from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

>>Hello. Welcome back to our super cloud 22 event. I'm John F host the cue with my co-host Dave ante. Extracting the signal from noise. We're proud to have two amazing cube alumnis here. We got Sanja Putin. Who's now the CEO of cohesive the emo Aaron who's the CTO. Co-founder also former CEO Cub alumni. The father of hyper-converged welcome back to the cube I endorsed the >>Cloud. Absolutely. Is the father. Great >>To see you guys. Thank thanks for coming on and perfect timing. The new job taking over that. The helm Mo it at cohesive big news, but part of super cloud, we wanna dig into it. Thanks for coming on. >>Thank you for having >>Us here. So first of all, we'll get into super before we get into the Supercloud. I want to just get the thoughts on the move Sanjay. We've been following your career since 2010. You've been a cube alumni from that point, we followed that your career. Why cohesive? Why now? >>Yeah, John David, thank you first and all for having us here, and it's great to be at your event. You know, when I left VMware last year, I took some time off just really primarily. I hadn't had a sabbatical in probably 18 years. I joined two boards, Phillips and sneak, and then, you know, started just invest and help entrepreneurs. Most of them were, you know, Indian Americans like me who were had great tech, were looking for the kind of go to market connections. And it was just a wonderful year to just de to unwind a bit. And along the, the way came CEO calls. And I'd asked myself, the question is the tech the best in the industry? Could you see value creation that was signi significant and you know, three, four months ago, Mohit and Carl Eschenbach and a few of the board members of cohesive called me and walk me through Mo's decision, which he'll talk about in a second. And we spent the last few months getting to know him, and he's everything you describe. He's not just the father of hyperconverge. And he wrote the Google file system, wicked smart, built a tech platform better than that second time. But we had to really kind of walk through the chemistry between us, which we did in long walks in, in, you know, discrete places so that people wouldn't find us in a Starbucks and start gossiping. So >>Why Sanjay? There you go. >>Actually, I should say it's a combination of two different decisions. The first one was to, for me to take a different role and I run the company as a CEO for, for nine years. And, you know, as a, as a technologist, I always like, you know, going deep into technology at the same time, the CEO duties require a lot of breadth, right? You're talking to customers, you're talking to partners, you're doing so much. And with the way we've been growing the with, you know, we've been fortunate, it was becoming hard to balance both. It's really also not fair to the company. Yeah. So I opted to do the depth job, you know, be the visionary, be the technologist. And that was the first decision to bring a CEO, a great CEO from outside. >>And I saw your video on the site. You said it was your decision. Yes. Go ahead. I have to ask you, cuz this is a real big transition for founders and you know, I have founder artists cuz everyone, you know, calls me that. But being the founder of a company, it's always hard to let go. I mean nine years as CEO, it's not like you had a, you had a great run. So this was it timing for you? Was it, was it a structural shift, like at super cloud, we're talking about a major shift that's happening right now in the industry. Was it a balance issue? Was it more if you wanted to get back in and in the tech >>Look, I, I also wanna answer, you know, why Sanja, but, but I'll address your question first. I always put the company first what's right for the company. Is it for me to start get stuck the co seat and try to juggle this depth and Brad simultaneously. I mean, I can stroke my ego a little bit there, but it's not good for the company. What's best for the company. You know, I'm a technologist. How about I oversee the technology part in partnership with so many great people I have in the company and I bring someone kick ass to be the CEO. And so then that was the second decision. Why Sanja when Sanjay, you know, is a very well known figure. He's managed billions of dollars of business in VMware. You know, been there, done that has, you know, some of the biggest, you know, people in the industry on his speed dial, you know, we were really fortunate to have someone like that, come in and accept the role of the CEO of cohesive. I think we can take the company to new Heights and I'm looking forward to my partnership with, with Sanja on this. >>It it's we, we called it the splash brothers and >>The, >>In the vernacular. It doesn't matter who gets the ball, whether it's step clay, we shoot. And I think if you look at some of the great partnerships, whether it was gates bomber, there, plenty of history of this, where a founder and a someone who was, it has to be complimentary skills. If I was a technologist myself and wanted to code we'd clash. Yeah. But I think this was really a match me in heaven because he, he can, I want him to keep innovating and building the best platform for today in the future. And our customers tell one customer told me, this is the best tech they've seen since VMware, 20 years ago, AWS, 10 years ago. And most recently this was a global 100 big customers. So I feel like this combination, now we have to show that it works. It's, you know, it's been three, four months. My getting to know him, you know, I'm day eight on the job, but I'm loving it. >>Well, it's a sluman model too. It's more modern example. You saw, he did it with Fred Ludy at service now. Yes. And, and of course at, at snowflake, yeah. And his book, you read his book. I dunno if you've read his book, amp it up, but app it up. And he says, I always you'll love this. Give great deference to the founder. Always show great respect. Right. And for good reason. So >>In fact, I mean you could talk to him, you actually met to >>Frank. I actually, you know, a month or so back, I actually had dinner with him in his ranch in Moana. And I posed the question. There was a number of CEOs that went there and I posed him the question. So Frank, you know, many of us, we grow being deaf guys, you know? And eventually when we take on the home of our CEO, we have to do breadth. How do you do it? And he's like, well, let me tell you, I was never a death guy. I'm a breath guy. >>I'm like, >>That's my answer. Yeah. >>So, so I >>Want the short story. So the day I got the job, I, I got a text from Frank and I said, what's your advice the first time CEO, three words, amp it up, >>Amp it up. Right? Yeah. >>And so you're always on brand, man. >>So you're an amazing operator. You've proven that time and time again at SAP, VMware, et cetera, you feel like now you, you, you wanna do both of those skills. You got the board and you got the operations cuz you look, you know, look at sloop when he's got Scarelli wherever he goes, he brings Scarelli with him as sort of the operator. How, how do you, how are you thinking >>About that? I mean it's early days, but yeah. Yeah. Small. I mean I've, you know, when I was, you know, it was 35,000 people at VMware, 80, 90,000 people at SAP, a really good run. The SAP run was 10 to 20 billion innovative products, especially in analytics and VMware six to 12 end user computing cloud. So I learned a lot. I think the company, you know, being about 2000 employees plus not to mayor tomorrow, but over the course next year I can meet everybody. Right? So first off the executive team, 10 of us, we're, we're building more and more cohesiveness if I could use that word between us, which is great, the next, you know, layers of VPs and every manager, I think that's possible. So I I'm a people person and a customer person. So I think when you take that sort of extroverted mindset, we'll bring energy to the workforce to, to retain the best and then recruit the best. >>And you know, even just the week we, we were announced that this announcement happened. Our website traffic went through the roof, the highest it's ever been, lots of resumes coming in. So, and then lots of customer engagement. So I think we'll take this, but I, I feel very good about the possibilities, because see, for me, I didn't wanna walk into the company to a company where the technology risk was high. Okay. I feel like that I can go to bed at night and the technology risk is low. This guy's gonna run a machine at the current and the future. And I'm hearing that from customers. Now, what I gotta do is get the, the amp it up part on the go to market. I know a little thing or too about >>That. You've got that down. I think the partnership is really key here. And again, nine use the CEO and then Sanja points to our super cloud trend that we've been looking at, which is there's another wave happening. There's a structural change in real time happening now, cloud one was done. We saw that transition, AWS cloud native now cloud native with an kind of operating system kind of vibe going on with on-premise hybrid edge. People say multi-cloud, but we're looking at this as an opportunity for companies like cohesive to go to the next level. So I gotta ask you guys, what do you see as structural change right now in the industry? That's disruptive. People are using cloud and scale and data to refactor their business models, change modern cases with cloud native. How are you guys looking at this next structural change that's happening right now? Yeah, >>I'll take that. So, so I'll start by saying that. Number one, data is the new oil and number two data is exploding, right? Every year data just grows like crazy managing data is becoming harder and harder. You mentioned some of those, right? There's so many cloud options available. Cloud one different vendors have different clouds. There is still on-prem there's edge infrastructure. And the number one problem that happens is our data is getting fragmented all over the place and managing so many fragments of data is getting harder and harder even within a cloud or within on-prem or within edge data is fragmented. Right? Number two, I think the hackers out there have realized that, you know, to make money, it's no longer necessary to Rob banks. They can actually see steal the data. So ransomware attacks on the rise it's become a boardroom level discussion. They say there's a ransomware attack happening every 11 seconds or so. Right? So protecting your data has become very important security data. Security has become very important. Compliance is important, right? So people are looking for data management solutions, the next gen data management platform that can really provide all this stuff. And that's what cohesive is about. >>What's the difference between data management and backup. Explain that >>Backup is just an entry point. That's one use case. I wanna draw an analogy. Let's draw an analogy to my former company, Google right? Google started by doing Google search, but is Google really just a search engine. They've built a platform that can do multiple things. You know, they might have started with search, but then they went down to roll out Google maps and Gmail and YouTube and so many other things on that platform. So similarly backups might be just the first use case, but it's really about that platform on which you can do more with the data that's next gen data management. >>But, but you am, I correct. You don't consider yourself a security company. One of your competitors is actually pivoting and in positioning themselves as a security company, I've always felt like data management, backup and recovery data protection is an adjacency to security, but those two worlds are coming together. How do you see >>It? Yeah. The way I see it is that security is part of data management. You start maybe by backing with data, but then you secure it and then you do more with that data. If you're only doing security, then you're just securing the data. You, you gotta do more with the data. So data management is much bigger. So >>It's a security is a subset of data. I mean, there you go. Big TA Sanjay. >>Well, I mean I've, and I, I, I I'd agree. And I actually, we don't get into that debate. You know, I've told the company, listen, we'll figure that out. Cuz who cares about the positioning at the bottom? My email, I say we are data management and data security company. Okay. Now what's the best word that describes three nouns, which I think we're gonna do management security and analytics. Okay. He showed me a beautiful diagram, went to his home in the course of one of these, you know, discrete conversations. And this was, I mean, he's done this before. Many, if you watch on YouTube, he showed me a picture of an ice big iceberg. And he said, listen, you know, if you look at companies like snowflake and data bricks, they're doing the management security and mostly analytics of data. That's the top of the iceberg, the stuff you see. >>But a lot of the stuff that's get backed archive is the bottom of the iceberg that you don't see. And you try to, if you try to ask a question on age data, the it guy will say, get a ticket. I'll come back with three days. I'll UNIV the data rehydrate and then you'll put it into a database. And you can think now imagine that you could do live searches analytics on, on age data that's analytics. So I think the management, the security, the analytics of, you know, if you wanna call it secondary data or backed up data or data, that's not hot and live warm, colder is a huge opportunity. Now, what do you wanna call one phrase that describes all of it. Do you call that superpower management security? Okay, whatever you wanna call it. I view it as saying, listen, let's build a platform. >>Some people call Google, a search company. People, some people call Google and information company and we just have to go and pursue every CIO and every CSO that has a management and a security and do course analytics problem. And that's what we're doing. And when I talk to the, you know, I didn't talk to all the 3000 customers, but the biggest customers and I was doing diligence. They're like this thing has got enormous potential. Okay. And we just have to now go focus, get every fortune 1000 company to pick us because this problem, even the first use case you talk back up is a little bit like, you know, razor blades and soap you've needed. You needed it 30 years ago and you'll need it for 30 years. It's just that the tools that were built in the last generation that were companies formed in 1990s, one of them I worked for years ago are aids are not built for the cloud. So I think this is a tremendous opportunity where many of those, those, those nos management security analytics will become part of what we do. And we'll come up with the right phrase for what the companies and do course >>Sanjay. So ma and Sanja. So given that given that's this Google transition, I like that example search was a data problem. They got sequenced to a broader market opportunity. What super cloud we trying to tease out is what does that change over from a data standpoint, cuz now the operating environments change has become more complex and the enterprises are savvy. Developers are savvy. Now they want, they want SAS solutions. They want freemium and expanding. They're gonna drive the operations agenda with DevOps. So what is the complexity that needs to be abstracted away? How do you see that moment? Because this is what people are talking about. They're saying security's built in, driven by developers. Developers are driving operations behavior. So what is the shift? Where do you guys see this new? Yeah. Expansive for cohesive. How do you fit into super cloud? >>So let me build up from that entry point. Maybe back up to what you're saying is the super cloud, right? Let me draw that journey. So let's say the legacy players are just doing backups. How, how sad is it that you have one silo sitting there just for peace of mind as an insurance policy and you do nothing with the data. If you have to do something with the data, you have to build another silo, you have to build another copy. You have to manage it separately. Right. So clearly that's a little bit brain damaged. Right. So, okay. So now you take a little bit of, you know, newer vendors who may take that backup platform and do a little bit more with that. Maybe they provide security, but your problem still remains. How do you do more with the data? How do you do some analytics? >>Like he's saying, right. How do you test development on that? How do you migrate the data to the cloud? How do you manage it? The data at scale? How do you do you provide a unified experience across, across multiple cloud, which you're calling the super cloud. That's where cohesive goes. So what we do, we provide a platform, right? We have tentacles in on-prem in each of the clouds. And on top of that, it looks like one platform that you manage. We have a single control plane, a UI. If you may, a single pin of glass, if, if you may, that our customers can use to manage all of it. And now it looks, starts looking like one platform. You mentioned Google, do you, when you go to, you know, kind Google search or a URL, do you really care? What happens behind the scenes mean behind the scenes? Google's built a platform that spans the whole world. No, >>But it's interesting. What's behind the scenes. It's a beautiful now. And I would say, listen, one other thing to pull on Dave, on the security part, I saw a lot of vendors this day in this space, white washing a security message on top of backup. Okay. And CSO, see through that, they'll offer warranties and guarantees or whatever, have you of X million dollars with a lot of caveats, which will never paid because it's like escape clause here. We won't pay it. Yeah. And, and what people really want is a scalable solution that works. And you know, we can match every warranty that's easy. And what I heard was this was the most scalable solution at scale. And that's why you have to approach this with a Google type mindset. I love the fact that every time you listen to sun pitch, I would, what, what I like about him, the most common word to use is scale. >>We do things at scale. So I found that him and AUR and some of the early Google people who come into the company had thought about scale. And, and even me it's like day eight. I found even the non-tech pieces of it. The processes that, you know, these guys are built for simple things in some cases were better than some of the things I saw are bigger companies I'd been used to. So we just have to continue, you know, building a scale platform with the enterprise. And then our cloud product is gonna be the simple solution for the masses. And my view of the world is there's 5,000 big companies and 5 million small companies we'll push the 5 million small companies as the cloud. Okay. Amazon's an investor in the company. AWS is a big partner. We'll talk about I'm sure knowing John's interest in that area, but that's a cloud play and that's gonna go to the cloud really fast. You not build you're in the marketplace, you're in the marketplace. I mean, maybe talk about the history of the Amazon relationship investing and all that. >>Yeah, absolutely. So in two years back late 2020, we, you know, in collaboration with AWS who also by the way is an investor now. And in cohesive, we rolled out what we call data management as a service. It's our SaaS service where we run our software in the cloud. And literally all customers have to do is just go there and sign on, right? They don't have to manage any infrastructure and stuff. What's nice is they can then combine that with, you know, software that they might have bought from cohesive. And it still looks like one platform. So what I'm trying to say is that they get a choice of the, of the way they wanna consume our software. They can consume it as a SAS service in the cloud. They can buy our software, manage it themselves, offload it to a partner on premises or what have you. But it still looks like that one platform, what you're calling a Supercloud >>Yeah. And developers are saying, they want the bag of Legos to compose their solutions. That's the Nirvana they want to get there. So that's, it has to look the same. >>Well, what is it? What we're calling a Superlo can we, can we test that for a second? So data management and service could span AWS and on-prem with the identical experience. So I guess I would call that a Supercloud I presume it's not gonna through AWS span multiple clouds, but, but >>Why not? >>Well, well interesting cuz we had this, I mean, so, okay. So we could in the future, it doesn't today. Well, >>David enough kind of pause for a second. Everything that we do there, if we do it will be customer driven. So there might be some customers I'll give you one Walmart that may want to store the data in a non AWS cloud risk cuz they're competitors. Right. So, but the control plane could still be in, in, in the way we built it, but the data might be stored somewhere else. >>What about, what about a on-prem customer? Who says, Hey, I, I like cohesive. I've now got multiple clouds. I want the identical experience across clouds. Yeah. Okay. So, so can you do that today? How do you do that today? Can we talk >>About that? Yeah. So basically think roughly about the split between the data plane and the control plane, the data plane is, you know, our cohesive clusters that could be sitting on premises that could be sitting in multiple data centers or you can run an instance of that cluster in the cloud, whichever cloud you choose. Right. That's what he was referring to as the data plane. So collectively all these clusters from the data plane, right? They stored the data, but it can all be managed using the control plane. So you still get that single image, the single experience across all clouds. And by the way, the, the, the, the cloud vendor does actually benefit because here's a customer. He mentioned a customer that may not wanna go to AWS, but when they get the data plane on a different cloud, whether it's Azure, whether it's the Google cloud, they then get data management services. Maybe they're able to replicate the data over to AWS. So AWS also gains. >>And your deployment model is you instantiate the cohesive stack on each of the regions and clouds, is that correct? And you building essentially, >>It all happens behind the scenes. That's right. You know, just like Google probably has their tentacles all over the world. We will instantiate and then make it all look like one platform. >>I mean, you should really think it's like a human body, right? The control planes, the head. Okay. And that controls everything. The data plane is large because it's a lot of the data, right? It's the rest of the body, that data plane could be wherever you want it to be. Traditionally, the part the old days was tape. Then you got disk. Now you got multiple clouds. So that's the way we think about it. And there on that piece of it will be neutral, right? We should be multi-cloud to the data plane being every single place. Cause it's customer demand. Where do you want your store data? Air gapped. On-prem no problem. We'll work with Dell. Okay. You wanna be in a particular cloud, AWS we'll work then optimized with S3 and glacier. So this is where I think the, the path to a multi-cloud or Supercloud is to be customer driven, but the control plane sits in Amazon. So >>We're blessed to have a number of, you know, technical geniuses in here. So earlier we were speaking to Ben wa deja VI, and what they do is different. They don't instantiate an individual, you know, regions. What they do is of a single global. Is there a, is there an advantage of doing it the way the cohesive does it in terms of simplicity or how do you see that? Is that a future direction for you from a technology standpoint? What are the trade offs there? >>So you want to be where the data is when you said single global, I take it that they run somewhere and the data has to go there. And in this day age, correct >>Said that. He said, you gotta move that in this >>Day and >>Age query that's, you know, across regions, look >>In this day and age with the way the data is growing, the way it is, it's hard to move around the data. It's much easier to move around the competition. And in these instances, what have you, so let the data be where it is and you manage it right there. >>So that's the advantage of instantiating in multiple regions. As you don't have to move the >>Data cost, we have the philosophy we call it. Let's bring the, the computation to the data rather than the data to >>The competition and the same security model, same governance model, same. How do you, how do you federate that? >>So it's all based on policies. You know, this overarching platform controlled by, by the control plane, you just, our customers just put in the policies and then the underlying nuts and bolts just take care >>Of, you know, it's when I first heard and start, I started watching some of his old videos, ACE really like hyperconverged brought to secondary storage. In fact, he said, oh yeah, that's great. You got it. Because I first called this idea, hyperconverged secondary storage, because the idea of him inventing hyperconverge was bringing compute to storage. It had never been done. I mean, you had the kind of big VC stuff, but these guys were the first to bring that hyperconverge at, at Nutanix. So I think this is that same idea of bringing computer storage, but now applied not to the warm data, but to the rest of the data, including a >>Lot of, what about developers? What's, what's your relationship with developers? >>Maybe you talk about the marketplace and everything >>He's yeah. And I'm, I'm curious as to do you have a PAs layer, what we call super PAs layer to create an identical developer experience across your Supercloud. I'm gonna my >>Term. So we want our customers not just to benefit from the software that we write. We also want them to benefit from, you know, software that's written by developers by third party people and so on and so forth. So we also support a marketplace on the platform where you can download apps from third party developers and run them on this platform. There's a, a number of successful apps. There's one, you know, look like I said, our entry point might be backups, but even when backups, we don't do everything. Look, for instance, we don't backup mainframes. There is a, a company we partner with, you know, and their software can run in our marketplace. And it's actually used by many, many of our financial customers. So our customers don't get, just get the benefit of what we build, but they also get the benefit of what third parties build. Another analogy I like to draw. You can tell. And front of analogy is I drew an analogy to hyperscale is like Google. Yeah. The second analogy I like to draw is that to a simple smartphone, right? A smartphone starts off by being a great phone. But beyond that, it's also a GPS player. It's a, it's a, it's a music player. It's a camera, it's a flashlight. And it also has a marketplace from where you can download apps and extend the power of that platform. >>Is that a, can we think of that as a PAs layer or no? Is it really not? You can, okay. You can say, is it purpose built for what you're the problem that you're trying to solve? >>So we, we just built APIs. Yeah. Right. We have an SDK that developers can use. And through those APIs, they get to leverage the underlying services that exist on the platform. And now developers can use that to take advantage of all that stuff. >>And it was, that was a key factor for me too. Cause I, what I, you know, I've studied all the six, seven players that sort of so-called leaders. Nobody had a developer ecosystem, nobody. Right? The old folks were built for the hardware era, but anyones were built for the cloud to it didn't have any partners were building on their platform. So I felt for me listen, and that the example of, you know, model nine rights, the name of the company that does back up. So there's, there's companies that are built on and there's a number of others. So our goal is to have a big tent, David, to everybody in the ecosystem to partner with us, to build on this platform. And, and that may take over time, but that's the way we're build >>It. And you have a metadata layer too, that has the intelligence >>To correct. It's all abstract. That that's right. So it's a combination of data and metadata. We have lots of metadata that keeps track of where the data is. You know, it allows you to index the data you can do quick searches. You can actually, you, we talking about the control plan from that >>Tracing, >>You can inject a search that'll through search throughout your multi-cloud environment, right? The super cloud that you call it. We have all that, all that goodness sounds >>Like a Supercloud John. >>Yeah. I mean, data tracing involved can trace the data lineage. >>You, you can trace the data lineage. So we, you know, provide, you know, compliance and stuff. So you can, >>All right. So my final question to wrap up, we guys, first of all, thanks for coming on. I know you're super busy, San Jose. We, we know what you're gonna do. You're gonna amp it up and, you know, knock all your numbers out. Think you always do. But what I'm interested in, what you're gonna jump into, cuz now you're gonna have the creative license to jump in to the product, the platform there has to be the next level in your mind. Can you share your thoughts on where this goes next? Love the control plane, separate out from the data plane. I think that plays well for super. How >>Much time do you have John? This guy's got, he's got a wealth. Ditis keep >>Going. Mark. Give us the most important thing you're gonna focus on. That kind of brings the super cloud and vision together. >>Yeah. Right away. I'm gonna, perhaps I, I can ion into two things. The first one is I like to call it building the, the machine, the system, right. Just to draw an analogy. Look, I draw an analogy to the us traffic system. People from all walks of life, rich, poor Democrats, Republicans, you know, different states. They all work in the, the traffic system and we drive well, right. It's a system that just works. Whereas in some other countries, you know, the system doesn't work. >>We know, >>We know a few of those. >>It's not about works. It's not about the people. It's the same people who would go from here to those countries and, and not dry. Well, so it's all about the system. So the first thing I, I have my sights on is to really strengthen the system that we have in our research development to make it a machine. I mean, it functions quite well even today, but wanna take it to the next level. Right. So that I wanna get to a point where innovation just happens in the grassroots. And it just, just like >>We automations scale optic brings all, >>Just happens without anyone overseeing it. Anyone there's no single point of bottleneck. I don't have to go take any diving catches or have you, there are people just working, you know, in a decentralized fashion and innovation just happens. Yeah. The second thing I work on of course is, you know, my heart and soul is in, you know, driving the vision, you know, the next level. And that of course is part of it. So those are the two things >>We heard from all day in our super cloud event that there's a need for an, an operating system. Yeah. Whether that's defacto standard or open. Correct. Do you see a consortium around the corner potentially to bring people together so that things could work together? Cuz there really isn't no stand there. Isn't a standards bodies. Now we have great hyperscale growth. We have on-prem we got the super cloud thing happening >>And it's a, it's kind of like what is an operating system? Operating system exposes some APIs that the applications can then use. And if you think about what we've been trying to do with the marketplace, right, we've built a huge platform and that platform is exposed through APIs. That third party developers can use. Right? And even we, when we, you know, built more and more services on top, you know, we rolled our D as we rolled out, backup as a service and a ready for thing security as a service governance, as a service, they're using those APIs. So we are building a distributor, putting systems of sorts. >>Well, congratulations on a great journey. Sanja. Congratulations on taking the hem. Thank you've got ball control. Now you're gonna be calling the ball cohesive as they say, it's, >>It's a team. It's, you know, I think I like that African phrase. If you want to go fast, you go alone. If you wanna go far, you go together. So I've always operated with the best deal. I'm so fortunate. This is to me like a dream come true because I always thought I wanted to work with a technologist that frees me up to do what I like. I mean, I started as an engineer, but that's not what I am today. Right? Yeah. So I do understand the product and this category I think is right for disruption. So I feel excited, you know, it's changing growing. Yeah. No. And it's a, it requires innovation with a cloud scale mindset and you guys have been great friends through the years. >>We'll be, we'll be watching you. >>I think it's not only disruption. It's creation. Yeah. There's a lot of white space that just hasn't been created yet. >>You're gonna have to, and you know, the proof, isn't the pudding. Yeah. You already have five of the biggest 10 financial institutions in the us and our customers. 25% of the fortune 500 users, us two of the biggest five pharmaceutical companies in the world use us. Probably, you know, some of the biggest companies, you know, the cars you have, you know, out there probably are customers. So it's already happening. >>I know you got an IPO filed confidentially. I know you can't talk numbers, but I can tell by your confidence, you're feeling good right now we are >>Feeling >>Good. Yeah. One day, one week, one month at a time. I mean, you just, you know, I like the, you know, Jeff Bezos, Andy jazzy expression, which is, it's always day one, you know, just because you've had success, even, you know, if, if a and when an IPO O makes sense, you just have to stay humble and hungry because you realize, okay, we've had a lot of success in the fortune 1000, but there's a lot of white space that hasn't picked USS yet. So let's go, yeah, there's lots of midmarket account >>Product opportunities are still, >>You know, I just stay humble and hungry and if you've got the team and then, you know, I'm really gonna be working also in the ecosystem. I think there's a lot of very good partners. So lots of ideas brew through >>The head. Okay. Well, thank you so much for coming on our super cloud event and, and, and also doubling up on the news of the new appointment and congratulations on the success guys. Coverage super cloud 22, I'm sure. Dave ante, thanks for watching. Stay tuned for more segments after this break.

