>> Narrator: Live from San Francisco, it's The Cube, covering Flink Forward, brought to you by Data Artisans. (upbeat music) >> Hi this is George Gilbert, we are at Flink Forward the conference for the Apache Flink community, sponsored by Data Artisans, which is the company commercializing Flink, and we have with us now Enrico Canzonieri, wait a minute I didn't get that right, Canzonieri, Sorry, Enrico from Yelp. And he's going to tell us how sort of Flink has taken Yelp by storm over the past year. Why don't we start off with where you were last year in terms of your data pipeline and what challenges you were facing. >> Yeah sure, so we had a Python company in the sense we developed most of our software in Python, so until last year we had most of our stream processing was depending on Python. We had developed and announced framework that was doing Python processing, and that was really what we had, there was no Flink running, most of the applications were built around a very simple interface that was process message function, that was what we expected developers to use, so no real obstruction there. >> Okay so, in other words, it sounds like you had a discrete task, request response or a batch, and then hand it off to the next function, and is that what the pipeline looked like? >> The pipeline was more of a streaming pipeline where we had a Kafka topic and input and we had these developers who would write this process message function where each message would be individually processed, there was a kind of the semantic of the pipeline there. And then we will get the result of that processing task into another Kafka topic and then get another processing function on top of that So we could have very easily, two or three processing tasks all connected by Kafka topics. Obviously there were like big limitations of that kind of architecture, especially when you want to do something more advanced that can include windowing, aggregation, or especially state management. >> Well Kafka has several layers of abstraction and I guess you'd have to go pretty low level to get the windowing, all the windowing and state management capabilities. >> Yeah it becomes really hard you basically have to implement by yourself unless you're using a (mumbles) on the conference platform or you're using what they call Kafka streams, but we are not using that. >> Oh, not? Okay. >> Obviously we were trying to implement that on top of what Python or Simple Flame work from zero. >> So tell us how the choice of Flink, sort of where did it hit your awareness and where did you start mapping it into this pipeline that was Python based? >> Yeah so we had the really I think two main use cases, this was last year, that we were struggling to get right and to really get working. The first one was a connector and the challenge there was to aggregate that locally, scale it to hundreds of streams, and then once we aggregated that locally, upload at our own S3. So that was one application, we were really struggling to get that work because in the framework we had, we had no real obstruction for windowing so we had this process message function where it was trying to implement all of that. And also because we were using a very low level Kafka code primitives, getting scalability was not as straight forward. So that was one application that was pretty challenging, the other one was really purer state full application, where we needed to retain the state forever. It was doing a windowed join across streams, so obviously the challenges in that case are even harder more because you have to implement a state management from the ground up. >> And all the time semantics. >> Yeah we had basically no even time semantics. We were not supporting that. >> Okay. >> So we looked at Flink because of even time support so then we could actually do even time processing. State management support, already implemented, it's way different than implementing it from the ground up. And then obviously the abstractions so the streaming primitives, you have windows, you have a nice interface that you can use that makes developers who are writing code it becomes easier for them. >> So let's start with the state management, help us walk through like, what capabilities in state management does Flink have relative to the lowest level abstraction you were using in Kafka or perhaps what spark structured streaming might provide. >> Yeah so I think the nice features in streams are really around the fact that the state management is implemented and fully supports the clusterized approach of Flink. So for example if you're using Kafka, Flink already, in the Kafka connector, Flink already provides a way to represent the Kafka state the state of a Kafka consumer. It also, for open editors, if you have a flat map or you have a window, state for Windows is already fully supported so if you are cumulating events, in your window, you don't really know what to do, then nothing special, these states will be automatically maintained by the Flink framework. That means that if Flink is taking a snapshot so a check point or a save point, all the state that was there will get stored in the check point and then will be able to recover. >> For the full window. >> Yeah. >> It's cause it understands the concept of the window when it does a check point. >> Yeah because there's native support in Flink for that. >> And what's the advantage of having state be integrated with the compute as opposed to compute and then some sort of API to a separate state manager? >> It's definitely like call to clarity, it's a big simplification of how you implement your code, your streaming application. Cause in the end if for every simple string application you need to go ahead and implement or define, implement basically the way your state gets stored, that really makes a very complex application, especially on the maintain, for maintenance. So in Flink you kind of focus on the business logic we actually did some tuning on the state manager that was necessary, but the tuning that we did applies in the same way across all the applications we built. Then users want to build an application, they focus on the business logic that they want, and they have, I would say the state is more kind of declarative, you say you want this map, you need this list and this state as part of the state and Flink will take care of actually making sure that that gets into the check point. >> So the sort of semantics of state management are built in at the compute layer, as opposed to going down to an API for a separate service in other implementations. >> Yeah, yeah. >> Okay. All right we have just a minute left, tell us about some of the things you're looking forward to doing with Flink, and are they similar to what the DA platform that's coming out from Data Artisans or do you have still a whole bunch of things on the data pipeline that you want to accomplish with just the core functionality? >> Yeah we definitely, I will say one of the features that we are really excited about is the stream sequel. I see a lot of potential there for new applications, we actually use a stream sequel at Yelp and we deploy that as a service so it makes it easier for users to deploy and to develop stream plus string applications. We definitely are planning to expand our Flink deployment into just new apps. Especially one of the things that we try to do especially building reusable components, and trying to deploy the reusable components are very coupled with the way we think about our data pipeline. >> Okay so would it be fair to say that can you look at the DA platform and say for companies that are not quite as sophisticated as you, that this is going to make it easier for you know main stream companies to build and deploy, operate? >> I see good potential there, I was looking at the presentation in the morning I like the integration we culminated for sure, since like that's where kind of the current trend for application deployment is going. So yeah I definitely see potential, I think for Yelp we clearly have a complex enough deployment and service integration that won't probably be a good fit for us. But probably companies that are approaching the route of Flink, now and we'll probably have an already existing deployment they may probably give it a try. >> Okay, all right Enrico we got to end it there but that was very helpful and thanks for stopping by. >> Thanks for having me here. >> Okay. And this is George Gilbert we are at Flink Forward, the Data Artisan's conference for the Apache Flink community, and we will be right back after this short break. (upbeat music)

>> Narrator: Live from Washington D.C., it's theCUBE. Covering .conf2017. Brought to you by Splunk. >> Well welcome back here on theCUBE. We continue our coverage of .conf2017, we're in Washington D.C. Along with Dave Vellante, I'm John Walls. And Dave, you know what time it is, by the way? Just about? >> I don't know, this is the penultimate interview. >> It's almost five o'clock. >> Okay. >> And that means it's almost happy hour time. So I was thinking where might we go tonight, so-- >> There's an app for that. >> There was, and so I looked. It turns out that the Penny Whiskey Cafe is just two tenths of a mile from here. And you know how I knew that? >> How's the ratings on that? >> We got four. >> Four and half with 52. >> 52 reviews? >> Yeah, I feel good about that. >> Yeah, that's pretty good. That's a substantive base. >> I feel very solid with that one. We'll make it 53 in about a half hour. Of course I found it on Yelp. We have a couple of gentlemen from Yelp with us tonight. I don't have to tell you what Yelp does, it does everything for everybody, right. Zach Musgrave, technical lead, and Chris Gordon, software engineer at Yelp. Gentlemen, thanks for being here. And U can join us, by the way, later on, at the Penny Whiskey if you'd like to. First off, what are you doing here, right, at Splunk? What's Yelp and Splunk, what's that intersection all about? Zach, if you would. >> Sure, well Yelp uses Splunk for all sorts of purposes. Operational, intelligence, business metrics, pretty much any sort of analytics from event driven data that you can really think of, Yelp has found a way, and our engineers have found a way to get that into Splunk and derive business value from it. So Chris and I are actually here, we just gave a breakout session at .conf, talking about how we find strong business value and how we quantify that value and mutate our Splunk cluster to really drive that. >> Okay. >> So, so how do you find value then, I mean, what was? >> It's hard. Chris was one of the people who really, really drove this for us. And when we looked at this, you know I once had an engineer who came up to our team, we maintain Splunk amongst other things, and the engineer said can I ingest 10 terabytes of data a day into Splunk and then keep it forever? And I said, um, please don't. And then we talked a bit more about what that engineer was actually trying to do and why they needed this massive amount of data, and we found a better way that was much more efficient. And then where we didn't need to keep all the data forever. So, by being able to have those conversations and to quantify with the data you're already ingesting into Splunk, being able to quanitfy that and actually show how many people were searching this, how's it being used, what's the depth of the search look like, how far back are they looking in time. You can really optimize your Splunk cluster to get a lot more business value than just naively setting it up and turning it on. >> So you weren't taking a brute force approach, you were smarter about that, but you weren't deduping, you were identifying the data that was not necessary to keep, did I get that right? >> Correct. Yeah, we essentially kind of identified what are highest cost per search logs, which we basically just totaled up how many times each log was searched, and then tried to quantify how much each logs was costing us. And then this ended up being a really good metric for figuring out what we'd want to remove or something that was a candidate for dislodging the data somehow. >> So, you guys gave a talk today. We were talking off camera about pricing, that's not something you guys get involved in, but I would categorize this as sort of how do you get the most out of that asset, called Splunk, right. Is that sort of the >> Exactly. >> theme of your talk, right? >> Yeah. We talk a lot about expected value amongst our team, and in the talk we just gave. And we don't ever think about this as, oh do this so that you can spend less money on Splunk or on your infrastructure that's backing Splunk. Think about is more as we have this right now and we can utilize it more effectively. We can get more value out of what we already have. >> Okay, so, I wonder if we could just talk a little bit about your environment. We know you run on AWS. How does that cloud fit in with Splunk, paint a picture for us, if you would. What does it all look like? >> Yeah, so we have two clusters actually. One is the high value, high quality of service cluster, it's the larger generic, we call it generic prod, and then we have another one, where we kind of have our more verbose, maybe slightly less valuable per log cluster. And this runs on a D2, which is just instant storage. And then the higher performance cluster runs all on a GP2. So it's basically just SSDs. And we also do, we also have four copies of each log and we have two searchable copies of each log, so it's pretty well replicated. >> Dave: Okay, so that's how you protect the data. >> Yeah. >> Is to make copies, in what, in different zones, or? >> Yeah, we have two copies of each log in each availability zone, and then one searchable copy of each log in each availability zone. >> And you guys are cloud natives, all cloud, just out of school and graduate school. So you talked about infrastructure as code. You don't do any of that on-prem stuff, you're not like installing gear. And so it's not part of your lexicon, right? >> No. >> Okay. So I want to do a little editorial thing. Kristen Nicole, our managing editor, sent the note around today saying 101s get the best traffic on the website. So I want to do a little DevOps 101, okay. Even though, it's second nature to you, and a lot of people in our audience know what it is. How do you describe DevOps? Give us the 101 on DevOps. >> Okay so, DevOps is a complicated thing, but and occasionally you see it as like a role on like a job board or something. And that always strikes me as odd, because it's not really a role. Like it's a philosophy moreso. The way that I always see it, is it used to be like pre DevOps, was the software developers make a thing, and then they throw it over the fence, and operations just picks it up. And they're like well what do we do with this, and deploy it, okay, good luck. And so with this result in a sort of an us against them mentality, where the developers aren't incentivized to really make it resilient, or really document it well, and operations and the sys admins are not incentivized to really be flexible and to be really hard charging and move quickly, because they're the ones who are going to be on call for whatever the developers made. DevOps is a we, instead of an us verses them. So for example, product teams have an on-call rotation. Operations and sys admins write code. There are still definitely specializations, but it all comes together in a much more holistic manner. >> Okay, and the ops guys will write code, as opposed to hacking code, messing up your code, throwing it back over the fence, and saying hey your code doesn't work. >> Exactly. >> And then you say well it worked when I gave it to you. And then like you said that sort of finger pointing. >> We are totally done with works on my machine, it's over. No more. >> Okay, and the benefits obviously are higher quality, faster time to market, less food fighting. >> Yup, exactly. In the old model you'd have a new deployment of like a website like maybe once a week or maybe even once a month. Yelp deploys multiple times everyday over and over again. And each one of those is going to include changes from a dozen different engineers. So we need to be agile in that manner, just like with our Splunk cluster. >> I mean you guys are relatively new, four years and two years, perspectively. But these days it's a long time. How would you describe your Splunk journey. Where did it start and where do you want to take it? >> I would say it started, you actually had Kris Wehner on here last year, and he talked a lot about it. He was the VP of engineering at SeatMe. And he kind of got Yelp onto the whole Splunk train. And at that point it was used mostly by SeatMe and everyone at Yelp was like oh this is fantastic, we want to use this. And we started basically migrating it to our VPC. And have generally, we're starting to now get everything going, get all the kinks worked out, and really now we're trying to see where we can provide the most value and make things as easy as possible for our developers to add logs and add searches and get what they need out of it. >> So what kind of use cases are you envisioning, and where are you getting value out of it? >> So we have our operations teams get a lot of value out of it when there's some outage happening. And it's really useful for them to be able to just look at the access logs and see what's going on. And Splunk makes that very easy. And we also get a lot of value out of Yelp's application logs. Splunk has been great for figuring out when something's not right. And allowing us to dig in further. >> So yeah, at the end of the day, as consumers, what does this mean to us, ultimately? Like our searches are faster, searches are more refined, searches are more accurate? What does it mean to me at the end of the day that you're enabling what activity through this technology. >> Dave: Yeah, it'll be more secure? >> Yeah, what does it mean? >> As an end user of Yelp? >> Yes. >> So, I'll give you one example that always sticks out in my mind. So I don't know if you all know this, but you can actually do things like order food via Yelp, you can make appointments via Yelp, even with like a dentist. You can beauty appointments, all sorts of personal services. >> Hair salon came up today actually, when I was looking for a bar. >> Absolutely. That's not supposed to happen. >> Dave: Well that was the Penny Whiskey Cafe. >> You never know, but what ever's next door I don't know. >> Can you get a haircut while you drink? >> Hair salons in the District are pretty impressive. >> I wasn't planning on it, no. But anyway, I'm sorry. >> Anyway, so we work with a lot of external partners to enable all these different integrations, right. So you press start order, and then eventually you see the menu, and then you add some stuff to your cart, and then you have to pay. And so if you haven't given us your credit card information yet, then you have to enter that, and that has to go to a payment processor, the order of course has to go out to the partner who's going to fulfill your order, and so on. So there's this pipeline of many different micro services plus the main Yelp application, plus this partner who's actually fulfilling your order, plus the payment processor, and so on, and so on. And it ends up with this really complicated state machine. So the way that actually works under the hood, to be very simplistic, is there's a unique order identifier that is assigned to you when you start the order. And then that passed through the whole process. So at every step in this process a bunch of events are emitted out of the various parts of the pipeline and into Splunk, where they're then matched to show that your order is progressing. And the order didn't get stuck. Because you know what's really sad is when you order food and it doesn't show up. So we really have to guard against that. >> Yeah, we hate that. >> Yeah, everybody does. So it's really important that we're able to unify this data, from all these different places, Splunk's really great for that, and to be able to then alert on that and page somebody and say hey, something's not quite right here, we have hungry folks. >> So while I have the smartest guys that we've interviewed all week here, you mentioned, >> Please. You mentioned, aw shucks, I know. You mentioned state machine. Are you playing around with functional programming, so called server lists, probably don't like that word either, but what are you doing there? Are you finding sort of new applications in use cases for so called server lists? >> I would say not so much. I don't know, is anyone at Yelp doing that? >> Yeah, there's some Lambda stuff going on. Like core back end is doing that work right now. A lot of our infrastructure is actually build up before the AWS Lambdas were a thing. So we found other ways to do that, and we have this really cool internal platform as a service, it's a docker, and some scheduling stuff on top of that. So a lot of things, like it's really easy to just launch a batch job in there. And it takes away some of the need for the true server lists. >> Well the reason I ask is because people are saying a lot of the state list IoT apps are going to use that sort of Lambda or homegrown stuff. And I'm not sure what the play is for Yelp in Internet of Things. I would imagine there's actually a play there for you guys though, and I'm curious as to the data angle, and maybe where Splunk might fit in. >> I'm certain that we're going to be using Splunk to read data from all of those different components as they're being launched. I know that there's been a couple early forays into the Lambda space that I've seen go by in code reviews and everything. But of course, with Splunk itself we can get data out of those. So as that happens, like we already have all our pipe lining set up. And it'll be pretty easy for them to analyze their self with Splunk. >> What gets you young folks excited these days? What keeps you enthralled and passionate? What do you look for? >> I don't know I think just in general anything that empowers you to get a lot done without having to fight it constantly. And general DevOps tools have been getting really good at that recently. And yeah, I would say anything that empowers you, gives you the feeling that you can do anything really. >> Yeah, all of the infrastructure is code stuff that's going on right now. So one of the pipelines that we use to get data out of Amazon S3, but it passes notifications through this S3 event notifications to Amazon SNS, to Amazon SQS, to our Splunk forwarders. And so that's a very complicated pipeline. And you have to set it all up, it works really well, but here's the cool part. That's all defined in code. And so this means that if you set up a new integration there's a code review. And we have some verification and validation that it's correct. And furthermore, if anything goes wrong with it, we can just hit a button and it recreates itself. That's what gets me happy. When tools get in my way that's not so good. >> Well and it just leaves more time for higher value activities and that's exciting. the transformation in infrastructure over the last five years has just been mind boggling. So, thanks you guys. >> It does. It does give me a lot of pleasure when something can go catastrophically wrong, and then just like, oh wait, it's self healing, all it can take is give three plays fine. And we're all dandy. >> Well to Dave's point, while I was off camera I did a search on the two smartest guys in the room. And it said one is six feet away the other one is seven feet away, so Yelp works, I mean it really does. But thanks for the time. It's been interesting. Next generation, right? So far over us. >> Yeah, I know. It's kind of depressing, but I love it. (laughing) >> Very good, thanks guys. >> Thank you so much. >> Back with more, here on theCUBE at .conf2017. We are live, Washington D.C. >> Dave: I've kind of had it with millennial. (upbeat music)

>> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (intro music) >> Good afternoon, everyone. Welcome back to "theCUBE's" day three coverage of MWC23. Lisa Martin here in Spain, Barcelona, Spain with Dave Nicholson. We're going to have a really interesting conversation next. We're going to really dig into MWC, it's history, where it's going, some of the controversy here. Please welcome our guests. We have Jim Harris, International Best Selling Author of "Blindsided." And Carolina Milanese is here, President and Principle Analyst of creative strategies. Welcome to "theCUBE" guys. Thank you. >> Thanks. So great to be here. >> So this is day three. 80,000 people or so. You guys have a a lot of history up at this event. Caroline, I want to start with you. Talk a little bit about that. This obviously the biggest one in, in quite a few years. People are ready to be back, but there's been some, a lot of news here, but some controversy going on. Give us the history, and your perspective on some of the news that's coming out from this week's event. >> It feels like a very different show. I don't know if I would say growing up show, because we are still talking about networks and mobility, but there's so much more now around what the networks actually empower, versus the network themselves. And a little bit of maybe that's where some of the controversy is coming from, carriers still trying to find their identity, right, of, of what their role is in all there is to do with a connected world. I go back a long way. I go back to when Mobile World Congress was called, was actually called GSM, and it was in Khan. So, you know, we went from France to Spain. But just looking at the last full Mobile World Congress here in Barcelona, in pre-pandemic to now, very different show. We went from a show that was very much focused on mobility and smartphones, to a show that was all about cars. You know, we had cars everywhere, 'cause we were talking about smart cities and connected cars, to now a show this year that is very much focused on B2B. And so a lot of companies that are here to either work with the carriers, or also talk about sustainability for instance, or enable what is the next future evolution of computing with XR and VR. >> So Jim, talk to us a little bit about your background. You, I was doing a little sleuthing on you. You're really focusing on disruptive innovation. We talk about disruption a lot in different industries. We're seeing a lot of disruption in telco. We're seeing a lot of frenemies going on. Give us your thoughts about what you're seeing at this year's event. >> Well, there's some really exciting things. I listened to the keynote from Orange's CEO, and she was complaining that 55% of the traffic on her network is from five companies. And then the CEO of Deutsche Telecom got up, and he was complaining that 60% of the traffic on his network is from six entities. So do you think they coordinated pre, pre-show? But really what they're saying is, these OTT, you know, Netflix and YouTube, they should be paying us for access. Now, this is killer funny. The front page today of the show, "Daily," the CO-CEO of Netflix says, "Hey, we make less profit than the telcos, "so you should be paying us, "not the other way around." You know, we spend half of the money we make just on developing content. So, this is really interesting. The orange CEO said, "We're not challenging net neutrality. "We don't want more taxes." But boom. So this is disruptive. Huge pressure. 67% of all mobile traffic is video, right? So it's a big hog bandwidth wise. So how are they going to do this? Now, I look at it, and the business model for the, the telcos, is really selling sim cards and smartphones. But for every dollar of revenue there, there's five plus dollars in apps, and consulting and everything else. So really, but look at how they're structured. They can't, you know, take somebody who talks to the public and sells sim cards, and turn 'em in, turn 'em in to an app developer. So how are they going to square this circle? So I see some, they're being disrupted because they're sticking to what they've historically done. >> But it's interesting because at the end of the day, the conversation that we are having right now is the conversation that we had 10 years ago, where carriers don't want to just be a dumb pipe, right? And that's what they are now returning to. They tried to be media as well, but that didn't work out for most carriers, right? It is a little bit better in the US. We've seen, you know, some success there. But, but here has been more difficult. And I think that's the, the concern, that even for the next, you know, evolution, that's the, their role. >> So how do they, how do they balance this dumb pipe idea, with the fact that if you make the toll high enough, being a dumb pipe is actually a pretty good job. You know, sit back, collect check, go to the beach, right? So where, where, where, where does this end up? >> Well, I think what's going to happen is, if you see five to 15 X the revenue on top of a pipe, you know, the hyperscalers are going to start going after the business. The consulting companies like PWC, McKinsey, the app developers, they're... So how do you engage those communities as a telco to get more revenue? I think this is a question that they really need to look at. But we tend to stick within our existing business model. I'll just give you one stat that blows me away. Uber is worth more than every taxi cab company in North America added together. And so the taxi industry owns billions in assets in cars and limousines. Uber doesn't own a single vehicle. So having a widely distributed app, is a huge multiplier on valuation. And I look to a company like Safari in Kenya, which developed M-Pesa, which Pesa means mo, it's mobile money in Swahili. And 25% of the country's GDP is facilitated by M-Pesa. And that's not even on smartphones. They're feature phones, Nokia phones. I call them dumb phones, but Nokia would call them "feature phones." >> Yeah. >> So think about that. Like 25, now transactions are very small, and the cut is tiny. But when you're facilitating 25% of a country's GDP, >> Yeah. >> Tiny, over billions of transactions is huge. But that's not the way telcos have historically thought or worked. And so M-Pesa and Safari shows the way forward. What do you think on that? >> I, I think that the experience, and what they can layer on top from a services perspective, especially in the private sector, is also important. I don't, I never believe that a carrier, given how they operate, is the best media company in the world, right? It is a very different world. But I do think that there's opportunity, first of all, to, to actually tell their story in a different way. If you're thinking about everything that a network actually empowers, there's a, there's a lot there. There's a lot that is good for us as, as society. There's a lot that is good for business. What can they do to start talking about differently about their services, and then layer on top of what they offer? A better way to actually bring together private and public network. It's not all about cellular, wifi and cellular coming together. We're talking a lot about satellite here as well. So, there's definitely more there about quality of service. Is, is there though, almost a biological inevitability that prevents companies from being able to navigate that divide? >> Hmm. >> Look at, look at when, when, when we went from high definition 720P, very exciting, 1080P, 4K. Everybody ran out and got a 4K TV. Well where was the, where was the best 4K content coming from? It wasn't, it wasn't the networks, it wasn't your cable operator, it was YouTube. It was YouTube. If you had suggested that 10 years before, that that would happen, people would think that you were crazy. Is it possible for folks who are now leading their companies, getting up on stage, and daring to say, "This content's coming over, "and I want to charge you more "for using my pipes." It's like, "Really? Is that your vision? "That's the vision that you want to share with us here?" I hear the sound of dead people walking- (laughing) when I hear comments like that. And so, you know, my students at Wharton in the CTO program, who are constantly looking at this concept of disruption, would hear that and go, "Ooh, gee, did the board hear what that person said?" I, you know, am I being too critical of people who could crush me like a bug? (laughing) >> I mean, it's better that they ask the people with money than not consumers to pay, right? 