(Gentle music) >> Hello and welcome to the Cube here in Palo Alto, California. I'm John Furrier here, joined by Platform nine, Amelia Bell the Chief Revenue Officer, really digging into the conversation around Kubernetes Cloud native and the journey this next generation cloud. Amelia, thanks for coming in and joining me today. >> Thank you, thank you. Great pleasure to be here. >> So, CRO, chief Revenue Officer. So you're mainly in charge of serving the customers, making sure they're they're happy with the solution you guys have. >> That's right. >> And this market must be pretty exciting. >> Oh, it's very exciting and we are seeing a lot of new use cases coming up all the time. So part of my job is to obtain new customers but then of course, service our existing customers and then there's a constant evolution. Nothing is standing still right now. >> We've had all your co-founders on, on the show here and we've kind of talked about the trends and where you guys have come from, where you guys are going now. And it's interesting, if you look at the cloud native market, the scale is still huge. You seeing now this next wave of AI coming on, which I call that's the real web three in my mind in terms of like the next experiences really still points to data infrastructure scale. These next gen apps are coming. And so that's being built on the previous generation of DevSecOps. >> Right >> And so a lot of enterprises are having to grow up really, really fast >> Right. >> And figure out, okay, I got to have scale I got large scale data, I got horizontal scalability I got to apply machine learning now the new software engineering practice. And then, oh, by the way I got the Kubernetes clusters I got to manage >> Right. >> I got what's containers weather, the security problems. This is a really complicated but important area of build out right now in the marketplace. >> Right. What are you seeing? >> So it's, it's really important that the infrastructure is not the hindrance in these cases. And we, one of our customers is in fact a large AI company and we, I met with them yesterday and asked them, you know, why are you giving that to us? You've got really smart engineers. They can run and create the infrastructure, you know in a custom way that you want it. And they said, we've got to be core to our business. There's plenty of work to do just on delivering the AI capabilities, and there's plenty of work to do. We can't get bogged down in the infrastructure. We don't want to have people running the engine we want them driving the car. We want them creating value on top of that. so they can't have the infrastructure being the bottleneck for them. >> It's interesting, the AI companies, that's their value proposition to their customers is that they don't want the technical talent. >> Right. >> Working on, you know, non-differentiated heavy lifting things. >> Right. >> And automate those and scale it up. Can you talk about the problem that you guys are solving? Because there's a lot going on here. >> Yeah. >> You can look at all aspects of the DevOps scale. There's a lot of little problems, some big problems. What are you guys focusing on? What's the bullseye for Platform known? >> Okay, so the bullseye is that Kubernetes infrastructure is really hard, right? It's really hard to create and run. So we introduce a time to market efficiency, let's get this up and running and let's get you into production and and producing results for your customers fast. But at the same time, let's reduce your cost and complexity and increase reliability. So, >> And what are some of the things that they're having problems with that are breaking? Is it more of updates on code? Is it size of the, I mean clusters they have, what what is it more operational? What are the, what are some of the things that are that kind of get them to call you guys up? What's the main thing? >> It's the operations. It's all operations. So what, what happens is that if you have a look at Kubernetes platform it's made up of many, many components. And that's where it gets complex. It's not just Kubernetes. There's load balances, networking, there's observability. All these things have to operate together. And all the piece parts have to be upgraded and maintained. The integrations need to work, you need to have probes into the system to predict where problems can be coming. So the operational part of it is complex. So you need to be observing not only your clusters in the health of the clusters and the nodes and so on but the health of the platform itself. >> We're going to get Peter Frey in on here after I talk about some of the technical issues on deployments. But what's the, what's the big decision for the customer? Because there's kind of, there's two schools of thought. One is, I'm going to build my own and have my team build it or I'm going to go with a partner >> Right. >> Say platform nine, what's the trade offs there? Because it seems to me that, that there's a there's a certain area of where it's core competency but I can outsource it or partner with it and, and work with platform nine versus trying to take it all on internally >> Right. >> Of which requires more costs. So there's a, there's a line where you kind of like figure out that customers have to figure out that, that piece >> Right >> What do, what's your view on that? Because I'm hearing that more people are saying, hey I want to, I want to focus my people on solutions. The app side, not so much the ops >> Right. >> What's the trade off? How do you talk about? >> It's a really interesting question because most companies think they have two options. It's either a DIY option and they love that engineers love playing with the new and on the latest. And then they think the other option is going to cloud, public cloud and have it semi managed by them. And you get very different out of those. So in the DIY you get flexibility coz you get to choose your infrastructure but then you've got all the complexities of the DIY piece. You've got to not only choose all your components but you've got to keep them working. Now if you go to public cloud option, you lose flexibility because a lot of those choices are made for you but you gain agility because quite frankly it's really easy to spin up clusters. So what we are, is that in the middle we bring the agility and the flexibility because we bring the control plane that allows you to spin up clusters and and lifecycle manage them very quickly. So the agility's there but you can do it on the infrastructure of your choice. And in the DIY culture, one of the hardest things to do actually is to convince them they don't have to do it themselves. They can focus on higher value activities, which are more focused on delivering outcomes to their customers. >> So you provide the solution that allows them to feel like they're billing it themselves. >> Correct. >> And get these scale and speed and the efficiencies of the op side. So it's kind of the best of both worlds. It's not a full outsource. >> Right, right. >> You're bringing them in to make their jobs easier >> Right, That's right. So they get choices. >> Yeah. >> We, we, they get choices on how they build it and then we run and operate it for them. But they, they have all the observability. The benefit is that if we are managing their operations and most of our customers choose the managed operations piece of it, then they don't. If something goes wrong, we fix that and they, they they get told, oh, by the way, you had a problem. We've dealt with it. But in the other model is they've got to create all that observability themselves and they've got to get ahead of the issues themselves, and then they've got to raise tickets to whoever they need to raise tickets to. Whereas we have things like auto ticket generation and so on where, look, just drive the car let us worry about the engine and all of that. Let us deal with that. And you can choose whatever you want about the engine but let us manage it for you. So >> What do you, what do you say to folks out there that are may have a need for platform nine? What's the signals inside their company that they should be calling you guys up and, and leaning in with platform nine? >> Right. >> Is it more sprawl on on clusters? Is it more errors? Is it more tickets? Is it more hassle? What are some of the signs? If someone's watching this say, hey I have, I have an issue with this. >> I would say, if there's operational inefficiencies you can't get things to market fast enough because you are building this and it's just taking too long you're spending way too much time operationally on the infrastructure, then you are, you are not using your resources where they should best be used. And, and that is delivering services to the customer. >> Ed me Hora on for International Women's Day. And she was talking about how they love to solve complex problems on the engineering team at Platform nine. It's going to get pretty complex with the edge emerging >> Indeed >> and cloud native on-premises distributed computing. >> Indeed. >> essentially is what it is. That's kind of the core DNA of the team. >> Yeah. >> What, how does that translate to the customers? Because IT seems to be, okay, I have virtual machines were great, now I got to scale up and and convert over a transform to containers, Kubernetes >> Right. >> And then large scale app, app applications. >> Right, so when it comes to Edge it gets complex pretty fast because it's highly distributed. So how do you have standardization and governance across all the different edge locations? So what we bring into play is an ability to, um, at each edge, location eh, provision from bare metal up all the way up to the application. So let's say you have thousands of stores and you want to modernize those stores, you know rather than having a server being sent somewhere to have an image loaded up and then sent that and then you've got to send a technical guide to the store and you've got to implement it all there. Forget all that. That's just, that's just a ridiculous waste of time. So what we've done is we've created the ability where the server can just be sent to the store. You can get your barista or your chef just to plug it in, right? You don't need to send any technical person over there. As long as we have access to it, we get access to it and we provision the whole thing from bare metal up and then we can maintain it according to the standards that are needed and upgrade accordingly. And that gives standardization across all your stores or edge locations or 5G towers or whatever it is, distribution centers. And we can create nice governance and good standardization which allows them to innovate fast as well. >> So this is a real opportunity for you guys. >> Yeah. >> This is an advantage from your expertise. >> Yes. >> The edge piece, dropping in a box, self-provisioning. >> That's right. So yeah. >> Can people do that? What's the, >> No, actually it, it's, it's very difficult to do. I I, from my understanding, we're the only people that can provision it from bare metal up, right? So if anyone has a different story, I'd love to hear about that. But that's my understanding today. >> That's a good value purpose. So talk about the value of the customer. What kind of scope do you got? Can you scope some of the customer environments you have from >> Sure. >> From, you know, small to the large, how give us an idea of the order of magnitude of the >> Yeah, so, so small customers may have 20 clusters or something like that. 20 nodes, I beg your pardon. Our large customers, like we're we are scaling one particular distributed environment from 2200 nodes to 10,000 nodes by the end of this year and 26,000 nodes next year. We have another customer that's scaling up to 10,000 nodes this year as well. So we have some very large scale, but some smaller ones too. And we're, we're happy to work with either end. >> Okay, so pretend I'm a customer. I'm really, I got pain and Kubernetes like I want to, I can't hire enough people. I want to have my all focus. What's the pitch? >> Okay. So skill shortage is something that that everyone is facing right now. And if, if you've got skill shortage it's going to be really hard to hire if you are competing against really, you know, high salary you know, offering companies that are out there. So the pitch is, let us do it for you. We have, we have a team of excellent probably the best Kubernetes engineers on the planet. We will create your environment for you. We will get it up and running. We will allow you to, you know, run your applica, just consume the platform, we'll run it for you. We'll have SLAs and up times guaranteed and you can just focus on delivering the software and the value needed to your customers. >> What are some of the testimonials that you get from people? Just anecdotally, what do they say? Oh my god, you guys save. >> Yeah. >> Our butts. >> Yeah. >> This is amazing. We just shipped our code out much faster. >> Yeah. >> What are some of the things that you hear? >> So, so the number one thing I hear is it just works right? It's, we don't have to worry about it, it just works. So that, that's a really great feedback that we get. The other thing I hear is if we do have issues that your team are amazing, they they fix things, they're proactive, you know, they're we really enjoy working with you. So from, from that perspective, that's great. But the other side of it is we hear things like if we were to do that ourselves we would've taken six to 12 months to build that. And you guys have just saved us six to 12 months. The other thing that we hear is with the same two engineers we started on, you know, a hundred nodes we're now running thousands of nodes. We have not had to increase the size of the team and expand and scale exponentially. >> Awesome. What's next for you guys? What's on your, your plate? >> Yeah. >> With CRO, what's some of the goals you have? >> Yeah, so growth of course as a CRO, you don't get away from that. We've got some very exciting, actually, initiatives coming up. One of the things that we are seeing a lot of demand for and is, is in the area of virtualization bringing virtual machine, virtual virtual containers, sorry I'm saying that all wrong. Bringing virtual machine, the virtual machines onto the cloud native infrastructure using Kubernetes technology. So that provides a, an excellent stepping stone for those guys who are in the virtualization world. And they can't move to containers, they can't refactor their applications and workloads fast enough. So just bring your virtual machine and put it onto the container infrastructure. So we're seeing a lot of demand for that, because it provides an excellent stepping stone. Why not use Kubernetes to orchestrate virtual the virtual world? And then we've got some really interesting cost optimization. >> So a lot of migration kind of thinking around VMs and >> Oh, tremendous. The, the VM world is just massively bigger than the container world right now. So you can't ignore that. So we are providing basically the evolution, the the journey for the customers to utilize the greatest of technologies without having to do that in a, in a in a way that just breaks the bank and they can't get there fast enough. So we provide those stepping stones for them. Yeah. >> Amelia thank you for coming on. Sharing. >> Thank you. >> The update on platform nine. Congratulations on your big accounts you have and >> thank you. >> And the world could get more complex, which Means >> indeed >> have more customers. >> Thank you, thank you John. Appreciate that. Thank you. >> I'm John Furry. You're watching Platform nine and the Cube Conversations here. Thanks for watching. (gentle music)