(gentle upbeat music) >> Welcome back everyone, to "theCUBE"'s live stage performance here in Palo Alto, California at "theCUBE" Studios. I'm John Furrier with Dave Vellante, kicking off our first inaugural Supercloud event. It's an editorial event, we wanted to bring together the best in the business, the smartest, the biggest, the up-and-coming startups, venture capitalists, everybody, to weigh in on this new Supercloud trend, this structural change in the cloud computing business. We're about to run the Ecosystem Speaks, which is a bunch of pre-recorded companies that wanted to get their voices on the record, so stay tuned for the rest of the day. We'll be replaying all that content and they're going to be having some really good commentary and hear what they have to say. I had a chance to interview and so did Dave. Dave, this is our closing segment where we kind of unpack everything or kind of digest and report. So much to kind of digest from the conversations today, a wide range of commentary from Supercloud operating system to developers who are in charge to maybe it's an ops problem or maybe Oracle's a Supercloud. I mean, that was debated. So so much discussion, lot to unpack. What was your favorite moments? >> Well, before I get to that, I think, I go back to something that happened at re:Invent last year. Nick Sturiale came up, Steve Mullaney from Aviatrix; we're going to hear from him shortly in the Ecosystem Speaks. Nick Sturiale's VC said "it's happening"! And what he was talking about is this ecosystem is exploding. They're building infrastructure or capabilities on top of the CapEx infrastructure. So, I think it is happening. I think we confirmed today that Supercloud is a thing. It's a very immature thing. And I think the other thing, John is that, it seems to me that the further you go up the stack, the weaker the business case gets for doing Supercloud. We heard from Marianna Tessel, it's like, "Eh, you know, we can- it was easier to just do it all on one cloud." This is a point that, Adrian Cockcroft just made on the panel and so I think that when you break out the pieces of the stack, I think very clearly the infrastructure layer, what we heard from Confluent and HashiCorp, and certainly VMware, there's a real problem there. There's a real need at the infrastructure layer and then even at the data layer, I think Benoit Dageville did a great job of- You know, I was peppering him with all my questions, which I basically was going through, the Supercloud definition and they ticked the box on pretty much every one of 'em as did, by the way Ali Ghodsi you know, the big difference there is the philosophy of Republicans and Democrats- got open versus closed, not to apply that to either one side, but you know what I mean! >> And the similarities are probably greater than differences. >> Berkely, I would probably put them on the- >> Yeah, we'll put them on the Democrat side we'll make Snowflake the Republicans. But so- but as we say there's a lot of similarities as well in terms of what their objectives are. So, I mean, I thought it was a great program and a really good start to, you know, an industry- You brought up the point about the industry consortium, asked Kit Colbert- >> Yep. >> If he thought that was something that was viable and what'd they say? That hyperscale should lead it? >> Yeah, they said hyperscale should lead it and there also should be an industry consortium to get the voices out there. And I think VMware is very humble in how they're putting out their white paper because I think they know that they can't do it all and that they do not have a great track record relative to cloud. And I think, but they have a great track record of loyal installed base ops people using VMware vSphere all the time. >> Yeah. >> So I think they need a catapult moment where they can catapult to the cloud native which they've been working on for years under Raghu and the team. So the question on VMware is in the light of Broadcom, okay, acquisition of VMware, this is an opportunity or it might not be an opportunity or it might be a spin-out or something, I just think VMware's got way too much engineering culture to be ignored, Dave. And I think- well, I'm going to watch this very closely because they can pull off some sort of rallying moment. I think they could. And then you hear the upstarts like Platform9, Rafay Systems and others they're all like, "Yes, we need to unify behind something. There needs to be some sort of standard". You know, we heard the argument of you know, more standards bodies type thing. So, it's interesting, maybe "theCUBE" could be that but we're going to certainly keep the conversation going. >> I thought one of the most memorable statements was Vittorio who said we- for VMware, we want our cake, we want to eat it too and we want to lose weight. So they have a lot of that aspirations there! (John laughs) >> And then I thought, Adrian Cockcroft said you know, the devs, they want to get married. They were marrying everybody, and then the ops team, they have to deal with the divorce. >> Yeah. >> And I thought that was poignant. It's like, they want consistency, they want standards, they got to be able to scale And Lori MacVittie, I'm not sure you agree with this, I'd have to think about it, but she was basically saying, all we've talked about is devs devs devs for the last 10 years, going forward we're going to be talking about ops. >> Yeah, and I think one of the things I learned from this day and looking back, and some kind of- I've been sauteing through all the interviews. If you zoom out, for me it was the epiphany of developers are still in charge. And I've said, you know, the developers are doing great, it's an ops security thing. Not sure I see that the way I was seeing before. I think what I learned was the refactoring pattern that's emerging, In Sik Rhee brought this up from Vertex Ventures with Marianna Tessel, it's a nuanced point but I think he's right on which is the pattern that's emerging is developers want ease-of-use tooling, they're driving the change and I think the developers in the devs ops ethos- it's never going to be separate. It's going to be DevOps. That means developers are driving operations and then security. So what I learned was it's not ops teams leveling up, it's devs redefining what ops is. >> Mm. And I think that to me is where Supercloud's going to be interesting- >> Forcing that. >> Yeah. >> Forcing the change because the structural change is open sources thriving, devs are still in charge and they still want more developers, Vittorio "we need more developers", right? So the developers are in charge and that's clear. Now, if that happens- if you believe that to be true the domino effect of that is going to be amazing because then everyone who gets on the wrong side of history, on the ops and security side, is going to be fighting a trend that may not be fight-able, you know, it might be inevitable. And so the winners are the ones that are refactoring their business like Snowflake. Snowflake is a data warehouse that had nothing to do with Amazon at first. It was the developers who said "I'm going to refactor data warehouse on AWS". That is a developer-driven refactorization and a business model. So I think that's the pattern I'm seeing is that this concept refactoring, patterns and the developer trajectory is critical. >> I thought there was another great comment. Maribel Lopez, her Lord of the Rings comment: "there will be no one ring to rule them all". Now at the same time, Kit Colbert, you know what we asked him straight out, "are you the- do you want to be the, the Supercloud OS?" and he basically said, "yeah, we do". Now, of course they're confined to their world, which is a pretty substantial world. I think, John, the reason why Maribel is so correct is security. I think security's a really hard problem to solve. You've got cloud as the first layer of defense and now you've got multiple clouds, multiple layers of defense, multiple shared responsibility models. You've got different tools for XDR, for identity, for governance, for privacy all within those different clouds. I mean, that really is a confusing picture. And I think the hardest- one of the hardest parts of Supercloud to solve. >> Yeah, and I thought the security founder Gee Rittenhouse, Piyush Sharrma from Accurics, which sold to Tenable, and Tony Kueh, former head of product at VMware. >> Right. >> Who's now an investor kind of looking for his next gig or what he is going to do next. He's obviously been extremely successful. They brought up the, the OS factor. Another point that they made I thought was interesting is that a lot of the things to do to solve the complexity is not doable. >> Yeah. >> It's too much work. So managed services might field the bit. So, and Chris Hoff mentioned on the Clouderati segment that the higher level services being a managed service and differentiating around the service could be the key competitive advantage for whoever does it. >> I think the other thing is Chris Hoff said "yeah, well, Web 3, metaverse, you know, DAO, Superclouds" you know, "Stupercloud" he called it and this bring up- It resonates because one of the criticisms that Charles Fitzgerald laid on us was, well, it doesn't help to throw out another term. I actually think it does help. And I think the reason it does help is because it's getting people to think. When you ask people about Supercloud, they automatically- it resonates with them. They play back what they think is the future of cloud. So Supercloud really talks to the future of cloud. There's a lot of aspects to it that need to be further defined, further thought out and we're getting to the point now where we- we can start- begin to say, okay that is Supercloud or that isn't Supercloud. >> I think that's really right on. I think Supercloud at the end of the day, for me from the simplest way to describe it is making sure that the developer experience is so good that the operations just happen. And Marianna Tessel said, she's investing in making their developer experience high velocity, very easy. So if you do that, you have to run on premise and on the cloud. So hybrid really is where Supercloud is going right now. It's not multi-cloud. Multi-cloud was- that was debunked on this session today. I thought that was clear. >> Yeah. Yeah, I mean I think- >> It's not about multi-cloud. It's about operationally seamless operations across environments, public cloud to on-premise, basically. >> I think we got consensus across the board that multi-cloud, you know, is a symptom Chuck Whitten's thing of multi-cloud by default versus multi- multi-cloud has not been a strategy, Kit Colbert said, up until the last couple of years. Yeah, because people said, "oh we got all these multiple clouds, what do we do with it?" and we got this mess that we have to solve. Whereas, I think Supercloud is something that is a strategy and then the other nuance that I keep bringing up is it's industries that are- as part of their digital transformation, are building clouds. Now, whether or not they become superclouds, I'm not convinced. I mean, what Goldman Sachs is doing, you know, with AWS, what Walmart's doing with Azure connecting their on-prem tools to those public clouds, you know, is that a supercloud? I mean, we're going to have to go back and really look at that definition. Or is it just kind of a SAS that spans on-prem and cloud. So, as I said, the further you go up the stack, the business case seems to wane a little bit but there's no question in my mind that from an infrastructure standpoint, to your point about operations, there's a real requirement for super- what we call Supercloud. >> Well, we're going to keep the conversation going, Dave. I want to put a shout out to our founding supporters of this initiative. Again, we put this together really fast kind of like a pilot series, an inaugural event. We want to have a face-to-face event as an industry event. Want to thank the founding supporters. These are the people who donated their time, their resource to contribute content, ideas and some cash, not everyone has committed some financial contribution but we want to recognize the names here. VMware, Intuit, Red Hat, Snowflake, Aisera, Alteryx, Confluent, Couchbase, Nutanix, Rafay Systems, Skyhigh Security, Aviatrix, Zscaler, Platform9, HashiCorp, F5 and all the media partners. Without their support, this wouldn't have happened. And there are more people that wanted to weigh in. There was more demand than we could pull off. We'll certainly continue the Supercloud conversation series here on "theCUBE" and we'll add more people in. And now, after this session, the Ecosystem Speaks session, we're going to run all the videos of the big name companies. We have the Nutanix CEOs weighing in, Aviatrix to name a few. >> Yeah. Let me, let me chime in, I mean you got Couchbase talking about Edge, Platform 9's going to be on, you know, everybody, you know Insig was poopoo-ing Oracle, but you know, Oracle and Azure, what they did, two technical guys, developers are coming on, we dig into what they did. Howie Xu from Zscaler, Paula Hansen is going to talk about going to market in the multi-cloud world. You mentioned Rajiv, the CEO of Nutanix, Ramesh is going to talk about multi-cloud infrastructure. So that's going to run now for, you know, quite some time here and some of the pre-record so super excited about that and I just want to thank the crew. I hope guys, I hope you have a list of credits there's too many of you to mention, but you know, awesome jobs really appreciate the work that you did in a very short amount of time. >> Well, I'm excited. I learned a lot and my takeaway was that Supercloud's a thing, there's a kind of sense that people want to talk about it and have real conversations, not BS or FUD. They want to have real substantive conversations and we're going to enable that on "theCUBE". Dave, final thoughts for you. >> Well, I mean, as I say, we put this together very quickly. It was really a phenomenal, you know, enlightening experience. I think it confirmed a lot of the concepts and the premises that we've put forth, that David Floyer helped evolve, that a lot of these analysts have helped evolve, that even Charles Fitzgerald with his antagonism helped to really sharpen our knives. So, you know, thank you Charles. And- >> I like his blog, by the I'm a reader- >> Yeah, absolutely. And it was great to be back in Palo Alto. It was my first time back since pre-COVID, so, you know, great job. >> All right. I want to thank all the crew and everyone. Thanks for watching this first, inaugural Supercloud event. We are definitely going to be doing more of these. So stay tuned, maybe face-to-face in person. I'm John Furrier with Dave Vellante now for the Ecosystem chiming in, and they're going to speak and share their thoughts here with "theCUBE" our first live stage performance event in our studio. Thanks for watching. (gentle upbeat music)

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hi everyone, this is Dave Vellante and welcome to this CUBE conversation where we're going to dig in to this, the area of cloud databases. And Gartner just published a series of research in this space. And it's really a growing market, rapidly growing, a lot of new players, obviously the big three cloud players. And with me are three experts in the field, two long time industry analysts. Marc Staimer is the founder, president, and key principal at Dragon Slayer Consulting. And he's joined by David Floyer, the CTO of Wikibon. Gentlemen great to see you. Thanks for coming on theCUBE. >> Good to be here. >> Great to see you too Dave. >> Marc, coming from the great Northwest, I think first time on theCUBE, and so it's really great to have you. So let me set this up, as I said, you know, Gartner published these, you know, three giant tomes. These are, you know, publicly available documents on the web. I know you guys have been through them, you know, several hours of reading. And so, night... (Dave chuckles) Good night time reading. The three documents where they identify critical capabilities for cloud database management systems. And the first one we're going to talk about is, operational use cases. So we're talking about, you know, transaction oriented workloads, ERP financials. The second one was analytical use cases, sort of an emerging space to really try to, you know, the data warehouse space and the like. And, of course, the third is the famous Gartner Magic Quadrant, which we're going to talk about. So, Marc, let me start with you, you've dug into this research just at a high level, you know, what did you take away from it? >> Generally, if you look at all the players in the space they all have some basic good capabilities. What I mean by that is ultimately when you have, a transactional or an analytical database in the cloud, the goal is not to have to manage the database. Now they have different levels of where that goes to as how much you have to manage or what you have to manage. But ultimately, they all manage the basic administrative, or the pedantic tasks that DBAs have to do, the patching, the tuning, the upgrading, all of that is done by the service provider. So that's the number one thing they all aim at, from that point on every database has different capabilities and some will automate a whole bunch more than others, and will have different primary focuses. So it comes down to what you're looking for or what you need. And ultimately what I've learned from end users is what they think they need upfront, is not what they end up needing as they implement. >> David, anything you'd add to that, based on your reading of the Gartner work. >> Yes. It's a thorough piece of work. It's taking on a huge number of different types of uses and size of companies. And I think those are two parameters which really change how companies would look at it. If you're a Fortune 500 or Fortune 2000 type company, you're going to need a broader range of features, and you will need to deal with size and complexity in a much greater sense, and a lot of probably higher levels of availability, and reliability, and recoverability. Again, on the workload side, there are different types of workload and there're... There is as well as having the two transactional and analytic workloads, I think there's an emerging type of workload which is going to be very important for future applications where you want to combine transactional with analytic in real time, in order to automate business processes at a higher level, to make the business processes synchronous as opposed to asynchronous. And that degree of granularity, I think is missed, in a broader view of these companies and what they offer. It's in my view trying in some ways to not compare like with like from a customer point of view. So the very nuance, what you talked about, let's get into it, maybe that'll become clear to the audience. So like I said, these are very detailed research notes. There were several, I'll say analysts cooks in the kitchen, including Henry Cook, whom I don't know, but four other contributing analysts, two of whom are CUBE alum, Don Feinberg, and Merv Adrian, both really, you know, awesome researchers. And Rick Greenwald, along with Adam Ronthal. And these are public documents, you can go on the web and search for these. So I wonder if we could just look at some of the data and bring up... Guys, bring up the slide one here. And so we'll first look at the operational side and they broke it into four use cases. The traditional transaction use cases, the augmented transaction processing, stream/event processing and operational intelligence. And so we're going to show you there's a lot of data here. So what Gartner did is they essentially evaluated critical capabilities, or think of features and functions, and gave them a weighting, or a weighting, and then a rating. It was a weighting and rating methodology. On a s... The rating was on a scale of one to five, and then they weighted the importance of the features based on their assessment, and talking to the many customers they talk to. So you can see here on the first chart, we're showing both the traditional transactions and the augmented transactions and, you know, the thing... The first thing that jumps out at you guys is that, you know, Oracle with Autonomous is off the charts, far ahead of anybody else on this. And actually guys, if you just bring up slide number two, we'll take a look at the stream/event processing and operational intelligence use cases. And you can see, again, you know, Oracle has a big lead. And I don't want to necessarily go through every vendor here, but guys, if you don't mind going back to the first slide 'cause I think this is really, you know, the core of transaction processing. So let's look at this, you've got Oracle, you've got SAP HANA. You know, right there interestingly Amazon Web Services with the Aurora, you know, IBM Db2, which, you know, it goes back to the good old days, you know, down the list. But so, let me again start with Marc. So why is that? I mean, I guess this is no surprise, Oracle still owns the Mission-Critical for the database space. They earned that years ago. One that, you know, over the likes of Db2 and, you know, Informix and Sybase, and, you know, they emerged as number one there. But what do you make of this data Marc? >> If you look at this data in a vacuum, you're looking at specific functionality, I think you need to look at all the slides in total. And the reason I bring that up is because I agree with what David said earlier, in that the use case that's becoming more prevalent is the integration of transaction and analytics. And more importantly, it's not just your traditional data warehouse, but it's AI analytics. It's big data analytics. It's users are finding that they need more than just simple reporting. They need more in-depth analytics so that they can get more actionable insights into their data where they can react in real time. And so if you look at it just as a transaction, that's great. If you're going to just as a data warehouse, that's great, or analytics, that's fine. If you have a very narrow use case, yes. But I think today what we're looking at is... It's not so narrow. It's sort of like, if you bought a streaming device and it only streams Netflix and then you need to get another streaming device 'cause you want to watch Amazon Prime. You're not going to do that, you want one, that does all of it, and that's kind of what's missing from this data. So I agree that the data is good, but I don't think it's looking at it in a total encompassing manner. >> Well, so before we get off the horses on the track 'cause I love to do that. (Dave chuckles) I just kind of let's talk about that. So Marc, you're putting forth the... You guys seem to agree on that premise that the database that can do more than just one thing is of appeal to customers. I suppose that makes, certainly makes sense from a cost standpoint. But, you know, guys feel free to flip back and forth between slides one and two. But you can see SAP HANA, and I'm not sure what cloud that's running on, it's probably running on a combination of clouds, but, you know, scoring very strongly. I thought, you know, Aurora, you know, given AWS says it's one of the fastest growing services in history and they've got it ahead of Db2 just on functionality, which is pretty impressive. I love Google Spanner, you know, love the... What they're trying to accomplish there. You know, you go down to Microsoft is, they're kind of the... They're always good enough a database and that's how they succeed and et cetera, et cetera. But David, it sounds like you agree with Marc. I would say, I would think though, Amazon kind of doesn't agree 'cause they're like a horses for courses. >> I agree. >> Yeah, yeah. >> So I wonder if you could comment on that. >> Well, I want to comment on two vectors. The first vector is that the size of customer and, you know, a mid-sized customer versus a global $2,000 or global 500 customer. For the smaller customer that's the heart of AWS, and they are taking their applications and putting pretty well everything into their cloud, the one cloud, and Aurora is a good choice. But when you start to get to a requirements, as you do in larger companies have very high levels of availability, the functionality is not there. You're not comparing apples and... Apples with apples, it's two very different things. So from a tier one functionality point of view, IBM Db2 and Oracle have far greater capability for recovery and all the features that they've built in over there. >> Because of their... You mean 'cause of the maturity, right? maturity and... >> Because of their... Because of their focus on transaction and recovery, et cetera. >> So SAP though HANA, I mean, that's, you know... (David talks indistinctly) And then... >> Yeah, yeah. >> And then I wanted your comments on that, either of you or both of you. I mean, SAP, I think has a stated goal of basically getting its customers off Oracle that's, you know, there's always this urinary limping >> Yes, yes. >> between the two companies by 2024. Larry has said that ain't going to happen. You know, Amazon, we know still runs on Oracle. It's very hard to migrate Mission-Critical, David, you and I know this well, Marc you as well. So, you know, people often say, well, everybody wants to get off Oracle, it's too expensive, blah, blah, blah. But we talked to a lot of Oracle customers there, they're very happy with the reliability, availability, recoverability feature set. I mean, the core of Oracle seems pretty stable. >> Yes. >> But I wonder if you guys could comment on that, maybe Marc you go first. >> Sure. I've recently done some in-depth comparisons of Oracle and Aurora, and all their other RDS services and Snowflake and Google and a variety of them. And ultimately what surprised me is you made a statement it costs too much. It actually comes in half of Aurora for in most cases. And it comes in less than half of Snowflake in most cases, which surprised me. But no matter how you configure it, ultimately based on a couple of things, each vendor is focused on different aspects of what they do. Let's say Snowflake, for example, they're on the analytical side, they don't do any transaction processing. But... >> Yeah, so if I can... Sorry to interrupt. Guys if you could bring up the next slide that would be great. So that would be slide three, because now we get into the analytical piece Marc that you're talking about that's what Snowflake specialty is. So please carry on. >> Yeah, and what they're focused on is sharing data among customers. So if, for example, you're an automobile manufacturer and you've got a huge supply chain, you can supply... You can share the data without copying the data with any of your suppliers that are on Snowflake. Now, can you do that with the other data warehouses? Yes, you can. But the focal point is for Snowflake, that's where they're aiming it. And whereas let's say the focal point for Oracle is going to be performance. So their performance affects cost 'cause the higher the performance, the less you're paying for the performing part of the payment scale. Because you're paying per second for the CPUs that you're using. Same thing on Snowflake, but the performance is higher, therefore you use less. I mean, there's a whole bunch of things to come into this but at the end of the day what I've found is Oracle tends to be a lot less expensive than the prevailing wisdom. So let's talk value for a second because you said something, that yeah the other databases can do that, what Snowflake is doing there. But my understanding of what Snowflake is doing is they built this global data mesh across multiple clouds. So not only are they compatible with Google or AWS or Azure, but essentially you sign up for Snowflake and then you can share data with anybody else in the Snowflake cloud, that I think is unique. And I know, >> Marc: Yes. >> Redshift, for instance just announced, you know, Redshift data sharing, and I believe it's just within, you know, clusters within a customer, as opposed to across an ecosystem. And I think that's where the network effect is pretty compelling for Snowflake. So independent of costs, you and I can debate about costs and, you know, the tra... The lack of transparency of, because AWS you don't know what the bill is going to be at the end of the month. And that's the same thing with Snowflake, but I find that... And by the way guys, you can flip through slides three and four, because we've got... Let me just take a quick break and you have data warehouse, logical data warehouse. And then the next slide four you got data science, deep learning and operational intelligent use cases. And you can see, you know, Teradata, you know, law... Teradata came up in the mid 1980s and dominated in that space. Oracle does very well