'Cause we've been through a phase where the carriers were actually asking for more money depending on critical things. Like for instance, if you're doing business email, then were going to charge you more than if you were a consumer. Or if you were watching video, they would charge you more for that. Then they understood that a consumer would walk away and go somewhere else. So they stopped doing that. But to your point, I think, and, and very much to what you focus from a disruption perspective, look at what Chat GTP and what Microsoft has been doing. Not much talk about this here at the show, which is interesting, but the idea that now as a consumer, I can ask new Bing to get me the 10 best restaurants in Barcelona, and I no longer go to Yelp, or all the other businesses where I was going to before, to get their recommendation, what happens to them? You're, you're moving away, and you're taking eyeballs away from those websites. And, and I think that, that you know, your point is exactly right. That it's, it's about how, from a revenue perspective, you are spending a lot of money to facilitate somebody else, and what's in it for you? >> Yeah. And to be clear, consumers pay for everything. >> Always. Always. (laughs) >> Taxpayers and consumers always pay for everything. So there is no, "Well, we're going to make them pay, so you don't have to pay." >> And if you are not paying, you are the product. Exactly. >> Yes. (laughing) >> Carolina, talk a little bit about what you're seeing at the event from some of the infrastructure players, the hyperscalers, obviously a lot of enterprise focus here at this event. What are some of the things that you're seeing? Are you impressed with, with their focus in telco, their focus to partner, build an ecosystem? What are you seeing? >> I'm seeing also talk about sustainability, and enabling telco to be more sustainable. You know, there, there's a couple of things that are a little bit different from the US where I live, which is that telcos in Europe, have put money into sustainability through bonds. And so they use the money that they then get from the bonds that they create, to, to supply or to fuel their innovation in sustainability. And so there's a dollar amount on sustainability. There's also an opportunity obviously from a growth perspective. And there's a risk mitigation, right? Especially in Europe, more and more you're going to be evaluated based on how sustainable you are. So there are a lot of companies here, if you're thinking about the Ciscos of the world. Dell, IBM all talking about sustainability and how to help carriers measure, and then obviously be more sustainable with their consumption and, and power. >> Going to be interesting to see where that goes over the years, as we talk to, every company we talk to at whatever show, has an ESG sustainability initiative, and only, well, many of them only want to work with other companies who have the same types of initiative. So a lot of, great that there's focus on sustainability, but hopefully we'll see more action down the road. Wanted to ask you about your book, "Blind," the name is interesting, "Blindsided." >> Well, I just want to tag on to this. >> Sure. >> One of the most exciting things for me is fast charging technology. And Shalmie, cell phone, or a smartphone maker from China, just announced yesterday, a smartphone that charges from 0 to 100% in five minutes. Now this is using GAN FEST technology. And the leader in the market is a company called Navitas. And this has profound implications. You know, it starts with the smartphone, right? But then it moves to the laptops. And then it'll move to EV's. So, as we electrify the $10 trillion a year transportation industry, there's a huge opportunity. People want charging faster. There's also a sustainability story that, to Carolina's point, that it uses less electricity. So, if we electrify the grid in order to support transportation, like the Tesla Semi's coming out, there are huge demands over a period. We need energy efficiency technologies, like this GAN FEST technology. So to me, this is humongous. And it, we only see it here in the show, in Shalmie, saying, "Five minutes." And everybody, the consumers go, "Oh, that's cool." But let's look at the bigger story, which is electrifying transportation globally. And this is going to be big. >> Yeah. And, and to, and to double click on that a little bit, to be clear, when we talk about fast charging today, typically it's taking the battery from a, not a zero state of charge, but a relatively low state of charge to 80%. >> Yep. >> Then it tapers off dramatically. And that translates into less range in an EV, less usable time on any other device, and there's that whole linkage between the power in, and the battery's ability to be charged, and how much is usable. And from a sustainability perspective, we are going to have an avalanche of batteries going into secondary use cases over time. >> They don't get tossed into landfills contrary to what people might think. >> Yep. >> In fact, they are used in a variety of ways after their primary lifespan. But that, that is, that in and of itself is a revolutionary thing. I'm interested in each of your thoughts on the China factor. Glaringly absent here, from my perspective, as sort of an Apple fanboy, where are they? Why aren't they talking about their... They must, they must feel like, "Well we just don't need to." >> We don't need to. We just don't need to. >> Absolutely. >> And then you walk around and you see these, these company names that are often anglicized, and you don't necessarily immediately associate them with China, but it's like, "Wait a minute, "that looks better than what I have, "and I'm not allowed to have access to that thing." What happens in the future there geopolitically? >> It's a pretty big question for- >> Its is. >> For a short little tech show. (Caroline laughs) But what happens as we move forward? When is the entire world going to be able to leverage in a secure way, some of the stuff that's coming out of, if they're not the largest economy in the world yet, they shortly will be. >> What's the story there? >> Well, it's interesting that you mentioned First Apple that has never had a presence at Mobile World Congress. And fun enough, I'm part of the GSMA judges for the GLOMO Awards, and last night I gave out Best Mobile Phone for last year, and it was to the iPhone4 Team Pro. and best disruptive technology, which was for the satellite function feature on, on the new iPhone. So, Apple might not be here, but they are. >> Okay. >> And, and so that's the first thing. And they are as far as being top of mind to every competitor in the smartphone market still. So a lot of the things that, even from a design perspective that you see on some of the Chinese brands, really remind you of, of Apple. What is interesting for me, is how there wouldn't be, with the exception of Samsung and Motorola, there's no one else here that is non-Chinese from a smartphone point of view. So that's in itself, is something that changed dramatically over the years, especially for somebody like me that still remember Nokia being the number one in the market. >> Huh. >> So. >> Guys, we could continue this conversation. We are unfortunately out of time. But thank you so much for joining Dave and me, talking about your perspectives on the event, the industry, the disruptive forces. It's going to be really interesting to see where it goes. 'Cause at the end of the day, it's the consumers that just want to make sure I can connect wherever I am 24 by seven, and it just needs to work. Thank you so much for your insights. >> Thank you. >> Lisa, it's been great. Dave, great. It's a pleasure. >> Our pleasure. For our guests, and for Dave Nicholson, I'm Lisa Martin. You're watching, "theCUBE," the leader in live and emerging tech coverage coming to you day three of our coverage of MWC 23. Stick around. Our next guest joins us momentarily. (outro music)

(upbeat music) >> Hey everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California. We've got Sam Kassoumeh, co-founder and chief operating office at SecurityScorecard here remotely coming in. Thanks for coming on Sam. Security, Sam. Thanks for coming on. >> Thank you, John. Thanks for having me. >> Love the security conversations. I love what you guys are doing. I think this idea of managed services, SaaS. Developers love it. Operation teams love getting into tools easily and having values what you guys got with SecurityScorecard. So let's get into what we were talking before we came on. You guys have a unique solution around ratings, but also it's not your grandfather's pen test want to be security app. Take us through what you guys are doing at SecurityScorecard. >> Yeah. So just like you said, it's not a point in time assessment and it's similar to a traditional credit rating, but also a little bit different. You can really think about it in three steps. In step one, what we're doing is we're doing threat intelligence data collection. We invest really heavily into R&D function. We never stop investing in R&D. We collect all of our own data across the entire IPV force space. All of the different layers. Some of the data we collect is pretty straightforward. We might crawl a website like the example I was giving. We might crawl a website and see that the website says copyright 2005, but we know it's 2022. Now, while that signal isn't enough to go hack and break into the company, it's definitely a signal that someone might not be keeping things up to date. And if a hacker saw that it might encourage them to dig deeper. To more complex signals where we're running one of the largest DNS single infrastructures in the world. We're monitoring command and control malware and its behaviors. We're essentially collecting signals and vulnerabilities from the entire IPV force space, the entire network layer, the entire web app player, leaked credentials. Everything that we think about when we talk about the security onion, we collect data at each one of those layers of the onion. That's step one. And we can do all sorts of interesting insights and information and reports just out of that thread intel. Now, step two is really interesting. What we do is we go identify the attack surface area or what we call the digital footprint of any company in the world. So as a customer, you can simply type in the name of a company and we identify all of the domains, sub domains, subsidiaries, organizations that are identified on the internet that belong to that organization. So every digital asset of every company we go out and we identify that and we update that every 24 hours. And step three is the rating. The rating is probabilistic and it's deterministic. The rating is a benchmark. We're looking at companies compared to their peers of similar size within the same industry and we're looking at how they're performing. And it's probabilistic in the sense that companies that have an F are about seven to eight times more likely to experience a breach. We're an A through F scale, universally understood. Ds and Fs, more likely to experience a breach. A's we see less breaches now. Like I was mentioning before, it doesn't mean that an F is always going to get hacked or an A can never get hacked. If a nation state targets an A, they're going to eventually get in with enough persistence and budget. If the pizza shop on the corner has an F, they may never get hacked because no one cares, but natural correlation, more doors open to the house equals higher likelihood someone unauthorized is going to walk in. So it's really those three steps. The collection, we map it to the surface area of the company and then we produce a rating. Today we're rating about 12 million companies every single day. >> And how many people do you have as customers? >> We have 50,000 organizations using us, both free and paid. We have a freemium tier where just like Yelp or a LinkedIn business profile. Any company in the world has a right to go claim the score. We never extort companies to fix the score. We never charge a company to see the score or fix it. Any company in a world without paying us a cent can go in. They can understand what we're seeing about them, what a hacker could see about their environment. And then we empower them with the tools to fix it and they can fix it and the score will go up. Now companies pay us because they want enterprise capabilities. They want additional modules, insights, which we can talk about. But in total, there's about 50,000 companies that at any given point in time, they're monitoring about a million and a half organizations of the 12 million that we're rating. It sounds like Google. >> If you want to look at it. >> Sounds like Google Search you got going on there. You got a lot of search and then you create relevance, a score, like a ranking. >> That's precisely it. And that's exactly why Google ventures invested in us in our Series B round. And they're on our board. They looked and they said, wow, you guys are building like a Google Search engine over some really impressive threat intelligence. And then you're distilling it into a score which anybody in the world can easily understand. >> Yeah. You obviously have page rank, which changed the organic search business in the late 90s, early 2000s and the rest is history. AdWords. >> Yeah. >> So you got a lot of customer growth there potentially with the opt-in customer view, but you're looking at this from the outside in. You're looking at companies and saying, what's your security posture? Getting a feel for what they got going on and giving them scores. It sounds like it's not like a hacker proof. It's just more of a indicator for management and the team. >> It's an indicator. It's an indicator. Because today, when we go look at our vendors, business partners, third parties were flying blind. We have no idea how they're doing, how they're performing. So the status quo for the last 20 years has been perform a risk assessments, send a questionnaire, ask for a pen test and an audit evidence. We're trying to break that cycle. Nobody enjoys it. They're long tail. It's a trust without verification. We don't really like that. So we think we can evolve beyond this point in time assessment and give a continuous view. Now, today, historically, we've been outside in. Not intrusive, and we'll show you what a hacker can see about an environment, but we have some cool things percolating under the hood that give more of a 360 view outside, inside, and also a regulatory compliance view as well. >> Why is the compliance of the whole third party thing that you're engaging with important? Because I mean, obviously having some sort of way to say, who am I dealing with is important. I mean, we hear all kinds of things in the security landscape, oh, zero trust, and then we hear trust, supply chain, software risk, for example. There's a huge trust factor there. I need to trust this tool or this container. And then you got the zero trust, don't trust anything. And then you've got trust and verify. So you have all these different models and postures, and it just seems hard to keep up with. >> Sam: It's so hard. >> Take us through what that means 'cause pen tests, SOC reports. I mean the clouds help with the SOC report, but if you're doing agile, anything DevOps, you basically would need to do a pen test like every minute. >> It's impossible. The market shifted to the cloud. We watched and it still is. And that created a lot of complexity, not to date myself. But when I was starting off as a security practitioner, the data center used to be in the basement and I would have lunch with the database administrator and we talk about how we were protecting the data. Those days are long gone. We outsource a lot of our key business practices. We might use, for example, ADP for a payroll provider or Dropbox to store our data. But we've shifted and we no longer no who that person is that's protecting our data. They're sitting in another company in another area unknown. And I think about 10, 15 years ago, CISOs had the realization, Hey, wait a second. I'm relying on that third party to function and operate and protect my data, but I don't have any insight, visibility or control of their program. And we were recommended to use questionnaires and audit forms, and those are great. It's good hygiene. It's good practice. Get to know the people that are protecting your data, ask them the questions, get the evidence. The challenge is it's point in time, it's limited. Sometimes the information is inaccurate. Not intentionally, I don't think people intentionally want to go lie, but Hey, if there's a $50 million deal we're trying to close and it's dependent on checking this one box, someone might bend a rule a little bit. >> And I said on theCUBE publicly that I think pen test reports are probably being fudged and dates being replicated because it's just too fast. And again, today's world is about velocity on developers, trust on the code. So you got all kinds of trust issues. So I think verification, the blue check mark on Twitter kind of thing going on, you're going to see a lot more of that and I think this is just the beginning. I think what you guys are doing is scratching the surface. I think this outside in is a good first step, but that's not going to solve the internal problem that still coming and have big surface areas. So you got more surface area expanding. I mean, IOT's coming in, the Edge is coming fast. Never mind hybrid on-premise cloud. What's your organizations do to evaluate the risk and the third party? Hands shaking, verification, scorecards. Is it like a free look here or is it more depth to it? Do you double click on it? Take us through how this evolves. >> John it's become so disparate and so complex, Because in addition to the market moving to the cloud, we're now completely decentralized. People are working from home or working hybrid, which adds more endpoints. Then what we've learned over time is that it's not just a third party problem, because guess what? My third parties behind the scenes are also using third parties. So while I might be relying on them to process my customer's payment information, they're relying on 20 vendors behind the scene that I don't even know about. I might have an A, they might have an A. It's really important that we expand beyond that. So coming out of our innovation hub, we've developed a number of key capabilities that allow us to expand the value for the customer. One, you mentioned, outside in is great, but it's limited. We can see what a hacker sees and that's helpful. It gives us pointers where to maybe go ask double click, get comfort, but there's a whole nother world going on behind the firewall inside of an organization. And there might be a lot of good things going on that CISO security teams need to be rewarded for. So we built an inside module and component that allows teams to start plugging in the tools, the capabilities, keys to their cloud environments. And that can show anybody who's looking at the scorecard. It's less like a credit score and more like a social platform where we can go and look at someone's profile and say, Hey, how are things going on the inside? Do they have two-factor off? Are there cloud instances configured correctly? And it's not a point in time. This is a live connection that's being made. This is any point in time, we can validate that. The other component that we created is called an evidence locker. And an evidence locker, it's like a secure vault in my scorecard and it allows me to upload things that you don't really stand for or check for. Collateral, compliance paperwork, SOC 2 reports. Those things that I always begrudgingly email. I don't want to share with people my trade secrets, my security policies, and have it sit on their exchange server. So instead of having to email the same documents out, 300 times a month, I just upload them to my evidence locker. And what's great is now anybody following my scorecard can proactively see all the great things I'm doing. They see the outside view. They see the inside view. They see the compliance view. And now they have the holy grail view of my environment and can have a more intelligent conversation. >> Access to data and access methods are an interesting innovation area around data lineage. Tracing is becoming a big thing. We're seeing that. I was just talking with the Snowflake co-founder the other day here in theCUBE about data access and they're building a proprietary mesh on top of the clouds to figure out, Hey, I don't want to give just some tool access to data because I don't know what's on the other side of those tools. Now they had a robust ecosystem. So I can see this whole vendor risk supply chain challenge around integration as a huge problem space that you guys are attacking. What's your reaction to that? >> Yeah. Integration is tricky because we want to be really particular about who we allow access into our environment or where we're punching holes in the firewall and piping data out out of the environment. And that can quickly become unwieldy just with the control that we have. Now, if we give access to a third party, we then don't have any control over who they're sharing our information with. When I talk to CISOs today about this challenge, a lot of folks are scratching their head, a lot of folks treat this as a pet project. Like how do I control the larger span beyond just the third parties? How do I know that their software partners, their contractors that they're working with building their tools are doing a good job? And even if I know, meaning, John, you might send me a list of all of your vendors. I don't want to be the bad guy. I don't really have the right to go reach out to my vendors' vendors knocking on their door saying, hi, I'm Sam. I'm working with John and he's your customer. And I need to make sure that you're protecting my data. It's an awkward chain of conversation. So we're building some tools that help the security teams hold the entire ecosystem accountable. We actually have a capability called automatic vendor discovery. We can go detect who are the vendors of a company based on the connections that we see, the inbound and outbound connections. And what often ends up happening John is we're bringing to the attention to our customers, awareness about inbound and outbound connections. They had no idea existed. There were the shadow IT and the ghost vendors that were signed without going through an assessment. We detect those connections and then they can go triage and reduce the risk accordingly. >> I think that risk assessment of vendors is key. I was just reading a story about this, about how a percentage, I forget the number. It was pretty large of applications that aren't even being used that are still on in companies. And that becomes a safe haven for bad actors to hang out and penetrate 'cause they get overlooked 'cause no one's using them, but they're still online. And so there's a whole, I called cleaning up the old dead applications that are still connected. >> That happens all the time. Those applications also have applications that are dead and applications that are alive may also have users that are dead as well. So you have that problem at the application level, at the user level. We also see a permutation of what you describe, which is leftover artifacts due to configuration mistakes. So a company just put up a new data center, a satellite office in Singapore and they hired a team to go install all the hardware. Somebody accidentally left an administrative portal exposed to the public internet and nobody knew the internet works, the lights are on, the office is up and running, but there was something that was supposed to be turned off that was left turned on. So sometimes we bring to company's attention and they say, that's not mine. That doesn't belong to me. And we're like, oh, well, we see some reason why. >> It's his fault. >> Yeah and they're like, oh, that was the contractor set up the thing. They forgot to turn off the administrative portal with the default login credentials. So we shut off those doors. >> Yeah. Sam, this is really something that's not talked about a lot in the industry that we've become so reliant on managed services and other people, CISOs, CIOs, and even all departments that have applications, even marketing departments, they become reliant on agencies and other parties to do stuff for them which inherently just increases the risk here of what they have. So there inherently could be as secure as they could be, but yet exposed completely on the other side. >> That's right. We have so many virtual touch points with our partners, our vendors, our managed service providers, suppliers, other third parties, and all the humans that are involved in that mix. It creates just a massive ripple effect. So everybody in a chain can be doing things right. And if there's one bad link, the whole chain breaks. I know it's like the cliche analogy, but it rings true. >> Supply chain trust again. Trust who you trust. Let's see how those all reconcile. So Sam, I have to ask you, okay, you're a former CISO. You've seen many movies in the industry. Co-founded this company. You're in the front lines. You've got some cool things happening. I can almost imagine the vision is a lot more than just providing a rating and score. I'm sure there's more vision around intelligence, automation. You mentioned vault, wallet capabilities, exchanging keys. We heard at re:Inforce automated reasoning, metadata reasoning. You got all kinds of crypto and quantum. I mean, there's a lot going on that you can tap into. What's your vision where you see SecurityScorecard going? >> When we started the company, the rating was the thing that we sold and it was a language that helped technical and non-technical folks alike level the playing field and talk about risk and use it to drive their strategy. Today, the rating just opens the door to that discussion and there's so much additional value. I think in the next one to two years, we're going to see the rating becomes standardized. It's going to be more frequently asked or even required or leveraged by key decision makers. When we're doing business, it's going to be like, Hey, show me your scorecard. So I'm seeing the rating get baked more and more the lexicon of risk. But beyond the rating, the goal is really to make a world a safer place. Help transform and rise the tide. So all ships can lift. In order to do that, we have to help companies, not only identify the risk, but also rectify the risk. So there's tools we build to really understand the full risk. Like we talked about the inside, the outside, the fourth parties, fifth parties, the real ecosystem. Once we identified where are all the Fs and bad things, will then what? So couple things that we're doing. We've launched a pro serve arm to help companies. Now companies don't have to pay to fix the score. Anybody, like I said, can fix the score completely free of charge, but some companies need help. They ask us and they say, Hey, I'm looking for a trusted advisor. A Sherpa, a guide to get me to a better place or they'll say, Hey, I need some pen testing services. So we've augmented a service arm to help accelerate the remediation efforts. We're also partnered with different industries that use the rating as part of a larger picture. The cyber rating isn't the end all be all. When companies are assessing risk, they may be looking at a financial ratings, ESG ratings, KYC AML, cyber security, and they're trying to form a complete risk profile. So we go and we integrate into those decision points. Insurance companies, all the top insurers, re-insurers, brokers are leveraging SecurityScorecard as an ingredient to help underwrite for cyber liability insurance. It's not the only ingredient, but it helps them underwrite and identify the help and price the risk so they can push out a policy faster. First policy is usually the one that's signed. So time to quote is an important metric. We help to accelerate that. We partner with credit rating agencies like Fitch, who are talking to board members, who are asking, Hey, I need a third party, independent verification of what my CISO is saying. So the CISO is presenting the rating, but so are the proxy advisors and the ratings companies to the board. So we're helping to inform the boards and evolve how they're thinking about cyber risk. We're helping with the insurance space. I think that, like you said, we're only scratching the surface. I can see, today we have about 50,000 companies that are engaging a rating and there's no reason why it's not going to be in the millions in just the next couple years here. >> And you got the capability to bring in more telemetry and see the new things, bring that into the index, bring that into the scorecard and then map that to potential any vulnerabilities. >> Bingo. >> But like you said, the old days, when you were dating yourself, you were in a glass room with a door lock and key and you can see who's two folks in there having lunch, talking database. No one's going to get hurt. Now that's gone, right? So now you don't know who's out there and machines. So you got humans that you don't know and you got machines that are turning on and off services, putting containers out there. Who knows what's in those payloads. So a ton of surface area and complexity to weave through. I mean only is going to get done with automation. >> It's the only way. Part of our vision includes not attempting to make a faster questionnaire, but rid ourselves of the process all altogether and get more into the continuous assessment mindset. Now look, as a former CISO myself, I don't want another tool to log into. We already have 50 tools we log into every day. Folks don't need a 51st and that's not the intent. So what we've done is we've created today, an automation suite, I call it, set it and forget it. Like I'm probably dating myself, but like those old infomercials. And look, and you've got what? 50,000 vendors business partners. Then behind there, there's another a hundred thousand that they're using. How are you going to keep track of all those folks? You're not going to log in every day. You're going to set rules and parameters about the things that you care about and you care depending on the nature of the engagement. If we're exchanging sensitive data on the network layer, you might care about exposed database. If we're doing it on the app layer, you're going to look at application security vulnerabilities. So what our customers do is they go create rules that say, Hey, if any of these companies in my tier one critical vendor watch list, if they have any of these parameters, if the score drops, if they drop below a B, if they have these issues, pick these actions and the actions could be, send them a questionnaire. We can send the questionnaire for you. You don't have to send pen and paper, forget about it. You're going to open your email and drag the Excel spreadsheet. Those days are over. We're done with that. We automate that. You don't want to send a questionnaire, send a report. We have integrations, notify Slack, create a Jira ticket, pipe it to ServiceNow. Whatever system of record, system of intelligence, workflow tools companies are using, we write in and allow them to expedite the whole. We're trying to close the window. We want to close the window of the attack. And in order to do that, we have to bring the attention to the people as quickly as possible. That's not going to happen if someone logs in every day. So we've got the platform and then that automation capability on top of it. >> I love the vision. I love the utility of a scorecard, a verification mark, something that could be presented, credential, an image, social proof. To security and an ongoing way to monitor it, observe it, update it, add value. I think this is only going to be the beginning of what I would see as much more of a new way to think about credentialing companies. >> I think we're going to reach a point, John, where and some of our customers are already doing this. They're publishing their scorecard in the public domain, not with the technical details, but an abstracted view. And thought leaders, what they're doing is they're saying, Hey, before you send me anything, look at my scorecard securityscorecard.com/securityrating, and then the name of their company, and it's there. It's in the public domain. If somebody Googles scorecard for certain companies, it's going to show up in the Google Search results. They can mitigate probably 30, 40% of inbound requests by just pointing to that thing. So we want to give more of those tools, turn security from a reactive to a proactive motion. >> Great stuff, Sam. I love it. I'm going to make sure when you hit our site, our company, we've got camouflage sites so we can make sure you get the right ones. I'm sure we got some copyright dates. >> We can navigate the decoys. We can navigate the decoys sites. >> Sam, thanks for coming on. And looking forward to speaking more in depth on showcase that we have upcoming Amazon Startup Showcase where you guys are going to be presenting. But I really appreciate this conversation. Thanks for sharing what you guys are working on. We really appreciate. Thanks for coming on. >> Thank you so much, John. Thank you for having me. >> Okay. This is theCUBE conversation here in Palo Alto, California. Coming in from New York city is the co-founder, chief operating officer of securityscorecard.com. I'm John Furrier. Thanks for watching. (gentle music)