(soft music) >> Welcome back to Chicago guys and gals. Lisa Martin here with John Furrier. We have been covering Ansible Fest '22 for the last two days. This is our show wrap. We're going to leave you with some great insights into the things that we were able to dissect over the last two days. John, this has been an action packed two days. A lot of excitement, a lot of momentum. Good to be back in person. >> It's great to be back in person. It was the first time for you to do Ansible Fest. >> Yes. >> My first one was 2019 in person. That's the last time they had an event in person. So again, it's a very chill environment here, but it's content packed, great active loyal community and is growing. It's changing. Ansible now owned by Red Hat, and now Red Hat owned by IBM. Kind of see some game changing kind of movements here on the chess board, so to speak, in the industry. Ansible has always been a great product. It started in open source. It evolved configuration management configuring servers, networks. You know, really the nuts and bolts of IT. And became a fan favorite mainly because it was built by the fans and I think that never stopped. And I think you started to see an opportunity for Ansible to be not only just a, I won't say niche product or niche kind of use case to being the overall capabilities for large scale enterprise system architectures, system management. So it's very interesting. I mean I find it fascinating how, how it stays relevant and cool and continues to power through a massive shift >> A massive shift. They've done a great job though since the inception and through the acquisition of being still community first. You know, we talked a lot yesterday and today about helping organizations become automation first that Ansible has really stayed true to its roots in being community first, community driven and really that community flywheel was something that was very obvious the last couple of days. >> Yeah, I mean the community thing is is is their production system. I mean if you look at Red Hat, their open source, Ansible started open source, good that they're together. But what people may or may not know about Ansible is that they build their product from the community. So the community actually makes the suggestions. Ansible's just in listening modes. So when you have a system that's that efficient where you have direct working backwards from the customer like that, it's very efficient. Now, as a product manager you might want to worry about scope creep, but at the end of the day they do a good job of democratizing that process. So again, very strong product production system with open source, very relevant, solves the right problems. But this year the big story to me is the cultural shift of Ansible's relevance. And I think with multicloud on the horizon, operations is the new kind of developer kind of ground. DevOps has been around for a while. That's now shifted up to the developer themselves, the cloud native developer. But at cloud scale and hybrid computing, it's about the operations. It's about the data and the security. All of it's about the data. So to me there's a new ops configuration operating model that you're seeing people use, SRE and DevOps. That's the new culture, and the persona's changing. The operator of a large scale enterprise is going to be a lot different than it was past five, 10 years. So major cultural shift, and I think this community's going to step up to that position and fill that role. >> They seem to be having a lot of success meeting people where they are, meeting the demographics, delivering on how their community wants to work, how they want to collaborate. But yesterday you talked about operations. We talked a lot about Ops as code. Talk about what does that mean from your perspective, and what did you hear from our guests on the program with respect that being viable? >> Well great, that's a great point. Ops as code is the kind of their next layer of progression. Infrastructure is code. Configuration is code. Operations is code. To me that means running the company as software. So software influencing how operators, usually hardware in the past. Now it's infrastructure and software going to run things. So ops as code's, the next progression in how people are going to manage it. And I think most people think of that as enterprises get larger, when they hear words like SRE, which stands for Site Reliable Engineer. That came out of Google, and Google had all these servers that ran the search engine and at scale. And so one person managed boatload of servers and that was efficient. It was like a multiple 10x engineer, they used to call it. So that that was unique to Google but not everyone's Google. So it became language or parlance for someone who's running infrastructure but not everyone's that scale. So scale is a big issue. Ops as code is about scale and having that program ability as an operator. That's what Ops as code is. And that to me is a sign of where the scale meets the automation. Large scale is hard to do. Automating at large scale is even harder. So that's where Ansible fits in with their new automation platform. And you're seeing new things like signing code, making sure it's trusted and verified. So that's the software supply chain issue. So they're getting into the world where software, open source, automation are all happening at scale. So to me that's a huge concept of Ops as code. It's going to be very relevant, kind of the next gen positioning. >> Let's switch gears and talk about the partner ecosystem. We had Stefanie Chiras on yesterday, one of our longtime theCUBE alumni, talking about what they're doing with AWS in the marketplace. What was your take on that, and what's the "what's in it for me" for both Red Hat, Ansible and AWS? >> Yeah, so the big news on the automation platform was one. The other big news I thought was really, I won't say watered down, but it seems small but it's not. It's the Amazon Web Services relationship with Red Hat, now Ansible, where Ansible's now a product in AWS's marketplace. AWS marketplace is kind of hanging around. It's a catalog right now. It's not the most advanced technical system in the world, and it does over 2 billion plus revenue transactions. So even if it's just sitting there as a large marketplace, that's already doing massive amounts of disruption in the procurement, how software is bought. So we interviewed them in the past, and they're innovating on that. They're going to make that a real great platform. But the fact that Ansible's in the marketplace means that their sales are going to go up, number one. Number two, that means customers can consume it simply by clicking a button on their Amazon bill. That means they don't have to do anything. It's like getting a PO for free. It's like, hey, I'm going to buy Ansible, click, click, click. And then by the way, draw that down from their commitment to AWS. So that means Amazon's going into business with Ansible, and that is a huge revenue thing for Ansible, but also an operational efficiency thing that gives them more of an advantage over the competition. >> Talk what's in it for me as a customer. At Red Hat Summit a few months ago they announced similar partnership with Azure. Now we're talking about AWS. Customers are living in this hybrid cloud world, often by default. We're going to see that proliferate. What do you think this means for customers in terms of being able to- >> In the marketplace deal or Ansible? >> Yeah, the marketplace deal, but also what Red Hat and Ansible are doing with the hyperscalers to enable customers to live successfully in the hyper hybrid cloud world. >> It's just in the roots of the company. They give them the choice to consume the product on clouds that they like. So we're seeing a lot of clients that have standardized on AWS with their dev teams but also have productivity software on Azure. So you have the large enterprises, they sit on both clouds. So you know, Ansible, the customer wants to use Ansible anyway, they want that to happen. So it's a natural thing for them to work anywhere. I call that the Switzerland strategy. They'll play with all the clouds. Even though the clouds are fighting against each other, and they have to to differentiate, there's still going to be some common services. I think Ansible fits this shim layer between clouds but also a bolt on. Now that's a really a double win for them. They can bolt on to the cloud, Azure and bolt on to AWS and Google, and also be a shim layer technically in clouds as well. So there's two technical advantages to that strategy >> Can Ansible be a facilitator of hybrid cloud infrastructure for organizations, or a catalyst? >> I think it's going to be a gateway on ramp or gateway to multicloud or supercloud, as we call it, because Ansible's in that configuration layer. So you know, it's interesting to hear the IBM research story, which we're going to get to in a second around how they're doing the AI for Ansible with that wisdom project. But the idea of configuring stuff on the fly is really a concept that's needed for multicloud 'Cause programs don't want to have to configure anything. (he laughs) So standing up an application to run on Azure that's on AWS that spans both clouds, you're going to need to have that automation, and I think this is an opportunity whether they can get it or not, we'll see. I think Red Hat is probably angling on that hard, and I can see them kind of going there and some of the commentary kind of connects the dots for that. >> Let's dig into some of news that came out today. You just alluded to this. IBM research, we had on with Red Hat. Talk about what they call project wisdom, the value in that, what it also means for for Red Hat and IBM working together very synergistically. >> I mean, I think the project wisdom is an interesting dynamic because you got the confluence of the organic community of Ansible partnering with a research institution of IBM research. And I think that combination of practitioners and research groups is going to map itself out to academic and then you're going to see this kind of collaboration going forward. So I think it's a very nuanced story, but the impact to me is very clear that this is the new power brokers in the tech industry, because researchers have a lot of muscle in terms of deep research in the academic area, and the practitioners are the ones who are actually doing it. So when you bring those two forces together, that pretty much trumps any kind of standards bodies or anything else. So I think that's a huge signaling benefit to Ansible and Red Hat. I think that's an influence of Red Hat being bought by IBM. But the project itself is really amazing. It's taking AI and bringing it to Ansible, so you can do automated configurations. So for people who don't know how to code they can actually just automate stuff and know the process. I don't need to be a coder, I can just use the AI to do that. That's a low code, no code dynamic. That kind of helps with skill gaps, because I need to hire someone to do that. Today if I want to automate something, and I don't know how to code, I've got to get someone who codes. Here I can just do it and automate it. So if that continues to progress the way they want it to, that could literally be a game changer, 'cause now you have software configuring machines and that's pretty badass in my opinion. So that thought that was pretty cool. And again it's just an evolution of how AI is becoming more relevant. And I think it's directionally correct, and we'll see how it goes. >> And they also talked about we're nearing an inflection point in AI. You agree? >> Yeah I think AI is at an inflection point because it just falls short on the scale side. You see it with chatbots, NLP. You see what Amazon's doing. They're building these models. I think we're one step away from model scaling. I think the building the models is going to be one of these things where you're going to start to see marketplace and models and you start to composability of AI. That's where it's going to get very interesting to see which cloud is the best AI scale. So I think AI at scale's coming, and that's going to be something to watch really closely. >> Something exciting. Another thing that was big news today was the event driven Ansible. Talk about that, and that's something they've been working on in conjunction with the community for quite a while. They were very proud of that release and what that's going to enable organizations to do. >> Well I think that's more meat on the bone on the AI side 'cause in the big trend right now is MLAI ops. You hear that a lot. Oh, data ops or AI ops. What event driven automation does is allows you to take things that are going on in your world, infrastructure, triggers, alarms, notifications, data pipelining flows, things that go on in the plumbing of infrastructure. are being monitored and observed. So when events happen they trigger events. You want to stream something, you send a trigger and things happen. So these are called events. Events are wide ranging number of events. Kafka streaming for data. You got anything that produces data is an event. So harnessing that data into a pipeline is huge. So doing that at scale, that's where I think that product's a home run, and I think that's going to be a very valuable product, 'cause once you understand what the event triggers are, you then can automate that, and no humans involved. So that will save a lot of time for people in the the higher pay grade of MLAI ops automate some of that low level plumbing. They move their skill set to something more valuable or more impactful. >> And we talked about, speaking of impact, we talked about a lot of the business impact that organizations across industries are going to be able to likely achieve by using that. >> Yeah, I mean I think that you're going to see the community fill the gap on that. I mean the big part about all this is that their community builds the product and they have the the playbooks and they're shareable and they're reusable. So we produce content as a media company. They'd talk about content as is playbooks and documentation for people to use. So reuse and and reusing these playbooks is a huge part of it. So as they build up these catalogs and these playbooks and rules, it gets better by the community. So it's going to be interesting to see the adoption. That's going to be a big tell sign for what's going to happen. >> Yep, we get definitely are going to be watching that space. And the last thing, we got to talk to a couple of customers. We talked to Wells Fargo who says "We are a tech company that does banking," which I loved. We got to talk with Rockwell Automation. What are some of your takeaways from how the customers are leveraging Ansible and the technology to drive their businesses forward