there. You can see Snowflake pop-up, SAP with the Data Warehouse, Amazon with Redshift. You know, Google with BigQuery gets a lot of high marks from people. You know, Cloud Data is in there, you know, so you see some of those names. But so Marc and David, to me, that's a different strategy. They're not trying to be just a better data warehouse, easier data warehouse. They're trying to create, Snowflake that is, an incremental opportunity as opposed to necessarily going after, for example, Oracle. David, your thoughts. >> Yeah, I absolutely agree. I mean, ease of use is a primary benefit for Snowflake. It enables you to do stuff very easily. It enables you to take data without ETL, without any of the complexity. It enables you to share a number of resources across many different users and know... And be able to bring in what that particular user wants or part of the company wants. So in terms of where they're focusing, they've got a tremendous ease of use, tremendous focus on what the customer wants. And you pointed out yourself the restrictions there are of doing that both within Oracle and AWS. So yes, they have really focused very, very hard on that. Again, for the future, they are bringing in a lot of additional functions. They're bringing in Python into it, not Python, JSON into the database. They can extend the database itself, whether they go the whole hog and put in transaction as well, that's probably something they may be thinking about but not at the moment. >> Well, but they, you know, they obviously have to have TAM expansion designs because Marc, I mean, you know, if they just get a 100% of the data warehouse market, they're probably at a third of their stock market valuation. So they had better have, you know, a roadmap and plans to extend there. But I want to come back Marc to this notion of, you know, the right tool for the right job, or, you know, best of breed for a specific, the right specific, you know horse for course, versus this kind of notion of all in one, I mean, they're two different ends of the spectrum. You're seeing, you know, Oracle obviously very successful based on these ratings and based on, you know their track record. And Amazon, I think I lost count of the number of data stores (Dave chuckles) with Redshift and Aurora and Dynamo, and, you know, on and on and on. (Marc talks indistinctly) So they clearly want to have that, you know, primitive, you know, different APIs for each access, completely different philosophies it's like Democrats or Republicans. Marc your thoughts as to who ultimately wins in the marketplace. >> Well, it's hard to say who is ultimately going to win, but if I look at Amazon, Amazon is an all-cart type of system. If you need time series, you go with their time series database. If you need a data warehouse, you go with Redshift. If you need transaction, you go with one of the RDS databases. If you need JSON, you go with a different database. Everything is a different, unique database. Moving data between these databases is far from simple. If you need to do a analytics on one database from another, you're going to use other services that cost money. So yeah, each one will do what they say it's going to do but it's going to end up costing you a lot of money when you do any kind of integration. And you're going to add complexity and you're going to have errors. There's all sorts of issues there. So if you need more than one, probably not your best route to go, but if you need just one, it's fine. And if, and on Snowflake, you raise the issue that they're going to have to add transactions, they're going to have to rewrite their database. They have no indexes whatsoever in Snowflake. I mean, part of the simplicity that David talked about is because they had to cut corners, which makes sense. If you're focused on the data warehouse you cut out the indexes, great. You don't need them. But if you're going to do transactions, you kind of need them. So you're going to have to do some more work there. So... >> Well... So, you know, I don't know. I have a different take on that guys. I think that, I'm not sure if Snowflake will add transactions. I think maybe, you know, their hope is that the market that they're creating is big enough. I mean, I have a different view of this in that, I think the data architecture is going to change over the next 10 years. As opposed to having a monolithic system where everything goes through that big data platform, the data warehouse and the data lake. I actually see what Snowflake is trying to do and, you know, I'm sure others will join them, is to put data in the hands of product builders, data product builders or data service builders. I think they're betting that that market is incremental and maybe they don't try to take on... I think it would maybe be a mistake to try to take on Oracle. Oracle is just too strong. I wonder David, if you could comment. So it's interesting to see how strong Gartner rated Oracle in cloud database, 'cause you don't... I mean, okay, Oracle has got OCI, but you know, you think a cloud, you think Google, or Amazon, Microsoft and Google. But if I have a transaction database running on Oracle, very risky to move that, right? And so we've seen that, it's interesting. Amazon's a big customer of Oracle, Salesforce is a big customer of Oracle. You know, Larry is very outspoken about those companies. SAP customers are many, most are using Oracle. I don't, you know, it's not likely that they're going anywhere. My question to you, David, is first of all, why do they want to go to the cloud? And if they do go to the cloud, is it logical that the least risky approach is to stay with Oracle, if you're an Oracle customer, or Db2, if you're an IBM customer, and then move those other workloads that can move whether it's more data warehouse oriented or incremental transaction work that could be done in a Aurora? >> I think the first point, why should Oracle go to the cloud? Why has it gone to the cloud? And if there is a... >> Moreso... Moreso why would customers of Oracle... >> Why would customers want to... >> That's really the question. >> Well, Oracle have got Oracle Cloud@Customer and that is a very powerful way of doing it. Where exactly the same Oracle system is running on premise or in the cloud. You can have it where you want, you can have them joined together. That's unique. That's unique in the marketplace. So that gives them a very special place in large customers that have data in many different places. The second point is that moving data is very expensive. Marc was making that point earlier on. Moving data from one place to another place between two different databases is a very expensive architecture. Having the data in one place where you don't have to move it where you can go directly to it, gives you enormous capabilities for a single database, single database type. And I'm sure that from a transact... From an analytic point of view, that's where Snowflake is going, to a large single database. But where Oracle is going to is where, you combine both the transactional and the other one. And as you say, the cost of migration of databases is incredibly high, especially transaction databases, especially large complex transaction databases. >> So... >> And it takes a long time. So at least a two year... And it took five years for Amazon to actually succeed in getting a lot of their stuff over. And five years they could have been doing an awful lot more with the people that they used to bring it over. So it was a marketing decision as opposed to a rational business decision. >> It's the holy grail of the vendors, they all want your data in their database. That's why Amazon puts so much effort into it. Oracle is, you know, in obviously a very strong position. It's got growth and it's new stuff, it's old stuff. It's, you know... The problem with Oracle it has like many of the legacy vendors, it's the size of the install base is so large and it's shrinking. And the new stuff is.... The legacy stuff is shrinking. The new stuff is growing very, very fast but it's not large enough yet to offset that, you see that in all the learnings. So very positive news on, you know, the cloud database, and they just got to work through that transition. Let's bring up slide number five, because Marc, this is to me the most interesting. So we've just shown all these detailed analysis from Gartner. And then you look at the Magic Quadrant for cloud databases. And, you know, despite Amazon being behind, you know, Oracle, or Teradata, or whomever in every one of these ratings, they're up to the right. Now, of course, Gartner will caveat this and say, it doesn't necessarily mean you're the best, but of course, everybody wants to be in the upper, right. We all know that, but it doesn't necessarily mean that you should go by that database, I agree with what Gartner is saying. But look at Amazon, Microsoft and Google are like one, two and three. And then of course, you've got Oracle up there and then, you know, the others. So that I found that very curious, it is like there was a dissonance between the hardcore ratings and then the positions in the Magic Quadrant. Why do you think that is Marc? >> It, you know, it didn't surprise me in the least because of the way that Gartner does its Magic Quadrants. The higher up you go in the vertical is very much tied to the amount of revenue you get in that specific category which they're doing the Magic Quadrant. It doesn't have to do with any of the revenue from anywhere else. Just that specific quadrant is with that specific type of market. So when I look at it, Oracle's revenue still a big chunk of the revenue comes from on-prem, not in the cloud. So you're looking just at the cloud revenue. Now on the right side, moving to the right of the quadrant that's based on functionality, capabilities, the resilience, other things other than revenue. So visionary says, hey how far are you on the visionary side? Now, how they weight that again comes down to Gartner's experts and how they want to weight it and what makes more sense to them. But from my point of view, the right side is as important as the vertical side, 'cause the vertical side doesn't measure the growth rate either. And if we look at these, some of these are growing much faster than the others. For example, Snowflake is growing incredibly fast, and that doesn't reflect in these numbers from my perspective. >> Dave: I agree. >> Oracle is growing incredibly fast in the cloud. As David pointed out earlier, it's not just in their cloud where they're growing, but it's Cloud@Customer, which is basically an extension of their cloud. I don't know if that's included these numbers or not in the revenue side. So there's... There're a number of factors... >> Should it be in your opinion, Marc, would you include that in your definition of cloud? >> Yeah. >> The things that are hybrid and on-prem would that cloud... >> Yes. >> Well especially... Well, again, it depends on the hybrid. For example, if you have your own license, in your own hardware, but it connects to the cloud, no, I wouldn't include that. If you have a subscription license and subscription hardware that you don't own, but it's owned by the cloud provider, but it connects with the cloud as well, that I would. >> Interesting. Well, you know, to your point about growth, you're right. I mean, it's probably looking at, you know, revenues looking, you know, backwards from guys like Snowflake, it will be double, you know, the next one of these. It's also interesting to me on the horizontal axis to see Cloud Data and Databricks further to the right, than Snowflake, because that's kind of the data lake cloud. >> It is. >> And then of course, you've got, you know, the other... I mean, database used to be boring, so... (David laughs) It's such a hot market space here. (Marc talks indistinctly) David, your final thoughts on all this stuff. What does the customer take away here? What should I... What should my cloud database management strategy be? >> Well, I was positive about Oracle, let's take some of the negatives of Oracle. First of all, they don't make it very easy to rum on other platforms. So they have put in terms and conditions which make it very difficult to run on AWS, for example, you get double counts on the licenses, et cetera. So they haven't played well... >> Those are negotiable by the way. Those... You bring it up on the customer. You can negotiate that one. >> Can be, yes, They can be. Yes. If you're big enough they are negotiable. But Aurora certainly hasn't made it easy to work with other plat... Other clouds. What they did very... >> How about Microsoft? >> Well, no, that is exactly what I was going to say. Oracle with adjacent workloads have been working very well with Microsoft and you can then use Microsoft Azure and use a database adjacent in the same data center, working with integrated very nicely indeed. And I think Oracle has got to do that with AWS, it's got to do that with Google as well. It's got to provide a service for people to run where they want to run things not just on the Oracle cloud. If they did that, that would in my term, and my my opinion be a very strong move and would make make the capabilities available in many more places. >> Right. Awesome. Hey Marc, thanks so much for coming to theCUBE. Thank you, David, as well, and thanks to Gartner for doing all this great research and making it public on the web. You can... If you just search critical capabilities for cloud database management systems for operational use cases, that's a mouthful, and then do the same for analytical use cases, and the Magic Quadrant. There's the third doc for cloud database management systems. You'll get about two hours of reading and I learned a lot and I learned a lot here too. I appreciate the context guys. Thanks so much. >> My pleasure. All right, thank you for watching everybody. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> The steepest drop in the stock market since June 11th flipped the narrative and sent investors scrambling. Tech got hammered after a two-month run, and people are asking questions. Is this a bubble popping, or is it a healthy correction? Are we now going to see a rotation into traditional stocks, like banks and maybe certain cyclicals that have lagged behind the technology winners? Hello, everyone, and welcome to this week's episode of Wikibon's CUBE Insights powered by ETR. In this Breaking Analysis, we want to give you our perspective on what's happening in the technology space and unpack what this sentiment flip means for the balance of 2020 and beyond. Let's look at what happened on September 3rd, 2020. The tech markets recoiled this week as the NASDAQ Composite dropped almost 5% in a single day. Apple's market cap alone lost $178 billion. The Big Four: Apple, Microsoft, Amazon, and Google lost a combined value that approached half a trillion dollars. For context, this number is larger than the gross domestic product for countries as large as Thailand, Iran, Austria, Norway, and even the UAE, and many more. The tech stocks that have been running due to COVID, well, they got crushed. These are the ones that we've highlighted as best positioned to thrive during the pandemic, you know, the work-from-home, SaaS, cloud, security stocks. We really have been talking about names like Zoom, ServiceNow, Salesforce, DocuSign, Splunk, and the security names like CrowdStrike, Okta, Zscaler. By the way, DocuSign and CrowdStrike and Okta all had nice earnings beats, but they still got killed underscoring the sentiment shift. Now the broader tech market was off as well on sympathy, and this trend appears to be continuing into the Labor Day holiday. Now why is this happening, and why now? Well, there are a lot of opinions on this. And first, many, like myself, are relatively happy because this market needed to take a little breather. As we've said before, the stock market, it's really not reflecting the realities of the broader economy. Now as we head into September in an election year, uncertainty kicks in, but it really looks like this pullback was fueled by a combination of an overheated market and technical factors. Specifically, take a look at volatility indices. They were high and rising, yet markets kept rising along with them. Robinhood millennial investors who couldn't bet on sports realized that investing in stocks was as much of a rush and potentially more lucrative. The other big wave, which was first reported by the Financial Times, is that SoftBank made a huge bet on tech and bought options tied to around $50 billion worth of high-flying tech stocks. So the option call volumes skyrocketed. The call versus put ratio was getting way too hot, and we saw an imbalance in the market. Now market makers will often buy an underlying stock to hedge call options to ensure liquidity in these cases. So to be more specific, delta in options is a measure of the change in the price of an option relative to the underlying stock, and gamma is a measure of the volatility of the delta. Now usually, volatility is relatively consistent on both sides of the trade, the calls and the puts, because investors often hedge their bets. But in the case of many of these hot stocks, like Tesla, for example, you've seen the call skew be much greater than the skew in the downside. So let's take an example. If people are buying cheap out of the money calls, a market maker might buy the underlying stock to hedge for liquidity. And then if Elon puts out some good news, which he always does, the stock goes up. Market makers have to then buy more of the underlying stock. And then algos kick in to buy even more. And then the price of the call goes up. And as it approaches it at the money price, this forces market makers to keep buying more of that underlying stock. And then the melt up until it stops. And then the market flips like it did this week. When stock prices begin to drop, then market makers were going to rebalance their portfolios and their risk and sell their underlying stocks, and then the rug gets pulled out from the markets. And that's really why some of the stocks that have run dropped so precipitously. Okay, why did I spend so much time on this, and why am I not freaking out? Because I think these market moves are largely technical versus fundamental. It's not like 1999. We had a double whammy of technical rug pulls combined with poor underlying fundamentals for high-flying companies like CMGI and Internet Capital Group, whose businesses, they were all about placing bets on dot-coms that had no business models other than non-monetizable eyeballs. All right, let's take a look at the NASDAQ and dig into the data a little bit. And I think you'll see what I mean and why I'm not too concerned. This is a year-to-date chart of the NASDAQ, and you can see it bottomed on March 23rd at 6,860. And then ran up until June 11th and had that big drop, but was still elevated at 9,492. And then it ran up to over 12,000 and hit an all-time high. And then you see the big drop. And that trend continued on Friday morning. The NASDAQ Composite traded below 11,000. It actually corrected to 10% of its high, 9.8% to be precise, and then it snapped back. But even at its low, that's still up over 20% for the year. In the year of COVID, would that have surprised you in March? It certainly would have surprised me. So to me, this pullback is sort of a relief. It's good and actually very normal and quite predictable. Now the exact timing of these pullbacks, of course, on the other hand is not entirely predictable. Not at all, frankly, at least for this observer. So the big question is where do we go from here? So let's talk about that a little bit. Now the economy continues to get better. Take a look at the August job report; it was good. 1.4 million new jobs, 340,000 came from the government. That was positive numbers. And the other good news is it translates into a drop in unemployment under 10%. It's now at 8.4%. And this is really good relative to expectations. Now the sell-off continued, which suggested that the market wanted to keep correcting, so that's good. Maybe some buying opportunities would emerge in over the next several months, the market snapped back, but for those who have been waiting, I think that's going to happen. And so that snapback, maybe that's an indicator that the market wants to keep going up, we'll see. But I think there are more opportunities ahead because there's really so much uncertainty. What's going to happen with the next round of the stimulus? The jobs report, maybe that's a catalyst for compromise between the Democrats and the Republicans, maybe. The US debt is projected to exceed 100% of GDP this calendar year. That's the highest it's been since World War II. Does that give you a good feeling? That doesn't give me a good feeling. And when we talk about the election, that brings additional uncertainty. So there's a lot to think about for the markets. Now let's talk about what this means for tech. Well, as we've been projecting for months with our colleagues at ETR, despite what's going on in the stock market and its rise, there's those real tech winners, we still see a contraction in 2020 for IT spend of minus 5 to 8%. And we talk a lot about the bifurcation in the market due to COVID accelerating some of these trends that were already in place, like digital transformation and SaaS and cloud. And then the work-from-home kicks in with other trends like video conferencing and the shift to security spend. And we think this is going to continue for years. However, because these stocks have run up so much, they're going to have very tough compares in 2021. So maybe time for a pause. Now let's take a look at the IT spending macroeconomics. This data is from a series of surveys that ETR conducted to try to better understand spending patterns due to COVID. Those yellow slices of the pies show the percent of customers that indicate that their budgets will be impacted by coronavirus. And you can see there's a steady increase from mid-March, which blend into April, and then you can see the June data. It goes from 63% saying yes, which is very high, to 78%, which is very, very high. And the bottom part of the chart shows the degree of that change. So 22% say no change in the latest survey, but you can see much more of a skew to the red declines on the left versus the green upticks on the right-hand side of the chart. Now take a look at how IT buyers are seeing the response to the pandemic. This chart shows what companies are doing as a result of COVID in another recent ETR survey. Now of course, it's no surprise, everybody's working from home. Nobody's traveling for business, not nobody, but most people aren't, we know that. But look at the increase in hiring freezes and freezing new IT deployments, and the sharp rise in layoffs. So IT is yet again being asked to do more with less. They're used to it. Well, we see this driving an acceleration to automation, and that's going to benefit, for instance, the RPA players, cloud providers, and modern software vendors. And it will also precipitate a tailwind for more aggressive AI implementations. And many other selected names are going to continue to do well, which we'll talk about in a second, but they're in the work-from-home, the cloud, the SaaS, and the modern data sectors. But the problem is those sectors are not large enough to offset the declines in the core businesses of the legacy players who have a much higher market share, so the overall IT spend declines. Now where it gets kind of interesting is the legacy companies, look, they all have growth businesses. They're making acquisitions, they're making other bets. IBM, for example, has its hybrid cloud business in Red Hat, Dell has VMware and it's got work-from-home solutions, Oracle has SaaS and cloud, Cisco has its security business, HPE, it's as a service initiative, and so forth. And again, these businesses are growing faster, but they are not large enough to offset the decline in core on-prem legacy and drive anything more than flat growth, overall, for these companies at best. And by the time they're large enough, we'll be into the next big thing, so the cycle continues. But these legacy companies are going to compete with the upstarts, and that's where it gets interesting. So let's get into some of the specific names that we've been talking about for over a year now and make some comments around their prospects. So what we want to do is let's start with one of our favorites: Snowflake. Now Snowflake, along with Asana, JFrog, Sumo Logic, and Unity, has a highly anticipated upcoming IPO. And this chart shows new adoptions in the database sector. And you can see that Snowflake, while down from the October 19th survey, is far outpacing its competitors, with the exception of Google, where BigQuery is doing very well. But you see Mongo and AWS remain strong, and I'm actually quite encouraged that it looks like Cloudera has righted the ship and you kind of saw that in their earnings recently. But my point is that Snowflake is a share gainer, and we think will likely continue to be one for a number of quarters and years if they can execute and compete with the big cloud players, and that's a topic that we've covered extensively in previous Breaking Analysis segments, and, as you know, we think Snowflake can compete. Now let's look at automation. This is another space that we've been talking about quite a bit, and we've largely focused on two leaders: UiPath and Automation Anywhere. But I have to say, I still like Blue Prism. I think they're well-positioned. And I especially like Pegasystems, which has, for years, been embarking on a broader automation agenda. What this chart shows is net score or spending velocity data for those customers who said they were decreasing spend in 2020. Those red bars that we showed earlier are the ones who are decreasing. And you can see both Automation Anywhere and UiPath show elevated levels within that base where spending is declining, so that's a real positive. Now Microsoft, as we've reported, is elbowing its way into the market with what is currently an inferior point product, but, you know, it's Microsoft, so we can't ignore that. And finally, let's have a look at the all-important security sector, which we've covered extensively and put out a report recently. So what this next chart does is cherry-picks of a few of our favorite names, and it shows the net score or spending momentum and the granularity for some of the leaders and emerging players. All of these players are in the green, as you can see in the upper right, and they all have decent presence in the dataset as indicated by the shared NS. Okta is at the top of the list with 58% net score. Palo Alto, they're a more mature player, but still, they have an elevated net score. CrowdStrike's net score dropped this quarter, which was a bit of a concern, but it's still high. And it followed by SailPoint and Zscaler, who are right there. The big three trends in this space right now are cloud security, identity access management, and endpoint security. Those are the tailwinds, and we think these trends have legs. Remember, net score in this survey is a forward-looking metric, so we'll come back and look at the next survey, which is running this month in the field from ETR. Now everyone on this chart has reported earnings, except Zscaler, which reports on September 9th, and all of these companies are doing well and exceeding expectations, but as I said earlier, next year's compares won't be so easy. Oh, and by the way, their stock prices, they all got killed this week as a result of the rug pull that we explained earlier. So we really feel this isn't a fundamental problem for these firms that we're talking about. It's more of a technical in the market. Now Automation Anywhere and UiPath, you really don't know because they're not public and I think they need to get their house in order so they can IPO, so we'll see when they make it to public markets. I don't think that's an if, that I think they will IPO, but the fact that they haven't filed yet says they're not ready. Now why wouldn't you IPO if you are ready in this market despite the recent pullbacks? Okay, let's summarize. So listen, all you new investors out there that think stock picking is easy, look, any fool can make money in a market that goes up every day, but trees don't grow to the moon and there are bulls and bears and pigs, and pigs get slaughtered. And I can throw a dozen other cliches at you, but I am excited that you're learning. You maybe have made a few bucks playing the options game. It's not as easy as you might think. And I'm hoping that you're not trading on margin. But look, I think there are going to be some buying opportunities ahead, there always are, be patient. It's very hard, actually impossible, to time markets, and I'm a big fan of dollar-cost averaging. And young people, if you make less than $137,000 a year, load up on your Roth, it's a government gift that I wish I could have tapped when I was a newbie. And as always, please do your homework. Okay, that's it for today. Remember, these episodes, they're all available as podcasts, wherever you listen, so please subscribe. I publish weekly on wikibon.com and siliconangle.com, so check that out, and please do comment on my LinkedIn posts. Don't forget, check out etr.plus for all the survey action. Get in touch on Twitter, I'm @dvellante, or email me at david.vellante@siliconangle.com. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, everyone. Be well, and we'll see you next time. (gentle upbeat music)