(upbeat music) >> Hello, and welcome to theCUBE special presentation of Unstoppable Domains Partner Showcase. I'm John Furrier, your host of theCUBE. We've got a great conversation talking about the future of the infrastructure of Web3, all around domains, non fungible tokens and more. Two great guests, Charlie Brooks with Business Development of Unstoppable Domains, and Michael Williams, Product Leader and Advisor with Unstoppable Domains. Gentlemen, thanks for coming on theCUBE, Partner Showcase with Unstoppable Domains. >> Thanks John, excited to be here. >> So I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure. Shift to Web3 is being called, but people who have been doing this for a while know that you see the blockchain, you see decentralization, you see immutability all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as you can imagine, you guys in the middle of it. So you guys are in the sweet spot of what I call the Pragmatic pioneers. You guys are the building solutions that are making a difference, like single sign-on you have the login product, let's get into it. What is the path to a digital identity beyond the web? 'Cause we know what web identity is. But now that the web is being abstracted a away by this new Web3 layer, what is digital identity? >> I can take that one. So I think what we're really seeing is this transition away from a purely physical identity. Where your online identity is really just a reflection of the parts of your physical identity. Where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account, or TikTok, or email address or username, all of these things together make up your digital identity. So congrats, if you have any of those things, you already have one. >> We see that all the time with Linktree, people put their Linktree out there and it's got the zillion handles. We all get up to Instagram. Everyone's got like zillion identities. Is that a problem or an opportunity? >> I think it's just a reality. The fact is our identities are spread across all of these different services and platforms that we use. The problem with something like Linktree is that it is owned by Linktree. If I won the lottery, purchased Linktree and decided I wanted to change your personal website, John, I could easily do that. Moving to the architecture that we have and NFT architecture, changes that significantly. It puts a lot of power back in the hands of the people who actually own those identities. I do a lot of CUBE showcases with folks around talking about machine learning and AI, and the number one conversation that they bring up, the number one issue, is data. And they say, when data's siloed and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity if someone else is managing the service like Linktree. This is a cultural shift, and infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and unstoppable domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >> Sure, I think so. Our domains are NFTs, so they are ERC 721 tokens. And if you think about in the past Web2 identities are controlled by the platforms that we use. Twitter, Facebook, whatnot. There's really a lack of data portability there. Our accounts and data live on their servers, they can be deleted any time. So using an NFT to anchor your data identity, really gives you full control over your identity. It can't be deleted, it can't be revoked or edited, or changed without your permission. And really even better, the information you store on your entity domain can be plugged into the services you use, so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data's being used and where it's being stored. >> So the innovation here is the NFT is your identity. And a non fungible token NFT is different than say a fungible token. So for the folks out there that's trying to follow the bouncing ball, Michael, what's the difference between an NFT and a fungible token? And why is that important for identity? >> My favorite metaphor here is baseball cards versus dollar bills. So a dollar bill is fungible. If I have a dollar and you have a dollar, we can trade dollars and none of us is richer or poorer. If I have a Babe Ruth and you have a Hank Aaron, and we swap baseball cards, we have changed something fundamental. So the important thing about NFTs is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique, they're independent, they're owned by each one of us, and then we can't swap them interchangeably. >> And that's why you're seeing NFTs hot with art and artists, because it's like a property. It's a property issue, not so much- >> Absolutely >> Interchangeable or divisible kind of asset. >> Yep, it is ownership rights in digital form, yes. >> All right, so now let's get into what the identity piece. I think find that interesting because if I have something that's an NFT, it's non fungible, it's unique to me, it's property, my property my login, this sounds compelling. So how does login work with the NFT? Can you guys take us through that architecture, what does it do? How does it work? And what's the benefit? >> Good, so the way our login product works is it effectively uses your NFT domain. So Michael.crypto, for example, as the authentication piece of a login session. So basically when I go and I try to log in with my domain, I type in Michael.crypto, I sign it with my wallet which cryptographically proves that I am this human, this is me, I have the rights to log in. And then when I do so, I have the ability to share certain parts of my identity information with the applications that I use. So it really blends the ease of use from Web2 of just a standard like login with Gmail, SSO experience, with all of the security and privacy benefits of Web3. >> How important is single sign-on? Because right now people are used to seeing things like log with your GitHub handle or LinkedIn, or Google, Apple. You seeing people offering login. What's the difference here from those solutions and why does it make sense for the user? >> Sure, the big difference is what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data, they're tracking everything you do. Login with unstoppable handles not only authentication, but data sharing as well. So when you log in a domain owner can choose to share aspects of their online identities, such as first name, preferred language, profile picture, location. So this is a user controlled way of using a sign-on where their permissioning these different of their identity. And really apps can use this information to enable new experiences, such as, for example, website might automatically enable high contrast mode for someone visually impaired. It could pre-populate your friends from a decentralized social graph. So, what we're doing is taking the best parts of Web2 SSO and combining them with the best of Web3. So, no more losing your password, entering in the same data hundreds of times depending on other services to keep your information safe. Login with unstoppable really puts you in complete control of your data. And a big part of that is you're not going to have 80 plus usernames and passwords anymore. We have these tools like password managers that exist to put a bandaid on this issue, but it's not really a long term solution. So what we're building is really seamless onboarding where everything can be tied to your domains so that you can navigate to different apps in a much more seamless way. >> Michael, I got to get your thoughts on this because in the product side, it's interesting, my mind's connecting some dots. If I have first of all, great convenience to reduce all those logins. So, check their little pain reduction. But when you just think about what's different, I can now broker my data as well as login. So let's just say, hypothetically, I'm cruising around some dApps and I'm doing things in earning reputation, or attention, or points, or whatever utility tokens. There could be a way for me to control what I own. I'm the product, I own the data. Is that where this is going? >> I think it's definitely a direction it could go, say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard. One of the things that I could request from a user, is their address. I can figure out where they live, what city they're in, that will help inform me the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase. We can start to build a stronger relationship between the applications that people use, and the people that use them. And try to optimize that whole experience, and try to just transfer information back and forth to make everyone's lives better. >> What's the roadmap on the business side Charlie, when you see companies adopting it, they're probably taking babies steps they're crawling before they walk, they're walking before they run. I can see decentralized applications in the future where there's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the script flips to the user first. Okay, so I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >> Sure, so a lot of Web3 apps are very sensitive about respecting the information that their users are providing. So, what we're doing is offering different ways for apps can touch with their users in a way that is user controlled. So, an example there is that a lot of Web3 companies will use WalletConnect to allow users to log in using a wallet address. An issue there is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So, what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who our unique user is. And the app is able to collect that information, they don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. It's really simple to maintain as well. So one example there is if you are a DeFi platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet. All because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies will ask users to follow them on Twitter or Discord when they need to provide updates or bug bounties, all these different things. And login if unstoppable lets them permission email addresses so they can collect emails if they want to do a newsletter. And instead of harvesting data from elsewhere and forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. I'm supporting your project, I want to be kept up to date with bugs or bounties or rewards programs. So really it's just a better way for users to share the data that they're willing to with dAPPs, and dAPPs can use it to create all sorts of incentives and really just understand their users on a different level. >> How is the development Michael, going on the smart contract side of the business? Ethereum has always been heralded as being very developer focused. There's been created innovations, you still got gas fees out there. You still got to do some things. How is the development environment? How are the applications coming? 'Cause I can see the flywheel kicking in as the developer front gets more streamlined, more efficient. And now you got the identity piece nailed down. I just see a lot of dominoes falling at the same time. What's the status on the DEV side. What you're doing. >> Good. The fascinating thing about crypto is how quickly it changes. When I joined Ethereum there was pretty reasonable still for transactions. It was very cheap to get things done very fast. With a look at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two. And we've moved over to the polygon as our primary source of record, which is built on top of Ethereum. Of course, I think saved well over a hundred million in gas fees for our users. We're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things. And really where of this industry is going to take us. In many ways we are just as much passengers as the other people floating around the ecosystem as well. >> It's certainly getting faster every day, I'm seeing a huge uptake on Ethereum. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join Web3 companies. This goes to show you this cultural shift and you're going to see a lot more companies getting involved. So I got to ask you Charlie, on the BizDev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? They jumping in full throttle? What's the roadmap? What's the best practice for people to get started with unstoppable? >> Absolutely. We're lucky that we get a lot of inbound interest from companies Web2 and Web3, because they first want to secure their domains. And we do a ton of work on the back end to protect trademark domains. We want to avoid squatting as much as possible. We don't think that's the spirit of Web3 at all. And certainly not what the original tension of the internet was. So, fair amount of companies will reach out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website, unstoppabledomains.com is a great starting point. We have an app submission page where apps can reach out to us, even request a grant. We have a grant program to help developers get started, provide them some resources to work with us and integrate some of our technology. We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a wallet and an exchange, as well as what it takes to integrate login with unstoppable, which is actually a super easy integration as well, which we're really excited about. So yeah, I'd say check out the website, apply for a grant if you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on Telegram, email. We're very reachable and we're always happy to chat with projects and learn more about what they're doing. >> What's the coolest thing you see going on Charlie, with your partners right now? What's the number one use case that's cool that people are jumping on right now to get in and get some success out of the gate? >> Maybe GameFi play to earn is huge. It's blowing up and the gaming community is really passionate, vibrant, just expanding like crazy. Same with DeFi, there's all this cool new stuff you can do with DeFi where no matter how big your portfolio is, you're able to stake and use all these interesting tools to grow your book. So it's super exciting to see and talk to all these projects. And, there's certainly an energy in the community where everyone wants to onboard the general public to Web3. So we're all working on these school projects, but we need everyone to come over from Web2, understand the advantages of DeFi, of GameFi of having an entity domain. So, I'm lucky that I'm one of the first layers there of meeting new projects and helping get access to more users so that they can grow along with us. >> I remember the early days of Bitcoin and Ethereum, we were giving it away. The community mantra was, give a Bitcoin to someone. That was like, >> Right. >> When you can actually give a Bitcoin to someone. What's the word of mouth or organic viral? I won't say growth hack 'cause that's got negative connotations. But what's the community's way of putting forth the mission for unstoppable? Is it just more domains? You guys have any programs got going on? Is it give it away? Obviously you can get domains on your site, but what's the way to get people ingratiated in and getting comfortable? >> So much of what we do is really to solve that question, answer that question. We spend a ton of time and energy just on education and whether that's specifically around domains or just general Web3. We have a podcast which is pretty exceptional, which talks to Web3 leaders from across the space and makes the project that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about our resources, of course. >> The pod, I think you guys are up to 117, but that's a deep dive. You guys go deep on the podcast. So that's where you go in. What else is new on digital identity? Where do you guys see the future going? Now that you get the baseline identity with the NFT. Makes a lot of sense, create innovation. Good logic, makes sense. Solid technically, what's next? >> I think this really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be. Like our data shouldn't live in these wild gardens, controlled by these large companies. Ultimately people should be responsible for their own identities. They should have control over of things that they do online. The data that's shared, the benefit of that data. It's about the world that we are working towards, is very much that. Where we are giving people the ability to be paid for sharing their data with companies. We're giving applications the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem through these products, to enable a better experience for everyone. So whether that's the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon, that just confirm that the person that you are you're looking at is actually a real person, not some bot that's been paid to load a review. The interesting thing about these products is they're so universally applicable. There are so many different ways that we can try to plug them in. So we are- >> A bots is a great example, double-edged sword. You can have a metaverse image and have pre-programmed conversations with liquid audio and the video application. Or it's a real person. How do you know the difference? These are going to be questions around who solves that problem. Now there's time for bots and there's a time not for bots. We all know what happens when you get into the game of manipulation, but also it can be helpful. This is where you got to be smart. And identity's critical in this future. Charlie, what's your reaction to the future of digital identity? So much to look at here on the trajectory. >> I think a big part of it is data portability. If you go to a site like Instagram, you're giving them all this content that's very personal to you, and you can't just pack up and leave Instagram. So we want a future where most of these apps are just a front end and you can navigate from one to the other and bring your data with you. And not be beholden to the companies that operate centralized servers. So, I think data portability is huge and it's going to open up a lot of doors. And just going back to that thought on cleaning up Web2 for a better web three. When I think about the Amazons, the Yelps of the world, there are all these bots, there are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. And I want to bring transparency back to the internet where when you see a review, you should know that that's a real human. And blockchain technology is enabling us to do that. And certainly FT domains are going to play a huge part of that. So I think that having an experience where you know and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. politically speaking, we've all seen all the issues with attacking communities and using bots and fake accounts to hit people's pain points, it's sad and certainly not something that we want to see continue happening. So, whatever we can do to give people their digital identity and help people understand that this is a real person on the other end, I think is huge for the future of the internet and really for society as well. >> That's a great call out there Charlie. Cleaning up the mess of Web 2.0, Web2, actually it was 2.0 technically, now Web3 is no point zero in it. But I saw on or listened to the podcast with Matt. This recent one, he had a great metaphor that went back to when I was growing up in the internet, you had IP addresses. And the mess there was, you couldn't find what you want to look. And no one could remember what to type in, 'cause you could type in IP address in the browser back then. And then DNS came out and then keywords that's web. Now that mess, now is fraud, misinformation, bot manipulation, deep fakes, many other kind of unwanted time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So, similar thing happening here, is that how you guys see it too? >> I think we're going back to some of the foundational architecture of the internet, DNS. And really bringing that forward about 30, 40 years in terms of technology. So loading in some more cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >> Awesome. Well guys, thanks so much for coming on and the spirit of TikTok, Emily summarizes asking, can you guys give us a quick TikTok moment, short comment on where this is all going, where is login, single sign-on mean and what should people do to steps to secure their digital identity? >> Sure, I'll jump in here. So, it's time for people to secure their digital identity. The great first step is going to sample domains and getting an NFT domain. You can control your data. You can do a lot of cool different things with your domain, including posting your own website that you will own forever, no one can take it away from you. I would certainly recommend that people join our Discord, Telegram communities, check out our podcasts. It's really great especially if you're new to crypto Web3. We do a great job of explaining all the basic concepts and expanding on them. So yeah, I would say, the time is now to get your digital identity and start embracing Web3 because it's really exploding right now. And there's just so many incredible advantages, especially for the user. >> Michael, what's your take? >> But not, have said it better myself. >> Like we always say, if you're not on the next wave, you're driftwood. And this is a big wave that's happening. It's pretty clear guys, it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on, the app integration. Congratulations and we got our CUBE domain too, by the way. So I think we're good. >> Excellent. >> So, we got to put it to use. Appreciate it, Charlie, Michael, thanks for coming on and sharing the update. >> It's pleasure. >> Welcome. >> Okay, this is theCUBE, with Unstoppable Domains Partner Showcase I'm John for your host, got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching. (upbeat music)

>>Hello, and welcome to the cube special presentation of unstoppable domains partner showcase. I'm John furrier, your host of the cube. We got a great conversation talking about the future of the infrastructure of web three, all around domains, non fungible tokens, and more two great guests. Charlie Brooks, with business development of ensemble domains, and Michael Williams, product leader and advisor with unstoppable doing gentlemen, thanks for coming on the cube partner showcase with unstoppable domains. >>Thanks John. Excited to be here. So >>I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure shift. Web three is being called, but people who have been doing this for a while, know that you see the blockchain, you see decentralization, you see immutability, all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as, as, as you can imagine, you guys are in the middle of it. So you guys are in, in, in the sweet spot of what I call the pragmatic pioneers. You guys are to building solutions that are making a difference like single sign-on. You have the login product, let's get into it. What is the path to I digital identity beyond the web, because we know what web identity is, but now that the web is kind of being abstracted away by this new web three layer, what is digital identity? >>Yeah, I can take that one. So I think what we're really seeing is this transition away from a purely physical identity where your digital life or where your, your online identity is really just a reflection of the, the parts of your physical identity, where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account or TechTalk or email address or username, all of these things together make up your digital identity. So congrats. If you have any of those things, you already have one. >>Yeah. And we see that all the time with link tree people put their link tree out there and it's got the zillion handles. You're right. We all get up to Instagram and everyone's got like zillion identities. Is that a problem or an opportunity? >>I think it's just a reality. The fact that as our identities are spread across all of these different services and platforms that we use, the problem with something like link tree is that it is owned by link tree. You know, if I won the lottery purchased link tree and decided I wanted to change your personal website, John, I could easily do that. Moving to the kind of architecture that we have. And then if T architecture changes that significantly, it puts a lot of power back in the hands of the people who actually own those identities. >>You know, I do a lot of cube showcases with folks rent on my machine, learning and AI, and the number one conversation that they bring up. The number one issue is data. And they say when data is siloed and, and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity. If someone else is managing the service like link tree, this is, this is a cultural shift. This is an infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and ensemble domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >>Sure. I think so. Our domains are NFTs, so they are ERC 7 21 tokens. And if you think about the past kind of web two identities are controlled by the platforms that we use, Twitter, Facebook, whatnot. There's a really a lack of data portability there. Our accounts and data live on their servers. They can be deleted at any time. So using an NFT to anchor your digital identity really gives you full control over your identity. You can't, it can't be deleted. It can't be revoked or edited or changed without your permission. And really, even better than information you store on your entity domain can be plugged into the services you use so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, kind of entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data is being used and where it's being stored. >>So the innovation here is the NFT is your identity and, and a non fungible token NFT is different than say a fungible tokens. So for the folks out there, that's trying to follow the bouncing ball. Michael, what's the difference between an NFT and a fungible token. And how does, and why is that important for identity? >>Yeah. My favorite metaphor here is baseball cards versus like dollar bills. So a dollar bill is fungible. If I have a dollar and then you have a dollar, we can trade dollars. And none of us is richer or poorer. If I have a babe Ruth and you have a Hank Aaron, and we swap baseball cards, like we have, we have changed something fundamental. So the, the important thing about NFT is, is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique. They're independent, they're owned by each one of us. And then we can kind of swap them interchangeably. >>And that's why you're seeing NFTs hot with art and artists, because it's like a property, it's a property issue, not so much absolutely changeable, a divisible kind of asset. >>It is a, it is ownership rights in digital >>Form. Yes. All right. So now let's get into what the, the identity piece. I think I find that interesting because if I have something that's an NFT, it's not fungible. It's unique to me. It's property, my property, my login, this sounds compelling. So how does log-in work with the NFT? Can you guys take us through that, that architecture, what does it do? How does it work? And what's the benefit? >>So the way our login product works is it effectively uses your NFT domain. So Michael dot crypto, for example, as the authentication piece of a, of a login session. So basically when I, when I go and I try to log in with my domain, I type in Michael dot crypto. I sign it with my wallet, which cryptographically proves that I am this human. This is me. I have the rights to log in. And then when I do so I have the ability to share certain parts of my identity information with the applications that I use. And so it really blends the best of the ease of use from web to have just a standard like login with Gmail SSL experience, with all of the security and privacy benefits of web three. >>How important is single sign-on because, I mean, right now people are used to like, seeing things like log with your kid hub handle or LinkedIn, or, you know, Google, apple. I mean, you're seeing people offering login. Okay. What's the difference here from those solutions and why is it make sense for the user? >>Sure. Yeah. The big differences, what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data and, you know, they're tracking everything you do logging in with unstoppable handles, not only authentication, but data sharing as well. So when you log in a domain or owner can choose to share aspects of their online identity, such as first name, preferred language profile, picture location. So this is a user controlled way of using a sign-on, where they are permissioning, these different pieces of their identity. And really apps can use this information to enable new experiences, such as for example, website might automatically enable high contrast mode for someone visually impaired. It could, pre-populate your friends from a decentralized social graph. So what we're doing is taking the best parts of web to SSL and combining them with the best parts of web three. >>So no more losing your password entering in the same data, hundreds of times, you know, depending on other services, keep your information safe. Logging with unstoppable really puts you in complete control of your data. And, you know, a big part of that is you're not going to have 80 plus usernames and passwords anymore. You know, we have these tools like password managers that exist to kind of put a bandaid on this issue, but it's not really a long-term solution. So we're, we're building is really seamless onboarding where everything can be tied to your domain so that you can navigate to different apps in a much more seamless way. >>Michael, I got to get your thoughts on this because on the product side, it's interesting. My mind's kind of connecting some dots if I have, first of all, great convenience to reduce all those logins, right? So, you know, check their little pain, pain reduction. But when you think about what's different, I can now broker my data as well as log in. So let's just say, hypothetically, I'm cruising around some D apps and, you know, doing things and earning reputation or attention or points or whatever, tokens utility tokens. There could be a way for me to control what I own. I'm the product I own the data. Is that kind of where this is going? >>I think it's definitely a direction. It could go say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard, you know, one of the things that I could request from a user is their address. I can figure out where they live, what city they're in that will help inform the, the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase, right? Like we can, we can start to build a stronger relationship between the applications that people use and the people that use them and try to optimize that whole experience and try to just transfer information back and forth to make everyone's lives better. >>What's the roadmap on the business side, Charlie, when you see companies kind of adopting it, they're probably taking baby steps or crawling before they walk they're walking before they run. I mean, I can see decentralized applications in the future, whether it's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the, the script flips to the user first. Okay. So I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >>Sure. So a lot of web three apps are very sensitive about respecting the, the information that their users are providing, right? So what we're doing is I'm offering different ways for apps can touch with their users in a way that is user controlled. So an example there is that a lot of web three companies will use wallet connect to allow users to log in using a wallet address, an issue. There is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who a unique user is. And the app is able to collect that information. They don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. >>It's really simple to implement and maintain as well. So one example there is if you are a DFI platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet all because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies well ask users to follow them on Twitter or discord when they need to provide updates or, you know, bug bounties, all these different things and log in with unstoppable, lets them permission, email addresses so they can collect emails if they want to do a newsletter. And instead of sort of harvesting data from elsewhere and kind of forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. You know, I'm supporting your project, want to be kept up to date with bugs or bounties or rewards programs. So really it's just kind of a, a better way for users to, to share the data that they're willing to with dApps and dabs can use it to create all sorts of incentives and really just kind of understand their users on a, on a different level. >>How has the development Michael going on the, on the smart contract side of the business, you know, theories has always been heralded as being very developer focused. There's been great innovations. Just, you still got, you know, gas fees out there. You still gotta do some things. How is the development environment, how are the applications coming? Cause I can see the really, I can see the flywheel kicking in as a developer, Frank gets more streamlined, more efficient, and now you've got the identity piece nailed down. I just see a lot of kind of dominoes falling at the same time. What's the status on the dev side? >>What's your tour? The fascinating thing about crypto is how quickly it changes. You know, when I, when I joined Ethereum was pretty reasonable still for transactions. It was very cheap to get things done very fast. We've looked at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two and we've moved over to the Pollyanna, our primary source of record, which is built on top of it. The area of course, I think saved well over a hundred million dollars in Gaspe is for our users that we're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things and really where this industry is going to take us. You know, in many ways we are, are just as much passengers as the other people floating around the ecosystem as well. >>Yeah, it's, it's certainly getting faster every day and seeing a huge uptake on a theorem. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join web three companies just goes to show you this cultural shift and you can see a lot more companies getting involved. So I got to ask you Charlie, on the biz dev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? Are they jumping in full throttle? What's, what's the, what's the roadmap. What's the best practice for people to get started with unstoppable? >>Absolutely. You know, we're lucky that we get a lot of inbound interest from companies web two and web three because they first want to secure their domains. And we do a ton of work on the backend to protect trademark domains. We want to avoid squatting as much as possible. You know, we don't think that's the spirit of, of weaponry at all. And certainly not what the original intention of the internet was. So fair amount of companies will reach out to, out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website and several domains.com is a great starting point. We have an app submission page where asking, reach out to us, even request a grant. We have a grant prop, a program to help developers get started, provide them some resources to, to work with us and integrate some of our technology. >>We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a water and an exchange, as well as what it takes to integrate login within softball, which is actually a super easy integration as well, which we're, we're really excited about. So yeah, I'd say check out the website apply for our grant. If you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on telegram email. We're very reachable and, and we're always happy to chat with projects and, and learn more about what they're doing. >>What's the coolest thing you've seen going on trial with your partners right now. What's, what's the, what's the number one use case that's cool that people are jumping on right now to get in and get some, some, you know, some success out of the gate. >>Yeah. Maybe, maybe gamefied kind of played, earns huge. It's blowing up. And the gaming community is really passionate, vibrant, just expanding like crazy same with there's all this cool new stuff you can do with defy where no matter, you know, how many, how, how big your kind of portfolio is, you're you're able to stake and use all these interesting tools to kind of grow your book. So it's super exciting to see and talk to all these projects and, you know, there's certainly kind of an energy in the community where everyone wants to onboard the general public to web three, right? So we're all working on these school projects, but we need everyone to come over from web to kind of understand the advantages of defy of game fi of having an empty domain. So I'm lucky that I'm kind of one of the first layers there of, of meeting new projects and kind of helping them get access to more users so that they can grow along with. >>Yeah. I remember the early days of Bitcoin and Ethereum, we were giving it away to give the, the community manager was give a, give a Bitcoin to someone that was when it was, you can actually give a Bitcoin to someone what's the, what's the word of mouth or organic viral. I won't say growth hack because that's got negative connotations, but what's the community's way of putting forth the mission for unstoppable. Is it just more domains you guys have any programs got going on? Is it give it away? I'll see you, you can get domains on your site, but what's the, what's the way to get people in gray shaded in and getting comfortable. >>Yeah. So much of what we do is really just all of that, to all that question, to answer that question, we spent a ton of time and energy just on education and whether that's specifically around domains or just general led three, we have a podcast which is pretty exceptional, which talks to what three leaders from across the space and makes the projects that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about resources. >>Yeah. The part I think you guys are up to one 17, but that's a deep dive that you guys go deep on the podcast. So that's, you know, where you go in, what else is new on digital identity? Where do you guys see the future going now that you get the baseline identity with the NFT? It makes a lot of sense. Create innovation. Good logic makes sense. Solid. Technically what's next. >>Yeah. I think that's really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be like our data shouldn't live in these walled gardens controlled by these large companies. Like ultimately people should be responsible for their own identity it's they should have control over the things that they do online, the data that's shared or the benefit of that data. And so the world that we are working towards is very much that where we are giving people the ability to be paid for sharing their data with companies, we're giving applications, the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem, through these products to enable a better experience for everyone. So whether that's the, the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon that just confirmed that the person that you are looking at is actually a real person, not some bot that's been paid to to the loader review. Like the, the interesting thing about these products is they're so universally applicable, applicable. There are so many different games that we can try to plug them in. So have >>It's a great example. It's double-edged sword. You can have a, a metaverse image and have pre-programmed conversations with, with, you know, liquid audio and the video application, you know, or it's a real person. How do you know the difference? You, these are going to be questions, you know, around, around who solves that problem. Now this is time for bots and is it time not for bots? We all know what happens when you get into the, you know, the game of manipulation, but also it can be helpful. This is where you gotta be smart and identity is critical in this future. Charlie, what's your reaction to the future of digital identity? I mean so much to look at here on the trajectory. >>Yeah. You know, I think a big part of it is data portability, right? If you go to a site like Instagram, you're giving them all this content that's very personal to you and you can't just pack up and leave Instagram. So we want a future where most of these apps are just kind of a front end and you can navigate from one to the other and bring your data with you and not be beholden to the companies that operate centralized servers. So I think data portability is huge and it's going to open up a lot of doors. And, and just going back to that thought on kind of cleaning up web two for a better web three. When I think about the Amazons, the Alps, the Yelps of the world, they're all these bots are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. >>And I want to bring kind of transparency back to the internet, where when you see a review, you should know that that's a real human and blockchain technology is enabling us to do that. And certainly enough, two domains are going to play a huge part of that. So I think that having an experience where, you know, and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. You know, politically speaking, we've, we've all seen all the issues with kind of attacking communities and using bots and fake accounts to kind of hit people's pain points is it's kind of sad and, and certainly not something that we want to see continue happening. So whatever we can do to kind of give people their digital identity and help people understand that this is a real person on the other end, I think is huge for, for the future of the internet and really for society as well. >>That's a great call out there. Charlie cleaning up the mess of web 2.0 web two. Well, actually I was, it was 2.0 technically now web three is no nos 0.0 in it, but, but I saw on our listen to the podcast with Matt, this recent one, and he had a great metaphor that went back to when I was growing up in the internet, you got IP addresses, right? And the mess there was, it was, you couldn't find what you want to look and no one could remember what to type in. Cause you can type in IP addresses in the browser back then. And then DNS came out and then keywords that's web. Okay. Now that mess now is fraud. Misinformation, bot manipulation, deep fakes, many other kind of unwanted kind of time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So similar thing happening here is that you guys see it too. >>Yeah. I think we're going back to some of the foundational architecture of the internet DNS and really bringing that forward about 30, 40 years in terms of technology. So loading in some work cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >>Yeah. Awesome. Well guys, thanks so much for coming on and the spirit of our tick talk, you know, I'm only summarize this. Can you guys give us a quick tick tock moment, short comment on, you know, where this is all going, whereas log-in single sign on mean and what should people do to take steps to secure their digital identity? >>Sure. I'll jump in here. So it's time for people to secure their digital identity. That great first step has gone on several domains and getting an entity domain. You know, you can control your data. You can do a lot of cool different things with your domain, including posting your own website that you own forever. And no one can take it away from you. I would certainly recommend the people join. Our discord, telegram community is check out our podcasts. It's really great. Especially if you're new to crypto web three, you know, we do a great job of sort of explaining all the basic concepts and expanding on them. So yeah, I'd say, you know, the time is now, so to get your digital identity and start embracing web three, because it's really exploding right now. And there's just so many incredible advantages, especially for the user, >>Michael, what's your take? >>I mean, I put not, I've said it better myself. >>Like we always say, if you're not on the next wave, your driftwood, and this is a big wave it's happening. It's pretty clear guys. It's it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on the app integration. Congratulations. And we've got our cube domain too, by the way. So we're we're I think we're good. You know, so we've got to put it to you. It's appreciate it, Charlie, Michael, thanks for coming on and sharing the update. Okay. This is the cube with unstoppable domains partner showcase, shout for your hosts. Got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching.

(peaceful music) >> Welcome to this cube conversation. I'm Dave Nicholson, and I am delighted to welcome back to the cube, cube veteran, Chen Goldberg, VP of engineering from Google. Chen, welcome back to the cube. >> Hey Dave, super happy to be here. >> Absolutely delighted to have you here. Let's dive right into this conversation. There was a, there was a blog post this week, talking about Google Cloud putting a lot of weight behind this idea of principles for software development. What are those principles and why are they important? >> The three principles that we put in that blog post is open, easy, and transformative. And I think what's really important to recognize with the three principles that those are not new principles, not for Google Cloud, and definitely not for me. I joined Google about, a little bit over five years ago. Right when just Kubernetes started to lead Kubernetes and Google Kubernetes engine team. And we immediately recognized, the idea of open and the importance of flexibility and choice is a foundation to the idea of Kubernetes and portability workloads. But pretty early on, it was clear that it's not enough just to have portability and flexibility because it creates a lot of complexity. So how can we still have that without creating a trade-off or tension for our customers? So really making sure that everything is also easy. You know, and one of the things, I use, I like to say it's not just portability of workloads, but also portability of skills and you achieve that through consistent experience, right? A lot of automation. And when you bring all of those things together, what I love about Google Cloud is that, you know, I'm an infrastructure person. I've always been infrastructure person. And what excites me the most is seeing others take this innovation and, and really empowers developers to make amazing, or, you know, unique ideas, a reality. And that's really the foundation principles for Google Cloud. >> So how does that translate into, from a customer perspective? >> So I would just start with some customer examples, right? Starting from, their perspective. So when we think about open, this is actually part of the, our customers cloud strategy, right? You say cloud, you immediately think only about public cloud, but from our customer perspectives, right? They think about public clouds, right? Most of them have more than one cloud, but they also think about the private cloud, you know, IOT edge and having that openness and flexibility to choose where they can run their workload, is critical. It's critical for them. What I hear mostly is of course, innovation, managing costs, and also making sure that they are not locked out of innovation that happens for example, in any cloud or, or somewhere else. So that's a really a key consideration for our customers when they think about their cloud strategy. The second thing that open matters is that it's really hard to hire talent that is expert and has the right skills. And we see that by using a leveraging open source technologies, it actually makes it easier to our customers to hire the best talent there is in the industry. At one of the previous Google Cloud Next sessions, we had the Loblaw for example, which is the biggest grocery in Canada. And, you know, we were joking on stage, that even though at our hiring for grocery shop, they still can hire the best talent because they are using the best technologies out there in the industry. So that's one, if you think about the importance of easy, I would just call out Western Digital that we've just announced how they decided to standardize on Anthos for their cloud strategy, right? Both of course, Google cloud platform, but On Prem and the Edge. And for them what's important is that when they have all of their amazing developers and operators, how can they provide them reach experience, right. We don't want our developers or operators to spend time on things that can be automated or managed by others. So having a smooth, intuitive experience is really critical. And we we've been announcing some new stuff like a, a Google Cloud deploy and really integrating the entire experience, especially integration for managing, deploying directly to Google Kubernetes engine. And of course, one of my favorite is Jiechi autopilot, which really takes all the goodness with Kubernetes and automatically managing. And then transformative, this is like what I said before, unleashing innovation. And we see Wendy's, for example, right, they want to actually have AI machine learning at run time at their branches, which will allow them to create a new experience for their customers. So this is how we see customers really appreciate these three principles. >> So whenever the subject of Kubernetes and Google comes up, we have to talk Anthos. We're now into what year three of Anthos. How has adoption looked what's the latest on that front? >> That has been really great. We actually have been seeing a 500% growth on the end of Q2 of year over year. And it's important you know to mention that the journey with Anthos is not something new, but something that we have built with our customers when they really love the experience they have on GCP, but needed to innovate elsewhere and not just on Google Cloud. So we've been seeing that, you know, I mentioned the Western Digital, blah, blah, and Wendy's we also have customers like MLB, which is really exciting how they've changed their entire fans' experience using Anthos. And for them, again, it was both the easy part, right? How can I deal with that complexity of having compute and storage everywhere in every one of the stadiums, but also how can I use AI and machine learning, which is unique to Google Cloud in order to create unique experiences for the fans, at real time, of course. >> Yeah. Now you've, touched on this a bit already, if you had to, if you thought about someone reviewing Anthos, their Anthos experience, because we're in the midst of people adopting Anthos and becoming new to Anthos at this point. What does a delighted customers response sound like to you? What is that Yelp review that they would write? If they were telling people we, doubled down on Anthos and we are thrilled because, fill in the blank for a second. >> The first thing that comes to mind is that it works everywhere and the developer experience that comes with it, right? So we have, of course the platform and the infrastructure, but where Anthos really shine is that experience, on top of thinking about all developers and operators that can really work in every environment without paying too much attention to that. And just having that intuitive experience, right? If you go to the Google Cloud console, you see all your clusters, and now we're actually also going to add your VMs into that view, and you can use tools like Anthos config managers, and Anthos service mash to manage your security posture or the configuration in all of those environments. >> So we hear a lot about Multicloud. Multicloud is fantastic, but it sounds like, dealing with the complexity associated with Multicloud is something that Anthos definitely helps with. >> Yes, you know, Google is best with complexity at scale, we've been running containers and really large environments for many years. And some of those principles really, you know, have been fundamental to the way we've started with Kubernetes. So the idea of the declarative intent and automation is really critical in managing large environment and high complexity because in those environments, lots of things can change, but with the declarative approach, you don't have to anticipate everything that is going to change, but you need to know what is your desired state. And that's really one way that Anthos is leveraging the Kubernetes primitives and those ideas to manage different types of environments. In addition to that, it's actually really adding that layer that I talked about before, around the easy can I make sure that my tools, right, if it's, for example, a cloud hybrid build or cloud deploy or Anthos service manager, Anthos config manager, can I make sure that this UI, the CLI the API will be consistent in all of those environments? Can I view in one place, all of my clusters, all of my applications, and this is really where Anthos shines. >> So the cloud data foundation had a, had to get together at the same time as, Google Cloud Next. And there's been a lot of discussion around topics like security. I just like to get your thoughts on, you know, what what's at the forefront of your mind, working in engineering at Google, working in this world where people are deploying Anthos, working in a world where in a multi-cloud environment, you don't necessarily have control as vice president of engineering at Google over what's happening in these other clouds. So what are some of the things that are at the front of your mind is security one of them, what are your thoughts? >> Security is top of mine. Similar to all of our customers and definitely internally. And there are many things that we are very worried about or create some risks. You know, we've just started talking about the secure central supply chain, by building with open source, how can we make sure that everything is secure, right? Then we know what is the contribution that's from the software that we are delivering, how can we make sure that the security posture is portable, right? We talked about workloads portability. We talked about skills portability, and experience, but really I think the next phase for us as an industry is to think about security posture portability. Can I really apply the same policy everywhere and still make sure that I have the right controls in place, which will have to be different depending on the environment, and to make sure that that really is the case. So lots of work around that, and again, talking about the other things we talked about. We talked about open and flexibility, how can you make sure that it's easy? One of the areas that we are very excited about is really around binary authorization, for example. So when you use our tools like cloud build, cloud deploy, artifact, registry, you can get your container images automatically scanned for vulnerabilities and tools like onto service mesh, which allows you to actually manage your security posture, traffic management, who can access what without doing any changes to your applications. >> Fantastic stuff. As we, as we wrap up our time here, do you have any final thoughts on the direction of cloud where we are in the adoption curve? You know, by some estimates, something like 75% of IT is still happening on premises. There've been some announcements coming out of Cloud Next regarding the ability to run all sorts of Google goodness on premises. So we seem to all be acknowledging that we're going to be in a bit of a hybrid world, in addition to a multicloud world, moving forward. Do you want to place any bets on, on when we'll hit the 50, 50 mark or the 25% on premises, 75% cloud mark. What do you think? >> Yeah, I'm not the best gambler to be honest, but I do have a thought about that. I think what's interesting is that customers started to talk, you know, few years back, it was, hey, I have my on-prem environment and I have the cloud. How can they, these two work together. And now what we see our customers talking, you know, they're on premises, their edge is part of their cloud strategy. It's not separated. And I think this is what we'll see more and more of, right? Regardless if this is your private cloud or public cloud, your edge, we would like to have a cloud like experience in that environment and consistency. And of course, we would love to leverage all the goodness of the cloud. If it's like machine learning, AI, and other capabilities, automation, everywhere we go. So I think this is the biggest change we're starting to see. And in addition to that, I think we will see, today everybody are already multicloud cloud, right? If it's recquisitions and just by cause of bottom up culture, you know, people choose different services. And I expect we'll see more strategic thinking about our customers multicloud strategy. Where do I deploy my workloads? What are the benefits? If it's latency, if it's specific services that are available, maybe cost, we'll see the customers becoming more intentional about that and this is really exciting. >> Well Chen, amazing insights. It's obvious why you're a cube veteran. It's obviously why we seek you out for your counsel and guidance on a variety of subjects. Thank you so much for spending time with us today in this cube conversation. With that I'd like to thank you for joining us. Until next time, I'm Dave Nicholson, thanks for joining (peaceful music)