to meet demanding customers where they are? >> I think you're seeing the script flipping a little bit here, where the folks that used to use Ansible for configuration are flipping to be on the front edge of the innovation strategy where what process to automate is going to drive the profitability and scale. Cause you're talking about things like skill gaps, workflows. These are business constructs and people These are assets so they have economic value. So before it was just, IT serve the business, configure some servers, do some stuff. When you start getting into automation where you have expertise around what this means, that's economic value. So I think you're going to see the personas change significantly in this community where they're on the front lines, kind of like developers are. That's why ops as code is to me a developer kind of vibe. That's going to completely change how operations runs in IT. And I think that's going to be a very interesting cultural shift. And some will make it, some won't. That's going to be a big thing. Some people say, I'm going to retire. I'm old school storage server person, or no, I'm the new guard. I'm going to be the new team. I'm going be on the right side of history here. So they're clearly going down that right path in my opinion. >> What's your overall summary in the last minute of what this event delivered the last couple of days in terms of really talking about the transformation of enterprises and industries through automation? >> I think the big takeaway from me in listening and reading the tea leaves was the Ansible company and staff and the community together. It was really a call for arms. Like, hey, we've had it right from the beginning. We're on the right wave and the wave's getting bigger. So expand your scope, uplevel your skills. They're on the right side of history. And I think the message was engage more. Bring more people in because it is open source, and if they are on that track, you're going to see more of hey, we got it right, let's continue. So they got platform release. They got the key products coming out after years of work. So you know, they're doing their work. And the message I heard was, it's bigger than we thought. So I think that's interesting. We'll see what that means. We're going to unpack that after the event in series of showcases. But yeah, it was very positive, I thought. Very positive. >> Yeah, I think there was definitely some surprises in there for them. John, thank you so much. It's been a pleasure co-hosting with you the last couple of days, really uncovering what Ansible is doing, what they're enabling customers in every industry to achieve. >> Been fun. >> Yes. All right for my co-host, John Furrier, I'm Lisa Martin. You've been watching theCUBE's coverage of Ansible Fest 2022 live from Chicago. We hope you take good care and we'll see you soon.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value >> from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the InfoBrief uncovered with respect to the the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy, as compared to the technology itself. And next, while data is everywhere, most organizations, 63%, from our survey, are still not using the full breadth of data types available. Yet, data's never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytics tools to help everyone unlock the power of data. They instead rely on outdated spreadsheet technology. In our survey, 9 out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely, you can do so. Yep, we'll go back to Lisa's question. Let's retake the question and the answer. >> That'll be not all analog spending results in the same ROI. What are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we can get that clean question and answer. >> Okay. >> Thank you for that. on your ISO, we're still speeding, Lisa. So give it a beat in your head, and then on you. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did. It did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads. Can I start that one over? Can I redo this one? >> Sure. >> Yeah >> Of course. Stand by. >> Tongue tied. >> Yep. No worries. >> One second. >> If we could get, if we could do the same, Lisa, just have a clean break. We'll go to your question. Yep. >> Yeah. >> On you Lisa. Just give that a count and whenever you're ready, here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

(bright music) >> Welcome back everyone to the live Cube coverage here in Boston, Massachusetts for AWS re:Inforce 22, with a great guest here, Denise Hayman, CRO, Chief Revenue of Sonrai Security. Sonrai's a featured partner of Season Two, Episode Four of the upcoming AWS Startup Showcase, coming in late August, early September. Security themed startup focused event, check it out. awsstartups.com is the site. We're on Season Two. A lot of great startups, go check them out. Sonrai's in there, now for the second time. Denise, it's great to see you. Thanks for coming on. >> Ah, thanks for having me. >> So you've been around the industry for a while. You've seen the waves of innovation. We heard encrypt everything today on the keynote. We heard a lot of cloud native. They didn't say shift left but they said don't bolt on security after the fact, be in the CI/CD pipeline or the DevStream. All that's kind of top of line, Amazon's talking cloud native all the time. This is kind of what you guys are in the middle of. I've covered your company, you've been on theCUBE before. Your, not you, but your teammates have. You guys have a unique value proposition. Take a minute to explain for the folks that don't know, we'll dig into it, but what you guys are doing. Why you're winning. What's the value proposition. >> Yeah, absolutely. So, Sonrai is, I mean what we do is it's, we're a total cloud solution, right. Obviously, right, this is what everybody says. But what we're dealing with is really, our superpower has to do with the data and identity pieces within that framework. And we're tying together all the relationships across the cloud, right. And this is a unique thing because customers are really talking to us about being able to protect their sensitive data, protect their identities. And not just people identities but the non-people identity piece is the hardest thing for them to reign in. >> Yeah. >> So, that's really what we specialize in. >> And you guys doing good, and some good reports on good sales, and good meetings happening here. Here at the show, the big theme to me, and again, listening to the keynotes, you hear, you can see what's, wasn't talk about. >> Mm-hmm. >> Ransomware wasn't talked about much. They didn't talk about air-gapped. They mentioned ransomware I think once. You know normal stuff, teamwork, encryption everywhere. But identity was sprinkled in everywhere. >> Mm-hmm. >> And I think one of the, my favorite quotes was, I wrote it down, We've security in the development cycle CSD, they didn't say shift left. Don't bolt on any of that. Now, that's not new information. We know that don't bolt, >> Right. >> has been around for a while. He said, lessons learned, this is Stephen Schmidt, who's the CSO, top dog on security, who has access to what and why over permissive environments creates chaos. >> Absolutely. >> This is what you guys reign in. >> It is. >> Explain, explain that. >> Yeah, I mean, we just did a survey actually with AWS and Forrester around what are all the issues in this area that, that customers are concerned about and, and clouds in particular. One of the things that came out of it is like 95% of clouds are, what's called over privileged. Which means that there's access running amok, right. I mean, it, it is, is a crazy thing. And if you think about the, the whole value proposition of security it's to protect sensitive data, right. So if, if it's permissive out there and then sensitive data isn't being protected, I mean that, that's where we really reign it in. >> You know, it's interesting. I zoom out, I just put my historian hat on going back to the early days of my career in late eighties, early nineties. There's always, when you have these inflection points, there's always these problems that are actually opportunities. And DevOps, infrastructure as code was all about APS, all about the developer. And now open source is booming, open source is the software industry. Open source is it in the world. >> Right. >> That's now the software industry. Cloud scale has hit and now you have the Devs completely in charge. Now, what suffers now is the Ops and the Sec, Second Ops. Now Ops, DevOps. Now, DevSecOps is where all the action is. >> Yep. >> So the, the, the next thing to do is build an abstraction layer. That's what everyone's trying to do, build tools and platforms. And so that's where the action is here. This is kind of where the innovation's happening because the networks aren't the, aren't in charge anymore either. So, you now have this new migration up to higher level services and opportunities to take the complexity away. >> Mm-hmm. >> Because what's happened is customers are getting complexity. >> That's right. >> They're getting it shoved in their face, 'cause they want to do good with DevOps, scale up. But by default their success is also their challenge. >> Right. >> 'Cause of complexity. >> That's exactly right. >> This is, you agree with that. >> I do totally agree with that. >> If you, you believe that, then what's next. What happens next? >> You know, what I hear from customers has to do with two specific areas is they're really trying to understand control frameworks, right. And be able to take these scenarios and build them into something that they, where they can understand where the gaps are, right. And then on top of that building in automation. So, the automation is a, is a theme that we're hearing from everybody. Like how, how do they take and do things like, you know it's what we've been hearing for years, right. How do we automatically remediate? How do we automatically prioritize? How do we, how do we build that in so that they're not having to hire people alongside that, but can use software for that. >> The automation has become key. You got to find it first. >> Yes. >> You guys are also part of the DevCycle too. >> Yep. >> Explain that piece. So, I'm a developer, I'm an organization. You guys are on the front end. You're not bolt-on, right? >> We can do either. We prefer it when customers are willing to use us, right. At the very front end, right. Because anything that's built in the beginning doesn't have the extra cycles that you have to go through after the fact, right. So, if you can build security right in from the beginning and have the ownership where it needs to be, then you're not having to, to deal with it afterwards. >> Okay, so how do you guys, I'm putting my customer hat on for a second. A little hard, hard question, hard problem. I got active directory on Azure. I got, IM over here with AWS. I wanted them to look the same. Now, my on-premises, >> Ah. >> Is been booming, now I got cloud operations, >> Right. >> So, DevOps has moved to my premise and edge. So, what do I do? Do I throw everything out, do a redo. How do you, how do you guys talk about, talk to customers that have that chance, 'cause a lot of them are old school. >> Right. >> ID. >> And, and I think there's a, I mean there's an important distinction here which is there's the active directory identities right, that customers are used to. But then there's this whole other area of non-people identities, which is compute power and privileges and everything that gets going when you get you know, machines working together. And we're finding that it's about five-to-one in terms of how many identities are non-human identities versus human identity. >> Wow. >> So, so you actually have to look at, >> So, programmable access, basically. >> Yeah. Yes, absolutely. Right. >> Wow. >> And privileges and roles that are, you know accessed via different ways, right. Because that's how it's assigned, right. And people aren't really paying that close attention to it. So, from that scenario, like the AD thing of, of course that's important, right. To be able to, to take that and lift it into your cloud but it's actually even bigger to look at the bigger picture with the non-human identities, right. >> What about the CISOs out there that you talk to. You're in the front lines, >> Yep. >> talking to customers and you see what's coming on the roadmap. >> Yep. >> So, you kind of get the best of both worlds. See what they, what's coming out of engineering. What's the biggest problem CISOs are facing now? Is it the sprawl of the problems, the hacker space? Is it not enough talent? What, I mean, I see the fear, what are, what are they facing? How do you, how do you see that, and then what's your conversations like? >> Yeah. I mean the, the answer to that is unfortunately yes, right. They're dealing with all of those things. And, and here we are at the intersection of, you know, this huge complex thing around cloud that's happening. There's already a gap in terms of resources nevermind skills that are different skills than they used to have. So, I hear that a lot. The, the bigger thing I think I hear is they're trying to take the most advantage out of their current team. So, they're again, worried about how to operationalize things. So, if we bring this on, is it going to mean more headcount. Is it going to be, you know things that we have to invest in differently. And I was actually just with a CISO this morning, and the whole team was, was talking about the fact that bringing us on means they have, they can do it with less resource. >> Mm-hmm. >> Like this is a a resource help for them in this particular area. So, that that was their value proposition for us, which I loved. >> Let's talk about Adrian Cockcroft who retired from AWS. He was at Netflix before. He was a big DevOps guy. He talks about how agility's been great because from a sales perspective the old model was, he called it the, the big Indian wedding. You had to get everyone together, do a POC, you know, long sales cycles for big tech investments, proprietary. Now, open sources like speed dating. You can know what's good quickly and and try things quicker. How is that, how is that impacting your sales motions. Your customer engagements. Are they fast? Are they, are they test-tried before they buy? What's the engagement model that you, you see happening that the customers like the best. >> Yeah, hey, you know, because of the fact that we're kind of dealing with this serious part of the problem, right. With the identities and, and dealing with data aspects of it it's not as fast as I would like it to be, right. >> Yeah, it's pretty important, actually. >> They still need to get in and understand it. And then it's different if you're AWS environment versus other environments, right. We have to normalize all of that and bring it together. And it's such a new space, >> Yeah. >> that they all want to see it first. >> Yeah. >> Right, so. >> And, and the consequences are pretty big. >> They're huge. >> Yeah. >> Right, so the, I mean, the scenario here is we're still doing, in some cases we'll do workshops instead of a POV or a POC. 90% of the time though we're still doing a POV. >> Yeah, you got