(upbeat music) >> From New York City, it's theCUBE. Covering "Welcome To The New Edge." Brought to you by Pensando Systems. >> Hey, welcome back here ready. Jeff Frick here with theCUBE. We are high atop Goldman Sachs in downtown Manhattan, I think it's 43 floors, for a really special event. It's the Pensando launch. It's really called welcome to the new edge and we talked about technology. We had some of the founders on but, these type of opportunities are really special to talk to some really senior leaders and we're excited to have John Chambers back on, who as you know, historic CEO of Cisco for many, many years. Has left that, is doing his own ventures he's writing books, he's investing and he's, happens to be chairman of the board of Pensando. So John, thanks for taking a few minutes with us. >> Well, more than a few minutes, I think what we talked about today is a major industry change and so to focus on that and focus about the implications will be a lot of fun. >> So let's jump into it. So, one of the things you led with earlier today was kind of these 10 year cycles and they're not exactly 10 years, but you outlined a series of them from mainframe, mini client server everybody knows kind of the sequence. What do you think it is about the 10 year kind of cycle besides the fact that it's easy and convenient for us to remember, that, kind of paces these big disruptions? >> Well, I think it has to do with once a company takes off they tend to, dominate that segment of the industry for so long that even if a creative idea came up they were just overpowering. And then toward the end of a 10 year cycle they quit reinventing themselves. And we talked earlier about the innovator's dilemma and the implications for it. Or an architecture that was designed that suddenly can't go to the next level. So I think it's probably a combination of three or four different factors, including the original incumbent who broke the glass, disrupted others, not disrupting themselves. >> Right, but you also talked about a story where you had to shift focus based on some customer feedback and you ran Cisco for a lot longer than 10 years. So how do you as a leader kind of keep your ears open to something that's a disruptive change that's not your regular best customer and your regular best salesman asking for a little bit faster, a little bit cheaper, a little bit of more the same versus the significant disruptive transformational shift? >> Well this goes back to one of my most basic views in life is I think we learn more from our setbacks or setbacks we were part of, or even the missteps or mistakes than you ever do your successes. Everybody loves to talk about successes and I'm no different there. But when you watched a great state like West Virginia that was the chemical center of the world and the coal mining center of the world, the 125,000 coal mines, six miners very well paid, 6,000 of the top engineers in the world, it was the Silicon Valley of the chemical industry and those just disappear. And because our state did not reinvent itself, because the education system didn't change, because we didn't distract attract a new set of businesses in we just kept doing the right thing too long, we got left behind. Then I went to Boston, it was the Silicon Valley of the world. And Route 128 around Boston was symbolic with the Silicon Valley and I-101 and 280 around it. And we had the top university at that time. Much like Stanford today, but MIT generating new companies. We had great companies, DEC, Wang, Data General. Probably a million jobs in the area and because we got stuck in a segment of the market, quit listening to our customers and missed the transitions, not only did we lose probably 1.2 million jobs on it, 100,000 out of DEC, 32,000 out of Wang, etc, we did not catch the next generation of technology changes. So I understand the implications if you don't disrupt yourself. But I also learned, that if you're not regularly reinventing yourself, you get left behind as a leader. And one of my toughest competitors came up to me and said, "John, I love the way you're reinventing Cisco "and how you've done that multiple times." And then I turned and I said "That's why a CEO has got to be in the job "for more than four or five years" and he said, "Now we disagree again." Which we usually did and he said, "Most people can't reinvent themselves." And he said "I'm an example." "I'm a pretty good CEO" he's actually a very good CEO, but he said, "After I've been there three or four years "I've made the changes, that I know "I've got to go somewhere else." And he could see I didn't buy-in and then he said, "How many of your top 100 people "you've been happy with once they've been "in the job for more than five years?" I hesitated and I said "Only one." And he's right, you've got to move people around, you've got to get people comfortable with disruption on it and, the hardest one to disrupt are the companies or the leaders who've been most successful and yet, that's when you got to think about disruption. >> Right, so to pivot on that a little bit in terms of kind of the government's role in jobs, specifically. >> Yes. >> We're in this really strange period of time. We have record low unemployment, right, tiny, tiny unemployment, and yet, we see automation coming in aggressively with autonomous vehicles and this and that and just to pick truck drivers as a category, everyone can clearly see that autonomous vehicles are going to knock them out in the not too distant future. That said, there's more demand for truck drivers today than there's every been and they can't fill the positions So, with this weird thing where we're going to have a bunch of new jobs that are created by technology, we're going to have a bunch of old jobs that get displaced by technology, but those people aren't necessarily the same people that can leave the one and go to the other. So as you look at that challenge, and I know you work with a lot of government leaders, how should they be thinking about taking on this challenge? >> Well, I think you've got to take it on very squarely and let's use the U.S. as an example and then I'll parallel what France is doing and what India is doing that is actually much more creative that what we are, from countries you wouldn't have anticipated. In the U.S. we know that 50% of the Fortune 500 will probably not exist in 10 years, 12 at the most. We know that the large companies will not incrementally hire people over this next decade and they've often been one of the best sources of hiring because of AI and automation will change that. So, it's not just a question of being schooled in one area and move to another, those jobs will disappear within the companies. If we don't have new jobs in startups and if we don't have the startups running at about three to four times the current volumes, we've got a real problem looking out five to 10 years. And the startups where everyone thinks we're doing a good job, the app user, third to a half of what they were two decades ago. And so if you need 25 million jobs over this next decade and your startups are at a level more like they were in the 90s, that's going to be a challenge. And so I think we've got to think from the government perspective of how we become a startup nation again, how we think about long-term job creation, how we think about job creation not taking money out of one pocket and give it to another. People want a real job, they want to have a meaningful job. We got to change our K through 12 education system which is broken, we've got to change our university system to generate the jobs for where people are going and then we've got to retrain people. That is very doable, if you got at it with a total plan and approach it from a scale perspective. That was lacking. And one of the disappointing things in the debate last night, and while I'm a republican I really want who's going to really lead us well both at the presidential level, but also within the senate, the house. Is, there was a complete lack of any vision on what the country should look like 10 years from now, and how we're going to create 25 million jobs and how we're going to create 10 million more that are going to be displaced and how we're going to re-educate people for it. It was a lot of finger pointing and transactional, but no overall plan. Modi did the reverse in India, and actually Macron, in all places, in France. Where they looked at GDP growth, job creation, startups, education changes, etc, and they executed to an overall approach. So, I'm looking for our government really to change the approach and to really say how are we going to generate jobs and how are we going to deal with the issues that are coming at us. It's a combination of all the the above. >> Yep. Let's shift gears a little bit about the education system and you're very involved and you talked about MIT. Obviously, I think Stanford and Cal are such big drivers of innovation in the Bay area because smart people go there and they don't leave. And then there's a lot of good buzz now happening in Atlanta as an investment really piggy-backing on Georgia Tech, which also creates a lot of great engineers. As you look at education, I don't want to go through K through 12, but more higher education, how do you see that evolving in today's world? It's super expensive, there's tremendous debt for the kids coming out, it doesn't necessarily train them for the new jobs. >> Where the jobs are. >> How do you see, kind of the role of higher education and that evolving into kind of this new world in which we're headed? >> Well, the good news and bad news about when I look at successful startups around the world, they're always centered around a innovative university and it isn't just about the raw horse power of the kids, It starts with the CEO of the university, the president of the university, their curriculum, their entrepreneurial approach, do they knock down the barriers across the various groups from engineering to business to law, etc? And are they thinking out of box? And if you watch, there is a huge missing piece between, Georgia Tech more of an exception, but still not running at the level they need to. And the Northeast around Boston and New York and Silicon Valley, The rest of the country's being left behind. So I'm looking for universities to completely redo their curriculum. I'm looking for it really breaking down the silos within the groups and focus on the outcomes. And much like Steve Case has done a very good job on focusing, about the Rust Belt and how do you do startups? I'm going to learn from what I saw in France at Polytechnique and the ITs in India, and what occurred in Stanford and MIT used to occur is, you've got to get the universities to be the core and that's where they kids want to stay close to, and we've got to generate a whole different curriculum, if you will, in the universities, including, continuous learning for their graduates, to be able to come back virtually and say how do I learn about re-skilling myself? >> Yeah. >> The current model is just not >> the right model >> It's broken. >> For the, for going forward. >> K through 12 is >> hopelessly broken >> Yeah. >> and the universities, while were still better than anywhere else in the world, we're still teaching, and some of the teachers and some of the books are what I could have used in college. >> Right, right >> So, we got to rethink the whole curriculum >> darn papers on the inside >> disrupt, disrupt >> So, shifting gears a little bit, you, played with lots of companies in your CEO role you guys did a ton of M&A, you're very famous for the successful M&A that you did over a number of years, but in an investor role, J2 now, you're looking at a more early stage. And you said you made a number of investments which is exciting. So, as you evaluate opportunities A. In teams that come to pitch to you >> Yeah. >> B. What are the key things you look for? >> In the sequence you've raised them, first in my prior world, I was really happy to do 180 acquisitions, in my current world, I'm reversed, I want them to go IPO. Because you add 76% of your headcount after an IPO, or after you've become a unicorn. When companies are bought, including what I bought in my prior role, their headcount growth is pretty well done. We'd add engineers after that, but would blow them through our sales channel, services, finance, etc. So, I want to see many more of these companies go public, and this goes back to national agenda about getting IPO's, not back to where they were during the 90's when it was almost two to three times, what you've seen over the last decade. But probably double, even that number the 90's, to generate the jobs we want. So, I'm very interested now about companies going public in direction. To the second part of your question, on what do I look for in startups and why, if I can bridge it, to am I so faired up about Pensando? If I look for my startups and, it's like I do acquisitions, I develop a playbook, I run that playbook faster and faster, it's how I do digitization of countries, etc. And so for a area I'm going to invest in and bet on, first thing I look at, is their market, technology transition, and business model transition occurring at the same time. That was Amazon of 15 years ago as an example. The second thing I look at, is the CEO and ideally, the whole founding team but it's usually just the CEO. The third thing I look for, is what are the customers really say about them? There's only one Steve Jobs, and it took him seven years. So, I go to the customers and say "What do you really think of this company?" Fourth thing I look for, is how close to an inflection point are they. The fifth thing I look for, is what they have in their ecosystem. Are they partnering? Things of that type. So, if I were to look at Pensando, Which is really the topic about can they bring to the market the new edge in a way that will be a market leading force for a whole decade? Through a ecosystem of partners that will change business dramatically and perhaps become the next major tech icon. It's how well you do that. Their vision in terms of market transitions, and business transitions 100% right. We've talked about it, 5G, IOT, internet of things, going from 15 billion devices to 500 billion devices in probably seven years. And, with the movement to the edge the business models will also change. And this is where, democratization, the cloud, and people able to share that power, where every technology company becomes a business becomes a, every business company becomes a technology company. >> Right. >> The other thing I look at is, the team. This is a team of six people, myself being a part of it, that thinks like one. That is so unusual, If you're lucky, you get a CEO and maybe a founder, a co-founder. This team, you've got six people who've worked together for over 20 years who think alike. The customers, you heard the discussions today. >> Right. >> And we've not talked to a single cloud player, a single enterprise company, a single insurance provider, or major technology company who doesn't say "This is very unique, let's talk about "how we work together on it." The inflection point, it's now you saw that today. >> Nobody told them it's young mans game obviously, they got the twenty-something mixed up >> No, actually were redefining (laughs) twenty-something, (laughs) but it does say, age is more perspective on how you think. >> Right, right. >> And Shimone Peres, who, passed away unfortunately, two years ago, was a very good friend. He basically said "You've got all your life "to think like a teenager, "and to really think and dream out of box." And he did it remarkably well. So, I think leaders, whether their twenty-something, or twenty-some years of experience working you've got to think that way. >> Right. So I'm curious, your take on how this has evolved, because, there was data and there was compute. And networking brought those two thing together, and you were at the heart of that. >> Mm-hmm. Now, it's getting so much more complex with edge, to get your take on edge. But, also more importantly exponential growth. You've talked about going from, how ever many millions the devices that were connected, to the billions of devices that are connected now. How do you stay? How do you help yourself think along exponential curves? Because that is not easy, and it's not human. But you have to, if you're going to try to get ahead of that next wave. >> Completely agree. And this is not just for me, how do I do it? I'm sharing it more that other people can learn and think about it perhaps the same way. The first thing is, it's always good to think of the positive, You can change the world here, the positive things, But I've also seen the negatives we talked about earlier. If you don't think that way, if you don't think that way as a leader of your company, leader of your country, or the leader of a venture group you're going to get left behind. The implications for it are really bad. The second is, you've got to say how do you catch and get a replicable playbook? The neat thing about what were talking about, whether it's by country in France, or India or the U.S., we've got replicable playbooks we know what to run. The third element is, you've got to have the courage to get outside your comfort zone. And I love change when it happens to you, I don't like it when it happens to me And I know that, So, I've got to get people around me who push me outside my comfort zone on that. And then, you've got to be able to dream and think like that teenager we talked about before. But that's what we were just with a group of customers, who were at this event. And they were asking "How do we get "this innovation into our company?" "How do we get the ability to innovate, through not just strategic partnerships with other large companies or partnerships with startups?" But "How do we build that internally?" It's comes down to the leader has to create that image and that approach. Modi's done it for 1.3 billion people in India. A vision, of the future on GDP growth. A digital country, startups, etc. If they can do it for 1.3 billion, tell me why the U.S. can not do it? (laughs) And why even small states here, can't do it. >> Yeah. Shifting gears a little bit, >> All right. >> A lot of black eyes in Silicon Valley right now, a lot of negativity going on, a lot of problems with privacy and trading data for currency and, it's been a rough road. You're way into tech for good and as you said, you can use technology for good you can use technology for bad. What are some things you're doing on the tech for good side? Because I don't think it gets the spotlight that it probably should, because it doesn't sell papers. >> Well, actually the press has been pretty good we just need to do it more on scale. Going back to Cisco days, we never had any major issues with governments. Even though there was a Snowden issue, there were a lot of implications about the power of the internet. Because we work with governments and citizens to say "What are the legitimate needs so that everybody benefits from this?" And where the things that we might have considered doing that, governments felt strongly about or the citizens wouldn't prosper from we just didn't do it. And we work with democrats and republicans alike and 90% of our nation believed tech was for good. But we worked hard on that. And today, I think you got to have more companies doing this and then, what, were doing uniquely in JC2, is were literally partnering with France on tech is for good and I'm Macron's, global tech ambassador and we focus about job creation and inclusion. Not just in Paris, or around Station F but throughout all the various regions in the country. Same thing within India, across 26 different states with Modi on how do you drive it through? And then if we can do it in France or India why can't we do it in each state in the U.S.? Partnering with West Virginia, with a very creative, president of the university there West Virginia University. With the democrats and republicans in their national senate, but also within the governor and speaker of the house and the president and senate within West Virginia, and really saying were going to change it together. And getting a model that you can then cookie cut across the U.S. if you change the curriculum, to your earlier comments. If you begin to focus on outcomes, not being an expert in one area, which is liable not to have a job >> Right. >> Ten years later. So, I'm a dreamer within that, but I think you owe an obligation to giving back, and I think they're all within our grasps >> Right >> And I think you can do, the both together. I think at JC2 we can create a billion dollar company with less than 10 people. I think you can change the world and also make a very good profit. And I think technology companies have to get back to that, you got to create more jobs than you destroy. And you can't be destroying jobs, then telling other people how to live their lives and what their politics should be. >> Yeah. >> That just doesn't work in terms of the environment. >> Well John, again, thanks for your time. Give you the last word on >> Sure >> Account of what happened here today, I mean you're here, and Tony O'Neary was here or at the headquarters of Goldman. A flagship launch customer, for the people that weren't here today why should they be paying attention? >> Well, if we've got this market transition right, the technology and business model, the next transition will be everything goes to the edge. And as every company or every government, or every person has to be both good in their "Area of expertise." or their vertical their in, they've got to also be good in technology. What happened today was a leveling of the playing field as it relates to cloud. In terms of everyone should have choice, democratization there, but also in architecture that allows people to really change their business models, as everything moves to the edge where 75% of all transactions, all data will be had and it might even be higher than that. Secondly, you saw a historic first never has anybody ever emerged from stealth after only two and a half years of existing as a company, with this type of powerhouse behind them. And you saw the players where you have a customer, Goldman Sachs, in one of the most leading edge areas, of industry change which is obviously finance leading as the customer who's driven our direction from the very beginning. And a company like NetApp, that understood the implication on storage, from two and a half years ago and drove our direction from the very beginning. A company like HP Enterprise's, who understood this could go across their whole company in terms of the implications, and the unique opportunity to really change and focus on, how do they evolve their company to provide their customer experience in a very unique way? How do you really begin to think about Equinix in terms of how they changed entirely from a source matter prospective, what they have to do in terms of the direction and capabilities? And then Lightspeed, one of the most creative intra capital that really understands this transition saying "I want to be a part of this." Including being on the board and changing the world one more time. So, what happened today? If we're right, I think this was the beginning of a major inflection point as everything moves to the edge. And how ecosystem players, with Pensando at the heart of that ecosystem, can take on the giants but also really use this technology to give everybody choice, and how they really make a difference in the future. As well as, perhaps give back to society. >> Love it. Thank you John >> My pleasure, that was fun. >> Appreciate it. You're John, I'm Jeff you're watching theCUBE. Thanks for watching, we'll see you next time. (upbeat music)

>> live from Mountain View, California. It's the queue covering definite create twenty nineteen. Brought to you by Cisco. >> Welcome back to the cave. Lisa Martin with John Barrier on our first day of two days of coverage of Cisco Definite Create twenty nineteen at the Computer History Museum in Mountain View, California. John Eyre. Please welcome to iniquitous and directors solutions, architecture and Devil Box from Liberty Technology. Tony, Welcome. >> How are you? >> Good, thanks for Thanks for having us tell our audience a little bit about liberty technology before we get into the community. What you doing your breakout session? >> Not a problem. The re technology is a company. Where? MSP company down in Griffin, Georgia. And so we handle a lot of a lot of clients are either public sector cities, all different types of all the different verticals. So well. And so do you have a client? A customer out there that needs needs an extra arm into it. We're there for them. >> So your basement of Georgia, Which means that how warm it is in here today Outside should be nothing for you right >> now. Tell me about >> well outside >> now, since there is no humanity I like it back home in few minutes, >> Californians were babies. >> Yeah, Joni, Public Sector. We've done a lot of interviews of public sector folks with their towns and cities, air, ground rules, municipalities, cities, their I t light. And then they don't have the Dev ops expertise, but clouds a perfect fit for them. But they have a lot of certain characters. Whether it's email is very ephemeral. People come and go, So getting people collaborating in these distinct user groups that have different roles and responsibilities is a challenge. How are you guys solving that? Because there's something I know you guys have worked on. There's a challenge that's only Republicans for enterprises do. How do you bring people that are distinct user populations that have an application or roll or use case into a collaborative, horizontally scaleable >> system? We show Be honest way. Go in there and we go in there and we discover as to what they're doing now, what are their pain points? What do they want? Change where they want to go and then we show them the collaboration started. We shone like what makes team's way? Show him all of the, uh, meetings room devices, things like that. And then not just on the collaboration side, but also if there helping with three, six, five their security than Rocky. That's how we bring. That's how we bring collaboration intothe public >> about the Cisco dynamic we've been covering definite create since it started. Definite. Now it's just go live couple years, seeing kind of a new vibe and new mojo going on with that within the Cisco ecosystem of actually coding stuff up, whether it's slinging AP eyes together or creating new ones. New capabilities. How is it changed the delivery in performance of the customers? Because this is not just your old school Cisco networking company. Yeah, they got APS. Things are connected. Date is moving from Point A to point B. All right, but he's kind of integration challenges. Kind of seamless program ability is the core theme here. What's your reaction? Thoughts on all this? >> No. >> Well, first off, this is my first definite create. I've been to other Siskel lives have not been too. Don't think great yet so so far, I'm enjoying this a lot. It's I like the tight niche, the community style of this of this event I'm sorry. Go back, >> Tio. Go live a little creations that are going on here. Very community already. Kind of be open source projects. Yeah, people talking to each other, a lot of hallway conversations. But it's a kind of a new kind of collaborative model that customers are now getting exposed to write. This is something >> new. I mean, it is. It's new, and I'm finding a lot times where a lot of customers and clients they've heard about it, but they don't know yet. So it's our job to actually get them to adopt to it and and also adapt to it as well. So it's almost like how we have our own like community here. For definite. It's almost how can we take that structure and show it to our clients >> and translation involved Kind of kind of taper down the excitement, maybe, or keeping up questions for you people watching that aren't here. A definite what's that? What's the vibe here? Like, what's some of the cools? Things you've seen and heard