(upbeat music) >> Welcome to this Cube Conversation. I'm Dave Nicholson, and this is continuing coverage of Google Cloud Next '21. I'm joined today by Sachin Gupta, General Manager and Vice President of Open Infrastructure at Google Cloud. Sachin, welcome to theCube. >> Thanks Dave, it's great to be here. >> So, you and I both know that the definition of what constitutes Cloud has been hotly contested by some over the last 20 years. But I think you and I both know that in some quarters there really has never been a debate. NIST, for example, the standard body that calls out what constitutes Cloud, has always considered Cloud an operational model, a set of capabilities, and it has never considered Cloud specifically tied to a location. With that in mind, how about if you share with us what was announced at Cloud Next '21 around Google Distributed Cloud? >> Yeah, thanks Dave. The power of Cloud in terms of automation, simplicity, observability, is undeniable, but our mission at Google Cloud is to ensure that we're meeting customers where they are, in their digital transformation journey. And so in talking to customers, we found that there are some reasons that could prevent them to move certain workloads to Cloud. And that could be because there's a low latency requirement. There is high amounts of data processing that needs to happen on-prem. So taking data from on-prem, moving into the Cloud to get it processed and all the way back may not be very efficient. There could be security, privacy, data residency, compliance requirements that they're dealing with. And then some industries, for some customers, there's some very strict data sovereignty requirements that don't allow them to move things into the public Cloud. And so when we talked to customers, we realized that we needed to extend the Cloud, and therefore we introduced Google Distributor Cloud at Next 2021. And what Google Distributed Cloud provides is all of that power of Cloud anywhere the customers need it. And this could be at a Google network edge, it could be at an operator or communication server provider edge as well. It could be at the customer edge, so right on-premise at their site, it could be in their data centers. And so a lot of flexibility in how you deploy three fully managed hardware and software solutions delivered through Google. >> Yeah it's interesting because often statistics are cited that somewhere near 75% of of what we do in IT, is still "on-premises." The reality is, however, that what's happening in those physical locations on the edge is looking a lot more Cloudy, isn't it. (laughs) >> Yes, and the customers are looking for that computational power, storage, automation, simplicity, in all of these locations. >> So what does this look like from an infrastructure stack perspective? Is there some secret sauce that you're layering into this that we should know about? >> Yeah, so let me just talk about it a little bit more. So we start off with third party hardware. So we're sourcing from Dell, HPE, Cisco, Nvidia, NetApp, bringing it together. We're using Anthos, you are hopefully familiar with Anthos, which is our hybrid multi-cloud software layer. And then on top of that, we use open source technologies. For example, built on Kubernetes. We offer a containerized environment, a VM environment, that enables both Google first-party services, as well as third-party services that customers may choose to deploy, on top of this infrastructure. And so the management of the entire infrastructure, top to bottom, is delivered to Google directly, and therefore customers can focus on applications, they can focus on business initiatives, and not worry about the infrastructure complexity. They can just leave that to us. >> So you mentioned both Kubernetes, thinking of containerization as Cloud native, you also said VMs. So this spans the divide between containerized microservices-based applications and say VM-ware style of virtual machines or other VMs? >> Yes, look, the majority of customers are looking to modernize and move to a containerized environment with Kubernetes, but there are some workloads that they may have that still require a VM-like environment, and having the simplicity and the efficiency of operating VMs like containers on top of Google Distributed Cloud, built on Anthos, is extremely powerful for them. And so it goes back to our mission. We're going to meet customers where they are, and if they need VM support as well, we're providing it. >> So let's talk about initial implementations of this. What kind of scale are you anticipating that customers will deploy? >> The scale is going to vary based on use case. So it could be a very small, let's think about it as a single server type of scale, all the way to many, many dozens of racks that could be going in to support Google Distributed Cloud. And so, for example, from a communication service provider point of view, looking to modernize their 5G network, in the core it could be many, many racks with Google Distributed Cloud the edge product. And for their RAM solutions, it could be a much smaller form factor, as an example. And so depending on use case, you're going to find all kinds of different form factors. And I didn't mention this before, but we also, in addition to scale, we offer two operational modes. One is the edge product. So Google Distributed Cloud edge that is connected to the Cloud. And so it gets operational updates, et cetera, directly through the Cloud. And the second one is something we call the hosted mode, and in hosted mode, it's completely air-gapped. So this infrastructure, what is modernized and provides rich 1PN third party services, does not connect to the Cloud at all. And therefore, the organizations that have the strictest data latency sovereignty requirements, can benefit from a completely air-gapped solution as well. >> So I'm curious, let's say you started with an air-gapped model. Often our capabilities in Cloud exceed our customer's comfort level for a period of time. Can that air-gapped, initial implementation be connected to the Cloud in the future? >> The air-gap implementation, typically customers, the same customer, may have multiple deployments, where one will require the air-gap solution, and another could be the hosted solution, and the other could be the edge product, which is connected. And in both cases, the underlying stack is consistent. So, while I don't hear customers saying, "I want to start from air-gap and move," we are providing Google Distributed Cloud as one portfolio to customers so that we can address these different use cases. In the air-gap solution, the software updates obviously still come from Google, and customers need to move that across the air gap check signatures, check for vulnerability, load it in the system, and the system will then automatically update itself. And so the software we still provide, but in that case, there's additional checks that that customer will typically go through before enabling that software onto their system. >> Yeah, so you mentioned at the outset, some of the drivers, latency security, et cetera, but can you restate that? I'd like to hear what the thinking behind this was at Google when customers were presenting you with a variety of problems they needed solutions for. I think it bears recapping that. >> Right, so let me give you a few examples here. So one is, when you think about 5G, when you think about what 4G did for the industry in terms of enabling the gig economy, with 5G we can really enable richer experiences. And this could be highly immersive experiences, it could be augmented reality, it could be all kinds of technologies that require lower latency. And for this, you need to build out the 5G infrastructure on top of a modernized solution like Google Distributed Cloud. Let me just get into a few use cases though, to just bring some color here. For example, for a retailer, instead of worrying about IP and infrastructure in the store, the people in the store can focus on their customers, and they can implement solutions using Google Distributed Cloud for things like inventory management, asset protection, et cetera, in the store. Inside a manufacturing facility, once again, you can reduce incidents, you can reduce injuries, you can look at your robotic solutions that require low latency feedback, et cetera. There's a whole bunch of emerging applications through ISVs, that a rich, on-prem or anywhere you want it in the edge infrastructure, can enable a new suite of possibilities that weren't possible before. In some cases, customers say, "You know what, I want 5G. But I actually you want a private 5G deployment." And that becomes possible with the Google Distributed Cloud as well. >> So we talked a little bit about scale. What's the smallest increment that someone could deploy? You just gave an example of retail. Some retail outfits are small stores, without any IT staff at all. There's the concept of a single-node Kubernetes cluster, which is something we love to come up with in our business terminology that makes no sense, single node cluster. The point is, these increments, especially in the containerized world, are getting smaller. What's the smallest increment that you can deliver, you're planning to deliver? >> I'll answer this two ways. First of all, we are planning to deliver a smallest increment, think of it as one server. We are planning to deliver that as well, all the way up to many, many racks. But in addition, there's something unique that I wanted to call out. Let's say you're in the medium or larger deployment in the racks, and you want to scale up, compute, and store it separately. That's something we enable as well, because we will work with customers in terms of what they need for their application, and then scale that hardware up and down based on their need. And so there's a lot of flexibility in that, but we will enable scale all the way down to a single server unit as well. >> So what is the feedback been from the partners that will be providing the hardware infrastructure, folks like Dell. What has their reaction been? >> I think that they're obviously very eager to work with us. We're happy to partner with them in order to provide customers flexibility, any kind of scale in any kind of location, different kind of hardware equipment that they need. But in addition to those partners on the hardware side, there are customers and partners as well who are enabling rich experiences and solutions for that retailer, for that manufacturer, for example. And so working with AT&T, we announced partnership on 5G and edge to enable experiences, especially in the areas of retail and manufacturing, like I talked about earlier, but then in Europe, we're partnering with OVHcloud, for example, in order to enable very strict data sovereignty requirements that are happening in that country. And so where there's many communication service providers, there's many partners trying to solve for different use cases for their end customers. >> Yeah, that makes a lot of sense. Let's pretend for a minute that you're getting Yelp reviews of this infrastructure that you're responsible for moving forward. What would a delighted customer's comments look like? >> I think a delighted customer's comments will be probably in two or three areas, all right? So first up will be, it's all about the applications and the end user experience that this can enable. And so the power of Google AI ML technology, third-party software as well, that can run consistently single operational model, build once, deploy anywhere, is extremely powerful. So I would say, the power of the applications and the simplicity that it enables is number one. I think number two is the scale of operations experience that Google has. They don't need to worry about, "do I have 5 sites or 500 sites or 5,000 sites?" It doesn't matter. The fleet operations, the scaled operations capability, the global network capability that Google has, all that experience in site reliability engineering, we can now bring to all of these vast amounts of edge locations, so they don't need to worry about scale at all. And then finally, they can be sort of rest assured that this is built on Anthos, it's built on Kubernetes, there's a lot of open source components here, they have flexibility, they have choice, they can run our one-piece services, they can run third-party services on this, and so we're going to preserve the flexibility in choice. I think these are the things that would likely get highlighted. >> So Sachin, you talk to customers around the world. Where do you see the mix between net-neu stuff going into infrastructure like this, versus modernized and migrated workloads into the solution? What does that mix look like? And I know it's a bit of speculation, but what are your thoughts? >> I think, Dave, that's a great question, I think it's a difficult one to answer because we find that those conversations happen together with the same customers. At least that's what I find. And so they are looking to modernize, create a much richer environment for their developers, so that they can innovate much more quickly, react to business needs much more quickly, to cater to their own end customers in a much better way, get business insights from the data that they have. They're looking to do all of this, but at the same time, they have, perhaps, legacy infrastructure or applications that they just can't easily migrate off of, that may still be in a VM environment, more traditional type of storage environment, and they need to be able to address both worlds. And so, yes, there are some who are so-called "born in the Cloud," everything is Cloud native, but the vast majority of customers that I talked to, are absolutely looking to modernize, like you don't find a customer that says, "Just help me lift and shift, I'm not looking to modernize." I don't quite see that. They are looking to modernize but they want to make sure that we have the options that they need to support different kinds of environment that they have today. >> And you mentioned insights. We should explore that a little further. Can you give us an example of artificial intelligence, machine learning being used now at the edge, where you're putting more compute power at the edge? Can you give us an idea of the kinds of things that that enables specifically? >> Yes, so when you think about video processing, for example, if I have a lot of video feeds and I'm looking based on that, I want to apply artificial intelligence, I'm trying to detect object inventory movement, people movement, et cetera. Again, adhering to all the privacy and local regulations. When I have that much data streaming in, if I have to take that out of my edge all the way across the WHEN network, into the Cloud for processing, and bring it all the way back and then make a decision, I'm just moving a lot of data up and down into the Cloud. And in this case, what you're able to do is say, no, you don't actually need to move it into the public Cloud. You can keep that data locally. You can have a Google Distributed Cloud edge instance there, you're going to run your AI application right there, achieve the insights and take an action very, very quickly. And so it saves you, from a latency point of view, significantly, and it saves you from a data transmission up and down into the Cloud significantly, which you sometimes, you know, you're not supposed to send that data up, that there's data residency requirements, and sometimes the cost of just moving it, it doesn't make sense. >> So do you have any final thoughts? What else should we know about this? Anything that we didn't touch on? >> I think we've touched on a lot of great things. I think I'm just going to reiterate, you started with a "what is the definition of Cloud itself" and our mission once again, is to really understand what customers are trying to do and meet them where they are. And we're finding that they're looking for Cloud solutions in a public region. We've announced a lot more regions. We continue to grow our footprint globally, but in addition, they want to be able to get that power of Google Cloud infrastructure and all the benefits that it provides in many different edge locations all the way on onto their premises. And I think one of the things we perhaps spent less time on is, we're also very unique that in our strategy, we're bringing in underlying third-party hardware, but it's a fully managed solution that can operate in that connected edge mode, as well as a disconnected hosted mode, which just enables pretty much all the use cases we've heard about from customers. So one portfolio that can address any kind of need that they have. >> Fantastic. Well, I said at the outset Sachin, before we got started, you and I could talk for hours on this subject. Sadly, we don't have hours. I'd like to thank you for joining us in theCube. I'd like to thank everyone for joining us for this Cube conversation, covering the events at Google Cloud NEXT 2021. I'm Dave Nicholson. Thanks for joining. (upbeat music)

(soft techno music) >> Good evening. Welcome back to the Kube. Live in Los Angeles. We are at KubeCon Cloud Native Con 2021. Lisa Martin with Dave Nicholson, rounding out our day. We're going to introduce you to a new company, a new company that's new to us. I should say, log DNA. Peter Choi joins us the VP of product. Peter, welcome to the program. >> Thanks for having me. >> (Lisa) Talk to us about log DNA. Who are you guys? What do you do? >> So, you know, log DNA is a log medicine platform. Traditionally, we've been focused on, you know, offering log analysis, log management capabilities to dev ops teams. So your classic kind of troubleshooting, debugging, getting into your systems. More recently, maybe in like the last year or so we've been focused on a lot of control functionality around log medicine. So what I mean by that is a lot of people typically think of kind of the analysis or the dashboards, but with the pandemic, we noticed that you see this kind of surge of data because all of the services are being used, but you also see a downward pressure on cost, right? Because all of a sudden you don't want to be spending two X on those digital experiences. So we've been focused really on kind of tamping down kind of controls on the volume of log data coming in and making sure that they have a higher kind of signal and noise ratio. And then, you know, I'll talk about it a little bit, but we've really been honing in on how can we take those capabilities and kind of form them more in a pipeline. So log management, dev ops, you know, focusing on log data, but moving forward really focused on that flow of data. >> (Dave) So, when you talk about the flow of data and logs that are being read, make this a little more real, bring it up, bring it up just to level in terms of data, from what? >> Yeah. >> What kind of logs? What things are generating logs? What's the relevant information that's being. Kept track of? >> Yeah, I mean, so from our perspective, we're actually agnostic to data source. So we have an assist log integration. We have kind of basic API's. We have, you know, agents for any sort of operating system. Funny enough people actually use those agents to install, log DNA on robots, right? And so we have a customer they're, you know, one of the largest E-commerce platforms on, in the, in the world and they have a warehouse robots division and they installed the agent on every single one of those robots. They're, you know, they're running like arm 64 processors and they will send the log data directly to us. Right? So to us, it's no different. A robot is no different from a server is no different from an application is no different from a router. We take in all that data. Traditionally though, to answer your question, I guess, in the simplest way, mostly applications, servers, firewalls, all the traditional stuff you'd expect kind of going into a log platform. >> So you mentioned a big name customer. I've got a guess as to who that is. I won't, I won't say, but talk to us about the observability pipeline. What is that? What are the benefits in it for customers? >> (Peter) Sure. So, like if we zoom out again, you know, you think about logs traditionally. I think a lot of folks say, okay, we'll ingest the logs. We'll analyze them. What we noticed is that there's a lot of value in the step before that. So I think in the earlier days it was really novel to say, Hey, we're going to get logs and we're going to put it into a system. We're going to analyze it. We're going to centralize. Right. And that had its merits. But I think over time it got a little chaotic. And so you saw a lot of the vendors over the last three years consolidating and doing more of a single pane of glass, all the pillars of observability and whatnot. But then the downside of that is you're seeing a lot of the teams that are using that then saying being constrained by single vendor for all the ways that you can access that data. So we decided that the control point being on the analysis side on, on the very far right side was constricting. So we said, okay, let's move the control point up into a pipeline where the logs are coming to a single point of ingress. And then what we'll do is we will offer views, but also allow you to stream into other systems. So we'll allow you to stream into like a SIM or a data warehouse or something, something like that. Right? So, and you know, we're still trying to like nail down the messaging. I'm sure our marketing person's going to roast me after this. But the simplest way to think of observability pipeline is it's the step before the analysis part, that kind of ingest processes and routes the data. >> (Dave) Yeah. This is the Kube, by the way, neither one of us is a weather reporter. (laughing) So, so the technical stuff is good with us. >> Yes. It is. What are, and talk to us about some of the key features and capabilities and maybe anything that's newly announced are going to be announced. >> Yeah. For sure. So what we recently announced early access on is our streaming capabilities. So it's something that we built in conjunction with IBM and with a couple of, you know, large major institutions that we were working with on the IBM cloud. And basically we realized as we were ingesting a log data, some of those consumers wanted to access subsets of that data and other systems such as Q radar or, you know, a security product. So we ended up taking, we filtered down a subset of that data and we stream it out into those systems. And so we're taking those capabilities and then bringing it into our direct product, you know, whatever you access via logging.com. That is what's essentially going to be the seed for the kind of observability pipeline moving forward. So when you start thinking about it, all of this stuff that I mentioned, where we say, we're focusing on control, like allowing you to exclude logs, allowing you to transform logs, you take those processing capabilities, you take the streaming capabilities, you put them together and all of a sudden that's the pipeline, right? So that's the biggest focus for us now. And then we also have supporting features such as, you know, control API's. We have index rate alerting so that you can get notified if you see aberrations in the amount of flow of data. We have things like variable retention. So when a certain subset of logs come in, if you want it store it for seven days or 30 days, you can go ahead and do that because we know that a large block of logs is going to have many different use cases and many different associated values, right? >> So let's pretend for a moment that a user, somebody who has spent their money on log DNA is putting together a Yelp review and they've given you five stars. >> Yup. >> What do they say about log DNA? Why did they give you that five star rating? >> Yeah. Absolutely. I think, you know, the most common one and it's funny it's Yelp because we actually religiously mine, our G2 crowd reviews. (all laughing) And so the thing that we hear most often is, it's ease of use, right? A lot of these tools. I mean, I'm sure, you know, you're talking to founders and product leaders every day with developers. Like the, the bar, the baseline is so low, you know, a lot of, a lot of organizations where like, we'll give them the, you know, their coders, they'll figure it out. We'll just give them docs and they'll figure it out. But we, we went a little bit extra in terms of like, how can we smooth that experience so that when you go to your computer and you type in QTPL, blah, blah, blah, two lines, and all of a sudden all your logs are shipping from your cluster to log DNA. So that's the constant theme for us in all of our views is, Hey, I showed up, I signed up and within 30 minutes I had everything going that I needed to get. >> (Lisa) So fast time to value. >> Yes. >> Which is critical these days. >> Absolutely. >> Talk to me. So here we are at, at KubeCon, the CNCF community is huge. I think I, the number I saw yesterday was 138,000 contributors. Lots of activity, because we're in person, which is great. We can have those hallway networking conversations that we haven't been able to have in a year and a half. What are some of the things that you guys have heard at the booth in terms of being able to engage with the community again? >> You know, the thing that we've heard most often is just like having a finger on the pulse. It's so hard to do that because you know, when we're all at our computers, we just go from zoom to zoom. And so it, it like, unless it punches you in the face, you're not aware of it. Right. But when you come here, you look around, you go, you can start to identify trends, you hear the conversations in the hallway, you see the sessions. It's just that, that sense of, it's almost like a Phantom limb that, that sense of community and being kind of connected. I think that's the thing that we've heard most often that people are excited. And, you know, I think a lot of us are just kind of treating this like a dry run. Like we're kind of easing our way back in. And so it, you know, it felt good to be back. >> Well, they've done a great job here, right? I mean, you have to show your proof of vaccination. They're doing temperature checks, or you can show your clear health pass. So they're making it. We were talking to the executive director of CNCF earlier today and you're making it, it's not rocket science. We have enough data to know that this can be done carefully and safely. >> (David) Don't forget the wristbands. >> That's right. And, and did you see the wristbands? >> (Peter) Oh yeah. >> Yeah, yeah that's great. >> Yep, it is great. >> I was, I was on the fence by the way. I was like, I was a green or yellow, depending on the person. >> (both) Yeah. >> Yeah. But giving, giving everybody the opportunity to socialize again and to have those, those conversations that you just can't have by zoom, because you have somebody you've seen someone and it jogs your memory and also the control of do I want to shake someone's hand or do I not. They've done a great job. And I think hopefully this is a good test in the water for others, other organizations to learn. This can be done safely because of the community. You can't replicate that on video. >> (Peter) Absolutely. And I'll tell you this one for us, this is our, this is our event. This is the event for us every single year. We, we it's the only event we care about at the end of the day. So. >> What are some of the things that you've seen in the last year, in terms of where, we were talking a lot about the, the adoption of Kubernetes, kind of, where is it in its maturation state, but we've seen so much acceleration and digital transformation in the last 18 months for every industry businesses rapidly pivoting multiple times to try to, to survive one and then figure out a new way to thrive in this, this new I'll call it the new. Now I'll borrow that from a friend at Citrix, the new now, not the new normal, the new now, what are some of the things that you've seen in the last year and a half from, from your customer base in terms of what have they been coming to you saying help? >> (Peter) You know, I think going back to the earlier point about time to value, that's the thing that a lot. So a lot of our customers are, you know, very big Kubernetes, you know, they're, they're big consumers of Kubernetes. I would say, you know, for me, when I do the, we do our, our QBRs with our top customers, I would say 80% of them are huge Kubernetes shops. Right. And the biggest bottleneck for them actually is onboarding new engineers because a lot of the, and you know, we have a customer, we have better mortgage. We have, IBM, we have Rappi is a customer of ours. They're like Latin American version of Instacart. They double their engineering base and you, you know, like 18 in 18 months. And so that's, you know, I think it was maybe from 1500 to 3000 developers or so, so their thing is like, we need to get people on board as soon as possible. We need to get them in these tools, getting access to, to, to their longs, to whatever they need. And so that's been the biggest thing that we've heard over and over again is A, how can we hire? And then B when we hire them, how do we onboard them as quickly as possible, so that they're ramped up and they're adding value. >> How do you help with that onboarding, making it faster, seamless so that they can get value faster? >> So for us, you know, we really lean in on our, our customer success teams. So they do, you know, they do trainings, they do best practices. Basically. We kind of think of ourselves given how much Kubernetes contradiction we have, we think of ourselves as cross pollinators. So a lot of the times we'll go into those decks and we'll try to learn just as much as we're trying to try to teach. And then we'll go and repeat that process through every single set of our customers. So a lot of the patterns that we'll see are, well, you know, what kinds of tools are you using for orchestration? What kind of tools are you using for deployment? How are you thinking about X, Y, and Z? And then, you know, even our own SRE teams will kind of get into the mix and, you know, provide tips and feedback. >> (Lisa) Customer centricity is key. We've heard that a lot today. We hear that from a lot of companies. It's one thing to hear it. It's another thing to see it. And it sounds like the Yelp review that you would have given, or, or what you're hearing through G2 crowd. I mean, that voice of the customer is valid. That's, that's the only validation. I think that really matters because analysts are paid. >> Yeah. >> But hearing that validation through the voice of the customer consistently lets you know, we're going in the right direction here. >> Absolutely. >> I think it's, it's interesting that ease of use comes up. You wonder if those are only anonymous reviews, you don't necessarily associate open source community with cutting edge, you know, we're the people on the pirate ship. >> (Peter) Yeah. And so when, when, when people start to finally admit, you know, some ease of use would be nice. I think that's an indication of maturity at a certain point. It's saying, okay, not everyone is going to come in and sit behind a keyboard and program things in machine language. Every time we want to do some simple tasks, let's automate, let's get some ease of use into this. >> And I'll tell you in the early days it drove me and our, our CEO talker. It drove us nuts that people would say easiest to be like, that's so shallow. It doesn't mean anything. Well, you know, all of that. However, but to your point, if we don't meet the use case, if we don't have the power behind it, the ease of use is abstracting away. It's like an iceberg, right. It's abstracting away a lot. So we can't even have the ease of use conversation unless we're able to meet the use case. So, so what we've been doing is digging into that more, be like, okay, ease of use, but what were you trying to do? What, what is it that we enabled? Because ease of use, if it's a very shallow set of use cases is not as valid as ease of use for petabytes of data for an organization like IBM. Right? >> That's a great, I'm glad that you dug into that because ease of use is one of those things that you'll see it in marketing materials, but to your point, you want to know what does this actually mean? What are we delivering? >> Right. >> And now, you know what you're delivering with Peter, thank you for sharing with us about logged in and what you guys are doing, how you're helping your community of customers and hearing the voice of the customer through G2 and others. Good work. >> Thank you. And by the way, I'll be remiss if I, if I don't say this, if you're interested in learning more about some of the stuff that we're working on, just go to logging in dot com. We've got, I think we've got a banner for the early access programs that I mentioned earlier. So, you know, at the end of the day, to your point about customer centricity, everything we prioritize is based on our customers, what they need, what they tell us about. And so, you know, whatever engagement that we get from the people at the show and prospects, like that's how we drive a roadmap. >> (Lisa) Yup. That's why we're all here. Log dna.com. Peter, thank you for joining Dave and me today. We appreciate it. >> Thanks for having me. >> Our pleasure for Dave Nicholson. I'm Lisa Martin signing off from Los Angeles today. The Kubes coverage of KubeCon clouding of con 21 continues tomorrow. We'll see then. (soft techno music)