to. >> Right. So, they can see what it is. >> They got to get their hands on it. >> Yep. >> This is one of those things they got to see in action. What is the best-of-breed? If you had to say best-of-breed in identity looks like blank. How would you describe that from a customer's perspective? What do they need the most? Is it robustness? What's some of the things that you guys see as differentiators for having a best-of-breed solution like you guys have. >> A best-of-breed solution. I mean, for, for us, >> Or a relevant solution for that matter, for the solution. >> Yeah. I mean, for us, this, again, this identity issue it, for us, it's depth and it's continuous monitoring, right. Because the issue in the cloud is that there are new privileges that come out every single day, like to the tune of like 35,000 a year. So, even if at this exact moment, it's fine. It's not going to be in another moment, right. So, having that continuous monitoring in there, and, and it solves this issue that we hear from a lot of customers also around lateral movement, right. Because like a piece of compute can be on and off, >> Yeah, yeah, yeah. >> within a few seconds, right. So, you can't use any of the old traditional things anymore. So to me, it's the continuous monitoring I think that's important. >> I think that, and the lateral movement piece, >> Yep. >> that you guys have is what I hear the most of the biggest fears. >> Mm-hmm. >> Someone gets in here and can move around, >> That's right. >> and that's dangerous. >> Mm-hmm. And, and no traditional tools will see it. >> Yeah. Yeah. >> Right. There's nothing in there unless you're instrumented down to that level, >> Yeah. >> which is what we do. You're not going to see it. >> I mean, when someone has a firewall, a perimeter based system, yeah, I'm in the castle, I'm moving around, but that's not the case here. This is built for full observability, >> That's right. >> Yet there's so many vulnerabilities. >> It's all open. Mm-hmm, yeah. And, and our view too, is, I mean you bring up vulnerabilities, right. It, it is, you know, a little bit of the darling, right. People start there. >> Yep. >> And, and our belief in our view is that, okay, that's nice. But, and you do have to do that. You have to be able to see everything right, >> Yep. >> to be able to operationalize it. But if you're not dealing with the sensitive data pieces right, and the identities and stuff that's at the core of what you're trying to do >> Yeah. >> then you're not going to solve the problem. >> Yeah. Denise, I want to ask you. Because you make what was it, five-to-one was the machine to humans. I think that's actually might be low, on the low end. If you could imagine. If you believe that's true. >> Yep. >> I believe that's true by the way If microservices continues to be the, be the wave. >> Oh, it'll just get bigger. >> Which it will. It's going to much bigger. >> Yeah. >> Turning on and off, so, the lateral movement opportunities are going to be greater. >> Yep. >> That's going to be a bigger factor. Okay, so how do I protect myself. Now, 'cause developer productivity is also important. >> Mm-hmm. >> 'Cause, I've heard horror stories like, >> Yep. >> Yeah, my Devs are cranking away. Uh-oh, something's out there. We don't know about it. Everyone has to stop, have a meeting. They get pulled off their task. It's kind of not agile. >> Right. Right. >> I mean, >> Yeah. And, and, in that vein, right. We have built the product around what we call swim lanes. So, the whole idea is we're prioritizing based on actual impact and context. So, if it's a sandbox, it probably doesn't matter as much as if it's like operational code that's out there where customers are accessing it, right. Or it's accessing sensitive data. So, we look at it from a swim lane perspective. When we try to get whoever needs to solve it back to the person that is responsible for it. So we can, we can set it up that way. >> Yeah. I think that, that's key insight into operationalizing this. >> Yep. >> And remediation is key. >> Yes. >> How, how much, how important is the timing of that. When you talk to your customer, I mean, timing is obviously going to be longer, but like seeing it's one thing, knowing what to do is another. >> Yep. >> Do you guys provide that? Is that some of the insights you guys provide? >> We do, it's almost like, you know, us. The, and again, there's context that's involved there, right? >> Yeah. >> So, some remediation from a priority perspective doesn't have to be immediate. And some of it is hair on fire, right. So, we provide actually, >> Yeah. >> a recommendation per each of those situations. And, and in some cases we can auto remediate, right. >> Yeah. >> If, it depends on what the customer's comfortable with, right. But, when I talk to customers about what is their favorite part of what we do it is the auto remediation. >> You know, one of the things on the keynotes, not to, not to go off tangent, one second here but, Kurt who runs platforms at AWS, >> Mm-hmm. >> went on his little baby project that he loves was this automated, automatic reasoning feature. >> Mm-hmm. >> Which essentially is advanced machine learning. >> Right. >> That can connect the dots. >> Yep. >> Not just predict stuff but like actually say this doesn't belong here. >> Right. >> That's advanced computer science. That's heavy duty coolness. >> Mm-hmm. >> So, operationalizing that way, the way you're saying it I'm imagining there's some future stuff coming around the corner. Can you share how you guys are working with AWS specifically? Is it with Amazon? You guys have your own secret sauce for the folks watching. 'Cause this remediation should, it only gets harder. You got to, you have to be smarter on your end, >> Yep. >> with your engineers. What's coming next. >> Oh gosh, I don't know how much of what's coming next I can share with you, except for tighter and tighter integrations with AWS, right. I've been at three meetings already today where we're talking about different AWS services and how we can be more tightly integrated and what's things we want out of their APIs to be able to further enhance what we can offer to our customers. So, there's a lot of those discussions happening right now. >> What, what are some of those conversations like? Without revealing. >> I mean, they have to do with, >> Maybe confidential privilege. >> privileged information. I don't mean like privileged information. >> Yep. I mean like privileges, right, >> Right. >> that are out there. >> Like what you can access, and what you can't. >> What you can, yes. And who and what can access it and what can't. And passing that information on to us, right. To be able to further remediate it for an AWS customer. That's, that's one. You know, things like other AWS services like CloudTrail and you know some of the other scenarios that they're talking about. Like we're, you know, we're getting deeper and deeper and deeper with the AWS services. >> Yeah, it's almost as if Amazon over the past two years in particular has been really tightly integrating as a strategy to enable their partners like you guys >> Mm-hmm. >> to be successful. Not trying to land grab. Is that true? Do you get that vibe? >> I definitely get that vibe, right. Yesterday, we spent all day in a partnership meeting where they were, you know talking about rolling out new services. I mean, they, they are in it to win it with their ecosystem. Not on, not just themselves. >> All right, Denise it's great to have you on theCUBE here as part of re:Inforce. I'll give you the last minute or so to give a plug for the company. You guys hiring? What are you guys looking for? Potential customers that are watching? Why should they buy you? Why are you winning? Give a, give the pitch. >> Yeah, absolutely. So, so yes we are hiring. We're always hiring. I think, right, in this startup world. We're growing and we're looking for talent, probably in every area right now. I know I'm looking for talent on the sales side. And, and again, the, I think the important thing about us is the, the fullness of our solution but the superpower that we have, like I said before around the identity and the data pieces and this is becoming more and more the reality for customers that they're understanding that that is the most important thing to do. And I mean, if they're that, Gartner says it, Forrester says it, like we are one of the, one of the best choices for that. >> Yeah. And you guys have been doing good. We've been following you. Thanks for coming on. >> Thank you. >> And congratulations on your success. And we'll see you at the AWS Startup Showcase in late August. Check out Sonrai Systems at AWS Startup Showcase late August. Here at theCUBE live in Boston getting all the coverage. From the keynotes, to the experts, to the ecosystem, here on theCUBE, I'm John Furrier your host. Thanks for watching. (bright music)

(ethereal music) >> Good morning, everyone, and welcome to theCUBE's day-two coverage of Snowflake Summit '22. Lisa Martin here with Dave Vellante. We are live in Las Vegas at Caesar's Forum, looking forward to an action-packed day here on theCUBE. Our first guest joins us, Bill Stratton, the global industry lead, media, entertainment and advertising at Snowflake. Bill, great to have you on the program talking about industry specifics. >> Glad to be here, excited to have a conversation. >> Yeah, the media and entertainment industry has been keeping a lot of us alive the last couple of years, probably more of a dependence on it than we've seen stuck at home. Talk to us about the data culture in the media, entertainment and advertising landscape, how is data being used today? >> Sure. Well, let's start with what you just mentioned, these last couple of years, I think, coming out of the pandemic, a lot of trends and impact to the media industry. I think there were some things happening prior to COVID, right? Streaming services were starting to accelerate. And obviously, Netflix was an early mover. Disney launched their streaming service right before the pandemic, Disney+, with ESPN+ as well. I think then, as the pandemic occurred these last two years, the acceleration of consumers' habits, obviously, of not just unbundling their cable subscription, but then choosing, you know, what services they want to subscribe to, right? I mean, I think we all sort of grew up in this era of, okay, the bundle was the bundle, you had sports, you had news, you had entertainment, whether you watched the channel or not, you had the bundle. And what the pandemic has accelerated is what I call, and I think a lot of folks call, the golden age of content. And really, the golden age of content is about the consumer. They're in control now, they pick and choose what services they want, what they watch, when they watch it. And I think that has extremely, sort of accelerated this adoption on the consumer side, and then it's creating this data ecosystem, as a result of companies like Disney having a direct-to-consumer relationship for the first time. It used to be a Disney or an NBC was a wholesaler, and the cable or satellite company had the consumer data and relationship. Now, the companies that are producing the content have the data and the consumer relationships. It's a fascinating time. >> And they're still coming over the top on the Telco networks, right? >> Absolutely right. >> Telco's playing in this game? >> Yeah, Telco is, I think what the interesting dynamic with Telco is, how do you bundle access, high speed, everybody still needs high speed at their home, with content? And so I think it's a similar bundle, but it takes on a different characteristic, because the cable and Telcos are not taking the content risk. AT&T sold Warner Media recently, and I think they looked at it and said, we're going to stay with the infrastructure, let somebody else do the content. >> And I think I heard, did I hear this right the other day, that Roku is now getting into the content business? >> Roku is getting into it. And they were early mover, right? They said the TVs aren't, the operating system in the television is not changing fast enough for content. So their dongle that you would slide into a TV was a great way to get content on connected televisions, which is the fastest growing platform. >> I was going to say, what are the economics like in this business? Because the bundles were sort of a limiting factor, in terms of the TAM. >> Yeah. >> And now, we get great content, all right, to watch "Better Call Saul", I have to get AMC+ or whatever. >> You know, your comment, your question about the economics and the TAM is an interesting one, because I think we're still working through it. One of the things, I think, that's coming to the forefront is that you have to have a subscription revenue stream. Okay? Netflix had a subscription revenue stream for the last six, eight, 10 years, significantly, but I think you even see with Netflix that they have to go to a second revenue model, which is going to be an ad-supported model, right? We see it in the press these last couple days with Reid Hastings. So I think you're going to see, obviously subscription, obviously ad-supported, but the biggest thing, back to the consumer, is that the consumer's not going to sit through two minutes of advertising to watch a 22 minute show. >> Dave: No way. >> Right? So what's then going to happen is that the content companies want to know what's relevant to you, in terms of advertising. So if I have relevancy in my ad experience, then it doesn't quite feel, it's not intrusive, and it's relevant to my experience. >> And the other vector in the TAM, just one last follow-up, is you see Amazon, with Prime, going consumption. >> Bill: That's right. >> You get it with Prime, it's sort of there, and the movies aren't the best in the world, but you can buy pretty much any movie you want on a consumption basis. >> Yeah. Just to your last quick point, there is, we saw last week, the Boston Red Sox are bundling tickets, season tickets, with a subscription to their streaming service. >> NESN+, I think it is, yeah. So just like Prime, NESN+- >> And it's like 30 bucks a month. >> -just like Prime bundling with your delivery service, you're going to start to see all kinds of bundles happen. >> Dave: Interesting. >> Man, the sky is the limit, it's like it just keeps going and proliferating. >> Bill: It does. >> You talk about, on the ad side for a second, you mentioned the relevance, and we expect that as consumers, we're so demanding, (clears throat) excuse me, we don't have the patience, one of the things I think that was in short supply during COVID, and probably still is, is patience. >> That's right. >> I think with all of us, but we expect that brands know us enough to surf up the content that they think we watched, we watched "Breaking Bad", "Better Call Saul", don't show me other things that aren't relevant to the patterns I've been showing you, the content creators have to adapt quickly to the rising and changing demands of the consumer. >> That's right. Some people even think, as you go forward and consumers have this expectation, like you just mentioned, that brands not only need to understand their own view of the consumer, and this is going to come into the Snowflake points that we