are something Well, the keynote was >> great either. Was amazing Kino how they actually showed how, especially with the Iraqi had when Mandy went while I was out there talking about from the small campus to the festival and to an actual >> there's a radio >> that was a great use of incredible, especially with like big Stadium and how John McDonough came out and showed about how there was a fight on the field with you. Yet no one saw it, but yet then, when they went through the actual demonstrate, the actual video were like, Oh, yeah, this's amazing how it's almost like it was like the minority report way. You're already >> exactly Dan. Yes, the data out there, >> all that data and they just machine learning A I just watching people, seeing what they're doing, kind of almost like predicting what they're going to do >> and every little bit, actually, a little bit. I agree with you. I thought they did a great job with that, Especially coming off the heels of Coachella and showing how they can enable Cisco enable developers for social folks to set up secure networks of different sizes and also be able to use in real time machine learning a eye to evaluate what's going on the offensive. And that was a very cool, real world example of what they showed. Leveraging machine learning, identifying. There's there's an issue here. There's an altercation. They surprised at a sports event, right? And deploying those. It has a lot security, many sports events, though I thought it was all that the security was just casually walking up to fight. That's another thing >> that you would slow >> down. But you don't know what >> you're right. >> And it is so many more etiquette rules now at events, whether it's, you know, hate crimes or just, you know, just violent language fights. Also, everyone sees those that write that events. But this actual now, surveillance tech out there. You know, you could tell the guys that how many beers he's had kicks in, You know, >> we're gonna have something where they can actually check out someone like Heat signature. They can't tell how >> much he's going to explode. Is the Red Sox going to blow the lead again? A. Having a good year? Well, you know, they wanted last year Yankee fans, so you would be off the charts now. Philly fans, a whole other story. I don't. Okay. My digress. You've >> got a breakout session. Sorry, John. A lightning session that's tomorrow Any time tomorrow. Tell us the title and what you're going to be talking about. >> Keisha, my title is orchestrate forty five percent. So >> we'LL just read the forty five percent correct Alright, Digging >> again tonight a little >> bit. I have a sly where we was actually Suzy. We actually did a presentation awhile back where she put up a slider, says where she talked about how fifty five percent of partners are creating APS and developing their own naps. So, way of liberty we saw that we were like, OK, what about the other forty five percent? So that's where that the idea came out too. Okay, let's I'll do a talk about how we orchestrate forty, forty five, forty five percent. So entails What I'm doing with that is that we actually have a platform called Consulate. Where there were that platform has the ability to integrate with multiple business processes. So we're connecting. We're integrating with connect allies with Iraqi doing eight about and so that I have it where that there'll be a trigger or Web hook from one my rocky cameras like emotion which will trigger which will create a ticket and connect allies so they can help out some help tasks service desk and then that which will also they get thrown into teams and click on the ticket and then also run commands and grab a snapshot from the camera. The right of the team's six teams >> fell by the Iraqi for a minute because we get a lot of hearing a lot of buzz about Muraki. It's not just wireless. It's not just what you might think it is, it seems to be connected tissue you meant. There's a great demo that added to she's showing around. They are with looking at network configuration. We're obviously to be connecting all of this together. What's your view on this? What's that? >> I for one, I love muraki. I run Rocky at home, so five the viol. Although the wireless is switching cameras and just that, it's it's one. Really. They have, like their own room platform that connects has all their devices connecting into the dashboard, and you could do so much with it that they're actually they're open up Now. The eyes, the web hooks this so much things that you can actually integrate with it. It's it's great, and it's the analytics that you get from it. >> And this is what you're talking about really about bringing these teams together through Webb Hooks for AP, eyes in through Morocco, the connected to direct and then allow the APS to be valuable, cross different groups >> very valuable, but then so that then you don't have it on. Engineer doesn't have have to touch different applications or devices. They get it all from one and from that one application, click and go to where you need to get got. >> So we're only on halfway through Day one of your first up that crate. But it sounds like you've already been exposed to so many things that I could see the wheels turning us without anticipating that you're going to be able to bring back to liberty. And that will really help drive. What you guys doing driving forward toward that customer engagement only, eh? Educate >> well, since it is, you know, it's like half day already on day one. There's still so much to see here. There's so much to see about Coyote. There's a bunch of workshops here about form Iraqi and the AP ice, which I want to join in and see what I can take out of that and bring it back. Um, you know, there's a bunch of stuff get on. So I want to gather all that and just be a sponge and then bring it back to liberty and say, Hey, this is what we can do. How can they fit into our business model? >> Awesome. Well, Tony, thank you so much for stopping by and talking with Jonah me on the program this afternoon. We appreciate it. Best of luck in your lightning session tomorrow as well. >> Thank you so much >> for John Ferrier. I'm Lisa Martin. You're watching us on the Cube. Live from Cisco. Definite great. Twenty nineteen. Thanks for watching. >> No.

Silicon Valley, it's theCUBE covering People First Network. Brought to you by Mayfield. >> Hello, I'm John Furrier here in Palo Alto for an exclusive conversation, CUBE conversation, part of the People First Network with theCUBE and Mayfield fund. I'm here with John Chambers at his house in Palo Alto. John Chambers is the former CEO/Chairman of Cisco Systems, now running J2C, JC2 Ventures. Great to see you, thanks for spending time! >> It's a pleasure to be together again. >> I'm here for two reasons. One, I wanted a conversation about People First and technology waves, but also, I want to talk about your new book, which is exciting, called Connecting the Dots. And it's not your standard business book, where, you know, hey, rah-rah, you know, like a media post these days on the internet; it's some personal stories weaved in with the lessons you've learned through the interactions you've had with many people over the years, so exciting book and I'm looking forward to talking about that. >> Thank you! >> Again, John Chambers, legend, Cisco, 1991 when you joined the company from Wang before that. 400 employees, one product, 70 million in revenue. And when you retired in 2015, not so much retired, 'cos you've got some--. >> I'm working on my next chapter! >> You've got your next chapter (laughs)! 180 acquisitions, 447 billion in revenue, you made 10,000 people millionaires, you created a lot of value, probably one of the biggest inflection points in computer history, the evolution of inter-networking and tying systems together, it was probably one of the biggest waves somewhat before the wave we're on now. So an amazing journey, now you're running JC2 Ventures and investing in game-changing start-ups. So you're not retired? >> No. It was only my next chapter. I made my decision almost 10 years before I left Cisco first, to make for a very smooth transition because it's my family, and out of the 75,000 people, I hired all but 23 of them! And in terms of what I wanted to do next, I really wanted to both give back, create more jobs, get our start-up engine going again in this country, and it's currently broken, and I want to do that on a global basis, in places like France and India as well. So I'm on to my next chapter, but the fun part in this chapter is that I do the things that I love. >> And you've got a great team behind you, but also, you have a great personal network. And I want to get into that, of your personal stories as well as your social network in business and in the community; but one of the things I want to get up front, because I think this is important for this conversation is, you've been very strong. I've seen you present many times over the years, going way back into the 90's. You're eloquent, you're people-oriented, but you have a knack for finding the waves, seeing transitions, you've been through many waves. >> Yes I have, good and bad. >> Good and bad. But one of the big ones, how do you spot those transitions? And what wave are we in now? I mean, talk about the wave that's happening now, it's unprecedented on many levels, but, different, but it's still a wave. >> It is, and outgoing market transitions and often combined with either economic changes or business model changes with technology. And part of the reason that I've been fortunate to be able to identify many of them is I listen to customers very carefully, but also, you're often a product of your prior experiences. Having experienced West Virginia, one of the top states in the US in terms of the chemical industry, uh, during the 40's and 50's and 60's when I was growing up there, and literally more millionaires in West Virginia than there were in the entire Great Britain. We were on top of the world in the chemical industry, and the coal industry, and yet, because we missed transitions, and we should've seen them coming, the state fell a long way, so now we're trying to correct that with some of the start-up activity we'll talk about later. As you see this, and then I went to Boston, 128, we were talking earlier, Wang Laboratories, the mini-computer era, but I was in IBM first out of the central part of the nation, so I watched IBM and Mainframes, and then I watched them miss on going to the mini-computer, and then miss in terms of the internet. So I was able to see the transitions that occurred in Boston, Route 128, where we were the Silicon Valley of the world, and we knew it, and this unusual area out in California called Silicon Valley, we paid almost no attention to, and we didn't realize we failed to make a transition from the mini-computer era to the pc and the internet era. Then I joined Cisco, and saw the internet era. So part of it is, you're a product of your experiences, and know the tremendous pain that occurs, because Boston 128 is nowhere near what it used to be, so there's no entitlement in this new world out of the thousand high-tech companies that I was associated with, including four or five giants in mini-computers, none of them are really in existence today, so it shows you, if you don't identify the transitions, number one, you're going to have an opportunity to benefit by them, but number two, you sure have an opportunity to get hurt by them. >> And you know, these waves also create a lot of wealth and value; not just personal wealth, but community wealth, and Cisco in particular had a good thing going for them, you know, TCP-IP was a defact-- not even a standard, it was a defacto standard at that time, IBM and these kinds of digital equipment corporations dominated the network protocol. Even today, people are still trying to take out Cisco competitively, and they can't because they connected the world. Now the world's connected with digital, it's connected with mobile, so we're kind of seeing this connected wave globally. How do you think about that, now that you've seen the movie at the plumbing levels at Cisco, you now have been traveling the world, we're all connected. >> We are. And it's important to understand that I'm completely arms-length with Cisco, it's their company to run now, and I'm excited about their future. But I'm focused on the next chapter in my life, and while I think about the people at Cisco everyday, I'm into the start-up world now, so how do I think about it now? I think most of the innovation over the next decade will come from start-ups. The majority of the top engineering students, for example, at a Stanford or an MIT or a Polytechnique in France, which is the top engineering school, I think, in Europe, or at the ITs in India, they are all thinking about going to start-ups, which means this is where innovations going to come from. And if you think about a digital world going from the time you and I, we almost recruited you to Cisco, and then we finally did; there's only a thousand devices connected then when Cisco was founded. Today there are about 20 billion devices connected to the internet; in the future, it's going to be 500 billion in a decade, and so this concept of digitalization combined with artificial intelligence, all of a sudden we'll get the right information at the right time to the right person or machine to make the right decision, sounds complex, and it is. And it's ability to do that, I think start-ups are well-positioned to play a key role in, especially in innovation. So while the first stage of the internet, and before that were all dominated by the very large companies, I think you're going to see, in this next phase of digitalization, you're going to see a number of start-ups really emerge, in terms of the innovation leaders, and that's what I'm trying to do with my 16 investments I've made, but also coaching probably another 50 uh, start-ups around the world on a regular basis. >> And the impact of outside Silicon Valley, globally, how do you see that ecosystem developing with the entrepreneurship models that are now globally connected in with these connection points like Silicon Valley? >> It will partially in parallel, partially, it's a new phenomenon. I sold the movie of Boston 128, as I said earlier, and on top of the world, and there is no entitlement. The same thing's true with Cisco, um, sorry, of Silicon Valley today; there's no entitlement for the future, and just because we've led up until this point in time, doesn't mean we will in 10 years, so you can't take anything for granted. What you are seeing, since almost all job creation will be from start-ups, and small companies getting bigger, the large companies in total will probably not add any head count over this next decade because of artificial intelligence and digitization, and so you're now going to see job growth coming from those smaller companies, if these small companies don't get a forum to all 50 states, if they don't get a chance to grow their head count there, and the economic benefits of that, then we're going to leave whole states behind. So I think it's very important that we look at the next wave of innovation, I think there's a very good probability that it will be more inclusive, both by geography, by gender, and all diversity measures, and I'm optimistic about the future, but there are no guarantees, and we'll see how it plays out. >> Let's talk about your next chapter. I was going to wait, but I want to jump while we're on the topic. JC2 is a global start-up, game-changing start-up focus that you have. What is the thesis? What are you looking for, and talk about your mission? >> Well, our mission is very simple. I had a chance to change the world one time with Cisco, and many people, when I said Cisco's going to change the way the world works, lives, learns, and plays by enabling the internet, everybody said nice marketing, but you're a router company. And yet, I think most people would agree, probably more than any other company, we had the leadership role in changing the internet and the direction going on, and now, a chance to do it again, because I think the next wave of innovation will come from the start-ups, and it doesn't come easy. They need coaches, they need strategic partners, they need mentors as much as they need the venture capitalists, so I would think of as this focusing on disruptive start-ups that get very excited in these new areas of technology, ranging from physical and virtual worlds coming together, to artificial intelligence and automation everywhere, to the major capabilities on cyber security across that to the internet of things, so we're trying to say, how do we help these companies grow in skill? But if I was just after financial returns, I'd stay right here in the Valley. I can channel anybody, VC's here that I trust and they trust me, and it would be a better financial return. But I'm after, how do you do this across a number of states, already in seven states, and how do you do it in France and India as role models? >> It's got a lot of purpose. It's not just a financial purpose. I mean, entrepreneurs want to make money, too, but you've made some good money over the years, but this is a mission for you, this is a purpose. >> It is, but you referred to it in your opening comments. When we were at Cisco, I've always believed that the most successful owe an obligation to give back, and we did. We won almost every corporate social responsibility award there was. We won it from the Democrats and the Republicans, from Condie Rice and George Bush and from Hillary Clinton and President Obama. We also, as you said, made 10,000 Cisco employees millionaires just in the first decade. And we tried to give back to society with training programs like Network Academies and trained seven million students. And I think it's very important for the next generation of leaders here in the Valley to be good at giving back. And it's something that I think they owe an obligation to do, and I think we're in danger now of not doing it as well as we should, and for my start-ups, I try to pick young CEOs that understand, they want to make a financial return, and they want to get a great product out of this, but they also want to be fair and giving back to society and make it a win-win, if you will. >> And I think that's key. Mission-driven companies are attracting the best talent, too, these days, because people are more cognizant of that. I want to get into some of your personal stories. You mentioned giving back. And reading your book, your parents have had a big role in your life--. >> Yes, they have. >> And being in West Virginia has had a big role in your life. You mentioned it having a prosperity environment, and then missing that transition. Talk about the story of West Virginia and the role your parents played, because, they were doctors, so they were in the medical field. The combination of those two things, the culture where you were brought up, and your family impacted your career. >> I'm very proud of being from West Virginia, and very proud of the people in West Virginia, and you see it as you travel around the world. All of us who, whether we're in West Virginia, or came out of it, care about the state a great deal. The people are just plain good people, and I think they care about treating people with respect. If I were ever run off a road at night in the middle of the night, I'd want to be in West Virginia, (both laugh) when I go up to knock on that door. And I think it carries through. And also, the image of our state is one that people tend to identify in terms of a area that you like the people. Now what I'm trying to do in West Virginia, and what we just announced since last week, was to take the same model we did on doing acquisitions, 180 of them, and say here's the playbook, the innovation playbook for doing acquisitions better than anyone else, and take the model that we did on country digitization, which we did in Israel and France and India with the very top leaders, with Netanyahu and Shimon Peres in Israel, with Macron in France and with Modi in India, and drove it through, and then do the same thing in terms of how we take the tremendous prosperity and growth that you see in Silicon Valley, and make it more uniform across the country, especially as traditional business won't be adding head count. And while I'd like to tell you the chemical industry will come back to West Virginia and mining industry will come back in terms of job creation, they probably won't, a lot of that will be automated in the future. And so it is the ability to get a generation of start-ups, and do it in a unique way! And the hub of this has to be the university. They have to set the pace. Gordon Gee, the President there, gets this. He's created a start-up mentality across the university. The Dean of the business school, Javier Reyes is going across all of the university, in terms of how you do start-ups together with business school, with engineering, with computer science, with med school, et cetera. And then how do you attract students who will want to really be a part of this, how do you bring in venture capital, how do you get the Governor and the President and the Senate and the Speaker of the House on board? How do you get our two national senators, Shelly Moore Capito and also Joe Manchin, a Democrat and a Republican working together on common goals? And then how do you say here's what's possible, write the press release, be the model for how a country, or a state, comes from behind and that at one time, then a slow faller, how do we leap frog? And before you say it can't be done, that was exactly what people said first about India, when I said India would be the strongest growing economy in the world, and it is today, probably going to grow another seven to 10%. That means you double the per capita of everyone in India, done right, every seven to 10 years. And France being the innovation engine in Europe to place your new business, you and I would have said John, no way, just five years ago, yet it has become the start-up engine for Europe. >> It's interesting, you mentioned playbook, and I always see people try to replicate Silicon Valley. I moved out here from the East Coast in 1999, and it's almost magical here, it's hard to replicate, but you can reproduce some things. One of the common threads, though, is education. The role of education in the ecosystem of these new environments seems to be a key ingredient. Your thoughts about how education's going to play a role in these ecosystems, because education and grit, and entrepreneurial zeal, are kind of the magic formula. >> Well they are in many ways. It's about leadership, it's about the education foundation, it's about getting the best and brightest into your companies, and then having the ability to dream, and role models you can learn from. We were talking about Hewlett-Packard earlier, a great role model of a company that did the original start-up and Lou Platt, who was the President of HP when I came out here, I called him up and said, you don't know me, Lou, I'm with a company you've probably never heard of, and we have 400 people, but I don't know the Valley, can you teach me? And he did, and he met with me every quarter for three years, and then when I said what can I do to repay you back, because at that time, Cisco was on a roll, he said John, do it for the next generation. And so, that's what I'm trying to do, in terms of, you've got to have role models that you can learn from and can help you through this. The education's a huge part. At the core of almost all great start-up engines is a really world-class university. Not just with really smart students, but also with an entrepreneur skill and the ability to really create start-ups. John Hennessey, Stanford did an amazing thing over the last 17 years on how to create that here at Stanford, the best in the world, probably 40% of the companies, when I was with Cisco, we bought were direct or indirect outgrowth of Stanford. Draw a parallel. Mercury just across the way, and this isn't a Stanford/CAL issue, (both laugh) equally great students, very good focus on interdisciplinary activities, but I didn't buy a single company out of there. You did not see the start-ups grow with anywhere near the speed, and that was four times the number of students. This goes back to the educational institution, it has to have a focus on start-ups, it has to say how they drive it through, this is what MIT did in Boston, and then lost it when 128 lost it's opportunity, and this is what we're trying to do at West Virginia. Make a start-up engine where you've got a President, Gordon Gee, who really wants to drive this through, bring the political leaders in the state, and bring the Mountaineers, the global Mountaineers to bare, and then bring financial resources, and then do it differently. So to your point, people try to mimic Silicon Valley, but they do it in silos. What made Silicon Valley go was an ecosystem, an education system, a environment for risk-taking, role models that you could steal people from--. >> And unwritten rules, too. They had these unwritten rules like pay it forward, your experience with Lou Platt, Steve Jobs talks about his relationship with David Packard, and this goes on and on and on. This is an important part. Because I want to just--. >> Debt for good is a big, big issue. Last comment on education, it's important for this country to know, our K through 12 system is broken. We're non-competitive. People talk about STEM, and that's important, but if I were only educating people in three things, entrepreneurship, how to use technology, and artificial intelligence; I would build that into the curriculum where we lose a lot of our diversity, especially among females in the third, fourth, fifth grade, so you haveta really, I think, get people excited about this at a much earlier age. If we can become an innovation engine again, in this country, we are not today. We're not number one in innovation, we're number 11! Imagine that for America? >> I totally agree with ya! And I don't want to rant and waste a lot of time, but my rants are all on Facebook and Twitter. (both laugh) Education's a problem. It's like linear, it's like a slow linear train wreck, in my opinion, but now you have that skills gaps, you mentioned AI. So AI and community are two hot trends right now. I'm going to stay with community for a minute. You mentioned paying it forward. Open source software, these new forms of operational scale, cloud computing, open source software, that all have this ethos of pay it forward; community. And now, community is more important than ever. Not just from the tech world, but you're talking about in West Virginia, now on a global scale. How does the tech industry, how can the tech industry, in your opinion, nurture community at local, regional, global scale? >> This is a tough one John, and I'd probably answer it more carefully if I was still involved directly with Cisco. But the fun thing is, now I represent myself. >> In your own opinion, not Cisco. There's a cultural thing. This is, Silicon Valley has magic here, and community is part of it. >> Yes, well it's more basic than that. I think, basically, we were known for two decades, not just Cisco, but all of the Valley as tech for good, and we gave back to the communities, and we paid it forward all the time, and I use the example of Cisco winning the awards, but so do many of our peers. We're going to Palestine and helping to rebuild Palestine in terms of creating jobs, et cetera. We went in with the Intels of the world, and the Oracles and the other players and HP together, even though at times we might compete. I think today, it's not a given. I think there is a tug of war going on here, in terms of what is the underlying purpose of the Valley. Is it primarily to have major economic benefits, and a little bit of arm's length from the average citizen from government, or is it do well financially, but also do very well in giving back and making it inclusive. That tug of war is not a given. When you travel throughout the US, today, or around the world, there are almost as many people that view tech for bad as they do tech for good, so I think it's going to be interesting to watch how this plays out. And I do think there are almost competing forces here in the Valley about which way should that go and why. The good news is, I think we'll eventually get it right. The bad news is, it's 50/50 right now. >> Let's talk about the skill gap. A lot of leaders in companies right now are looking at a work force that needs to be leveled up, and as new jobs are coming online that haven't been trained for, these openings they don't have skills for because they haven't been taught. AI is one example, IOT you mentioned a few of those. How do great leaders, proactively and reactively, too, get