>>mhm >>Hello welcome to this cube conversation here in Palo alto California and john for with the cube we had a great conversation around the rise of the cloud and the massive opportunities and challenges around analytics data ai suggestion. Air ceo of thought spot is here with me for conversation. Great to see you. Welcome back to the cube. How are you? >>Well john it is so good to be back. I wish that we could do one of those massive set up that you have and do this face to face but zoom is not bad. >>You guys are doing very well. We have been covering you guys been covering the progress um great technology enabled business. You're on the wave of this cloud analytics you're seeing, we've seen massive changes and structural changes for the better. It's a tailwind for anyone in the cloud data business. And you also on the backdrop of all that the Covid and now the covid is looking at coming out of covid with growth strategies. People are building modern or modernizing their infrastructure and data is not just a department, it's everywhere. You guys are in the middle of this. Take us through what's the update on thought spot. What are you guys doing? What do you see the market right now? Honestly, delta variants coming coming strong but we think will be out of this soon. Where where are >>we look I think it all starts with the users like you said the consumers are demanding more and more from the business they are interacting with. You're no longer happy with being served like uh I'm gonna put you all in a bucket and then Delaware services to you. Everyone's like look look at me, I have likes and dislikes that is probably going to be different from someone that you think are similar to me. So unless you get to know me and deliver bespoke services to me, I'm gonna go somewhere else who does that And the call that the way you do that is through the data that I'm giving to you. So the worst thing you can do is to take my data and still treat me like an average and numbers and what's happening with the cloud is that it is now possible and it wasn't okay. So I grew up in India where newspapers will always have stock market summary on like one full page full of takers and prices and the way it used to work is that you wake up in the morning you look at the newspaper, I don't know if you have had the same thing and then you call your broker is based on in place of that. Can you imagine doing that now? I mean the information is at your fingertips. Hurricane IDa either is actually going to enter in Louisiana somewhere. What good is it? Yesterday morning state on this morning state if I'm trying to make a decision on whether I should pack my stuff and move away or you know finding to from home depot supply chain manager. I shouldn't figure out what should I be doing for Louisiana in the next two days, this is all about the information that's available to you. If you plan to use it and deliver better services for your consumer cloud makes it possible. >>You know, it's interesting you mentioned that the old way things were it seems so slow, then you got the 15 minute quotes, then there's now a real time. Everything has to be real time. And clearly there's two major things happening at the same time which makes exciting the business model and the competitive advantages for leaders and business to use data is critical but also on the developer side where apps are being developed if you don't have the data access, the machine learning won't work well. So as machine learning becomes really courted driving ai this modern analytics cloud product that you guys announced brings to bear kind of two major lifts the developer app modernization as well as competitive advantage for the companies that need to deploy this. So you guys have announced this modern approach analytics cloud, so to speak. What are some of the challenges that companies are having? Because you gotta, if you hit both of those you're gonna right a lot of value. What are some of the challenges for people who want to do this modern cloud? >>I think the challenge is basically all inside in the company. If you ask companies why are they failing to modernize? They will point to what's inside, it's not outside the technology is there the stack is the vendors are there, It is sometimes lack of courage at the leadership level which is a huge problem. I'll give an example. Uh, we have recently announced what we call thoughts part everywhere, which is our way of looking at how to modernize and bring the data inside that you're looking forward to where you are because Lord knows we all have enough apps on our Octa or a single sign on. The last thing you need is one more how no matter how good it is, they don't want to log into yet under their tool, whether it's thought spot or not. But the insights that you are talking about needs to be there when you need. And the difference is uh, the fundamental approach of data analytics was built on embedded model. You know what we are proposing is what we call data apps. So the difference between data apps and the typical dashboard being embedded into your analytics model is sort of like think of it. Uh newspapers telephones and the gap in between. So there is newspapers radio that is walkie talkie and telephone. They're all different and newspapers get printed and it comes to you and you read in the morning, you can talk back to it, you can drag and drop, you can change it right walkie talkies on the other hand, you know, you could have one conversation then come back to that. Whereas phone, you can have true direction conversation? They're all different if you think of embedding it is sort of like the newspaper, the information that you can't talk back. So somebody resembling something that came out monday, you're going to a board meeting on Wednesday and you look at that and make decisions. That is not enough in the new world, you just can't do that. It's not about what a lot of tools can actually answer what the real magic the real value for customers are unlocked when you ask three subsequent questions and answer them and they will come down to when you hear what you have to know. So what? Right and then what if and then the last is what next Imagine you can answer those three questions every business person every time no matter how powerful the dashboard is, they will always have the next question. What? So what? Okay the business customers are turning so what is it good, is it bad? Is it normal or the next question is like now what what do I do with it two, the ability to take all these three questions so what and what a fun. Now what? That requires true interactivity, you know, start with an intent and with an action and that is what we are actually proposing with the data apps which is only possible if you're sitting on top of a snowflake or red shift kind of really powerful and massive cloud data warehouse where the data comes and moves with agility. >>So how has this cloud data model rewritten the rules of business? Because what you're bringing up is essentially now full interactivity really getting in, getting questions that are iterating and building on context to each other. But with all this massive cloud data, people are really excited by this. How is it changing business than the rules of business? >>Yeah. So think about, I mean topical things like there is a hurricane able to enter, hit the cost of the United States. It's a moving target. No one knows exactly where it is going to be. There is only 15 models from here. 10, 10 models from Europe that's going to predict which way it's going to take every millimeter change in that map is going to have significant consequences for lives and resources and money. Right. This is true for every business. What cloud does this? Uh you have your proprietary data for example, let's say you're a bank and you have proprietary data, you're launching a new product And the propriety data was 2025 extremely valuable. But what what's not proprietary but what is available to you? Which could make that data so much more relevant if you layer them on top census data, this was a census here. The census data is updated. Do you not want that vaccination leader? We clearly know that purchasing power parity will vary based on vaccinations and county by county. But is that enough? You need to have street by street is county data enough. If you're going to open startup, Mr Starbucks? No, you probably want to know much more granular data. You wanna know traffic. Is the traffic picking up business usually an office space where people are not coming to office or is it more of a shopping mall where people are still showing all of these data is out there for you? What cloud is making it possible? Unlike the old era where you know, your data is an SFP oracle or carry later in your data center, it's available for you with a matter of clicks. What thought sport modern analytics. Cloud is a simple thing. We are the front end to bring all of this data and make sense of it. You can sit on top of any cloud data and then interact with a complete sort of freedom without compromising on security, compliance or relevance. And what happens is the analysts, the people who are responsible for bringing the data and then making sure that it is secure and delivered. They are no longer doing incremental in chart updates and dashboard updates. What they're doing is solving business problems, business people there freely interacting and making bigger decisions. That actually adds value to their consumers. This is what your customers are looking for, your users are looking for and if you're not doing it, your competitor will do that. So this is why cloud is not a choice for you. It's not an option for you. It is the only way and if you fail to take that back the other way is taking the world out of a cliff. >>Yeah, that's I love it. But I want to get this uh topic of thoughts about anywhere, but I want to just close out on this whole idea of modern cloud scale analytics. What technology under the hood do you guys see that customers should pay attention to with thought spot and in general because the scale there. So is it just machine learning? We hear data lakes, you know, you know different configurations of that. Machine learning is always thrown around like a buzzword. What new technology capability should every executive by your customer look for when it comes to really doing analytics, modern in the cloud >>analytics has to be near real time, Which means what two things speed at scale, make sure it's complex, it can deal with complexity in data structure. Data complexity is a huge problem. Now imagine doing that at scale and then delivering with performance. That means you have to rethink Look Tableau grew out of excellent worksheets that is the market leader, it is a $40 billion dollar market with the largest company having only a billion dollars in revenue. This is a massive place where the problems need to be solved differently. So the underlying technology to me are like I said, these three things, number one cannot handle the cloud scale, you will have hundreds of billions of rows of data that you brought. But when you talk about social media sentiment of customers, analysis of traffic and weather patterns, all of these publicly available valuable data. We're talking trillions of rows of data. So that is scale. Now imagine complexity. So financial sector for example, there is health care where you know some data is visible, some data is not visible, some some is public assumption not or you have to take credit data and let it on top of your marketing data. So it becomes more complex. And the last is when you answer ask a question, can you deliver with absolute confidence that you're giving the right answer With extremely high performance and to do that you have to rebuild the entire staff. You cannot take your, you know, stack that was built in 1990s and so now we can do search So search that is built for these three things with the machine learning and ai essentially helping at every step of the way so that you're not throwing all this inside directly to a human, throw it to a i engine and the ai engine curates what is relevant to you, showing it to you. And then based on your interaction with that inside, I improve my own logic so that the next interaction, the next situation is going to be significantly better. My point is you cannot take a triple a map and then try to act like this google maps. One is built presuming and zoom out and learn from you. The other one is built to give you rich information but doesn't talk back. So the staff has to be fundamentally rebuilt for the club. That's what he's doing. >>I love I love to buy direction. I love the interactivity. This topic of thought spot everywhere, which you mentioned at the beginning of this conversation, you mentioned data apps which by the way I love that concept. I want to do a drill down on that. Uh I saw data marketplace is coming somewhat working but I think it's going to get it better. I love that idea of an app um, and using as developers but you also mentioned embedded analytics. You made a comment about that. So I gotta ask you what's the difference between data apps and embedded analytics? >>Embedded analytics means that uh you know the dashboards that you love but the one that doesn't talk back to you is going to be available inside the app that you built for your other So if a supply chain app that was built by let's say accenture inside that you haven't had your dashboard without logging into tablet. Great. But what you do, what's the big deal? It is the same thing. My point is like I said every time a business user sees a chart. The questions are going to come up. The next 10 question is where the values on earth for example on Yelp imagine if you will piece about I'm hungry. I want to find a restaurant and it says go to this burrito place. It doesn't work like that. It's not good enough. The reason why yell towards is because I start with an intent. I'm hungry. Okay show me all restaurants. Okay I haven't had about it for a while. Let me see the photos. Let me read the reviews. Let me see if my friends have eaten, let me see some menu. Can I walk there? I do all of this but just what underneath it. There is a rich set of data that probably helped have their own secret source and reviews and then you have google map powering some of them. But I don't care all of that is coming together to deliver a seamless experience that satisfies my hunger. Which will be very different from if you use the same map at the same place you might go to an italian place. I go to bed right. That is the power of a data app in business people are still sitting with this. I am hungry. I gotta eat burrito. That's not how it should be in the new world. A business user should have the freedom to add exactly what the customers require looking for and solve that problem without delay. That means every application should be power and enriched with the data where you can interact and customized. That is not something that enterprise customers are actually used to and to do that you need like I said a I and search powering like the google map underneath it, but you need an app like a yelp like app, that's what we deliver. So for example, uh just last week we delivered a service now app on snowflake. You know, it just changes the game. You are thinking about customer cases. You're a large company, you have support coming from Philippines and India some places the quality is good. Some places bad dashboards are not good enough saying that okay, 17% of our customers are unhappy but we are good. That's not the world we live in. That is the tyranny of >>average, >>17% were unhappy. You got to solve for them. >>You mentioned snowflake and they had their earnings. David and I were commenting about how some of the analysts got it all wrong. And you bring up a really good point that kind of highlights the real trend. Not so much how many new customers they got. But there do what customers are doing more. Right? So, so what's happening is that you're starting to see with data apps, it does imply Softwares in there because it's it's application. So the software wrapping around data. This is interesting because people that are using the snowflakes of the world and thought spot your software and your platform, they're doing more with data. So it's not so much. I use snowflake, I use snowflake now I'm going to do more with it. That's the scale kicking. So this is an opportunity to look at that more equation. How do you talk >>with >>when you see that? Because that's the real thing is like, okay, that's I bought software as a service. But what's the more that's happening? What do you see >>that is such an important point? Even I haven't thought about it that john but you're absolutely right. That is sometimes people think of snowflake is taking care of it and no. Yeah, yes, Sarah later used to store once and zeros and they're moving it into club. That is not the point. Like I said, marketplace as an example when you are opening it up for for example, bringing the entire world's data with one click accessible to you securely. That is something you couldn't do on number two. You can have like 100 suppliers and all of a sudden you can now take a single copy of data and then make it available to all of them without actually creating multiple copies and control it differently. That's not something without cloudy, potentially could do. So things like that are fundamentally different. It is much more than like one plus one equals two. It is one plus one is 33. Like our view is that when you are re platform ng like that, you have to think from customer first. What does the customer do? The customer care that you meant from Entre into cloud or event from Teradata snowflake. No, they will care if their lives are better. Are they able to get better services are able to get it faster. That's what it is. So to me it is very simple. The destiny of an insight or data information is action, right? Imagine you're driving a car and if your car updates the gas tank every monday morning, imagine how you know, stressful your life will be for the whole week. I have to wait until next monday wanting to figure out what, whether I have enough gas or not, that's not the new world, that information is there, you need to have it real time and act on it. If you go through the Tesla you realize now that you know, I'm never worried about mileage because it is going to take me to the supercharger because it knows what I need to get to, it knows how long it is going to be, how bad the traffic is. It is synthesizing all of that to give me peace of mind. >>So this is a great >>conversation. That's a >>great question. It's a great conversation because it's really kind of brings in kind of what's happening, you see successful companies that are working with cloud scale and data like you're talking about, it's you get in there, you get the data, the data apps and all of a sudden you hit it, you hit the value equation and it's like almost like discovering oil all of a sudden you have a gusher and then people just see massive increase in value. It's not like the outcome, it's kind of there, you've got to kind of get in there and this is the scale piece and you see people having strategies to do that, they say okay we're gonna get in there, we're going to use the data to iterate but also watch the data learn where's that value, This is that more trend and and there's a successful of the developing. So I have to ask you when you, when you talk about people and culture, um that's not the way it used to be, used to be like okay I'm buying an outcome. I deployed some software mechanisms and at the end of the day there's some value there. Maybe I write it off maybe I, you know, overtime charges and some accounting thing. All changed the culture and the people in charge now are transforming the management techniques. What do you see as a successful mindset for a customer as they managed through these new paradigms and new new success formulas. >>I see a fork in leadership when it comes to courage. There are people with the spine and there are people without the spine and the ones with the spine are absolutely killing it. They are unafraid. They are not saying, look, I'm just going to stick with the incumbents that I've known for the last 20 years. Look, I used to drive a Toyota forever because I love the Toyota. And then you know after Nutanix IPO went to Lexus still Toyota because it's reliable. I don't, I'm not a huge card person. It works. But guess what? I knew they were missing Patrick and I care about the environment. I don't want to keep pushing hydrocarbons out there. It's not politics. I just don't like burning stuff into the earth atmosphere. So when Tesla came out, it's not like I love the quality I don't personally like alone mask, you know after that Thailand fiasco of cave rescue and all of that. But I can clearly see that Toyota is not going to catch up to Tesla in the next 10 years. And guess what? My loyalty is much more to doing the right thing for my family and to the world. And I switched this is what business leaders need to know. They can't simply say, well, tabloid as search to. They're not as good as thought sports. We'll just stick with them because they have done with us. That's what weak leaders do and customers suffer for that. What I see like the last two weeks ago when I was in new york. I met with them. A business leader for one of the largest banks in the world with 25,000 people reporting to him. The person walks into the room wearing shorts and t shirts uh, and was so full of energy and so full of excitement. I thought I'm going to learn from him and he was asking questions about how we do our business in bed and learning from me. I was humbled, I was flawed and I realized that's what a modern business leader looks like. Even if it is one of the largest and oldest banks in the world, that's the kind of people are making big difference and it doesn't matter how all the companies, how old their data is they have mainframes or not. I hear this excuses all the type of er, mainframes, we can't move, we have COBOL going on. And guess what? You keep talking about that and hear leaders like him are going to transform those companies And next thing you know, there are some of the most modern companies in the world. >>Well certainly they, we know that they don't have any innovation strategy or any kind of R and D or anything going on that could be caught flat footed in the companies that didn't have that going on, didn't have the spine or the, the, the vision to, to at least try the cloud before Covid when Covid hit, those companies are really either going out of business or they're hurting the people who were in the cloud really move their teams into the cloud quicker to take advantage of uh, the environment that they had to. So this became a skill issue. So, so this is a big deal. This is a big deal. And having the right skills are people skilled, it will be a, I both be running everything for them. What is your take on that? >>This is an important question. You can't just say you got to do more things or new things and not take care of all things. You know, there's only 89, 10 hours so you can work in their uh, analysts in the Atlantic species constantly if your analysts are sitting there and making incremental dashboards and reports change every day and then backlog is growing for 56 days and the users are unhappy because you're not getting answers and then you ask them to go to new things. It's just not going to be enough and you can hire your way out of it. You have to make sure that if you say that I have 20 100 x product already, I don't want 21st guess what? Sometimes to be five products, you need to probably go to 21 you got to do new things to actually take away the gunk off the old and in that context, the re skilling starts with unburdening, unburdening of menial task, unburned routine task. There is nothing more frustrating than making reports and dashboards that people don't even use And 90% of the time analysts, they're amazing experiences completely wasted when they're making incremental change to tabloid reports. I kind of believe thought spot and self service on top of cloud data takes away all of that without compromising security and then you invest the experienced people. Business experience is so critical. So don't just go and hire university students and say, okay, they'll go come and quote everything the experience that they have in knowing what the business is about and what it matters to their users, that domain experience and then uplevel them res kill them and then bring fresh energy to challenge that and then make sure there is a culture that allows that to happen. These three things. That's why I said leadership is not just about hiring event of firing another, it's about cultivating a culture and living that value by saying, look if I am wrong, call me, call me out in public because I want to show you how I deal with conflict. So this is I love this thing because when I see these large companies where they're making these massive changes so fast, it inspires you to say you know what if they can do it, anyone can do it. But then I also see if the top leadership is not aligned to that. They are just trying to retire without the stock tanking too much and let me just get through two more years. The entire company suffers. >>So that's great to chat with you got great energy, love your business, love the energy, love the focus. Um it's a new wave you're on. It's a big wave um and it's it's relevant, it's cool and relevant and it's the modern way and people have to have a spine to be successful if not for the faint of heart, but the rewards are there if you get this right. This is what I I love about this new environment. Um so I gotta ask you just to kind of close it out. How would you plug the company for the folks watching that might want to engage with you guys. What's the elevator pitch? What's the positioning? How would you describe thought spot in a bumper sticker or in a positioning statement. Take a minute to talk about that. >>Remember martin Anderson said that software is eating the world, I think it is now time to update that data is eating everything including software. If you don't have a way to turn data into bespoke action for your customers. Guess what? Your customers are gonna go somewhere where they that's happening right? You may not be in the data business but the data company is going to take your business. Thought spot is very simple. We want to be the friend tent for all cloud data when it comes to structured because that's where business value numbers is world satisfaction and dissatisfaction for reduces allying it is important to move data to action and thought Spot is the pioneer in doing that through search and I >>I really think you guys want something very powerful. Looking forward to chatting with you at the upcoming eight of a startup showcase. I think data is a developer mindset. It's an app, it's part of everything. It will. Everyone's a data company, everyone is a media company. Data is everything you guys are on something really big and people got a program it with it, make experiences whether it's simple scripts, point and click. That is a new kind of developer out there. You guys are tapping into it. Great stuff. Thank >>you for coming on. Thank you john it's good to talk to you. >>Okay. It's a cube conversation here in Palo alto California were remote. We're virtual. That's the cube virtual. I'm sean for your host. Thanks for watching. Mhm. Mhm

>>Welcome to data, citizens, to anyone I'm thrilled that so many of you joining us this year for what I think will be our best conference yet. This is always my favorite moment of the year. And what makes it especially meaningful for me at this time is that we've all faced so much uncertainty over the last year. Being able to bring together or community of data, citizens, data professionals, customers, and partners gives me so much energy. We all share the same passion to use data, to create positive change in our work. And in our lives 2021 has been called a year of transitions and rightfully so the pandemic has changed our lives, our businesses and our society. It has changed or world. There's been a number of notable shifts over the last 18 months. And I like to bring up three shifts that I personally connect to. >>And these will likely resonate with many of you too. First as a shift though, it's remote work at the start of the pandemic, tens of millions of people across many industries, transition to working from home. This transition happened and presented really fast. And in many cases have happened overnight. For me not being able to meet our customers and our federal court. He begins in Berson, especially during such turbulent times. I've always actually welcomed over 200 new colleagues. New Colombians was especially hard. The second is of course, a shift towards online retail in the U S e-commerce was forecasted to reach 24% of total retail sales by 2024, but by July, 2020. So four years earlier, it had already reached 33% that has translated into an enormous boost for delivery companies. And finally, the supply chain reinvention, the pandemic reveal the complexity and vulnerabilities in the supply chains of many different companies from raw materials to freight disruptions, to labor shortages. >>The damage from the pandemic was felt everywhere. For example, my wife and I have been waiting for us for over six months for a four year old daughter's first bike. Now, many companies are oriented towards data and analytics to reduce costs and better understand, manage and optimize their entire value chain. Now, the one thing that all of these shifts have in common is that they accelerated the massive growth of digitization. This transition to digital isn't new, but how much it has accelerated. Hasn't been easy for organizations in many cases as has happened under enormous pressure. And that digitization has resulted in two related trends. First, an explosion of digital channels, which has created unprecedented amounts of new data, this more volume and more variety of data than ever before. It's been distributed broadly across organizations. Again, this is not a nutrient, but one that has also accelerated imagine just the amount of data that is now on tick-tock. >>It's also a great example of the responsibilities and risks that come with all of that data. This brings me to the second trend and risk that we had started seeing even before the pandemic, the creation of ever more data silos, these silos result in disjointed and often ineffective data teams. And what is more concerning is that it's often a lack of confidence in the outcome. This leads to an overall lack of trust in the information we need to solve this every day, maybe every hour, every minute we rely on data to make both transactional and transformative business decisions. Every organization today depends on mission, critical insights and data critical processes. What happens if suddenly there's a data problem, this could impact our resourcing or customers or back-office or entire ecosystem, the integrity and the reliability of data has real immediate, uh, long-term implications for our businesses and our reputations. >>And this will determine the trajectory of our success. We all feel the weight of data, the immense opportunities and potential implications associated with it. And this is a lot of pressure to bear, but I believe that we have the ability to take control of our data to become more effective and how we work to be more productive and to ultimately generate faster and better outcomes. I believe this is a pivotal moment as organizations transition from reacting to the pandemic, to building a healthy new, normal, we have an extraordinary opportunity to make good use of our data and by doing so, I believe we can achieve extraordinary things by making trusted data more accessible and more usable. We can do even more. We can get more out of our work. Uh, we can put more work into it. We can help our organizations serve more customers and enrich more communities with trusted data. We have the power to change things for good and with it, there's no limit to what people, businesses or society can achieve. When we are United by data, >>The world doesn't just run on information. It runs on people living their passion, dreaming big ideas, but without information without the data, those ideas won't become innovations. That's why at Colibra we're changing how organizations use data. So our customers can change the world. We make data easier to access by making it usable, manageable, and practical. We make it make sense. So people have a common language to share and shape their ideas. And no matter how far and wide that data is scattered, we make sure it's all within reach, connecting the disconnected, joining the disjointed so people can collaborate and trust that their data won't slow them down so they can prove that data has the power to change things for good, doing more enriching, more, helping more together with Collibra. You can be United by data >>United by data. All of us here are United by our passion for data. We are all data citizens, and there's so much power in this community. Uniting is also what the Colibra data intelligence cloud or product does it unites your entire organization to deliver accurate, trusted data for every use for every user and across every source managed, trusted, and accessible. These are the crucial elements that will give your teams the ability to easily collaborate and make every data workflow more productive. There's also some of the experience and the impacts of our customers take Freddie Mac. For example, it's driving their data ecosystem transformation with 5.5 billion data points and over true trillion dollars in assets. Under management, Freddie Mac leveraged Columbia to support the digital transformation and management of its data ecosystem. They eliminate duplicate data, spending improve data lake productivity and drive enhance data quality while delivering increased value for their customers. >>It's also at the heart of what Yelp is doing to connect its engineers, to trusted data unleashed product innovation and instill a data-driven culture. And why companies like audio and BT are promoting the importance of data, culture, and making data easily accessible to the data citizens throughout their organization. Over the next couple of days, the knowledge shared by our partners, our customers, guest speakers. And could you begins, will inspire and energize you to keep moving forward as change agents United by data. Again, I'm so glad to kick off data citizens and thank you for being here with us.