talk about in a minute, but the larger view that a brand has about a consumer, not just their own view, but how they consume content, where they consume it, what other brands they even like, that all builds that picture of making it relevant for the consumer and viewer. >> Where does privacy come into the mix? So we want it to be relevant and personalized in a non-creepy way. Talk to us about the data clean rooms that Snowflake launched, >> Bill: That's right. >> and how is that facilitating from a PII perspective, or is it? >> Yeah. Great question. So I think the other major development, in addition to the pandemic, driving people watching all these shows is the fact that privacy legislation is increasing. So we started with California with the CCPA, we had GDPR in Europe, and what we're starting to see is state by state roll out different privacy legislations. At some point, it may be true that we have a federal privacy legislation, and there are some bills that are working through the legislature right now. Hard to tell what's going to happen. But to your question, the importance of privacy, and respecting privacy, is exactly happening at the same time that media companies and publishers need to piece together all the viewing habits that you have. You've probably watched, already this morning, on your PC, on your phone, and in order to bring that experience together a media company has to be able to tie that together, right? Collaborate. So you have collaboration on one side, and then you have privacy on the other, and they're not necessarily, normally, go together, Right? They're opposing forces. So now though, with Snowflake, and our data clean room, we like to call it a data collaboration platform, okay? It's not really what a data warehouse function traditionally has been, right? So if I can take data collaboration, and our clean room, what it does is it brings privacy controls to the participants. So if I'm an advertiser, and I'm a publisher, and I want to collaborate to create an advertising campaign, they both can design how they want to do that privacy-based collaboration, Because it's interesting, one company might have a different perspective of privacy, on a risk profile, than another company. So it's very hard to say one size is going to fit all. So what we at Snowflake do, with our infrastructure, is let you design how you create your own clean room. >> Is that a differentiator for Snowflake, the clean rooms? >> It's absolutely a very big differentiator. Two reasons, or probably two, three reasons, really. One is, it's cross cloud. So all the advertisers aren't going to be in the same cloud, all the publishers aren't going to be in the same cloud. One big differentiator there. Second big differentiator is, we want to be able to bring applications to the data, so our clean room can enable you to create measurement against an ad campaign without moving your data. So bringing measurement to the data, versus sending data to applications then improves the privacy. And then the third one is, frankly, our pricing model. You only pay for Snowflake what you use. So in the advertising world, there's what's called an ad tech tax, there is no ad tech tax for Snowflake, because we're simply a pay-as-you-go service. So it's a very interesting dynamic. >> So what's that stack look like, in your world? So I've pulled up Frank's chart, I took a picture of his, he's called it the new, modern data stack, I think he called it, but it had infrastructure in the bottom, okay, that's AWS, Google, Azure, and then a lot of you, live data, that would be the media data cloud, the workload execution, the specific workload here is media and entertainment, and then application development, that's a new layer of value that you're bringing in, marketplace, which is the whole ecosystem, and then monetization comes from building on top. >> Bill: Yes. >> So I got AWS in there, and other clouds, you got a big chunk of that, where do your customers add value on top of that? >> Yeah. So the way you described it, I think, with Frank's point, is right on. You have the infrastructure. We know that a lot of advertisers, for example, aren't going to use Amazon, because the retailer competes with Amazon, So they want to might be in Google or Azure. And then sort of as you go up the stack, for the data layer that is Snowflake, especially what we call first-party data, is sitting in that Snowflake environment, right? But that Snowflake environment is a distributed environment, so a Disney, who was on stage with me yesterday, she talked about, Jaya talked about their first-party datas in Snowflake, their advertisers' datas in their own Snowflake account, in their own infrastructure. And then what's interesting is is that application layer is coming to the data, and so what we're really seeing is an acceleration of companies building that application natively on Snowflake to do measurement, to do targeting, to do activation. And so, that growth of that final application layer is what we're seeing as the acceleration in the stack. >> So the more data that's in that massive distributed data cloud, the more value your customers can get out of it. And I would imagine you're just looking to tick things off that where customers are going outside of the Snowflake data cloud, let's attack that so they don't have to. >> Yeah, I think these partners, (clears throat) excuse me, and customers, it's an interesting dynamic, because they're customers of ours. But now, because anybody who is already in Snowflake can be their customer, then they're becoming our partner. So it's an interesting dynamic, because we're bringing advertisers to a Disney or an NBCU, because they already have their data in Snowflake. So the network effect that's getting created because of this layer that's being built is accelerated. >> In 2013, right after the second reinvent, I wrote a piece called "How to Compete with the Amazon Gorilla." And it seemed to us pretty obvious at the time, you're not going to win an infrastructure again, you got to build on top of it, you got to build ecosystems within industries, and the data, the connection points, that network effect that you just talked about, it's actually quite thrilling to see you guys building that. >> Well, and I think you know this too, I mean, Amazon's a great partner of ours as well, right? So they're part of our media data cloud, as Amazon, right? So we're making it easier and easier for companies to be able to spin up a clean room in places like AWS, so that they get the privacy controls and the governance that's required as well. >> What do you advise to, say, the next generation of media and advertising companies who may be really early in the data journey? Obviously, there's competition right here in the rear view mirror, but we've seen services that launch and fail, what do you advise to those folks that maybe are early in the journey and how can Snowflake help them accelerate that to be able to launch services they can monetize, and get those consumers watching? >> I think the first thing for a lot of these brands is that they need to really own their data. And what I mean by that is, they need to understand the consumer relationship that they have, they need to take the privacy and the governance very seriously, and they need to start building that muscle. It's almost, it's a routine and a muscle that they just need to continue to kind of build up, because if you think about it, a media company spends two, three hours a day with their customer. You might watch two hours of a streaming show, but how much time do you spend with a single brand a day? Maybe 30 seconds, maybe 10 seconds, right? And so, their need to build the muscle, to be able to collect the data in a privacy-compliant way, build the intelligence off of that, and then leverage the intelligence. We talked about it a few days ago, and you look at a retailer, as a really good example, a retailer is using Snowflake and the retail data cloud to optimize their supply chain. Okay? But their supply chain extends beyond their own infrastructure to the advertising and marketing community, because if I can't predict demand, how do I then connect it to my supply chain? So our media data cloud is helping retailers and consumer product goods companies actually drive demand into their reconstructed supply chain. So they both work together. >> So you have a big focus, obviously, on the monetization piece, of course, that's a great place to start. Where do you see the media data cloud going? >> Yeah. I think we'll start to expand beyond advertising and beyond marketing. There's really important sub-segments of media. Gaming is one. You talk about the pandemic and teenagers playing games on their phones. So we'll have an emphasis around gaming. We'll have an emphasis in sports. Sports is going through a big change in an ecosystem. And there's a big opportunity to connect the dots in those ecosystems as well. And then I think, to what we were just talking about, I think connecting commerce and media is a very important area. And I think the two are still very loosely connected today. It used to be, could I buy the Jennifer Aniston sweater from "Friends", right? That was always the analogy. Now, media and social media, and TikTok and everything else, are combining media and commerce very closely. So I think we'll start to see more focus around that as well. So that adds to your monetization. >> Right, right. And you can NFT that. (Lisa laughs) >> Bill: That's right, there you go, you can mint an NFT on that. >> It's the tip of the iceberg. >> Absolutely. >> There's so much more potential to go. Bill, thank you so much for joining us bright and early this morning, talking about what snowflake is doing in media, entertainment and advertising. Exciting stuff, relevant to all of us, we appreciate your insights and your forward-looking statements. >> Thank you for having me. I enjoyed it. >> Our pleasure. >> Thank you. >> Good >> Bill: Bye now. >> For our guest and Dave Vellante, I'm Lisa Martin, you're up early with us watching theCUBE's day-two coverage of Snowflake Summit '22. We'll be back in a moment with our next guest. (upbeat music)

(intro music) >> Good evening. Welcome back to theCUBE's coverage of day one of Snowflake Summit 22 live from Caesar's Forum in Las Vegas. Lisa Martin, here with Dave Vellante. Dave, we have had an action-packed day one. A lot of news coming out this morning. We've talked to Snowflake folks. We've talked to partners, we've talked to customers. A lot going on today. >> It's our light day. Tomorrow it even gets more intense. >> I know. I'm a little scared. (Dave Vellante laughing) We've got another partner of Snowflakes onboard with us here. Please welcome, let me get this, Sudhir Chaturvedi, President and Executive Board Member at LTI. How did I do? >> Yeah, very well, actually. (laughing) >> Dave Vellante: Outstanding. >> Welcome to the program. Tell us a little bit about you and then talk to the audience about LTI and what you're doing with Snowflake. >> Sure. So, LTI is a global technology consulting and services firm. We had (indistinct) out of India. We're part of a large conglomerate, which is over 80 years old. Our founders were two Danish engineers who came to India and were essentially stuck when World War II broke out, and they created a company that's lasted 80 years. So we are very proud of our heritage. We come from an engineering background and frankly what we do with Snowflake is really bring that engineering DNA to Snowflake. So we are, we've been a partner of Snowflake. We are an elite partner of Snowflake, and we work with them across all regions in the world, actually. 50 plus customers today. So, we have great partnership for today. >> And I have a note here. It says you're the GSI Delivery Platform Partner of the Year. Congratulations. What does that entail? What are the requirements to get that award? >> Yeah, I know we are very proud that we are the Delivery Platform Partner of the Year this year. We were the Innovation Partner of the Year, last year. So it shows the journey from innovation to execution in showing delivery. I think what it entails is that we've been recognized for leadership and excellence in executing Snowflake programs at scale, the migration programs and the implementation programs that we've done for customers across the globe. >> Take us back, how did you first find Snowflake? When did you decide to lean in as a company? >> Yeah, it's a great question actually. You know, in fact, so we went public as a company in 2016 and at that time, how do I put it politely? People weren't expecting that much of us. They thought we'll be one amongst many other companies. And we decided that we will vector the company on data, digital, and cloud, and we'll make bets on partners that are perhaps unknown at that time. So in late 2017, early 2018, we started partnering with Snowflake. And since then I must, you know, hand it to Snowflake. We have an phenomenal partnership with them. I just met Frank this morning. Chris Degnan is their Chief Revenue Officer, Colleen Kapase. All of these people have been tremendous in terms of how they work together with us across the world to bring what essentially is phenomenal technology to our clients. >> What was the allure back then? It was, you know, cloud data warehouse, simplified data warehouse, the technically splitting storage from compute, you know, infinite, blah, blah, blah. Was that the allure and saying or did you have a broader vision? >> No, I think what happened was clients were struggling with data because data and applications in our world were sort of very tightly intertwined and they weren't really leveraging data for making realtime decisions. So the moment we saw the promise of Snowflake that you can create true data on cloud, which on sort of all data on cloud, you know what Frank was talking about this morning, and it's available in real time and you can do a lot of things on it. We said, this is technology of the future. It truly is because it separated storage and compute. It did many things that were not possible before. So I think the thing is when you see promising technology as a GSI, you always wonder, should we wait for it to be proven before we jump in? >> Dave Vellante: Right. >> Or should we jump in right up front and help them prove the model? And we decided to take the first approach where we jumped in right up front. >> Dave Vellante: You bet. >> And I think that's helped us earlier. >> Jumped in head first, pandemic hits, they go public. >> Yes. >> Lots of stuff going on. Talk to us about how you're leveraging the power this flywheel that Snowflake has created that I think is just getting bigger and faster. >> Sudhir: Absolutely. >> How are you leveraging the power of the technology to really deliver business outcomes for clients? >> No, that's a great question. And the thing with our initial focus was to get people onto data on cloud and with Snowflake, but now it's really around driving business outcomes from there. So we have a suite called Fosfor which is a data to decisions product suite, which is Snowflake ready. We've also launched PolarSled too which is based on business outcomes. So what we've done is we've done is we've