the skills gaps closed? What strategies can you do, what's the playbook there? >> Well two separate issues. How do they get it closed, in terms of their employees, and second issue, how do we train dramatically better than we've done before? Let's go to the first one. In terms of the companies, I think that your ability to track the millennials, the young people, is based upon your vision of doing more than quote just making a profit, and you want to be an exciting place to work with a great culture, and part of that culture should be giving back. Having said that, however, the majority of the young people today, and I'm talking about the tops out of the key engineering schools, et cetera, they want to go to start-ups. So what you're going to see is, how well established companies work with start-ups, in a unique partnership, is going to be one of the textbook opportunities for the future, because most companies, just like they didn't know how to acquire tech companies and most of all tech acquisitions failed, even through today. We wrote the textbook on how to do it differently. I think how these companies work with start-ups and how they create a strategic relationship with a company they know has at least a 50/50 probability of going out of business. And how do you create that working relationship so that you can tap into these young innovative ideas and partnerships, and so, what you see with the Spark Cognition, 200 people out of Texas, brilliant, brilliant CEO there in terms of what he is focused on, partnering with Boeing in that 50/50 joint venture, 50/50 joint venture to do the next FAA architecture for unmanned aircraft in this country. So you're going to see these companies relate to these start-ups in ways they haven't done before. >> Partnership and collaboration and acquisitions are still rampant on the horizon, certainly as a success for you. Recently in the tech industry we're seeing big acquisitions, Dell, EMC, IBM bought Red Hat, and there's some software ones out there. One was just going public and got bought, just recently, by SAP, how do you do the acqui-- you've done 180 of them? How do you do them successfully without losing the innovation and losing the people before they invest and leave; and this is a key dynamic, how do companies maintain innovation in an era of collaboration, partnerships, and enmity? >> I had that discussion this morning at Techonomy with David Kirkpatrick, and David said how do you do this. And then as I walked out of the room, I had a chance to talk with other people and one of them from one of the very largest technology companies said, John, we've watched you do this again and again; we assumed that when we acquired a company, we'd get them to adjust to our culture and it almost never worked, and we lost the people at a tremendously fast pace, especially after their lock-in of 18 to 24 months came up. We did the reverse. What we did was develop a replicatible innovation playbook, and I talk about it in that book, but we did this for almost everything we did at Cisco, and I would've originally called that, bureaucracy, John. (both laugh) I would've said that's what slow companies do. And actually, if done right, allows you to move with tremendous speed and agility, and so we'd outline what we'd look for in terms of strategy and vision; if our cultures weren't the same, we didn't acquire them. And if we couldn't keep the people, to generate the next generation of product, that was a bad financial decision for us, as well. So our attrition rate averaged probably about 5% or over while I was at Cisco for 20 years. Our voluntary attrition rate of our acquired companies, which normally runs 20% in these companies, we had about four. So we kept the people, we got the next generation product out, and we went in with that attitude in terms of you're acquiring to be able to keep the people and make them a part of your family and culture. And I realize that that might sound corny today, but I disagree. I think to attract people, to get them to stay at your company, it is like a family, it is like how you succeed and occasionally lose together, and how you build that family attitude under every employee, spouse, or their children that was life-threatening, and we were there for them in the ways that others were not. So you're there when your employees have a crisis, or your customer does, and that's how you form trust in relationships. >> And here's the question, what does People First mean to you? >> Well people first is our customer first. It means your action and everything you do puts your customers and your people first, that's what we did at Cisco. Any customer you would talk to, almost every customer I've ever met in my life would do business with us again, or with me again, because your currency in today's world is trust, track record, and relationships, and we built that very deep. Same thing with the employees. I still get many, many notes from people we helped 10 or 15 years ago; here's the picture of my child that you all helped make a difference in, Cisco and John, and you were there for us when we needed you most. And then in customers. It surprises you, when you help them through a crisis, they remember that more than when you helped them be successful, and they're there for you. >> Talk about failure and successes. You talk about this in the book. This is part of entrepreneurship, you can't succeed without failures. Handling failures is just as important as handling successes, your thoughts on people should think about that from a mindset standpoint? >> Well, you know, what's fun is those of you who are parents, or who will be parents in the future, when your child scores a goal in soccer or makes a good grade on a test, you're proud for them, but that isn't what worries you. What worries you is when they have their inevitable setbacks, everybody has that in life. How do you learn to deal with them? How do you understand how much were self-inflicted and how much of it was done by other causes, and how they navigate through that determines who they are. Point back to the West Virginia roots, I'm dyslexic, which means that I read backwards. Some people in early grade school thought I might not even graduate from high school much less go to college. My parents were doctors, they got it, but how I handled that was key. And while I write in the book about our successes, I spend as much time on when disaster strikes, how you handle that determines who you are in the future. Jack Welch told me in the 90's, he said John, you have a very good company, and I said Jack, you're good at teaching me something there, we're about to become the most valuable company in the world, we've won all of the leadership awards and everything else, what does it take to have a great company? He said a near-death experience. At the time I didn't understand it. At the end of 2001 after the dot com bubble, he called me up, he said, you now have a great company, I said Jack, it doesn't feel like it. Our stock price is down dramatically, people are questioning can I even run the company now, many of the people who were so positive turned very tough and--. >> How did you handle that? How did you personally handle that, 'cos--. >> It's a part of leadership. It's easy to be a leader when everything goes well, it's how you handle when things are tough, and leadership is lonely, you're by yourself. No matter how many friends you have around you, it's about leadership, and so you'd lead it through it. So 2001, took a real hard look, we made the mistake of focusing, me, on the numbers, and my numbers in the first week of December were growing at 70% year over year. We'd never had anything negative to speak of, much less below even 30% growth, and by the middle of January, we were -30%. And so you have to be realistic, how much was self-inflicted, how much the market, I felt the majority of it was market-inflicted, I said at the time it's a hundred year flood. I said to the employees, here's how we're going to go forward, we need to bring our head count back in line to a new reality, and we did it in 51 days. And then you paint the picture from the very beginning of what you look like as you recover and in the future and why your employees want to stay here, your customers stay with you and your shareholders. It wiped out most of our competitors. Jack Welch said, John, this is probably your best leadership year ever, and I said Jack, you're the only one that's going to say that. He said probably, and he has been. >> And you've got the scar tissue to prove it. And I love this story. >> But you're a product of your scars. And do you learn how to deal with them? >> Yeah, and how you-- and be proud of them, it's what, who you are. >> I don't know if proud's the right word. >> Well, badge of honor. (both laugh) >> Red badge of honor, they're painful! >> Just don't do it again twice, right? >> We still make the same mistake twice, but at the same time when I teach all these start-ups, I expect you to make mistakes. If you don't make mistakes, you're not taking enough risk. And while people might've, might say John, one of your criticisms is that you spread yourself a little bit too thin in the company at times, and you were too aggressive. After thinking about it, I respectfully disagree. If I had to do it over, I'd be even bolder, and more aggressive, and take more risks, and I would dream bigger dreams. With these start-ups, that's what I'm teaching them, that's what I'm doing myself. >> And you know, this is such a big point, because the risk is key. Managing risk is actually, you want to be as risky as possible, just don't cut an artery, you know, do the right things. But in your book, you mention this about how you identify transitions, but also you made the reference to your parents again. This is, I think, important to bring up, because we have an expression in our company: let's put the patient on the table and let's look at the problem. Solving the problems and not going out of business at that time, but your competitors did, you had to look at this holistically, and in the book, you mentioned that experience your parents taught you, being from West Virginia, that it changed how you do problem solving. Can you share what that, with that in conscience? >> Well, both parents were doctors, and the good news is, you got a lot of help, the bad news is, you didn't get a lot of self 'cos they'd fix you. But they always taught me to focus on the real, underlying issue, to your point. What is the real issue, not what the symptom is, the temperature, or something else. And then you want to determine how much of that was self-inflicted, and how much of it was market, and if your strategy's working before, continue, if your strategy was starting to get long in the tooth, how do you change it, and then you got to have the courage to reinvent yourself again and again. And so they taught me how to deal with that. I start off the book by talking about how I almost drowned at six years of age, and as I got pulled down through the rapids, I could still see my dad in my mind today running down the side of the river yelling hold on to the fishing pole. It was an ugly fishing pole. Might've cost $5. But he was concerned about the fishing pole, so therefore I obviously couldn't be drowning so I focused both hands on the fishing pole and as I poked my head above water, I could still see him running down. He got way down river, swam out, pulled me in, set me on the side, and taught me about how you deal when you find yourself with major setbacks. How do you not panic, how do you not try to swim against the tide or the current, how you be realistic of the situation that you're in, work your way to the side, and then you know what he did? He put me right back in the rapids and let me do it myself. And taught me how to deal with it. Dad taught me the business picture and how you deal with challenges, Mom, uh, who was internal medicine, psychiatry, taught me the emotional IQ side of the house, in terms of how you connect with people, and I believe, this whole chapter, I build relationships for life. And I really mean it. I think your currency is trust, relationships, and track record. >> And having that holistic picture to pull back and understand what to focus on, and this is a challenge for entrepreneurs. You're now dealing with a lot of entrepreneurs and coaching them; a lot of times they get caught in the forest and miss the trees, right? Or have board meetings or have, worry about the wrong metrics, or hey, I got to get financing. How should an entrepreneur, or even a business leader, let's talk about entrepreneur first and then business leader, handle their advisors, their investors, how do they manage that, how do they tap into that? A lot of people say, ah, they don't add much value, I just need money. This is important, because this could save them, this could be the pole for them. >> It could, or it could also be the pole that causes the tent to collapse (both laugh). So I think the first thing when you advise young entrepreneurs, is realize you're an advisor, not a part of management. And I only take young entrepreneurs who want to be coached. And as I advise them, I say all I'm asking is that you listen to my thoughts and then you make the decision, and I'll support you either way you go, once you've listened to the trade-offs. And I think you want to very quickly realize where they are in vision and strategy, and where they are on building the right team and evolving the team and changing the team, where they are in culture, and where they are on their communication skills because communication skills were important to me, they might not have been to Jack Welch, the generation in front of me, but they were extremely important to ours. And today, your communication mismatch on social media could cost your company a billion dollars. If you're not good at listening, if you're not good at communicating with people and painting the picture, you've got a problem. So how do you teach that to the young players? Then most importantly, regardless of whether you're in a big company or a small company, public or private sector, you know what you know and know what you don't. Many people who, especially if they're really good in one area, assume that carries over to others, and assume they'll be equally as good in the others, that's huge mistake; it's like an engineer hiring a good sales lead, very rarely does it happen. They recruit business development people who appeals to an engineer, not the customer. (both laugh) So, know what you know, know what you don't. For those things you don't know, surround yourself with those people in your leadership team and with your advisors to help you navigate through that. And I had, during my career, through three companies, I always had a number of advisors, formal and informal, that I went to and still go to today. Some of them were very notable players, like our President Clinton or President Bush, Shimon Peres, Henry Kissinger, or names that were just really technical leads within companies, or people that really understood PR like Thomas Freedman out of the New York Times, or things of that. >> You always love being in the trenches. I noticed that in Cisco as an observer. But now that you're in start-ups, it's even more trenches deeper (laughs) and you've got to be seeing the playing field, so I got to ask ya a personal question. How do you look back at the tech trends that's happening right now, globally, both political, regulatory technology, what advice would you give your 23-year-old self if you were breaking into the business, you were at Wang and you were going to make your move; in this world today, what's going on, what would you be doing? >> Well the first thing on the tech trend is, don't get too short-term focused. Picture the ones that are longer term, what we refer to as digitization, artificial intelligence, et cetera. If I were 23 years old, or better yet, 19 years old, and were two years through college and thinking what did I want to do in college and then on to MBA school and perhaps beyond that, legal degree if I'd followed the prior path. I would focus on entrepreneurship and really understand it in a lot more detail. I learned it over 40 years in the business. And I learned it from my dad and my mom, but also from the companies I went into before. I would focus on entrepreneurship, I'd focus on technology that enables entrepreneurship, I would probably focus on what artificial intelligence can do for that and that's what we're doing at West Virginia, to your point earlier. And then I would think about security across that. If you want really uh, job security and creativity for the future, if you're a really good entrepreneur, with artificial intelligence capability, and security capability, you're going to be a very desired resource. >> So, we saw you, obviously networking is a big part of it. You got to be networking with other people and in the industry, would you be hosting meet ups? Young John Chambers right now, tech meet ups, would you be at conferences, would you be writing code, would you be doing a start-up? >> Well, if we were talking about me advising them? >> No, you're 23-years-old right now. >> No, I'd just be fooling around. No, I'd be in MBA school and I'd be forming my own company. (both laugh) And I would be listening to customers. I think it's important to meet with your peers, but while I developed strong relationships in the high-tech industry, I spent the majority of time with my customers and with our employees. And so, I think at that age, my advice to people is there was only one Steve Jobs. He just somehow knew what to build and how to build it. And when you think about where they were, it still took him seven years (laughs). I would say, really get close to your customers, don't get too far away; if there's one golden rule that a start-up ought to think about, it's learning and staying close to your customers. There too, understand your differentiation and your strategy. Well John, thanks so much. And the book, Connecting the Dots, great read, it's again, not a business book in the sense of boring, a lot of personal stories, a lot of great lessons and thanks so much for giving the time for our conversation. >> John, it was my pleasure. Great to see you again. >> I'm John Furrier here with the People First interview on theCUBE, co-created content with Mayfield. Thanks for watching! (upbeat electronic music)

(upbeat violin music) >> Hello and welcome to Special CUBE conversations. I'm John Furrier here at theCUBE Studios in Palo Alto. I'm joined with Jeff Jonas who's the co-founder and CEO of a stealth start-up called Senzing. He won't talk about it. I try to wrestle him to the ground to get information launching later. You're in town. Thanks for swinging by. Former IBM fellow, CUBE alumni. Some great videos. Check out Jeff Jonas, search Jeff Jonas theCUBE on Google and check out the videos. We've got great conversations over the years. Last time we saw you at your IBM event, riffing on, you know, the context of data. You're written and recognized by National Geographic as one of the major, the innovator in data space, which is a big honor, congratulations. >> Thank you. >> I appreciate it. Couldn't happen to a better person. >> Lucky, lucky. >> So what's going on? Tell us about the new startup. >> You know, I had a great run at IBM. They were really good to me when they bought my company. They were good to me for 11 and a half years. I think it was the longest-standing founder from an acquired company that IBM ever had. Great run and then they were good to me on an exit. I proposed something last, in 2016 in June. I kind of like it was a red pill, blue pill Matrix kind of move. I went hey, I got some ideas, but it's time to go. I've got to get back to my entrepreneurial spirit. Blue pill, red pill and they were like yeah, but you're a fellow. Go to research and live happily ever after. >> You've made it, you're a fellow. Why would you do anything? Why would you be a lowly entrepreneur? >> And it truly is, of all the things I've done, that I'm like wow, that is crazy to happen in my life. That's actually the single highest. It's over a few other things. >> John: It's a big deal. >> It is a huge deal, so. >> But you're an entrepreneur. You're scratching the itch. So what happened with the blue pill, red pill? >> So one of the options was hey, I've been working on this thing here at IBM called G2. It was my next generation entity engine. Figures out who's who in your data, matches identities. We've been working on it for years, I think nine years and I just said, I'd like to go build a company around that and I'll give you a rev share. You'll make more money than if I stayed. They were like, oh that was a great idea. Let's have a partnership, let's do that. So August of 2016, I spun out the source code. >> John: Who was the main executive at that point? Was it -- >> It was Bob Picciano. >> Bob Picciano. >> Yeah. >> He's very entrepreneurial-friendly. >> Yeah and he had to get in alignment across a whole bunch of IBM to make this happen. Anyways, I was really fortunate and the partnership that I had with IBM even to this day is just extraordinary. >> So did they fund you as well? >> Fund, no. I funded it myself for the first five or six months. I took two, money from two private investors that I've known a long time. Really smart, strategic money. Very active in my business. >> John: And you know them. >> Yeah, I've known them for a long time. One of them was a customer of mine. One I sat on the board with. It was just great. >> So the inner circle, they're in the boat. You've got some good people that you know. >> Yeah. Some people are like how do you manage your investors and I'm like, we don't even talk like that. >> We hang out. >> Yeah, we hang out. They manage me. Like, I go to them and, help me. >> That's how it should be, right? >> It's different. >> You don't have VCs on your board? No, but that's the formula. That's what you want. Entrepreneurs these days get so star-struck on having investors, but it's hard work. You want to get people that you trust and you like. >> Yeah, I learned that in my first company. We had two rounds of venture capitals in my first company. I learned a bunch of things, but they were great investors. It was a great relationship. I learned about VC because I had my own money in four VC funds. I've been able to fund four, five companies, but with all of that in mind, I have a really clean cap table. But anyway, we went off to the races since, since August of 2015. >> John: So that's when you left IBM, last time we checked. >> Yeah. >> Okay. >> And then I went into stealth mode. We've been collecting real customers. We've been iterating on the product. Our calling, if you will. You know, when I left IBM, I sat there with this thing called G2 and I'm like, this is the only thing that makes my team and I special is how to figure out in data, especially big data, who is the same as who across cultures, across languages and scripts and doing it where you don't need a data scientist. You don't need an expert to tune it and I did a survey of about 50 companies out there that are out there in the same business of selling entity resolution and almost all of them say call for a quote because it's all so hard and really, it's hard to find any software that's world class that's less than a quarter of a million and you're going to spend a million and so what we've been doing is working on making it so easy to consume that-- >> You're moving it down from a high ticket item, probably bolted on a ton of professional services to a much more turn key democratized-- >> Yeah, totally. You're absolutely right. Like we don't even have professional services. We're like download it, try it on a subscription license. You pay monthly, we send them the code so no data flows to us and when I, this is kind of funny and it's very private. Oh, I know I'm saying this on your cameras and all, but every team meeting, you know, our mission is smarter entity resolution for everyone everywhere and then I tell my team, what's going to make our company amazing is no one calls us. Everyone loves us and we've been really working on iterating on that. You know, any time somebody has any reason they have to call, that's not a moment of joy. >> You're launching when? This month, right? >> We are launching. >> 'cause there's nothing on the web. >> Yeah, yeah, yeah. Senzing.com is on the web, but at right this split second, it's a holding site. There will be a better, the real site's coming out very, very soon like in the quarter of the next week. >> Total stealth dark mode. >> We're in really dark mode. Although we've been collecting, again, customers and great logos. IBM's a customer. They license G2 from us. >> And so they didn't put money in. >> No, they did not put money in. I put my own money in. >> I guess they bumped my company and then I put my money in so in some sense, you can say if you followed the money. >> Do they own any? >> No, they don't own any of the company. >> But there's a business partnership. >> Absolutely. >> Okay, got it. >> And it's an incredible relationship. We have all kinds of interesting things we're doing with IBM. It's almost as if I've not left. They just don't give me a paycheck anymore. >> Which is why they're like, that guy's a fellow. Why is he doing it? He's going to go start a company? Why would he do that? 'cause you're an entrepreneur. That's why. Well, that's awesome. What are you working on at IBM with the G2 and I know you don't want to talk about the product and I respect that even though I try to dig at it. But what I really want to do 'cause you're going to launch in a couple weeks anyway. Let's get the aperture of what you're looking at. What market are you looking at? What problems out there, you mentioned entity is one piece. What's the key thing that you're looking at? >> You know, the key thing is that organizations have all of this data in all of these piles and they don't, they're having difficulty knowing about the same person at the same company. And I'll give you one of my favorite use cases that's, you know, G2's been in production already for many years, maybe my favorite deployment to date was deployed in 2012? Yeah, 2012, five years ago, six, for a company called ERIC. It's a non-profit. It's run by states. 22 states put their data in there on voter registration data, and it's used to improve the quality of election roles and it's got my privacy by design features baked into it and I'm just so damn proud of this thing. You know, the Democrats like it, the Republicans like it. I share the privacy community. >> No calls and everyone loves you. >> Yeah, no, that's the truth and this system, it's got a quarter of a billion records of about 100 million people and they have one person in IT that runs the entire IT department including G2. Like this is unheard of. So that's been in production for five years. But the range of companies that are having a challenge with who is who in their data is just everywhere. >> And give me an example of what that means. I'm trying to crop that, who is who like across multiple databases or? >> Yeah, I'll give you an example. See, in the voter registration system, you have somebody's registered in two different states, but it's the same person. You've got to get the data together to realize that somebody's registered in two states and that's because they moved. If you've ever moved between states, you may have forgotten to unregister. Most people do. >> Every person does. >> That's illegal. >> Like 1% would actually go through the motions. >> Lawbreaker. >> Tell the state I moved. >> Right. >> As far as the jury knows, I'm getting a new jersey. What's happening? >> Exactly, so you've got these two piles of data, but we combine it, you see that these two are the same and they're registered in both. So now they have to go back to somebody and say do you want to be registered to vote? But now I'll flip and give you an example of companies. There's a, one of our customers does supply chain risk. They take a vendor, some of the biggest global brands, and in their vendor list of all these customers across the world, there's duplicates in there, and then of course these companies reach the same manufacturers and there's duplicates across these lists but this is messy data. Then they scrape the web and look for toxic spills, child labor and other derogatory data about manufacturers in China, the Philippines, India and this is super messy and then they extract the data off the web, with just a crappy as you can see. We, they got our code on a Tuesday. They didn't call us until Thursday and when they called us Thursday they just said, and what they did was they combined all the data so they can go back to a global brand and say hey, this manufacturer is going to cause you risk to your reputation. So they're resolving who is who. >> You're untangling a lot of messy data. >> Yeah. >> And making it insightful. >> We get insights and we got a, this is an example. They got this offer on Tuesday without a call. We got a call on Thursday and said we canceled all of our internal work to try to mess with all this. We're just using your stuff, it's done. And the last we heard from them, they just went, the quality of your matching you're doing, without any tuning or training, it's a special kind of real-time machine learning that we invented, no training, no tuning and they went, the results it's getting are human-quality. >> So how, obviously you don't want to talk about price points, but it's affordable, it sounds like. It sounds like you're mission-driven on this thing so it's not like getting, you've already made some good dough as an entrepreneur. You're not afraid to make more money, but this is a mission-driven opportunity. >> So many organizations are struggling with this. We are going to make it affordable to the smallest companies and I can't quite tell you the price point. >> It's okay, we're at theCUBE. >> Think order of magnitude life in any other option. >> Can you take care of us? >> Oh, I could hook you up. >> We have duplicates all over the place. >> We'll give it to you and you'll get a towel set too. >> That would be great. Question for you. What's your take on crypto block chain because you mentioned, you know, your customer's a great part of anti-money laundering, big part of, you mentioned privacy baked into by design there. This is now a phenomenon. You looked at China with WeChat. They're making real names, real identities be part of that system. So more and more of this potential attention, public data's going to be out there. What's on your take on, you know, your customer and some of these trends that are involved in this? >> You know, on block chain, what it really is, it's calling, I mean I've seen a lot of people use the term block chain around that just ain't it. 