(introductory upbeat music) >> Hello and welcome to this Cube conversation. I'm Natalie Ehrlich your host for theCube. Today we're going to speak with an AI enhancing data startup that recently raised $75 million in C-series funding. Now we're joined by the chief marketing officer of Exosporium Ajay Khanna. [Natalie] Thank you so much for being with us today. >> Thank you so much, Natalie. Thanks for inviting me in. >> So tell us what is Exosporium. >> Sure. So Exosporium, we provide external data platform and this platform helps you discover thousands of relevant data signals external data signals that you can then use in your analytics or in your machine learning models and all. So what we are offering here is this a unique end to end platform where you can have access to thousands and thousands of data signals. And then you can take those signals and match it with your internal data. You can enrich your internal data, do the transformations and then build pipelines that business analysts can use and take it to their, their tool of their choice. Or what data scientists can do is take that enriched data and improve their ML algorithms. So that is the end-to-end platform that we provide. >> That's really fascinating. So you're constantly improving on the data and providing better analytics. Can you tell us how specifically are you helping your customers? >> Ajay: Absolutely. So as we kind of jump into the customer use cases let's first discuss this challenge with the external data, right? So when we refer to external data with the increase in AI and ML adoption there has been increase in interest in external data like getting the company data from external sources whether it is formal graphics, technographic data, you want socio-economic data, you may want like foot traffic data. You may want to include like data about website visits and, and the tons of data out there website interaction that are not within your organization but you want to get that data to get better understanding of your customers. But the challenge is that getting external data is really hard. So, and what I mean by that is that it is hard to access. First of all you don't even know how many data sources out there. It could be thousands of data sources. If you just go to data.gov there are like 250,000 data sources out there. So that is the first problem to tackle is where do I get the data from? And how do I get? And even before that what is the data that is going to impact my business? So having that issue of like data access is, is big problem. Second thing is that once you know which data you want to get it is very hard to use within your systems, or it is hard to kind of like you're going to just directly use the data into your analytics or into machine learning. You have to clean it up. You have to evaluate the quality of the data. You have to do the proper alignment and matching and integration and so on and so forth. And by various estimates like data scientists and analysts spend 80% of their time doing just that job. And the third is around the, compliance issues. We want to make sure that data is compliant with the GDPR or CCPA kind of regulations. So what we are helping our customers do is have an easy access to all these relevant data sources and where the system can recommend that, okay this is the relevant data which is going to make an impact to your business. This is the relevant data, which is going to make your ML and analytics better, and then match that data with your internal data sources automatically so that you can focus on the business value that you want to generate and take that data... Once you understand the impact of the data take it to your actual business use cases of the models that you have created. So our customers are in like various kind of industries, right? They are in CPG, they are in retail. Our customers are coming from various FinTech organizations like payments and lending and insurance. And they are using us for like various use cases. Like whether it is lead gen or whether it is a lead enrichment fraud and risk kind of use cases understanding the loan risk loan application risks and the by having access to these additional data sources that helps them make better decisions about their customers, about their business. >> Natalie: Fascinating. Well tell us, how do you see this market evolving? >> Market is, is, is really dynamic. And we have seen this whole market changing the whole data market, kind of like changing in, last year and a half with the pandemic coming in, right? So the models that we were working on for credit risk for evaluating loan applications were not working anymore. The data that we had was not really usable to make those decisions. So many of our customers, they had to depend on external data to make those credit decisions, right? I mean, if I have to approve an application for a small or a medium business restaurant and the restaurant is closed for last to five months how do I do that? So they were looking for additional data sources like foot traffic data about the Yelp reviews or about the ratings around how they're signed up for various delivery services and use those alternative sources to make those decisions. I think with these kind of like, as the situation come in, companies will become much more agile to react to these kinds of either data losses or changes in the data that they need. And some of the things that we also see right now is where Google is stopping the third party cookies with Chrome, right? Or Apple saying that with iOS 14, there are new transparency requirements that you have to, you have to abide by. So if those signals are gone, then how do companies better understand their customers? How do the companies will redesign their information, that they are delivering to their customers or the products that they are presenting to their customers. So having that agility will be determining the competitive advantage for these companies. And once these data signal losses happen, you cannot start evaluating the alternate data at that point in time because it takes like six, seven months to going to find the data sources and negotiate for those data sources bring them on board and then integrate them to kind of start using them. Then it is already too late. So what we are seeing is that companies will be much more agile and looking for a lot of external data sources to bring them in seamlessly and be able to make their business decision by incorporating those data sources as well. So, so that's how we are seeing that the use of external data is going to, going to increase with the time. >> Fascinating. And also that you mentioned the pandemic and the company added new data signals to help organizations understand risk. >> Ajay: Absolutely. Can you explain how that actually works to our audience? >> Ajay: Sure. So let's take a couple of scenarios, right? So for example, there is a lending organization and then they are looking for approving a loan application for a small medium business. And they had like three years back revenues or three years previous employee data or their tax returns and everything. But that is irrelevant right now because the business is not running. So how can they use alternate data signals to make that loan decisions or credit decisions? So they will be relying on some of like foot traffic data. They may rely on ratings and reviews. They may rely on, on other delivery services subscription that they have subscribed to and helping their customers, and then use those additional signals to make those credit decisions. This is like one situation. Another situation that we came across was in, CPG where food and beverages, sellers, whether those are like convenience stores or whether those are like small restaurants they're going in and out of business. And now when they're coming back in or the new restaurants or convenience stores are emerging, how do this food and beverage provider find those new customers? What are the additional signals they can use to go to that customer right away and say that, okay we are there with you. We are here to kind of like support your business. What are the additional things that you need to kind of like bring everything back to business? What are the additional shelf spaces available to place your product out there? Because now you don't have data, there's a data lag now. So you need to kind of like provide that additional data to your field operations so that they can find the right businesses. They can find they can prioritize them and they can see that, okay these are the businesses which are going to kind of like come back and we need to proactively go and market to them. So that once we are out of this COVID which hopefully we are now and how to support the small businesses that come come right back on track. >> Very, very interesting. And recently your company Exosporium closed $75 million in seed series funding and not even a year before another $31 million. So what do you attribute to that success? >> I think it is, it is the whole idea of a increase in adoption of AI and ML that we are seeing in the last few years. And as this adoption increases there is an increase in appetite for external data. So companies do realize that just having ML algorithms is not enough. That is not a competitive advantage. Everybody has the same algorithms. The advantage is the data that you have, advantages the domain expertise that you have, and then having the wide variety of data that is really important. So what we are seeing is that there is an increase in trust and getting access to these external data sources as a competitive advantage and then having that access easily and being able to easily use that external data into your analytics, into your ML models. That's where the, the real kind of advantages where you can actually bring your big ideas to life and execute on those ideas, but are coming from your business analysts and from your data scientists. So I think that increased interest is what we are seeing here. >> Well, that's a fascinating point on how data is really the central point of analytics. Really appreciate your fantastic insights on this program for this conversation on theCUBE. I'm Natalie Ehrlich your host. And that was Ajay Khanna the chief marketing officer of Exosporium. Thanks so much for joining us today. (concluding upbeat music)

>> Narrator: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE Conversation. >> Hey, welcome back everybody Jeff Frick here with theCUBE. We're coming to you today from our Palo Alto studios with theCUBE conversation, talking about data, and we're excited to have our next guest. He's been on a number of times, many times, CUBE alum, really at the forefront of helping companies and customers be more data centric in their activities. So we'd like to welcome onto the show Satyen Sangani. He is the co founder and CEO of Alation. Satyen, great to see you. >> Great to see you, Jeff. It's good to see you again in this new world, a new format. >> It is a new world, a new format, and what's crazy is, in March and April we were talking about this light switch moment, and now we've just turned the calendar to October and it seems like we're going to be doing this thing for a little bit longer. So, it is kind of the new normal, and even I think when it's over, I don't think everything's going to go back to the way it was, so here we are, but you guys have some exciting news to announce, so let's just jump to the news and then we'll get into a little bit more of the nitty gritty. So what do you got coming out today, right? >> Yeah its so. >> What we are announcing today is basically Alation 2020, which is probably one of the biggest releases that I've been with, that we've had since I've been with the company. We with it are releasing three things. So in some sense, there's a lot of simplicity to the release. The first thing that we're releasing is a new experience around what we call the business user experience, which will bring in a whole new set of users into the catalog. The second thing that we're announcing is basically around Alation analytics and the third is around what we would describe as a cloud-native architecture. In total, it brings a fully transformative experience, basically lowering the total cost of getting to a data management experience, lower and data intelligent experience, much lower than previously had been the case. >> And you guys have a really simple mission, right? You're just trying to help your customers be more data, what's the right word? Data centric, use data more often and to help people actually make that decision. And you had an interesting quote in another interview, you talked about trying to be the Yelp for information which is such a nice kind of humanizing way to think about it because data isn't necessarily that way and I think, you mentioned before we turned on the cameras, that for a lot of people, maybe it's just easier to ignore the data. If I can just get the decision through, on a gut and intuition and get onto my next decision. >> Yeah, you know it's funny. I mean, we live in a time where people talk a lot about fake news and alternative facts and our vision is to empower a curious and rational world and I always smile when I say that a little bit, because it's such a crazy vision, right? Like how you get people to be curious and how do you get people to think rationally? But you know, to us, it's about one making the data really accessible, just allowing people to find the data they need when and as they want it. And the second is for people to be able to think scientifically, teaching people to take the facts at their disposal and interpret them correctly. And we think that if those two skills existed, just the ability to find information and interpret it correctly, people can make a lot better decisions. And so the Yelp analogy is a perfect one, because if you think about it, Yelp did that for local businesses, just like Amazon did it for really complicated products on the web and what we're trying to do at Alation is, in some sense very simple, which is to just take information and make it super usable for people who want to use it. >> Great, but I'm sure there's the critics out there, right? Who say, yeah, we've heard this before the promise of BI has been around forever and I think a lot of peoples think it just didn't work whether the data was too hard to get access to, whether it was too hard to manipulate, whether it was too hard to pull insights out, whether there's just too much scrubbing and manipulating. So, what is some of the secret sauce to take? What is a very complex world? And again and you got some very large customers with some giant data sets and to, I don't want to say humanize it, but kind of humanize it and make it easier, more accessible for that business analyst not just generally, but more specifically when I need it to make a decision. >> Yeah I mean, it's so funny because, making something, data is like a lot of software death by 1000 cuts. I mean you look at something from the outside and it looks really, really, really simple, but then you kind of dwell into any problem and that can be CRM something like Salesforce, or it can be something like service now with ITSM, but these are all really, really complicated spaces and getting into the depths and the detail of it is really hard. And data is really no different, like data is just the sort of exhaust from all of those different systems that exist inside of your company. So the detail around the data in your company is exhaustingly minute. And so, how do you make something like that simple? I think really the biggest challenge there is progressively revealing complexity, right? Giving people the right amount of information at the right amount of time. So, one of the really clever things that we do in this business user experience is we allow people to search for and receive the information that's most relevant to them. And we determined that relevance based upon the other people in the enterprise that happen to be using that data. And we know what other people are using in that company, because we look at the logs to understand which data sources are used most often, and which reports are used most often. So right after that, when you get something, you just see the name of the report and it could be around the revenues of a certain product line. But the first thing that you see is who else uses it. And that's something that people can identify with, you may not necessarily know what the algorithm was or what the formula might be, how the business glossary term relates to some data model or data artifact, but you know the person and if you know the person, then you can trust the information. And so, a lot of what we do is spend time on design to think about what is it that a person expects to see and how do they verify what's true. And that's what helps us really understand what to serve up to somebody so that they can navigate this really complicated, relevant data. >> That's awesome, cause there's really a signal to noise problem, right? And I think I've heard you speak before. >> Yeah >> And of course this is not new information, right? There's just so much data, right? The increasing proliferation of data. And it's not that there's that much more data, we're just capturing a lot more of it. So your signal to noise problem just gets worse and worse and worse. And so what you're talking about is really kind of helping filter that down to get through a lot of that, a lot of that noise, so that you can find the piece of information within the giant haystack. That is what you're looking for at this particular time in this particular moment. >> Yeah and it's a really tough problem. I mean, one of the things that, it's true that we've been talking about this problem for such a long time. And in some instance, if we're lucky, we're going to be talking about it for a lot longer because it used to be that the problem was, back when I was growing up, you were doing research on a topic and you'd go to the card catalog and you'd go to the Dewey decimal system. And in your elementary school or high school library, you might be lucky if you were to find, one, two or three books that map to the topic that you were looking for. Now, you go to Google and you find 10,000 books. Now you go inside of an enterprise and you find 4,000 relational database tables and 200 reports about an artifact that you happened to be looking for. And so really the problem is what do I trust? And what's correct and getting to that level of accuracy around information, if there's so much information out there is really the big problem of our time and I think, for me it's a real privilege to be able to work on it because I think if we can teach people to use information better and better then they can make better decisions and that can help the world in so many different. >> Right, right, my other favorite example that everybody knows is photographs, right? Back when you only got 24 and a roll and cost you six bucks to develop it. Those were pretty special and now you go buy a fancy camera. You can shoot 11, 11 frames a second. You go out and shoot the kids at the soccer game. You come home with 5,000 photos. How do you find the good photo? It's a real, >> Yeah. >> It's a real problem. If you've ever faced something like that, it's kind of a splash of water in the face. Like where do I even begin? But the other piece that you talk about a lot, which is slightly different but related is context, and in favorite concept, it's like 55, right? That's a number, but if you don't have any context for that number, is it a temperature? Is it cold inside the building? Is it a speed? Is it too slow on i5? Or is it fast because I'm on a bicycle going down a Hill and without context data is just, it's just a number. It doesn't mean anything. So you guys really by adding this metadata around the data are adding a lot more contextual information to help figure out kind of what that signal is from the noise. >> Yap, you'll get facts from anywhere, right? Like, you're going to have a Hitchcock, you've got a 55 or 42, and you can figure out like what the meaning of the universe is and apparently the answer is 42 and what does that mean? It might mean a million different things and that, to me, that context is the difference between, suspecting and knowing. And there's the difference between having confidence and basically guessing. And I think to the extent that we can provide more of that over time, that's, what's going to make us, an ever more valuable partner to the customers that we satisfy today. >> Right, well, I do know why 42 is always the answer 'cause that's Ronnie Lot and that's always the answer. So, that one I know that's an easy one. (both chuckles) But it is really interesting and then you guys just came out. I heard Aaron Kalb on, one of your co-founders the other day and we talked about this new report that you guys have sponsored the Data Culture Report and really, putting some granularity on a Data Culture Index and I thought it was pretty interesting and I'm excited that you guys are going to be doing this, longitudinally because whether you do or do not necessarily agree with the method, it does give you a number, It does give you a score, It's a relatively simple formula. And at least you can compare yourself over time to see how you're tracking. I wonder if you could share, I mean, the thing that jumps out right off the top of that report is something we were talking about before we turned the cameras on that, people's perception of where they are on this path doesn't necessarily map out when you go bottoms up and add the score versus top down when I'm just making an assessment. >> Yeah, it's funny, it's kind of the equivalent of everybody thinks they're an above average driver or everybody thinks they're above average in terms of obviously intelligence. And obviously that mathematically is not possible or true, but I think in the world of data management, we all talk about data, we all talk about how important it is to use data. And if you're a data management professional, you want people in your company to use more data. But ironically, the discipline of data management doesn't actually use a lot of data itself. It tends to be a very slow methodical process driven gut oriented process to develop things like, what data models exist and how do I use my infrastructure and where do I put my data and which data quality is best? Like all of those things tend to be, somewhat heuristic driven or gut driven and they don't have to be and a big part of our release actually is around this product called Alation Analytics. And what we do with that product is really quite interesting. We start measuring elements of how your organization uses data by team, by data source, by use case. And then we give you transparency into what's going on with the data inside of your landscape and eco-system. So you can start to actually score yourself both internally, but also as we reveal in our customer success methodology against other customers, to understand what it is that you're doing well and what it is that you're doing badly. And so you don't need necessarily to have a ton of guts instinct anymore. You can look at the data of yourselves and others to figure out where you need to improve. And so that's a pretty exciting thing and I think this notion that says, look, you think you're good, but are you really good? I mean, that's fundamental to improvement in business process and improvement in data management, improvement in data culture fundamentally for every company that we work with. >> Right, right and if you don't know, there's a problem, and if you're not measuring it, then there's no way to improve on it, right? Cause you can't, you don't know, what you're measuring is. >> Right. >> But I'm curious of the three buckets that you guys measured. So you measured data search and discovery was bucket number one, data literacy, you know what you do once you find it and then data governance in terms of managing. It feels like that the search and discovery, which is, it sounds like what you're primarily focused on is the biggest gap because you can't get to those other two buckets unless you can find and understand what you're looking for. So is that JIve or is that really not problem, is it more than manipulation of the data once you get it? >> Yeah, I mean we focus really. We focus on all three and I think that, certainly it's the case that it's a virtuous cycle. So if you think about kind of search and discovery of data, if you have very little context, then it's really hard to guide people to the right bit of information. But if I know for example that a certain data is used by a certain team and then a new member of that team comes on board. Then I can go ahead and serve them with exactly that bit of data, because I know that the human relationships are quite tight in the context graph on the back end. And so that comes from basically building more context over time. Now that context can come from a stewardship process implemented by a data governance framework. It can come from, building better data literacy through having more analytics. But however, that context is built and revealed, there tends to be a virtuous cycle, which is you get more, people searching for data. Then once they've searched for the data, you know how to necessarily build up the right context. And that's generally done through data governance and data stewardship. And then once that happens, you're building literacy in the organization. So people then know what data to search for. So that tends to be a cycle. Now, often people don't recognize that cycle. And so they focus on one thing thinking that you can do one to the exclusion of the others, but of course that's not the case. You have to do all three. >> Great and I would presume you're using some good machine, Machine Learning and Artificial Intelligence in that process to continue to improve it over time as you get more data, the metadata around the data in terms of the usage and I think, again I saw in another interview there talking about, where should people invest? What is the good data? What's the crap data? what's the stuff we shouldn't use 'cause nobody ever uses it or what's the stuff, maybe we need to look and decide whether we want to keep it or not versus, the stuff that's guiding a lot of decisions with Bob, Mary and Joe, that seems to be a good investment. So, it's a great application of applied AI Machine Learning to a very specific process to again get you in this virtuous cycle. That sounds awesome. >> Yeah, I know it is and it's really helpful to, I mean, it's really helpful to think about this, I mean the problem, one of the biggest problems with data is that it's so abstract, but it's really helpful to think about it in just terms of use cases. Like if I'm using a customer dataset and I want to join that with a transaction dataset, just knowing which other transaction datasets people joined with that customer dataset can be super helpful. If I'm an analyst coming in to try to answer a question or ask a question, and so context can come in different ways, just in the same way that Amazon, their people who bought this product also bought this product. You can have all of the same analogies exist. People who use this product also use that product. And so being able to generate all that intelligence from the back end to serve up simple seeming experience on the front end is the fun part of the problem. >> Well I'm just curious, cause there's so many pieces of this thing going on. What's kind of the, aha moment when you're in with a new customer and you finish the install and you've done all the crawling and where all the datasets are, and you've got some baseline information about who's using what I mean, what is kind of the, Oh, my goodness. When they see this thing suddenly delivering results that they've never had at their fingertips before. >> Yeah, it's so funny 'cause you can show Alation as a demo and you can show it to people with data sets that are fake. And so we have this like medical provider data set that, we've got in there and we've got a whole bunch of other data sets that are in there and people look at it and interestingly enough, a lot of time, they're like, Oh yeah, I can kind of see it work and I can kind of like understand that. And then you turn it on against their own data. The data they have been using every single day and literally their faces change. They look at the data and they say, Oh my God, like, this is a dataset that Steven uses, I didn't even know that Steven thought that this data existed and, Oh my God, like people are using this data in this particular way. They shouldn't be using that data at all, Like I thought I deprecated that dataset two years ago. And so people have all of these interesting insights and it's interesting how much more real it gets when you turn it on against the company's systems themselves. And so that's been a really fun thing that I've just seen over and over again, over the course of multiple years where people just turn on the cup, they turn on the product and all of a sudden it just changes their view of how they've been doing it all along. And that's been really fun and exciting. >> That's great yeah, cause it means something to them, right? It's not numbers on a page, It's actually, it's people, it's customers, it's relationships, It's a lot of things. That's a great story and I'm curious too, in that process, is it more often that they just didn't know that there were these other buckets of reports and other buckets of data or was it more that they just didn't have access to it? Or if they did, they didn't really know how to manipulate it or to integrate it into their own workflow. >> Yeah, It's kind of funny and it's somewhat role dependent, but it's kind of all of the above. So, if you think about it, if you're a data management professional, often you kind of know what data sources might exist in the enterprise, but you don't necessarily know how people are using the data. And so you look at data and you're like, Oh my God, I can't believe this team is using this data for this particular purpose. They shouldn't be doing that. They should be using this other data set. I deprecated that data set like two years ago. And then sometimes if you're a data scientist, you're you find, Oh my gosh, there's this new database that I otherwise didn't realize existed. And so now I can use that data and I can process that for building some new machine learning algorithms. In one case we've had a customer where they had the same data set procured five different times. So it was a pure, it was a data set that cost multiple hundreds of thousands of dollars. They were spending $2 million overall on a data set where they could have been spending literally one fifth of that amount. And then you had a sort of another case finally, where you're basically just looking at it and saying, Hey, I remember that data set. I knew I had that dataset, but I just don't remember exactly where it was. Where did I put that report? And so it's exactly the same way that you would use Google. Sometimes you use it for knowledge discovery, but sometimes you also use it for just remembering the thing you forgot. >> Right but, but the thing, like I remember when people were trying to put Google search in that companies just to find records not necessarily to support data efforts and the knock was always, you didn't have enough traffic to drive the algorithm to really have effective search say across a large enterprise that has a lot of records, but not necessarily a lot of activity. So, that's a similar type of problem that you must have. So is it really extracting that extra context of other people's usage that helps you get around kind of that you just don't have a big numbers? >> Yeah, I mean that kind of is fundamentally the special sauce. I mean, I think a lot of data management has been this sort of manual brute force effort where I get a whole bunch of consultants or a whole bunch of people in the room and we do this big documentation session. And all of a sudden we hope that we've kind of, painted the golden gate bridge is at work. But, knowing that three to six months later, you're going to have to go back and repaint the golden gate bridge overall all over again, if not immediately, depending on the size and scale of your company. The one thing that Google did to sort of crawl the web was to really understand, Oh, if a certain webpage was linked to super often, then that web page is probably a really useful webpage. And when we crawled the logs, we basically do the exact same thing. And that's really informed getting a really, really specific day one view of your data without having to have a whole bunch of manual effort. And that's been really just dramatical. I mean, it's been, it's allowed people to really see their data very quickly and new different ways and I think a big part of this is just friction reduction, right? We'd all love to have an organized data world. We'd love to organize all the information in a company, but for anybody has an email inbox, organizing your own inbox, let alone organizing every database in your company just seems like a specificity in effort. And so being able to focus people on what's the most important thing has been the most important thing. And that's kind of why we've been so successful. >> I love it and I love just kind of the human factors kind of overlay, that you've done to add the metadata with the knowledge of who is accessing these things