actually created about 155 NorthStars. So various industry sectors, what business outcome do you want to achieve? We call that a NorthStar. And then we say, how do you achieve it with Snowflake? You know, so what we are doing is we're saying let's achieve the business outcome that's going to drive more consumption, but essentially, you know, we live in a difficult world, a increasingly difficult world. So we want to help people take better database decisions. >> Well, what are some of the more interesting ways in which your clients are using Snowflake? >> Yeah, I think when I look at, for example, we have a client in the financial services sector who was struggling with, you know, they're one of the largest asset management and fund management companies in the world. They're a household name, everybody knows them. And they probably have an EFT or some sort of 401k with them. And what they were struggling with was to say, how do I actually get various sources of data together in a way that I can make better asset, you know, better fund management decisions because otherwise it was left to a lot of very traditional equity research reporting and fund managers taking their expertise. Here, the data from multiple sources being available, running some AIML routines on it, we're able to show them patterns in various asset classes, on options, on investments that they hadn't seen before. And now that they've jumped headlong into it, 15 of their units across the world are using it now. So I think the power of once you see data in action that it's sort of, it's almost like the superpower that smart people get. It's like, yeah, like you suddenly arm them with so much more than they had previously. And then they get so much better at what they're doing. And ultimately consumers like us benefit from that. So, you know, that's really where we want to go. >> What's LTIs like best sweet spot where, you go into a client and you know, wow, this is a perfect fit for what we do? >> Yeah. So I think I would say banking and insurance is 47% of our business. We really understand that business extremely well. The other aspect of that is because we come from a manufacturing heritage. We've had that as well. And media is something we've done more recently. So, you know we've got a media cloud along with Snowflake. So I would say these are the sectors that we are, so we've been very domain focused as a client, as a company. You know, domain first, technology, we'll work with whatever technology the domain needs but that's really been helpful to us all. And this is where that whole point of NorthStar and Fosfor comes back in, which is, today, I think without the data on cloud you would've never achieved the kind of outcomes that we are able to achieve with our clients today. >> How did you feel about the recent sales pivot that Snowflake has made in terms of retail, but also healthcare and life sciences? Talk to me about that and is that enabling your joint customers to really leverage? >> Yeah, no, I think it's very exciting. We are working with clients on that. They like the new model. They're looking forward to, I think what clients are now doing is they're putting data perhaps ahead of even in these times where people are looking at, you know, we are seeing seven or eight very difficult macroeconomic trends. People are wondering, clients are wondering, what's this going to mean for their business in the future? So they're looking at spends and saying, what do I prioritize? But what I find is that that data spend only goes up, you know? So, our own data practice has sort of grown fourfold in the last six years, you know? So it's been just an exponential growth for us. And essentially Snowflake is our largest bet in that space even over every other technology that's out there. So I think clients, when they see that combination of how Snowflake is changing and what we can bring to them, I think the model works well for them. >> You know, ecosystem is one of the areas that we always pay attention to. You can see, just look around,. I mean, you compare 2019 to where we are today. What's the importance of ecosystem to LTI and how do you see it evolving? >> That's a great question. So, you know, it's like, I think in About a Boy, you know, Hugh Grant says that no man is an island. You know, and I think the same thing applies for companies. Any company, no matter what size they are, if they think that they can do everything themselves and I think they're not going to be successful in the long run. We believe that the ecosystem of partnerships is what drives all the best outcomes for our clients and our clients expect that today. They want (indistinct) partners to work together. And the thing with an ecosystem is, you know no one person can dominate an ecosystem, you know? The customer has to be at the center of the ecosystem and then everybody in the ecosystem is actually saying how best do I service the customer? So I think if you have that kind of customer centricity and you understand that ecosystems, you know, on your own you'll never be as good as an ecosystem. I think you nailed it, but it requires, a partnering ethos and that's what we really like about Snowflake. Such a strong partnering ethos. I still, I keep telling people if I text or message Chris or Colleen, I'll get a response in within 15, 20 minutes. You know, that's invaluable when you're trying to do great things for your joint clients, you know, so. >> Sounds like there's a lot of synergies there around the customer obsession, customer centricity. >> Absolutely. I think responsiveness in today's world is key. You know, I think the first people to respond, even if it's to say, you know what, I hear you I'm going to get back to you. I think, you know, people love that about you. It's easy to say customer centric. It's difficult to actually practice it in real life. And we believe that, for us, responsiveness is the key. We'll respond no matter what time of day or night. And the other thing is we'll respond even with our partners, right? We are not going to respond on our own and then bring everybody else along. Even things like, I don't know this but I can refer you to a partner who can help you do this. That's also a response. >> That responsiveness is so critical, especially in this day and age where I think one of the things that was in short supply during COVID and one of the many things is patience and tolerance. >> Correct. >> Right? On us as consumers and our business lives. So being able to respond even just to say we're checking, don't know yet, that builds trust between organizations with customers. >> Well, yeah, absolutely. In fact, you know, even the first year of the pandemic we grew nine and a half percent, year and year. >> In India, we were the fastest growing company that year. And if anybody asked me why did you grow nine and half percent when the industry grew at -1%, you know, in that financial. I think it was the speed at which we responded between February and June to client requests. We responded even before, I know I was in calls till 12:30 in the night working with clients to say, okay how do we fix this? How do we change this? How do we stop doing something? How do we cut costs, whatever they needed. And what we did in the first three months actually helped us our first four months when the first wave of the pandemic really hit. Actually clients were like these guys were on our side when times are tough. Let's sort of bet on them. And the data business actually grew. And I keep saying this, you know, whenever a big macro trend hits when there's more uncertainty, people look to the data because your judgment and experience is no longer applicable. Nobody in the world had any experience or judgment that could be applied in COVID times, right? So you need to now look at the data and say, okay, is the data telling me something that I would never come to know based on my own experience? And I think, you know, this is what I call the real database decisions is no company in the world will say we don't do it. But I think today's world, we are seeing real time data decisions being taken. We see it in the supply chain all the time. We see it in how banks are processing interest rate rises, et cetera. It's the speed at which they're acting would not be possible without a data first kind of approach they've taken. >> Right. And it has to be real time these days. >> It has to be. >> Every organization. That's no longer a nice to have. >> No, you know, and data is getting out of date also so quickly. I mean, in today's world, with the war in Ukraine I think the first thing we realized was that almost every parameter on commodity, whether it was oil or steel or shipping or whatever, it changed so rapidly that the only way to predict, many of our clients were not able to to tell their customers when they would be able to deliver products and service or products, especially manufacturing clients because they just didn't know when they would get their materials and go get their parts, et cetera. And we used data to say, okay, let's at least establish a base on which, because clients get disappointed, more customers get disappointed when you don't meet a delivery date. So we wanted to say, let's make it more predictable, even in unpredictable times. So we were able to manage expectations. We were able to do that better. Without the data there was no way it would've happened. There was just no way. And frankly, for us, Snowflake is the reason. For us it's our biggest bet in the data space. And that's how most of the work that we are doing in supply chain, in fact, I'm just headed to a manufacturing event that our team has organized, which is with Snowflake on data on cloud for manufacturing clients. So we've been slightly behind the curve compared to some of the others, but now seeing the promise and saying, hey let's go for this. >> There's a tremendous amount of potential. We're only scratching the surface. We thank you so much >> Sudhir: Thank you. >> For joining David me on the program, talking about LTI, the power of what you're doing together with Snowflake. We'll let you get to that manufacturing event. I'm sure that they are looking forward to talking to you. >> Yeah, no. Thank you so much. It was lovely to speak to you. Thank you so much. >> Likewise. My pleasure. For our guest and Dave Vellante, this is Lisa Martin signing off from the show floor of Snowflake Summit 22. Day one coverage is complete. Dave and I look forward to seeing you bright and early tomorrow for a jam packed day two. Thanks so much for watching. Take good care. (outro music)

>>The cube presents, Dell technologies world brought to you by Dell. >>Hello. Welcome to the cube here at Dell tech world. I'm John furry host of the cube with Dave Alon here with Michael Dell, the CEO of Dell technologies cube alumni comes on every year. We have the cube here. It's been two years. Michael, welcome to the cube. Get to see you. >>Hey, John, Dave, great to be with you guys. Thanks for being here. Wonderful to be back here in Vegas with >>You. Well, great to be in person two years ago, we had the cue with the pandemic a lot's happened. We were talking end to end solutions here at Dell tech world in person two years ago, pandemic hits. Thank God you had all that supply for the, for the people having the remote remote end to work now back in person. What's it look like now with, with Dell tech end to end, the edge is important. What's the story, >>You know, edge is, is the physical world. And if you, if you step back from clouds and, you know, multi-cloud, you sort of think about what is the purpose of a cloud or a data center? Well, it's to take data out of the physical world and move it to this place, to somehow enhance it or do something with it and create business value and hopefully create better outcomes. Well, it turns out that, you know, increasingly a lot of that data is gonna stay in the physical world and all of those nodes are gonna be connected. They're gonna be intelligent and we're seeing it in manufacturing and retail and healthcare, transportation, logistics. We're seeing this rapidly intelligent edge being formed. And then of course, with the new networks, the 5g we're seeing, you know, all, all this develop. And so here on the show floor, we're showing a lot of those solutions, but our customers are, are highly engaged. And certainly we think that's a, a big, a big growth factor for the next decade. >>And it's been ING to watch the transformation of the it world and cloudification and the as service, uh, consumption model, which you guys are putting out there has been very successful, but cloud operations is more prominent now on premises and edge and cloud. So the combination of cloud on-premise and edge hardware matters more now than ever before Silicon advances, um, abstraction layers from modern cloud native applications are what people are focused on. What's the story that you cite to the CIOs saying, we're here to help you with that new architecture cloud multi-cloud on premise and edge. What's the main story for you guys with the customers? >>Well, you know, customers want to go faster, right? And they want to accelerate their transformation. And so they wanna shift more resources over to developers, to applications, to access their data, to create competitive advantage. And so we talk a lot about the value line and what are those things below the value line, where we can provide that as a service on a consumption based model and accelerate their transformation, kind of, you know, do for them what we've done inside our own business. And, you know, it's absolutely resonating. We're seeing great growth there. People continue to, to need the solutions, but as we can automate the management and deployment of infrastructure and make it super easy, it gives them a lot of cycles back. >>You know, Michael, my, the favorite part, my favorite part of your book was you were in, I think you were in his, in his home court, in his dining room at Carl Icahn's house. And you said, well, why don't you just buy the company? And then you'll do what you're doing. I I'll buy it back for cheaper. Now, thankfully, you didn't have to do that. Cuz you had an environment of low interest rates and you obviously took it into the other direction, added tremendous value, 101 billion in revenue last year, 17% revenue growth, which was out astounding. When you think about that, um, now we're entering a new chapter with VMware untethered of course you're the chairman of both companies. So how should we think about the new Dell what's next? >>Well, so look, we, we have some unbelievable core businesses, right? We have our client system business and we've all learned during these last two years, how incredibly important it is to enable and empower your workforce with the right tools in the remote and high hybrid work. And we're showing off all kinds of new innovations here. That's a huge business force continues to grow, continues to be super important. Then we have our ISG, the cloud data center, the network of the future, the edge, you know, the, the sort of epicenter of where we're embracing, consumption based business models. That's absolutely huge. Then we have these new, new businesses that we're