'cause it's got a lot of buzz. >> Buzzword. >> But the reality is, it is a tamper-resistance ledger and I've been writing about immutable audit logs and tamper-resistance ledgers in my privacy by design work before block chain came out, which is really distributed form. The value of it to the kinds of work that we do is a tamper-resistance log allows you to connect it to software so that when say, somebody searches for something, you can record it in a tamper-resistance way and why do you want to do that? Well if you've created an index in some central data, you want to make sure it's not being abused. You want to make sure that the person who's searching is not searching out their neighbor or their daughter's new boyfriend. That would be an abuse, right? >> Yeah, yeah. >> Right. So a tamper-resistance auto log would be a great place to put that. That would be a natural thing to do with block chain. >> Awesome. So you got the launch coming. How are you doing and are you doing any of the marathons and triathlons? What are you doing? What's the latest? >> Since I was last on your show here, I became one of three people to do every Iron Man on the world, every Iron Man triathlon. There's one person in Canada. There's one person in Mexico and I'm representing America. >> You're the American representation. All triathlons. >> You know, if you go to the IronMan.com webpage, there's a list of races around the world and I'm one of three that can just look at every single race and say yes, yes, yes. >> Your favorite. >> Austria. >> Why? >> It's beautiful, it's a great course. It was well-run. I had a good time. >> Beautiful weather and people. >> And your worst? The one where you had your bike on a plane and you lost your luggage? >> Oh, I had no, I had a really really dark time this last year at the race in South Korea. And this is how bad it was. It's the only race where I walked across the finish and I sat in the bath tub. This is embarrassing, okay? I sat in this bath tub with the shower thing that you have to hand-hold over my head and I was trying to cry 'cause I was so defeated, but I was too dehydrated to even cry. The level of failure. >> It just knocked you down. >> When you can't even cry. >> Well you know you went from IBM Fellow to lowly entrepreneur, how's it feel? I mean you're back, rolling your sleeves up, getting down and dirty. Fun, having a blast? >> I really love being a benevolent dictator. >> John: How many people on the team? >> We're like about 16 if you count people that are full time or half time or better. I have a few people who are half time or better so yeah, about 16. >> Sounds like fun. >> Great fun. >> Great, Jeff Jonas. We'll be looking forward to your launch Senzing.com. S-E-N-Z-I-N-G.com. Former IBMer, great to see you and we'll keep you in touch. And where are you going to be headquartered out of? What's the location? >> Venice Beach, California, where I live. Although my team is scattered all over the country. We also are licensed in Singapore and we are hoping to launch Senzing Lab's RND activities out of Singapore. >> Alright, so we'll pop down to LA to check you out when you're up and running. Okay, Jeff Jonas stopping by theCUBE here on a great Thought Leader Thursday. I'm John Furrier. Every Thursday, we do the Thought Leader interviews with friends, colleagues, CUBE alumni and more. Always look up to great people. Have to be a thought leader, have to have original content and be an innovator. Thanks for watching. (upbeat violin music)

>> Narrator: The Wynn resort in Las Vegas It's theCUBE. Covering .NEXT conference 2016 brought to you by Nutanix. Now here are your hosts, Dave Vellante and Stu Miniman. >> Welcome back everybody. Professor Deepak Malhotra here. He's with the Harvard Business school and author of Negotiating the Impossible: How to Break Deadlocks and Resolve Ugly Conflicts. Parenthetical without money or muscle end parenthetical. Deepak, welcome to theCUBE, great to see you. Thanks for having me here. Happy to be here. So what do you do in here? Well among the other things that I do with my time, I happen to be on the board of advisors for Nutanix. And I've been working with Nutanix for the last, a little over two years on various aspects of negotiation, deal making, training, etcetera. And so I attend a few of their conferences a few of the sessions. I talk at a few of their conferences as well. So that's what brings me here. >> So it's somewhat odd, right to have a negotiations expert come and talk to customers about negotiations. But I guess the angle would be if you're stuck in sort of a legacy world. You need to negotiate your way out is that. >> Well there's a couple of things going on there, right. So under one hand I think it shows a little bit about Nutanix's perspective. That it isn't a zero sum game. It's not we're going to train the Nutanix people so they can get an advantage over customers. I think the company really is focused on creating as much value as possible for the end user. And when you take that mind set it actually makes sense to be inclusive. And bring everybody in the ecosystem into the room. So it's not just, "Hey Professor Malhotra can you train our sales people?" It's you know we want to share your ideas with everybody. And I think that's really a good sign when a company is willing to do that. The second thing is as you just eluded to, a lot of the folks that are coming here and a lot of the people that are customers were thinking about moving in the direction of Nutanix. Or have bought into the idea. They still may need to sell it internally. They still may need to negotiate internally how do we change our organization or how do we move our organization from what its been doing to what it wants to be doing or it should be doing. And they're also many of the same skills can be useful. So why not educate them about some of the things they might not have thought about yet. >> So let's talk about your book a little bit. The premise. I guess I told you I haven't read it yet but I do have it. In the book you talked about a three thousand year old Treaty of Kadesh. And things that we can learn from three thousand years ago. Give us the basics and the premise. >> So this was. The books starts out with this story of the Treaty of Kadesh which I don't think is something that many business books start out talking about. Certainly, I hadn't seen it before I started researching it. And one of the interesting thing that happens is that there's a lesson embedded in the story of the Treaty of Kadesh that I think is as relevant today in negotiations of just about every kind in the business world and outside that, that's worth telling. And the basic story goes as follows. The Treaty of Kadesh is the most ancient peace treaty known to man kind. As far as we know it's as old a peace treaty as we have evidence of. And it was between the Egyptians and the Hittites. And these two parties were at war. And at some point they must of decided enough of this we need to put an end to this. There's too many cost internally and externally. Too many other threats. We need to find a way to resolve this kind of conflict. What often happens in these situations is that nobody wants to look weak. Nobody wants to be the one asking for peace because that might just embolden the other side. So what ends up happening is that somehow they overcome these hesitations. They reach this agreement. Now what's interesting is that we actually have access to both language's version of the treaty. So we have the Arcadian and the hieroglyphics. The hieroglyphics being the Egyptian version and the Arcadian being the one from the Hittites. And if you were to read both of these or if you were to first learn how to read these and then to read both of these. What you find is as you'd expect, they have a lot of the kinds of things that you would normally expect in a peace treaty. You know exchanging prisoners of war. Mutual assistance packs and things like this. And they're basically identical as they should be because they're the same peace treaty. But there is one difference. When you compare the two peace treaties the one difference that sort of stands out is that in the Egyptian version it says it's the Hittites who came asking for peace. And in the Hittite version it says it's the Egyptians who came asking for peace. And what it goes to show I think is that no matter how far back you go this need for every side to declare victory at the end of a negotiation at the end of a conflict. That need for every side to declare victory is as old as human beings themselves. When you understand that. I think it actually changes the way in which you try and negotiate these deals. How you think about what stands in the way of getting the deal done. Sometimes it's not the substance of the deal. You're already proposing something that's good enough. You're already have something on the table that's rich enough, valuable enough. They should say yes. But they might be other reasons they can't say yes. For example they might lose face. Or they may look bad. And when you recognize that I think you come at it a different way. >> Looking at your research. One of things you focus on is trust. And one of the challenges we have in technology is you know, people are entrenched with the way they do things. They're not likely to you know be first or go there. We've now got thousands of people using Nutanix but you know. How does Nutanix or others that are new get a proper seat at the table and be able to be part of a discussion that you know when you've got (mumbles) in there and the old ways of doing things. >> You know the way I see it. You have to get the economics right and you have to get the psychology right. The economics is you have to have a good product. It needs to be price appropriate. You need to be bringing value to the table. And be pricing based on that value proposition. So that's sort of basic business stuff. The problem is as I mentioned earlier. You may have the right product. You may have something that people, quote should be using. It is better than the alternative. But they might be these psychological hurdles that you need to get over. A prominent one being what you just eluded to which is when nobody else is doing it, nobody feels the urgency to do it. If you get the sense that you know there's not a mass of folks running after your product. They sort of feel like, well maybe that means something. Maybe it means it's not a big deal. Maybe it means it's not so urgent. Maybe it's not that good of a product. So the early hurdles that companies like these face are really big ones. You don't have a long list of customers that you can use to prove to other people that this is the way you should be going. There's always a risk that somebodies going to take a bet on this and if something goes wrong. It's sort of the old nobody lost their job buying IBM kind of mentality. And so as a negotiator and as a company that's starting out as an early stage company, especially in technology where you're doing something disruptive, you need to start thinking a little bit about how do we get them over that. How do we get them to start understanding that you know what. Here is a list of customers that are using it. And here's the testimonials, etcetera. You think about the pricing. The most common thing that happens when you walk into the room with a new disruptive technology is that the person on the other side says, "Are you crazy? "You're charging ten times what your competitor is charging. "You know you're sitting here telling me "to pay x. "If I do nothing I have to pay zero." Alright. "Nobody pays this kind of money for this kind of thing." That is a very common response sales people get when they are in an environment like this. And one of the things I advise people to do in that situation. Is to make sure they don't make the worst mistake a sales person can make in a moment where somebody says, "You're price is ten x what everybody else "is charging. "Nobody pays this much." The worst mistake a sales person can make is to apologize for the price being too high. Now they don't always do it by saying, "Oh my god I'm so sorry." But they seem apologetic. You know they're very quick to say, "Oh yeah I know it's high." >> "Let's see if we can do something." >> "I'm sure we can work something out. "But yeah you know I know it's a lot of money." The moment you go in that direction what you're basically doing is you're giving the other side a license to haggle with you. 'Cause what you're telling them is even you don't think the price is appropriate. A better response in a situation like this is for the sales person to say, "Listen I think the question you're asking me is, "how is it that despite our price being ten x "what some other people are charging, "we have a long list of people wanting to buy our product. "What kind of value must we be bringing to the table "for so many people wanting to buy this product? "Now I'm happy to talk about that value "because at the end of the day we all know nobody's "going to pay more for something than it's worth. "Nobody would do that, you're not going to do that. "So why don't we figure out what it's worth "and then you can make the right decision." And what you're doing there is you're shifting the conversion from price to value. You're shifting the frame of this conversation from how much am I having to pay and what's the cost to me to what is the value proposition. >> Stu's laughing. I mean your price is too high is the best sales objection ever. Right, you love to hear that as a sales person. Much better than your product sucks. (chuckles) Now the answer of this question is probably it depends. But when you advise your clients and your friends. When I go into a negotiation am I trying to get the best deal or am I trying to find common ground and get a win-win? >> Actually I don't think it depends. I think. (exhales loudly) Well I would. I would articulate the question slightly differently. Because in my experience it is possible to get a great deal and a great relationship. It's also possible to get neither. And so what you're trying to do is you're trying to optimize on both. What's interesting is that very often we assume it's a zero sum game enough. That the only way for me to get a good deal is for me to sacrifice the relationship in some way. That's not how it works in most sort of richer context, more complicated deal scenarios. Because what people evaluate when they walk away from the table isn't just did I get a quote, good economic deal. When people think back and say, "Do I want to work with this person again? "Do I like this person? "Did I get a good deal?" Often what they're thinking about is not so much of the substance of what they got. What's in the agreement. But the process they went through. For example. You know did the negotiation go as long as should of or did it drag on too long or end too abruptly? Was my voice heard? Did both sides move away from their opening positions? Did the person haggle with me on every little thing, even though they knew and I knew it's not a big deal to them and is a big deal to me? Those sort of process elements if you navigate the process more effectively you can often get to a point where you get the deal that you think is right for you and you get a relationship that both sides can walk away feeling good about. And from my perspective you know what does depend in, on it. It depends on the situation is what kind of feeling do you want them to have walking away. You don't always need to have them love you. But at the very least they should respect you. Right? And I think it's perfectly fair even in a very contentious negotiation to keep as one of your objectives. You know when the deal ends I want them to be able to walk away saying, "You know what, I maybe didn't agree with this person. "It didn't go exactly the way I wanted it to go. "But you know I can respect this person "for the way they handled the situation. "And if I were them I hope I would do it the same way." >> So I wonder. If I look at the society as a whole, it seems as if we kind of retreated to our sides and I find that lots of people aren't open for debate. They're intractable in what's going on. How do I get beyond that? >> How do we change society, is that the question? >> Stu: Yeah. >> How much time do we have? >> Am I wrong. (laughs) Is it only ten percent of the people that are intractable or are most people reasonable? >> So I think what happens is, there's a few interesting dynamics. Now I wouldn't have the precise numbers. What I can say is that it is certainly the case that even a minority of people being in those entrenched positions, they get a lot more of the media. They get a lot more of the attention. They tend to be louder, etcetera. And they can often drive our sense of what's actually happening. And it can drive the narrative. Now that doesn't mean there aren't real differences. Like strong differences. You know what's interesting is if you take people that are not on the extremes. You take the moderates. Sometimes the way in which we engage with people on the other side of the argument pushes them to be more extreme. See when we ourselves show up, thinking of ourselves as relatively moderate, enlightened people who have a set of point of view. But you know what I'm very open to other peoples perspective. But then we get into the conversation. And we end up challenging people in a way they don't find particularly useful. We start poking holes. We start making it's about a winning and a losing and a debate. And there's going to be at the end of the day points, score based on who wins the argument. Then people end up getting more and more entrenched. Even in ways that they otherwise wouldn't be. So the question is can we get to a point where at least those people on each side. And I find on any political issue I can find people on both sides that I think are trying to do the right thing and have perhaps limited information but they're trying to do the best they can with that information. They have good intentions and they're reasonably smart people. In my experience, you don't need two people one of whom is either evil, or crazy, or irrational to have conflict. You just need two people. You see good, smart, reasonably well-intentioned people getting into conflict all the time. Which then becomes the question of this book, which is how do we manage those situations? How do we get people to back away from these entrenched positions? How do we overcome deadlock that allows both sides to walk away feeling a little bit better about the situation? >> So examples are instructive. So let's talk about some great negotiators. Who are they? Let's start with sports. Scott Boras. You know you think of him as an agent. I mean grinding the teams, the general managers. Is he a good negotiator? >> So I don't follow many of the sports deal making and negotiations enough to be able to really elaborate on who would be a good negotiator in sports. But I can say this. That in a context where it's really just about things like price. Just about the money. And a sports agent often is, it's not really all about that but it is the most (mumbles). It is the most (mumbles) issue. You're going to go at it a certain way. And it would be similar to a negotiation in the business world where all you care about is price. You're buying or selling a house. You're buying or selling a car. And from my perspective there are people who are very good at haggling. There's people who can hold their cards to the chest and they can be aggressive when they need to be. And they can be persuasive in certain things. But when you look at negotiation as a whole. I think of haggling as a very, very thing slice of what negotiation is about. That's sort of the easy stuff. You may not be naturally good at it. But what it takes to be good at it is not so hard. We teach that on sort of day one of class. Day one of class is the price haggle. It's the you know there's two sides and you want opposite things. And how do you frame it in the right way and what kind of concession rate should you make or not make. How do you justify your proposal etcetera. We cover that on day one. And the problem is there is in our owner president program where I teach there's 15 more days left. In our MBA program there's like 27 more days left. And there the question becomes how do we get past just being a good haggler. Somebody who can just put fist to the table and say take it or leave it. And all that kind of stuff. Which will work in certain defined contexts but will not carry over to more important deals. >> You're right. That is a narrow context in sports because the agent has all the leverage of the players performed. How 'about Donald Trump? He's negotiating isn't he when he says Mexico's going to build the wall. He wrote the book, Art of the Deal. >> He did write that book. Yeah we co-authored that book actually. So is he negotiating when he says that. In the broader sense of the word negotiation which is basically how do we interact with other human beings who see things differently than we do. He absolutely is negotiating. If the question then becomes is he doing it effectively. My view would be that, that he is not. (chuckles) And I think if you actually were to look at the evidence and then stack it up. I think you would find that he's not a very effective negotiator. >> We don't have to go there. That's good. >> Deepak: That's okay I don't mind. >> We'll leave it there. But how 'about (mumbles), right. I mean you've had like an epic negotiation to bring those two. Is that an example? I mean even though it ended in tragedy on both sides is that an example of a successful negotiation? >> So it's an example of a, it is an example of a successful negotiation. And I think even more instructively it's an example of one of the biggest barriers in conflicts like this. The hardest part is often to bring your own side with you. And that is a challenge for leadership. It's not just in the bubble of negotiation. This is about leadership generally. To be able to have someone who can not only personally be willing to do the kinds of things that make the kinds of sacrifices but to be able to move a group of folks who for years, sometimes decades or centuries have been thinking differently. And to your point what often happens with these peace makers is you know the risk is you do one of these things and you're going to get killed. And usually you get killed by your own side. And exactly in the context you're talking about that's usually what happens. And so here what we see is not only an impressive set of events that led to negotiation and the negotiation itself but you see a certain amount of courage that leaders don't often enough show. And again some leaders aren't placed well. They don't have the support going in. Or they just don't have the ability to do it. But even those that do. The question is are you willing to expend the social and political capital necessary and put yourself on the line to be able to do something that you think is worth doing? >> I said I wasn't going to ask you but I am going to ask you 'cause your answer is so good. The Iran Deal. Good deal, not a good deal? You see to your point about getting killed by your own side. >> So I was not involved with the Iran deal. I do work with sometimes governments negotiating difficult conflicts and such. But I was not in any way involved with the Iran deal. What I can say is, based on the folks I've talk to leading up to the Iran deal and then after the Iran deal. It is my sense looking at what was accomplished that is actually a phenomenal deal for when it was done. Could a better deal have been done ten years earlier? Yes. One of the hardest things to negotiate against in the real world is the status quo. It's a lot easier to negotiate don't create center (mumbles) when there are none than it is to negotiate remove the center (mumbles) you have already created. So if you could go back in time which I have not met anybody yet who's able to do effectively it would be possible to get a better deal. Where things were last year and the year before I can say that pretty much everybody you talk to before the deal was announced on either side of the political spectrum, Republicans, Democrats, left, right, Hawkish, Dovish, you name it. Nobody would of expected a deal this good for the American side at the time. Now you may still not like it. You may be against any deal and that's okay. You can certainly have that perspective but if you're going to get a deal in this environment and what was being said leading up to this. I think both sides were pretty surprised and I would even say impressed. Until it came time to start talking about it publicly at which point of course you have to go back to your narrative. So you know again, I had nothing to do with it. But when you look at it, it surprised most people in terms of what it came out to be. >> So what are you working on? Next projects? Things that are exciting you these days. >> So I have sort of three areas where my attention is going. One is on ethnic conflict and armed conflict. As I was eluding to earlier I do some work with governments that are dealing with insurgency and conflict. And looking at what we know and what do we not know about resolving these kind of things. And how we can maybe push forward in that direction. So that's an area of advisory work but also research that I'm doing. Second area is I'm working with doctors. Thinking about how they can be more effective in prescribing a course of action to patients. How they can have more effective kind of conversations when a patient comes in and has a strong set of beliefs about what they should and shouldn't do. Or they're resistant to change. Or they're unwilling to do things. How can you be more effective in the time you spend with patients. And I do work on gun violence. And we've been looking at mass shootings. And we just had some research that got a lot of coverage unfortunately because of the tragedy that took place in Orlando not so long ago. Looking at whether mass shootings really have any impact on gun laws. And we find some interesting results there. So in a sense I'm sort of looking at insurgency and dealing with cancer patients and then gun violence. >> Interesting topics. >> Deepak: All of the darkest stuff we can find. >> It's a tragic but timely. And then there's another sequence there. Do gun laws have an impact on mass shooting. >> Deepak: And that's basically the next set of projects. >> Excellent. Well thank you very much. (mumbles) >> Deepak: It was great. >> Fantastic. >> Deepak: Absolutely. >> Alright keep right there everybody. Stu and I will be back with our next guest. We're live this is theCUBE SiliconANGLE's flagship production from .NEXT in Vegas. Be right back.