and how are they accessing it. And the other thing I think is so important Satyen is, we talk about innovation all the time. Everybody wants more innovation and they've got DevOps so they can get software out faster, et cetera, et cetera. But, I fundamentally believe in my heart of hearts that it's much more foundational than that, right? That if you just get more people, access to more information and then the ability to manipulate and clean knowledge out of that information and then actually take action and have the power and the authority to take action. And you have that across, everyone in the company or an increasing number of people in the company. Now suddenly you're leveraging all those brains, right? You're leveraging all that insight. You're leveraging all that kind of First Line experience to drive kind of a DevOps type of innovation with each individual person, as opposed to, kind of classic waterfall with the Chief Innovation Officer, Doing PowerPoints in his office, on his own time. And then coming down from the mountain and handing it out to everybody to go build. So it's a really a kind of paradox that by adding more human factors to the data, you're actually making it so much more usable and so much more accessible and ultimately more valuable. >> Yeah, it's funny we, there's this new term of art called data intelligence. And it's interesting because there's lots of people who are trying to define it and there's this idea and I think IDC, IDC has got a definition and you can go look it up, but if you think about the core word of intelligence, it basically DevOps down to the ability to acquire information or skills, right? And so if you then apply that to companies and data, data intelligence then stands to reason. It's sort of the ability for an organization to acquire, information or skills leveraging their data. And that's not just for the company, but it's for every individual inside of that company. And we talk a lot about how much change is going on in the world with COVID and with wildfires here in California. And then obviously with the elections and then with new regulations and with preferences, cause now that COVID happened everybody's at home. So what products and what services do you have to deliver to them? And all of this change is, basically what every company has to keep up with to survive, right? If capitalism is creative destruction, the world's getting destroyed, like, unfortunately more often than we'd like it to be,. >> Right. >> And so then you're say there going, Oh my God, how do I deal with all of this? And it used to be the case that you could just build a company off of being really good at one thing. Like you could just be the best like logistics delivery company, but that was great yesterday when you were delivering to restaurants. But since there are no restaurants in business, you would just have to change your entire business model and be really good at delivering to homes. And how do you go do that? Well, the only way to really go do that, is to be really, really intelligent throughout your entire company. And that's a function of data. That's a function of your ability to adapt to a world around you. And that's not just some CEO cause literally by the time it gets to the CEO, it's probably too late. Innovations got to be occurring on the ground floor. And people have got to repackage things really quickly. >> I love it, I love it. And I love the other human factor that we talked about earlier. It's just, people are curious, right? So if you can make it easy for them to fulfill their curiosity, they're going to naturally seek out the information and use it versus if you make it painful, like a no fun lesson, then people's eyes roll in and they don't pay attention. So I think that it's such an insightful way to address the problem and really the opportunity and the other piece I think that's so different when you're going down the card catalog analogy earlier, right? Is there was a day when all the information was in that library. And if you went to the UCLA psych library, every single reference that you could ever find is in that library, I know I've been there, It was awesome, but that's not the way anymore, right? You can't have all the information and it's pulling your own information along with public information and as much information as you can. where you start to build that competitive advantage. So I think it's a really great way to kind of frame this thing where information in and of itself is really not that valuable. It's about the context, the usability, the speed of these ability and that democratization is where you really start to get these force multipliers and using data as opposed to just talking about data. >> Yeah and I think that that's the big insight, right? Like if you're a CEO and you're kind of looking at your Chief Data Officer or Chief Data and Analytics Officer. The real question that you're trying to ask yourself is, how often do my people use data? How measurable is it? Like how much do people, what is the level at which people are making decisions leveraging data and that's something that, you can talk about in a board room and you can talk about in a management meeting, but that's not where the question gets answered. The question gets really answered in the actual behaviors of individuals. And the only way to answer that question, if you're a Chief Analytics Officer or somebody who's responsible for data usage within the company is by measuring it and managing it and training it and making sure it's a part of every process and every decision by building habit and building those habits are just super hard. And that's, I think the thing that we've chosen to be sort of the best in the world at, and it's really hard. I mean, we're still learning about how to do it, but, from our customers and then taking that knowledge and kind of learning about it over time. >> Right, well, that's fantastic. And if it wasn't hard, it wouldn't be valuable. So those are always the best problems to solve. So Satyen, really enjoyed the conversation. Congratulations to you and the team on the new release. I'm sure there's lots of sweat, blood and tears that went into that effort. So congrats on getting that out and really great to catch up. Look forward to our next catch up. >> You too Jeff, It's been great to talk. Thank you so much. >> All right, take care. All righty Satyen and I'm Jeff, you're watching theCUBE. We'll see you next time. Thanks for watching. (ethereal music)

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi everybody, welcome to this CUBE conversation. This is Dave Vellante, and as part of my CEO and CXO series I've been bringing in leaders around the industry and I'm really pleased to have Sudheesh Nair, who is the CEO of ThoughtSpot Cube alum. Great to see you against Sudheesh, thanks for coming on. >> My pleasure Dave. Thank you so much for having me. I hope everything is well with you and your family. >> Yeah ditto back at you. I know you guys were in a hot spot for a while so you know we power on together, so I got to ask you. You guys are AI specialists, maybe sometimes you can see things before they happen. At what point did you realize that this COVID-19 was really going to be something that would affect businesses globally and then specifically your business. >> Yeah it's amazing, isn't it? I mean we used to think that in Silicon Valley we are sitting at the top of the world. AI and artificial intelligence, machine learning, Cloud, IOT and all of a sudden this little virus comes in and put us all in our places basically. We are all waiting for doctors and others to figure these things out so we can actually go outside. That tells you all about what is really important in life sometimes. It's been a hard journey for most people because of what a huge health event this has been. From a Silicon Valley point of view and specifically from artificial intelligence point of view, there is not a lot of history here that we can use to predict the future, however early February we had our sales kick off and we had a lot of our sellers who came from Asia and it became sort of clear to us immediately during our sales kick off in Napa Valley that this is not like any other event. The sort of things that they were going through in Asia we sort of realized immediately that us and when it gets to the shores of the US, this is going to really hurt. So we started hunkering down as a company, but as you mentioned early when we were talking, California in general had a head start, so we've been hunkered down for almost five weeks now, as a company and as the people and the results are showing. You know it is somewhat contained. Now obviously the real question is what next? How do we go out? But that's probably the next journey. >> So a lot of the executives that I've talked to, of course they start with the number one importance is the health and well-being of our employees. We set up the work from home infrastructure, et cetera. So that's I think, been fairly well played in the media and beginning to understand that pretty well. Also, you saw I talked to Frank Slootman and he's sort of joked about the Sequoia memos, that you know eliminate unnecessary expenses and practices. I've always eliminated unnecessary expenses, keep it to the essentials, but one of the things that I haven't probed with CEOs and I'd love your thoughts on this is, did you have to rethink sort of the ideal customer profile and your value proposition in the specific context of COVID? Was that something that you deliberately did? >> Yeah so it's a really important question that you asked, and I saw the Frank interview and I a 100% agree with that. Inside the company we have this saying, and our co-founder Ajeet actually coined the phrase of living like a middle-class company, and we've always lived that, even though we have, 300 plus million dollars in the bank and we raised a big round last year. It is important to know that as a growth stage company, we are not measured on what's in the bank. It's about the value that we are delivering and how much I'll be able to collect from customers to run the business. The living like a middle-class family has always been the ethos of the company and that has been a good thing. However, I've been with ThoughtSpot for a little more than 18 months. I joined as the CEO. I was an early investor in the company and there are a couple of big changes that we made in the last 18 months, and one of is moving to Cloud which we can talk. The other one has been around narrowing our focus on who we sell to, because one of the things that, as you know very well Dave, is that the world of data is extremely complex. Every company can come in and say, "We have the best solution out there" and it can just be in the world, but the reality is no single product is going to solve every problem for a customer when it comes to a data analytics issue. All we can hope for is that we become part of a package or solution that solves a very specific problem, so in that context there's a lot of services involved, a lot of understanding of customer problems involved. We are not a bi-product in the sense of Tableau or click on Microsoft, but they do. We are about a use case based outcomes, so we knew that we can't be everywhere. So the second change we made is actually a narrower focus, exclusively sell to global. That class, the middle class mentality, really paid off now because almost all the customers we sell to are very large customers and the four work verticals that we were seeing tremendous progress, one was healthcare, second was financial sector, the third was telecom and manufacturing and the last one is repair. Out of these four, I would say manufacturing is the one where we have seen a slowdown, but the other verticals have been, I would say cautiously spending. Being very responsible and thus far, I'm not here to say that everything is fine, but the impact if you take Zoom as a spectrum, on one end of the spectrum, where everything is doing amazingly well, because they are a good product market fit to hospitality industry on the other side. I would say ThoughtSpot and our approach to data analytics is closer to this than that. >> That's very interesting Sudheesh because, of course health care, I don't think they have time to do anything right now. I mean they're just so overwhelmed so that's obviously an interesting area that's going to continue to do well I would think. And they, the Financial Services guys, there's a lot of liquidity in the system and after 2009 the FinTech guys or the financial, the banks are doing quite well. They may squeeze you a little bit because they're smart negotiators, but as you say manufacturing with the supply chains, and in retail, look, if your ecommerce I mean Amazon hit, all-time highs today up whatever, 20% in the last two weeks. I mean just amazing what's happening, so it's really specific parts of those sectors will continue to do well, won't they? >> Absolutely, I think look, I saw this joke on Twitter, what's the number one cost? What is in fact (mic cuts out). Very soon people will say it is COVID and even businesses that have been tried to, sort of relatively, reluctant to really embrace the transformation that the customers have been asking for. This has become the biggest forcing function and that's actually a good thing because consumers are going to ultimately win because once you get groceries delivered to you into your front doors, it's going to be hard to sort of go back to standing in the line in Costco, when InstaCart can actually deliver it for you and you get used to it, so there are some transformation that is going to happen because of COVID. I don't think that society will go back from, but having said that, it's also not transformation for the sake of transformation. So speaking from our point of view on data analytics, I sort of believe that the last three to four years we have been sort of living in the Renaissance of enterprise data analytics and that's primarily because of three things. The first thing, every consumer is expecting, no matter how small or the big business, is to get to know them. You know, I don't want you to treat me like an average. I don't want you treat me like a number. Treat me like a person, which means understand me but personalize the services you are delivering and make sure that everything that you send me are relevant. If there's a marketing campaign or promo or customer support call, make sure it's relevant. The relevance and personalization. The second is, in return for that. customers are willing to give you all sorts of data. The privacy, be damned, so to a certain extent they are giving you location information, medical information,-- And the last part is with Cloud, the amount of data that you can collect and free plus in data warehouse like Snowflakes, like Redshift. It's been fundamentally shifted, so when you toggle them together the customers demand for better actors from the business, then amount of data that they're willing to give and collect to IOT and variables and then cloud-based technologies that allows you to process and store this means that analyzing this data and then delivering relevant actions to the consumers is no longer a nice to have and that I think is part of the reason why ThoughtSpot is finding sort of a tailwind, even with all this global headwind that we are all in. >> Well I think too, the innovation formula really has changed in our industry. I've said many times, it's not Moore's law anymore, it's the combination of data plus AI applied to that data and Cloud for scale and you guys are at the heart of that, so I want to talk about the market space a little bit. You look at BI and analytics, you look at the market. You know the Gartner Magic Quadrant and to your point, you know the companies on there are sort of chalk and cheese, to borrow a phrase from our friends across the pond. I mean, you're not power BI, you're not SaaS. I mean you're sort of search led. You're turning natural language into complex sequel queries. You're bringing in artificial intelligence and machine intelligence to really simplify and dramatically expand and put into the hands of business people analytics. So explain a little bit. First of all, do I have that sort of roughly right? And help us frame the market space how you think about it. >> Yeah I mean first of all, it is amazing that the diverse industry and technologies that you speak to and how you are able to grasp all of them and summarize them within a matter of seconds is a term to understand in itself. You and Stew, you both have that. You are absolutely right. So the way I think of this is that BI technologies have been around and it's played out really well. It played it's part. I mean if you look at it the way I think of BI, the most biggest BI tool is still Excel. People still want to use Excel and that is the number one BI tool ever. Then 10 years ago Tableau came in and made visualizations so delightful and a pic so to speak. That became the better way to consume complex data. Then Microsoft came in Power BI and then commoditized and the visualization to a point that, you know Tableau had to fight and it ended up selling to the Salesforce. We are not trying to play there because I think if you chase the idea of visualization it is going to be a long hard journey for ThoughtSpot to catch Tableau in visualization. That's not what we are trying to do. What we are trying to do is that you have a lot of data on one hand and you have a consumer sitting here and saying data doesn't mean you treated me well. What is my action that is this quote, very customized action quote. And our question is, how does beta turn into bespoke action inside a business? The insurance company is calling. You are calling an insurance company's customer support person. How do you know that the impact that you are getting from them is customized. But turning data into insight is an algorithmic process. That's what BI does, but that's like a few people in an organization can do that. Think of them like oil. They don't mix with water, that's the business people. The merchandising specialist who figures out which one should become site and what should be the price what should be ranking. That's the merchandiser. Their customer support person, that's a business user. They don't necessarily do Python or SQL, so what happens is in businesses you have the data people like water and the business people who touch the customer and interact with them every day, they're like the water. They don't mix. The idea of ThoughtSpot is very simple. We don't want this demarcation. We don't want this chasm. We want to break it so that every single person who interact with the customer should be able to have an interactive storytelling with the data, so that every decision that they make takes data into insight to knowledge to action, and that decision-making pipeline cannot be gut driven alone. It has to be enabled by data science and human experience coming together. So in our view, a well deployed data platform, decision-making platform, will enhance and augment human experience, as opposed to human experience says, this data says that, so you've got to pick one. That's an old model and that has been the approach with natural language based interactive access with the BI being done automated through AI in the backend, parts what we are able to put very complex data science in front of a 20 year experienced merchandising specialist in a large e-commerce website without learning Python, without learning people, without understanding data warehouse >> Right so, a couple of things I want to pick up on. I mean data is plentiful, insights aren't. That's really the takeaway from one of the things that you mentioned and this notion of storytelling is very, very important. I mean, all business people, they better be storytellers in some way shape or form and what better way to tell stories than with data, and so, because as you say it's no longer gut feel, it's not the answer anymore. So it seems to me Sudheesh, that you guys are transformative. The decision to focus on the global 2000 and really not, get washed up in the Excel, well I could just do it in Excel, or I'm going to go get Power BI, it's good enough. It's really, you're trying to be transformative and you've got a really disruptive model that we talked about before, search led and you're speaking to the system, or, typing in a way that's more natural, I wonder if you could comment on that and particularly that disruption of that transformation. >> Remember we are selling to global 2000. Almost all of them will have Tableau or one of these power BI or one of these solutions already, so you're not trying to go right and change that. What we have done is very clearly focus on use cases. We're transforming data into action. We will move the needle for the bit, but for example with the COVID situation going on, one of the most popular use cases for us is around working capital management. Now a CFO who's been in the business for 20 or 30 years is an expert and have the right kind of gut feeling about how her business is running when it comes to working capital. However, imagine now she can do 20 what-if scenarios in the next five seconds or next 10 minutes without going to the SPN 18, without going to the BI team. She can say what if we reduce hiring in Japan and instead we focus them on Singapore? What if we move 20% of marketing dollars from Germany to New York? What would be the impact of AR going up by 1% versus AP going down by 1%? She needs to now do complex scenarios, but without delay. It's sort of like how do I find a restaurant through Yelp versus going to the lobby to talk to a specialist who tells me the local restaurant. This interactive database storytelling for gut enhances the decision-making is very powerful. This is why, customer have, our largest customer has spent more than $26 million with ThougthSpot and this is not small. Our average is around close to 700k. This week for example, we are having a webinar where Verizon's SVP of Analytics specifically focused on finance. He's actually going to be on a webinar with our CFO. Our CFO Sophie, one of our financial specialists and Jeff Noto from Verizon are going to be on this talking about working capital management. What parts ThoughtSpot is a portion of, but they are sharing their experience of how do we manage, so that kind of varies, like extremely rigid focus on use cases, supply chain, modeling different things so that someone who knows Asia can really interact with the data to figure out if our supply chain from Bangladesh is going to be impacted because of COVID can we go to Ecuador? What will that look like? What will be the cost? What's the transportation cost, the fuel cost, Business has become so complex you don't have time to take five, six days to look at the report, no matter how pretty that report is, you have to make it efficient. You need to be able to make a lightning fast decision and something like COVID is really exposing all of that because day by day situation on the ground is changing. You know, employees are calling in sick. The virus is breaking out in one place, other place. If it's not, curves are going up and down so you cannot have any sort of delay between human experience and data signs and all of that comes down to your point telling visual stories so that the organization can rally behind the changes that they want to make. >> So these are mission-critical use cases. They are big problems that you're solving and attacking. As you said, you're not all things to all people. One of the things you're not is a data store, right? So you've got a partner, you've got to have an ecosystem, whether it's cloud databases, the cloud itself. I wonder if you could talk about some of the key partnerships that you're forming and how you're going to market and how that's affecting your business. >> Yeah, I mean one of the things that I've always believed in Silicon Valley is that companies die out of indigestion, not out of starvation. You try to do everything. That's how you end up dying and for us in the space of data, it's an extremely humbling space because there is so much to do, data prep, data warehousing, you know a mash-up of data, hosting of data, We have clearly decided that our ability is best spent on making artificial intelligence to work, interactive storytelling for business use and that's it. With that said, we needed a high velocity agility partner in the back end and Cloud based data warehouse have become a huge tailwind for us because our entire customer deployments are on Cloud, and the number one, obviously as you know from Frank's thing, the Snowflake has actually given, customers have seen Snowflakes plus ThoughtSpot is actually a good thing and we are exclusive in global 2000 and the Snowflake is climbing up there and we are able to build a good mutual partnership, but we are also seeing a really creative partnership all the way from product design to go to market and compensation alignment with Amazon on their push on Redshift as well. Google, we have announced partnership. There is a little bit of (mic cuts out) in the beginning we are getting, and just a couple of weeks ago we started working with Microsoft on their Azure Synapse algo. Now I would say that it's lagging, we still have work to do but Amazon and Snowflake are really pushing in terms of what customers want to see, and it completely aligns with our value popular, one plus one equals three. It really works well for our customers >> And Google is what, BigQuery plus Google Cloud, or what are you doing there? >> Yep so both Amazon and Google. Well, what we are doing at three different pieces. One if obviously the hosting of their cloud platforms. Second is data warehouse and enterprise data warehouse, which is Redshift and BigQuery. Third, we are also pretty good at taking machine learning algorithms that they have built for specific verticals. We're going to take those and then ingest them and deliver better. So for example if you are one of the largest supply companies in the world and you want to know what's the shipment rate from China and it shows and then the next thing you want to know is what the failure rate on this based on last behavior when you compressed a shipment rate, and that probably could use a bit of specific algorithms and you know Google and others have actually built a library of algorithms that can be injected into ThoughtSpot. We will simply answer the question of we may have gotten that algorithm from the Google library, sort of the business use is concerned. It doesn't really matter, so we have made all that invisible and we are able to deliver democratized access to Bespoke Insights to a business user, who are too sort of been afraid to deal with the sector data. >> Since you mentioned that you've got obviously several hundred million dollars in cash. You've raised over half a billion. You've talked previously about potential acquisitions, about IPO, are you considering acquisitions? M&A at this point in time? I mean there may be some deals out there. There's certainly some talent out there, but boy the market is changing so fast. I mean, it seems to, certain sectors are actually doing quite well. Will you consider M&A at this point? >> Yes, so I think IPO and M&A are two different-- IPO definitely, it will be foolish to say that this hasn't pushed our clients back a little bit because this is a huge event. I think there will be a correction across valuation and all of that. However, it is also important for us we use this opportunity to look at how we are investing our resources and investment for long-term versus the short-term and make sure that we are more focused and more tightening at the belt. We are doing that internally. Having said that, being a private company our valuation is, you know at least in theory, frozen, and then we have a pretty good cash position of close to $300 million, which means that it is absolutely an opportunity for us to seriously consider M&A. The important thing going back to my adage of, companies don't die out of starvation. It is critical to make sure that whatever we do, we do it with clarity. Are we doing it for talent? Are we doing it for tech? Or are we doing it for market? When you have a massive event like this, it is a poor idea to go after new market. It is important to go to our existing customers who are very large global 2000 firms and then identify problems that we cannot solve otherwise and then add technology to solve those problems, so technology acquisitions are absolutely something to consider, but it needs some more time to settle in because, the first two weeks were all people who were blindsided by this, then the last two weeks we have now gotten the mojo back in sales and mojo back in engineering, and now I think it is time for us to digest and prepare for these next two, three quarters of event and as part of that, companies like us who are fortunate enough to be on a good cash position, we'll absolutely look for interesting and good deals in the M&S space. >> Yeah, it makes sense, is tell and tech and, post IPO you can worry about Tam expansion. You'll be under pressure to do that as the CEO, but for now that's a very pragmatic approach. My last question is, there's some things when you think about, you say five weeks now you've been essentially on lockdown. You must, as many of us start thinking about wow, a lot of this work from home which came so fast people wouldn't even think about it earlier. You know, some companies mandated the beehive approach. Now everybody's open to that. There are certain things that are likely to remain permanent post COVID. Have you thought much about that? Generally and specifically how it might affect your business, the permanence of post COVID. Your thoughts. >> Yeah I've thought a lot about it. In fact, this morning I was speaking with our CRO Brian McCarthy about this. I think the change will happen, think of like an onion's inner most layer, I think the most, my hope is, that the biggest change will be in every one of us internally, as a what sort of a person am I and what does my position in the world means. The ego of each one of us that we carry because if this global event in one shot did not make you rethink your own sort of position in this big universe I think that's a mess. So the first thing has to be about being a better person. The second thing is, I had this two, three days of fever which was negative for COVID but I isolated myself, but that gave me sort of an idea of dipping in the dark room where I'm hoping my family won't get infected and you know my parents are in India so I sort of also realized that what is really important for you in life and how much family should mean to you, so that goes to the first, yourself second, your relationship with family, but having said that, the third thing when it comes to business building is also the importance for building with quality people, because when things go wrong it is so critical to have people who believe in the purpose of what you are trying to build. People with good faith and unshakable faith, personal faith and unshakable faith in the purpose of the company and most importantly you mentioned something which is the story telling. People, leaders who can absolutely communicate with clarity and certainty. It becomes the most important thing to lead an organization. I mean, you are a small business owner. You know we are in a small company with around 500 people. There is nothing like sitting at home waiting to see how the company is doing over email if you're a friend line engineer or a seller. Communication becomes so critical, so having the trust and the respect of organization and have the ability to clearly and transparently communicate is the most important thing for the company and over communicating due to the time of crisis. These things are so useful even after this crisis is over. Obviously from a technology point of view, you know people have been speaking a lot about working remotely and technology changes, security, those things will happen but I think if these three things were to happen in that order. Be a better person, be a better family member and be a better leader, I think the world will be better off and the last thing I'll also tell you, that you know in Silicon Valley sometimes we have this disregard for arts and literature and fight over science. I hope that goes away, because I can't imagine living without books, without movies, without Netflix and everything. Art makes yourself creative and enriches our lives. You know, sports is no longer there on TV and the fact that people are able to immerse their imagination in books and fiction and watch TV. That also reminds you how important it is to have a good balance between arts and science in this world, so I have a long list of things that I hope we as a people and as a society will get better. >> Yeah, a lot more game playing in our household and it's good to reconnect in that regard. Well Sudheesh, you've always been a very clear thinker and you're in a great spot and an awesome leader. Thanks so much for coming on theCUBE. It was really great to see you again. All the best to you, your family and the broader community in your area. >> Dave, you've been very kind with this. Thank you so much, I wish you the same and hopefully we'll get to see face-to-face in the near future. Thanks a lot. >> I hope so, thank you. All right and thank you for watching everybody. This is Dave Vellante for theCUBE and we'll see you next time. (upbeat music)