building with telco with edge, put it all together. It's a 1.3 trillion Tam that we operate in, as you said, more than a hundred billion dollars last year. So there's plenty of room for us to continue to grow and, and expand. And you know, as we make this shift to outcomes, it's obviously more valuable for customers and that, you know, increases our opportunity, increases the, the value we can create for all our stakeholders. >>And number one, number one, share in PCs, by the way, congratulations, again, hit that milestone. All of our gamer, uh, fans in our discord want to know what's the hottest chips coming. What's the fastest machines. What, how's the monitors coming? They want faster, cheaper. What's the coolest, uh, monitors out there right now and, and machines. >>Well, uh, you know, what what's, what's amazing is the, the pace of innovation continues to improve. So whether it's in the GPU, the CPU, the, the resolution, I I'm pretty partial to our 41, uh, display 11 million pixels of fun. And look, I mean, we, we it's, it's, it's clear that people are more productive when they have large screens and all the performance is enabling photo realistic, uh, you know, uh, gaming and photo realistic, everything. And these are immersive experiences. And, you know, again, uh, what companies have figured out to bring it back to, to, to a little bit of business here, John, is that when you, uh, give people the right tools, they're more productive, they're more engaged and look, people are smart. They know what tools are available. And, you know, uh, the thing that actually is most representative of how a person thinks about the tools they have at their organization is actually the thing that's right in front of 'em. And so, you know, this ability for us to provide a pool set of solutions for organizations to keep their workforce productive, to run their applications and infrastructure securely anywhere they want. That's, that's a winning proposition. >>Michael trust was a big theme of your keynote yesterday. And when you acquired EMC and got VMware, it really changed the dynamic with regard to your ability to, into new parts of organizations. You became a much more strategic supplier. I, I would argue. And now with VMware as a separate company, do you feel like you have built up over the, you know, five or whatever years that muscle memory you kinda earn that trust. So how do you see the customer relationship with that regard to that integration that they, they loved the eco. So system competitors might not have loved it so much, but the customers really did love. In fact, the, the U S a, a gentleman yesterday kind of mentioned that, how do you see it? >>You know, customers, uh, are not as interested in the balance sheet and what you know, where different holdings are, what they, they want things to work together, right? And they want partnerships in ecosystems. And certainly, you know, with VMware, even before the combination, we had a powerful partnership. It obviously solidified in a super special way. And now we have this first and best relationship and I've remained the chairman of VMware and super excited about their future. But our ecosystem is incredibly broad. And you see that here in this show floor, and again, making things work together better and more effectively building these engineered solutions that allow people to very quickly deploy the kind of capabilities they want, whether it's, you know, snowflake now working with the on premise and the edge data and more of these, you know, multi-cloud, uh, eco of systems that are being built. It's not gonna be just one company >>You called the edge a couple years ago. You're really prominent in your, in your speeches. And your keynotes data also is a big theme. You mentioned data now, data engineering seems to be the hottest track of, of, of students graduating with data engineering skills, not data science, data engineering, large scale data as code concepts. So what's your vision now with data, how's that fitting into the solutions and the role of data, obviously data protection with cybersecurity data as code is becoming really part of that next big thing. >>Yeah. I mean, if, if you look at anything that is interesting in the world today, uh, at the center of it is data, right? Whether it's the blockchain or the defi or the AI drug discovery, or the autonomous vehicles or whatever you wanna do, there's data in, in, in the middle of that. And of course with that data, well, you've gotta manage it. You, you need compute engines, right? You need to be able to protect it, secure it. And, you know, that's kind of what we do, and we're not going to create all those solutions, but we are gonna be an enabling layer to allow that data to be accessed no matter, you know, where, where it is. And, and, and of course, you know, leading in storage continues to be a super important part of our business. Number one, larger than number two than number three, number four, combined, and, and most of number five as well, and, and growing share. And, and you saw today, the software defined innovations, allowing that, you know, data layer to exist across the edge, the colos, the OnPrem, and the public clouds >>Throughout a stat yesterday. I can't remember if it was a keynote of the analyst round table, but it was 9 million cell towers. And if I heard, right, you kinda look at those as potential data centers talk about that's >>Right. It it's actually 7 million, but, but probably will be 9 million and not, not too long, I don't have the update, but so yeah, the public clouds all together is about 600 data centers. They're about 7 million cellular base stations in the world. Every single one of those is becoming a, you know, multi access, edge compute node. And what are they putting in there? They're putting many data centers of compute and GPS and storage. And, you know, 5g is not about, uh, connecting people that was 4g and before 5g is about connecting things. And there are way more things than there are people, right? And, uh, you know, this, this, this edge is, is rapidly developing. You'll also have private 5g and you'll have, you know, again, embedded intelligence I believe is gonna be in everything this next decade is going to be about that intelligent, connected future, taking that data, turning it into useful outsides in insights and outcomes. And, you know, lots of new businesses will be existing. Businesses will be transformed and also disrupted. >>Yeah. I mean, I think that's so right on and not to pat ourselves on the back day, but we called that edge distributed computing a couple years ago on the cube. And that's, what's turning into the home with COVID you saw that become a workplace, basically compute center, these compute nodes, tying it together as we, what everyone's talking about right now. So as customers say, okay, I want to keep my operations steady, steady, and secure. How do I glue it together? How do I bring these compute node together? That seems to be the top question on, on top of people's minds. And they want it to be cloud native, which means they want it to run cloud-like and they want to connect these compute node together. That's a big discussion point. What's your view on, >>Well, you know, if you, if you sort of have a, a cloud here, a cloud there cloud everywhere, and you, you know, have lots of different Kubernetes frameworks, uh, and you've got, you know, everything is, is spread out, it's a disaster, right? And, and, and it's, it's a, it's a, it's a real challenge to manage all that. So what people are trying to do is create ruthless standardization. It's like, how do you drive cost out and get speed? It's ruthless standardization create consistent environments where you can operate the across all the different domains that, that you want. And so, uh, you know, this is what we're bringing together in, in, in the capabilities that we're delivering. >>And that chaos is great opportunity for you. Um, how are you feeling about VMware these days, new team, uh, give us the update there. >>Yeah. The team is doing well. You know, I think the tons message is resonating. You know, people want Kubernetes and, and, and container based apps, for sure. That's the main, you know, growth in, in, in, in, in new, in new workloads. Uh, but they also want it to work with what they have. Yeah. And they don't want it to be locked into one particular infrastructure. So software finding everything, making it run in all the public clouds, you know, we've had a great success with VxRail, you know, that, that absolutely continues. We have, uh, 200,000 plus nodes, 15,000 customers and growing, we have edge satellite nodes and we continue to work together in SD wan in software defined networking in VMware cloud foundation, uh, you know, expressed, uh, in, in, in all locations. >>You know, one of the things that we've been seeing with the trend towards, um, future of work, which is a big theme, here is a lot of managed services are popping up where the complexity is so ha high that customers want to manage services. Uh, and also the workforce of it's kind of changing. You got a younger generation coming in, how do you see that future of the workforce? The next level? It's not gonna be like, yesterday's it, it's gonna be distributed computing dashboard based. And then you've got these managed services, you know, need to have the training and expertise maybe to run something at scale. How do, how do you see that connecting? Cuz that seems to be another big trend people are talking about, Hey, it's complex someone manage it for me. And I want ease of views. I want the easy button in it. >>Yeah. Well we we've all been at this a while. So we can remember, you know, the beginnings of converged infrastructure and then hyperconverged, which wasn't that long go. And now we have consumption based business models. These are all along the trajectory of the easy button that you're talking about and customers really thinking about the value line, where are the things that really differentiate and add value for their business. And it's not below the value line in those infrastructure areas are creating that easy button with appliances, with consumption based models and allowing them to deploy the scarce resources. They have to the things that really drive their unique differe. And you know, if you look at our managed services flex on demand, all the sort of ancestors and predecessors of apex, those have been great businesses for us. And now with apex, we're kind of industrializing this and, and making it, you know, at scale for all >>Customers, you know, the three of us, we go back, we, we, our first interactions with you separately, we're in the nine. And then we reconnected in the 2012. I think it was Tarkin Mayer had a little breakout session with CIOs. You brought us to early on a Dell tech world in Austin. And of course it was, >>It was just Dell world. Then Dell >>Four, we had Dell tech, you and then EMC world in 2010 was our first cube. And now that's all come together here in Las Vegas. So, you know, it's been great. Uh, the three of us come together and so really appreciate that. Yeah. >>Awesome. Absolutely awesome. >>Well, you know, really appreciate you guys being here, the wonderful work you do in thank you in, you know, bringing out the, the, the stories and, and showing off and helping us show off the innovations that, you know, our team has been working on. You know, during the past year >>It's been great in conversations and, and on a personal note, it's been great to have, uh, chat with all the top people and your company. Appreciate it. Um, someone told me to ask you this question, I want to ask you, you, we've all seen waves of innovation cycles up and down. We're kind of on one. Now you're seeing an inflection point, this next gen, uh, computing and, and web three cultural shit F with workforces and distributed computing decentralization. You mentioned that DFI earlier, how do you see this wave coming? Cause we've seen cycles come and go.com. Bubble kind of looks the same as the web three NFTs and stuff. Now it seems to be Look different, but how do you see this next wave? Cuz looking back on all the other ones that you you have lived through and you rode >>Well. So, you know, the, the way I see it is is, uh, to some extent, these are like foundational layers that have to be built for the next phase to occur. And if you look at the sort of new companies that are being founded today, and we see a lot of those, you, you, you, you see'em, we invest in a bunch of 'em, you know, they're, they're not going and, and kind of redoing the old foundational layers, they're going deeply into vertical businesses and, and disrupting and adding value on top of those. And I think that's, that's really the, the point of, of technology, right? It's enabling human progress us in, in all fields, it's making us healthier. It's making us safer. It's making us more successful in everything that, that we as humans do. And so all these layers of technology are enabling further progress and I think it's absolutely gonna continue. It's all been super exciting. Yeah. You know, so far for the first several decades, but as I, as I believe it, it's, it's just a pre-game show. >>And it's clear your strategy is, is, is really building that foundation of a layer, hardening it, but making it flexible enough, anybody read your book, you're a technology, visionary. A lot of people put you in a, you know, finance bucket, but you can, you can see that you can connect the dots. And that's what you're doing with your foundation of layers. You that's where you're making the bets, isn't it? Uh, you don't can't predict the future. You've said that many times, but you can sort of see where it's going and be prepared for >>It. Well, you, you, you know, you think about any company in, in the industry or any public sector organization, right? Uh, they're, they're, they're wanting to evolve more quickly and transform more quick, more quickly. Right. And we can give them an infrastructure or set of tools, a set of capabilities to help them go faster. >>Yeah. And the other one thing in the eighties, when you started Dell and we were in college, there was no open source really then if look at the growth of open source, talk about those layers, open source, better Silicon GPS, faster, cheap >>More now and now we even have, uh, open source instruction sets for processors. So I mean the whole world's changing. It's exciting. You have people around the world working together. I mean, when you see our development teams, uh, whether they're in Israel or Ireland or Bangalore or Singapore, Hopton Austin, Silicon valley, you know, Taiwan, they're, they're all, they're all collaborating together and, you know, driving, driving innovation and, and, and our business is not that dissimilar from our customers >>Like great to have you in the queue. Great. To have a physical event. People are excited. I'm talking to people, Hey, haven't been back in Vegas in two years. Thanks for having this event. Great to see you. Thanks for coming on the cube. >>Absolutely. Thank you guys. >>Michael Dell here in the cube CEO of Dell technologies. I'm John far, Dave Volante. We'll be right back, more live coverage here at Dell tech world.