>>Hi buddy, we're back. This is Dave Volante with the cube goes out to the shows. We extract the signal from the noise. Nate Silver's here. Nate, we've been saying that since 2010, rip you off. Hey Marcus feeder. Oh, you have that trademarks. Okay. So anyway, welcome to the cube. You man who needs no introduction, but in case you don't know Nate, uh, he's a very famous author, five 30 eight.com. Statistician influence, influential individual predictor of a lot of things including presidential elections. And uh, great to have you here. Great to be here. So we listened to your keynote this morning. We asked earlier if some of our audience, can you tweet it and you know, what would you ask Nate silver? So of course we got the predictable, how the red Sox going to do this year? Who's going to be in the world series? Are we going to attack Syria? >>Uh, will the fed E's or tightened? Of course we're down here. Who'd you vote for? Or they, you know, they all want to know. And of course, a lot of these questions you can't answer because it's too far out. But, uh, but anyway, again, welcome, welcome to the cube. Um, so I want to start by, uh, picking up on some of the themes in your keynote. Uh, you're here at the Tableau conference. Obviously it's all about about data. Uh, and you, your basic, one of your basic premises was that, um, people will misinterpret data, they'll just use data for their own own biases. You have been a controversial figure, right? A lot of people have accused you of, of bias. Um, how, what do you F how do you feel about that as a person who's, uh, you know, statistician, somebody who loves data? >>I think everyone has bias in the sense that we all have one relatively narrow perspective as compared to a big set of problems that we all are trying to analyze or solve or understand together. Um, you know, but I do think some of this actually comes down to, uh, not just bias, but kind of personal morality and ethics really. It seems weird to talk about it that way, but there are a lot of people involved in the political world who are operating to manipulate public opinion, um, and that don't really place a lot of value on the truth. Right. And I consider that kind of immoral. Um, but people like that I think don't really understand that someone else might act morally by actually just trying to discover the way the objective world is and trying to use science and research to, to uncover things. >>And so I think it's hard people to, because if they were in your shoes, they would try and manipulate the forecast and they would cheat and put their finger on their scale. They assume that anyone else would do the same thing cause they, they don't own any. Yeah. So will you, you've made some incredibly accurate predictions, uh, in the face of, of, of others that clearly had bias that, that, that, you know mispredicted um, so how did you feel when you got those, those attacks? Were you flabbergasted? Were you pissed? Were you hurt? I mean, all of the above having you move houses for, for you? I mean you get used to them with a lot of bullshit, right? You're not too surprised. Um, I guess it surprised me how, but how much the people who you know are pretty intelligent are willing to, to fool themselves and how specious arguments where meet and by the way, people are always constructing arguments for, for outcomes they happen to be rooting for. >>Right? It'd be one thing if you said, well I'm a Republican, but boy I think Obama's going to crush Romney electoral college or vice versa. But you should have an extra layer of scrutiny when you have a view that diverges from the consensus or what kind of the markets are saying. And by the way, you can go and they're betting Margaret's, you can go and you could have bet on the outcome of election bookies in the UK, other countries. Right. And they kind of had forecast similar to ours. We were actually putting their money where their mouth was. Agree that Obama was a. Not a lot, but a pretty heavy favorite route. Most of the last two months in the election. I wanted to ask you about prediction markets cause as you probably know, I mean the betting public are actually very efficient. Handicappers right over. >>So I'll throw a two to one shot is going to be to three to one is going to be a four to one, you know, more often than not. But what are your thoughts on, on prediction markets? I mean you just sort of betting markets, you'd just alluded it to them just recently or is that a, is that a good, well there a lot there then then I think the punditry right. I mean, you know, so with, with prediction markets you have a couple of issues. Number one is do you have enough, uh, liquidity, um, and my volume in the markets for them to be, uh, uh, optimal. Right. And I think the answer right now is maybe not exactly. And like these in trade type markets, knowing trade has been, has been shut down. In fact, it was pretty light trading volumes. It might've had people who stood to gain or lose, um, you know, thousands of dollars. >>Whereas in quote, unquote real markets, uh, the stakes are, are several orders of magnitude higher. If you look at what happened to, for example, just prices of common stocks a day after the election last year, um, oil and gas stocks lost billions of dollars of market capitalization after Romney lost. Uh, conversely, some, you know, green tech stocks or certain types of healthcare socks at benefit from Obamacare going into play gain hundreds of millions, billions of dollars in market capitalization. So real investors have to price in these political risks. Um, anyway, I would love to have see fully legal, uh, trading markets in the U S people can get bet kind of proper sums of money where you have, um, a lot of real capital going in and people can kind of hedge their economic risk a little bit more. But you know, they're, they're bigger and it's very hard to beat markets. They're not flawless. And there's a whole chapter in the book about how, you know, the minute you assume that markets are, are clairvoyant and perfect, then that's when they start to fail. >>Ironically enough. But they're very good. They're very tough to beat and they certainly provide a reality check in terms of providing people with, with real incentives to actually, you know, make a bet on, on their beliefs and people when they have financial incentives, uh, uh, to be accurate then a lot of bullshit. There's a tax on bullshit is one way. That's okay. I've got to ask him for anyway that you're still a baseball fan, right? Is that an in Detroit fan? Right. I'm a tiger. There's my bias. You remember the bird? It's too young to remember a little too. I, so I grew up, I was born in 78, so 84, the Kirk Gibson, Alan Trammell teams are kind of my, my earliest. So you definitely don't remember Mickey Lola cha. I used to be a big guy. That's right fan as well. But so, but Sony, right when Moneyball came out, we just were at the Vertica conference. >>We saw Billy being there and, and uh, when, when, when, when, when that book came out, I said Billy Bean's out of his mind for releasing all these secrets. And you alluded to in your talk today that other teams like the rays and like the red Sox have sort of started to adopt those techniques. At the same time, I feel like culturally when another one of your V and your Venn diagram, I don't want you vectors, uh, that, that Oakland's done a better job of that, that others may S they still culturally so pushing back, even the red Sox themselves, it can be argued, you know, went out and sort of violated the, the principles were of course Oakland A's can't cause they don't have a, have a, have a budget to do. So what's your take on Moneyball? Is the, is the strategy that he put forth sustainable or is it all going to be sort of level playing field eventually? >>I mean, you know, the strategy in terms of Oh fine guys that take a lot of walks, right? Um, I mean everyone realizes that now it's a fairly basic conclusion and it was kind of the sign of, of how far behind how many biases there were in the market for that, you know, use LBP instead of day. And I actually like, but that, that was arbitrage, you know, five or 10 years ago now, um, put butts in the seat, right? Man, if they win, I guess it does, but even the red Sox are winning and nobody goes to the games anymore. The red Sox, tons of empty seats, even for Yankees games. Well, it's, I mean they're also charging 200 bucks a ticket or something. you can get a ticket for 20, 30 bucks. But, but you know, but I, you know, I, I, I mean, first of all, the most emotional connection to baseball is that if your team is in pennant races, wins world series, right then that produces multimillion dollar increases in ticket sales and, and TV contracts down the road. >>So, um, in fact, you know, I think one thing is, is looking at the financial side, like modeling the martial impact of a win, but also kind of modeling. If you do kind of sign a free agent, then, uh, that signaling effect, how much does that matter for season ticket sales? So you could do some more kind of high finance stuff in baseball. But, but some of the low hanging fruit, I mean, you know, almost every team now has a Cisco analyst on their payroll or increasingly the distinctions aren't even as relevant anymore. Right? Where someone who's first in analytics is also listening to what the Scouts say. And you have organizations that you know, aren't making these kind of distinctions between stat heads and Scouts at all. They all kind of get along and it's all, you know, finding better ways, more responsible ways to, to analyze data. >>And basically you have the advantage of a very clear way of measure, measure success where, you know, do you win? That's the bottom line. Or do you make money or, or both. You can isolate guys Marshall contribution. I mean, you know, I am in the process now of hiring a bunch of uh, writers and editors and developers for five 38 right? So someone has a column and they do really well. How much of that is on the, the writer versus the ed or versus the brand of the site versus the guy at ESPN who promoted it or whatever else. Right. That's hard to say. But in baseball, everyone kind of takes their turn. It's very easy to measure each player's kind of marginal contribution to sort of balance and equilibrium and, and, and it's potentially achieved. But, and again, from your talk this morning modeling or volume of data doesn't Trump modeling, right? >>You need both. And you need culture. You need, you need, you know, you need volume of data, you need high quality data. You need, uh, a culture that actually has the right incentives align where you really do want to find a way to build a better product to make more money. Right? And again, they'll seem like, Oh, you know, how difficult should it be for a company to want to make more money and build better products. But, um, when you have large organizations, you have a lot of people who are, uh, who are thinking very short term or only about only about their P and L and not how the whole company as a whole is doing or have, you know, hangups or personality conflicts or, or whatever else. So, you know, a lot of success I think in business. Um, and certainly when it comes to use of analytics, it's just stripping away the things that, that get in the way from understanding and distract you. >>It's not some wave a magic wand and have some formula where you uncover all the secrets in the world. It's more like if you can strip away the noise there and you're going to have a much clearer understanding of, of what's really there. Uh, Nate, again, thanks so much for joining us. So kind of wanna expand on that a little bit. So when people think of Nate silver, sometimes they, you know, they think Nate silver analytics big data, but you're actually a S some of your positions are kind of, you take issue with some of the core notions of big data really around the, the, the importance of causality versus correlation. So, um, so we had Kenneth kookier on from, uh, the economist who wrote a book about big data a while back, the strata conference. And you know, he, in that book, they talk a lot about it really doesn't matter how valid anymore, if you know that your customers are gonna buy more products based on this dataset or this correlation that it doesn't really matter why. >>You just try to try to try to exploit that. Uh, but in your book you talk about, well and in the keynote today you talked about, well actually hypothesis testing coming in with some questions and actually looking for that causality is also important. Um, so, so what is your, what is your opinion of kind of, you know, all this hype around big data? Um, you know, you mentioned volume is important, but it's not the only thing. I mean, like, I mean, I'll tell you I'm, I'm kind of an empiricist about anything, right? So, you know, if it's true that merely finding a lot of correlations and kind of very high volume data sets will improve productivity. And how come we've had, you know, kind of such slow economic growth over the past 10 years, where is the tangible increase in patent growth or, or different measures of progress. >>And obviously there's a lot of noise in that data set as well. But you know, partly why both in the presentation today and in the book I kind of opened up with the, with the history is saying, you know, let's really look at the history of technology. It's a kind of fascinating, an understudied feel, the link between technology and progress and growth. But, um, it doesn't always go as planned. And I certainly don't think we've seen any kind of paradigm shift as far as, you know, technological, economic productivity in the world today. I mean, the thing to remember too is that, uh, uh, technology is always growing in and developing and that if you have roughly 3% economic growth per year exponential, that's a lot of growth, right? It's not even a straight line growth. It's like exponential growth. And to have 3% exponential growth compounding over how many years is a lot. >>So you're always going to have new technologies developing. Um, but what I, I'm suspicious that as people will say this one technology is, is a game changer relative to the whole history of civilization up until now. Um, and also, you know, again, a lot of technologies you look at kind of economic models where you have different factors or productivity. It's not usually an additive relationship. It's more a multiplicative relationships. So if you have a lot of data, but people who aren't very good at analyzing it, you have a lot of data but it's unstructured and unscrutinised you know, you're not going to get particularly good results by and large. Um, so I just want to talk a little bit about the, the kind of the, the cultural issue of adopting kind of analytics and, and becoming a data driven organization. And you talk a lot about, um, you know, really what you do is, is setting, um, you know, try to predict the probabilities of something happening, not really predicting what's going to happen necessarily. >>And you talked to New York, you know, today about, you know, knowledging where, you know, you're not, you're not 100% sure acknowledging that this is, you know, this is our best estimate based on the data. Um, but of course in business, you know, a lot of people, a lot of, um, importance is put on kind of, you know, putting on that front that you're, you know, what you're talking about. It's, you know, you be confident, you go in, this is gonna happen. And, and sometimes that can actually move markets and move decision-making. Um, how do you balance that in a, in a business environment where, you know, you want to keep, be realistic, but you want to, you know, put forth a confident, uh, persona. Well, you know, I mean, first of all, everyone, I think the answer is that you have to, uh, uh, kind of take a long time to build the narrative correctly and kind of get back to the first principles. >>And so at five 38, it's kind of a case where you have a dialogue with the readers of the site every day, right? But it's not that you can solve in one conversation. If you come in to a boss who you never talked to you before, you have to present some PowerPoint and you're like, actually this initiative has a, you know, 57% chance of succeeding and the baseline is 50% and it's really good cause the upside's high, right? Like you know, that's going to be tricky if you don't have a good and open dialogue. And it's another barrier by the way to success is that uh, you know, none of this big data stuff is going to be a solution for companies that have poor corporate cultures where you have trouble communicating ideas where you don't everyone on the same page. Um, you know, you need buy in from, from all throughout the organization, which means both you need senior level people who, uh, who understand the value of analytics. >>You also need analysts or junior level people who understand what business problems the company is trying to solve, what organizational goals are. Um, so I mean, how do you communicate? It's tricky, you know, maybe if you can't communicate it, then you find another firm or go, uh, go trade stocks and, and uh, and short that company if you're not violating like insider trading rules of, of various kinds. Um, you know, I mean, the one thing that seems to work better is if you can, uh, depict things visually. People intuitively grasp uncertainty. If you kind of portray it to them in a graphic environment, especially with interactive graphics, uh, more than they might've just kind of put numbers on a page. You know, one thing we're thinking about doing with the new 580 ESPN, we're hiring a lot of designers and developers is in case where there is uncertainty, then you can press a button, kind of like a slot, Michigan and simulate and outcome many times, then it'll make sense to people. Right? And they do that already for, you know, NCAA tournament stuff or NFL playoffs. Um, but that can help. >>So Nate, I asked you my, my partner John furry, who's often or normally the cohost of this show, uh, just just tweeted me asking about crowd spotting. So he's got this notion that there's all this exhaust out there, the social exhaustive social data. How do you, or do you, or do you see the potential to use that exhaust that's thrown off from the connected consumer to actually make predictions? Um, so I'm >>a, I guess probably mildly pessimistic about this for the reason being that, uh, a lot of this data is very new and so we don't really have a way to kind of calibrate a model based on it. So you can look and say, well, you know, let's say Twitter during the Republican primaries in 2016 that, Oh, Paul Ryan is getting five times as much favorable Twitter sentiment as Rick Santorum or whatever among Republicans. But, but what's that mean? You know, to put something into a model, you have to have enough history generally, um, where you can translate X into Y by means of some function or some formula. And a lot of data is so new where you don't have enough history to do that. And the other thing too is that, um, um, the demographics of who is using social media is changing a lot. Where we are right now you come to conference like this and everyone has you know, all their different accounts but, but we're not quite there yet in terms of the broader population. >>Um, you have a lot of kind of thought leaders now a lot of, you know, kind of young, smart urban tech geeks and they're not necessarily as representative of the population as a whole. That will over time the data will become more valuable. But if you're kind of calibrating expectations based on the way that at Twitter or Facebook were used in 2013 to expect that to be reliable when you want a high degree of precision three years from now, even six months from now is, is I think a little optimistic. Some sentiment though, we would agree with that. I mean sentiment is this concept of how many people are talking about a thumbs up, thumbs down. But to the extent that you can get metadata and make it more stable, longer term, you would see potential there is, I mean, there are environments where the terrain is shifting so fast that by the time you know, the forecast that you'd be interested in, right? >>Like things have already changed enough where like it's hard to do, to make good forecast. Right? And I think one of the kind of fundamental themes here, one of my critiques is some of the, uh, of, uh, the more optimistic interpretations of big data is that fundamentally people are, are, most people want a shortcut, right? Most people are, are fairly lazy like labor. What's the hot stock? Yeah. Right. Um, and so I'm worried whenever people talk about, you know, biased interpretations of, of the data or information, right? Whenever people say, Oh, this is going to solve my problems, I don't have to work very hard. You know, not usually true. Even if you look at sports, even steroids, performance enhancing drugs, the guys who really get the benefits of the steroids, they have to work their butts off, right? And then you have a synergy which hell. >>So they are very free free meal tickets in life when they are going to be gobbled up in competitive environments. So you know, uh, bigger datasets, faster data sets are going to be very powerful for people who have the right expertise and the right partners. But, but it's not going to make, uh, you know anyone to be able to kind of quit their job and go on the beach and sip my ties. So ne what are you working on these days as it relates to data? What's exciting you? Um, so with the, with the move to ESPN, I'm thinking more about, uh, you know, working with them on sports type projects, which is something having mostly cover politics. The past four or five years I've, I've kind of a lot of pent up ideas. So you know, looking at things in basketball for example, you have a team of five players and solving the problem of, of who takes the shot, when is the guy taking a good shot? >>Cause the shot clock's running out. When does a guy stealing a better opportunity from, from one of his teammates. Question. We want to look at, um, you know, we have the world cup the summer, so soccer is an interest of mine and we worked in 2010 with ESPN on something called the soccer power index. So continuing to improve that and roll that out. Um, you know, obviously baseball is very analytics rich as well, but you know, my near term focus might be on some of these sports projects. Yeah. So that the, I have to ask you a followup on the, on the soccer question. Is that an individual level? Is that a team level of both? So what we do is kind of uh, uh, one problem you have with the national teams, the Italian national team or Brazilian or the U S team is that they shift their personnel a lot. >>So they'll use certain guys for unimportant friendly matches for training matches that weren't actually playing in Brazil next year. So the system soccer power next we developed for ESPN actually it looks at the rosters and tries to make inferences about who is the a team so to speak and how much quality improvement do you have with them versus versus, uh, guys that are playing only in the marginal and important games. Okay. So you're able to mix and match teams and sort of predict on your flow state also from club league play to make inferences about how the national teams will come together. Um, but soccer is a case where, where we're going into here where we had a lot more data than we used to. Basically you had goals and bookings, I mean, and yellow cards and red cards and now you've collected a lot more data on how guys are moving throughout the field and how many passes there are, how much territory they're covering, uh, tackles and everything else. So that's becoming a lot smarter. Excellent. All right, Nate, I know you've got to go. I really appreciate the time. Thanks for coming on. The cube was a pleasure to meet you. Great. Thank you guys. All right. Keep it right there, everybody. We'll be back with our next guest. Dave Volante and Jeff Kelly. We're live at the Tableau user conference. This is the cube.