? You, are you building it out? Is that a big part of your increase in your customer service? Cause a lot of you got great fans. Loyalties, high products is good. So are you building out? >>Yeah. You know, we actually, we got predominantly with inside sales, so we started with inside sales and then enterprise sales came later. And with our inside sales, we still have a very, very robust inside sales. We have kind of both models, some customers prefer to be interacted with field, face to face. And so we have field folks that are all over, uh, in our, all our major regions and we have a lot of inside folks. And the same is true when we look at how we're going to support them. So we have technical folks and services folks in training folks that will go out and meet the customer on their site, help to enable them setting up center of excellence, all that. And then we have a large number of that is that is done remotely. The benefit we have at Tableau is actually tablets, pretty easy to use. >>And so we don't always have to sit down and do it beside them. So how about sales compensation, if you will? Not with numbers, but like, I mean culturally is it, is it, we're hiring you killed like in the early days of Cisco sales guys were making zillions of dollars. Um, there's Tableau have, um, the kind of product pricing mix where you guys have a lot of like huge compensation, uh, rewards. So how does that work? You know, what we focus on having our salespeople be really excited about working here, having it be a very good as you know, right. I mean, compensation drives behavior. How do you guys, we have a lot of salespeople that have been here for a very long period of time. So we have a huge opportunity and we focus on the opportunity to help more customers and then the opportunity to have a really good career progression path. >>You know? Yes. I'm not going to answer your question, but you can keep on top a little bit about the competitive landscape. So, and again, maybe you know, because you've been with Tableau since the beginning, how has it evolved again, when you guys started, you were very much the disruptor going in. Yeah. Let's name some names, the disruptor, SAP business objects. You had Cognos, Hyperion, you guys are going in there and say, no, that's the old way. This is the new way. Um, since then you've now that some of those old players are started, they're focusing now on you know, being very self service, kind of emulating a lot of the things top load yet now you've got also kind of even newer companies, newer startups out there that are coming, even some are maybe mobile focused or cloud focused. What's the competitive landscape look like for you and from a sales perspective, again, how do you adapt as you got to come in from, you know, from the, from the new guys, you've got to come in from the old guard, you guys are targeted. >>When you're this successful you're always going to be a target. What it's like from your perspective. You know what, one of the things that we actually really focused on at Tableau, cause we talk about this a lot internally with our team is we can only control what we can control. We can control what our products are, we can control what our customer success is, we can control how we engage with our customers. And so we spend a lot of time just focusing on what it is that Tableau can do. And as we're now talking more about data discovery and agile and analytics and self-service, there's a lot of noise out there. A lot of other players who are saying that they can do the same thing and that they can do it as well. And our strategy is really, if you think you can use that, so why don't you go download their product and download our product and see how long it takes. And we actually encourage people to go out and test it out and try. And what we find is when someone is really interested in self service and helping people to answer their own questions, then the answer to them becomes really clear when it is an a question of we just want traditional old pixel perfect reporting you have. There are a lot of people that can play in that game. Uh, but we're finding the conversations changing quite a bit when they really want self-service. Then we actually feel like we're, we're pretty well positioned competitively. >>So are your lottery, your deals going up in, you know, competitive environments where you've got Tableau lined up against business objects against, I don't know. Good data against whoever. Is it a lot of that or do you have a lot of, you know, people who are trying the product love it and just say, Hey, we want to go with Tableau. >>You know, there's both, but the majority of our deals are actually when we're competing against the status quo, they actually aren't even looking at other business intelligence. They might have it in their company but it's not solving their need and their requirement. So a lot of people are just using what is already commissioned on their computer. Now there are situations where there is a competitive bake-off and we love competition. I mess with salespeople. Do we go and compete? Uh, but we're finding that the conversation is shifting and where we tend to really focus our time and energy is with those companies that are really looking for the new way. >>Kelly, you got to get the, I got to get the hook here, but I want to ask you two final questions. One is an easy one. What's it like working with Christian? >>It's great working with Christen. You know what? We've worked together all for so long and it's, it's really, we say it's like we're a family, right? We, we know each other, we know each other's families, we know each other's kids and it's pretty much the same as it was when I started almost 10 years ago. Nothing's really >>the second question. Share with the folks out there watching what is the culture of Tablo, if you could. Every culture has their own little weird tweak that makes them so unique. Intel, it's Moore's law. What's Tableau's cultural? >>Well, you have to go ask all the Tablo people if they think our culture is weird, probably not like a unique tweak that makes them so successful. The Moore's law was first called the weird, you know, people that work here are really, really passionate about what we do. We're passionate, we're mission focus and people have a lot of fun at what they do. They work hard and they play hard and it's, it's a very fun place to be. But we go fast. Yeah, certainly not weird, that's for sure. I didn't mean that, but I want a good way, a good thing. And it's usually the, it's the ones that the best deals are the ones that no one sees that doesn't look like it's going to be. And you guys were certainly a great winner of our hiring, so everyone in the world were hiring. We couldn't get the sales comp out of her, but we, you know, we tried our best, uh, Kelly, seriously, thanks for coming on cue. Really appreciate it. We know the journey you've been on has fantastic. It's a >>whirlwind now. You just got to go to the next leg of the journey, which is build a global 50 million customer business. Congratulations. Thank you for having me. We'll be right back with our next guest after this short break live in Seattle, Washington to the cube. Thank you.