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante snowflake they love the stock at 400 and hated at 165 that's the nature of the business i guess especially in this crazy cycle over the last two years of lockdowns free money exploding demand and now rising inflation and rates but with the fed providing some clarity on its actions the time has come to really dig into the fundamentals of companies and there's no tech company that's more fun to analyze than snowflake hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we look at the action of snowflake stock since its ipo why it's behaved the way it has how some sharp traders are looking at the stock and most importantly what customer demand looks like the stock has really provided some great theater since its ipo i know people who got in at 120 before the open and i know lots of people who kind of held their noses and bought the stock on day one at over 300 a day when it closed at around 240 that first day of trading snowflake hit 164 this week it's all-time low as a public company as my college roommate chip simonton a long time trader told me when great companies trade at all times time lows because of panic it's worth taking a shot he did now of course the stock could go lower there's geopolitical risk and the stock with a 64 billion market cap is expensive for a company that's forecast to do around 2 billion in product revenue this year and remember i don't recommend stocks you shouldn't take my advice and my comments you got to do your own research but i have lots of data and i have opinions and i'm willing to share that with you stocks like snowflake crowdstrike z-scaler octa and companies like this are highly volatile when markets are moving up they're going to move up faster than the mean when they're declining they're going to drop more severely and that's clearly what's happened to snowflake so with a company like this you when you see panic selling you'll also see panic buying sometimes like we we've seen with this name it went from 220 to 320 in a very short period earlier snowflake put in a short-term bottom this week and many traders feel the issue was oversold so they bought okay but not everyone felt this way and you can see this in the headlines snowflake hits low but cloud stocks rise and we're going to come back to that is it a buy don't buy the dip buy the dip and what snowflake investors can learn from microsoft and from the street.com snow stock is sliding on the back of ill-conceived guidance and to that i would say that conservative guidance these days is anything but ill-conceived now let's unpack all this a bit and to do so i reached out to ivana delevska who has been on this program before she's with spear invest a female-led etf that goes deep into understanding supply chains she came on breaking analysis and laid out her thesis to buy the dip on snowflake this is a while ago she told me currently spear still likes snowflake and has doubled its position let me share her analysis she called out two drivers for the downside interest rates you know rising of course in snowflakes guidance which my own publication called weak in that previous chart that i just showed you so let's dig into that a bit snowflake guided for product revenues of 67 year on year which was below buy side expectations but i believe within sell side consensus regardless the guide was nuanced and driven by snowflake's decision to pass along price efficiencies to customers from optimizing processor price performance predominantly from aws's graviton too this is going to hit snowflakes revenue a net of about a hundred million dollars this year but the timing's not precise because it's going to hit 165 million but they're going to make up 65 million in increased demand frank slootman on the earnings call made this very clear he said quote this is not philanthropy this stimulates demand classic slootman the point is spear and other bulls believe that this will result in a gain for snowflake over the medium term and we would agree price goes down roi gets better you throw more projects at snowflakes customers going to buy more snowflake and when that happens and it gives the company an advantage as they continue to build their moat it's a longer term bet on cloud and data which are good bets now some of this could also be competitive pressures there have been you know studies that are out there from competitors attacking snowflakes pricing and price performance and they make comparisons oracle's been pretty aggressive as have others but so far the company's customers continue to consume now at a very fast rate now on on this front what can we learn from microsoft that applies to snowflake that's the headline here from benzinga so the article quoted a wealth manager named josh brown talking about what happened to microsoft after the dot-com bubble burst and how they quadrupled earnings over the next decade and the stock went sideways suggesting the same thing could happen to snowflake now i'd like to make a couple of comments here first at the time microsoft was a 23 billion dollar company and it had a monopoly and was already highly profitable steve ballmer became the ceo of microsoft right after the dot-com bubble burst and he hugged onto windows for dear life and lived off of microsoft's pc software monopoly microsoft became an extremely profitable and remarkably uninteresting caretaker of a pc in on-prem software estate during balmer's tenure so i just don't see the comparison as relevant snowflake you know they're going to make struggle for other reasons but that one didn't really resonate with me what's interesting is this chart it poses the question do cloud and data markets behave differently it's a chart that shows aws growth rates over time and superimposes the revenue in the red in q1 2018 aws generated 5.4 billion dollars in revenue and that was growing at the time at nearly a 50 rate now that rate as you can see decelerated quite significantly as aws grew to a 50 billion dollar run rate company that down below where you see it bottoms now it makes sense right law of large numbers you can't keep growing that fast when you get that big well oops look what happened in 2021 aws's growth rate bottoms in the high 20s and then rockets back up to 40 this past quarter as aws surpasses a 70 billion dollar run rate so you have to ask is cloud different is data different is cloud data different or data cloud different let's put it in the snowflake parlance can cloud because of its consumption model and the speed of innovation and ecosystem depth and breadth enable snowflake to exhibit lots of variability in its growth rates versus a say progressive and somewhat linear decline as the company grows revenue which is what you would expect historically and part of the answer relates to its market size here's a chart we've shared before with some additions it's our version of snowflake's total available market they're tam which snowflake's version that that blue data cloud thing superimposed on the right it shows the various layers of market opportunity that we came up with that that snowflake and others we think have in front of them emerging from the disruption of legacy data lakes and data warehouses to what snowflake refers to as its data cloud we think about the data mesh concept and decentralized data architectures with domain ownership and data product and service builders as consistent with snowflake's data cloud vision where snowflake data stores are nodes they're just simply discoverable nodes on the mesh you could have you know data bricks data lakes you know s3 buckets on that mesh it doesn't matter they can be discovered they can be shared and of course they're governed in a federated model now in snowflake's model it's all inside the snowflake data cloud that's fine then you'll go to the out years it gets a little fuzzy you know from edge locations and ai inference it becomes massive and decision making occurs in real time where machines and machine data take over the world instead of you know clicks and keystrokes sounds out there but it's real and how exactly snowflake plays there at this point is unclear but one thing's for sure there'll be a lot of data and it's going to find its way into snowflake you know snowflake's not a real-time engine it's an analytical system it's moving into the realm of data science and you know we've talked about the need for you know semantic layer between those those two worlds of analytics and data science but expanding the scope further out we think that snowflake is a big role to play in this future and the future is massive okay check you got the big tam now as someone that looks at companies through a fundamentals prism you've got to look obviously at the markets in the tan which we just did but you also want to understand customers and it's not hard to find snowflake customers capital one disney micron alliance sainsbury sonos and hundreds of other companies i've talked to snowflake customers who have also been customers of oracle teradata ibm neteza vertica serious database practitioners and they tell me it's consistent soulflake is different they say it's simpler it's more agile it's less complicated to secure and it's disruptive to their traditional ways of doing data management now of course there are naysayers i've spoken to a number of analysts that feel snowflake is deficient in areas like workload management and course complex joins and it's too specialized in a world where we're seeing the convergence of analytics and transactional workloads our own david floyer believes that what oracle is doing with mysql heatwave is radically disruptive to many of the database architectures and blows away anything out there and he believes that snowflake and the likes of aws are going to have to respond now this the other criticism here is that snowflake is not architected for real-time inference where a lot of that edge activity is is going to happen it's a multi-hundred billion dollar market and so look snowflake has a ton of competition that's the other thing all the major cloud players have very capable and competitive database platforms even though they all partner with snowflake except oracle of course but companies like databricks and have garnered tons of vc other vc funded companies have raised billions of dollars to do this kind of elastic consumption based separate compute from storage stuff so you have to always keep an open mind and be aware of potential blind spots for these companies but to the criticisms i would say look snowflake they got there first and watch their ecosystem it's a real key to its continued success snowflake's not going to go it alone and it's going to use its ecosystem partners to expand its reach and accelerate the network effects and fill those gaps and it will acquire its stock is valuable so it should be doing that just as it did with streamlit a zero revenue company that it bought for 800 million dollars in stock and cash just recently streamlit is an open source python library that gets snowflake further deeper into that data science space that data brick space and look watch what snowflake is doing with snowpark it's an api library for processing data and building data intensive applications we've talked about snowflake essentially being becoming the super cloud and building this sort of path-like layer across clouds rather than trying to do it all themselves it seems snowflake is really staring at the api economy and building its ecosystem to plug those holes so let's come back to the customers here's a chart that shows snowflakes customer spending momentum or net score on the the top line that's the vertical axis and pervasiveness in the data or market share and that bottom brown line snowflake has unprecedented net scores and held them up for many many quarters as you can see here going back you know a couple years all leading to its expanded market penetration and measured as pervasiveness of so-called market share within the etr survey it's not like idc market share it's pervasiveness in the data set now i'll say this i don't see how this is sustainable i've been waiting for this to moderate i wouldn't be surprised to see snowflake come back to earth a little bit i think they'll clearly still be highly elevated based on the data that i've seen but but i could see in in one or more of the etr surveys this year this starting to moderate as they get they get big it's just it has to happen um but i would again expect them to have a high spending velocity score but i think we're going to see snowflake you know maybe porpoise a bit here meaning you know it moderates it comes back up it's just really hard to sustain this piece of momentum and higher train retain and scale without absorbing some some friction and some head woods that's going to slow you down but back to the aws growth example it's entirely possible that we could see a similar dynamic with snowflake that you saw with aws and you kind of see it with salesforce and servicenow very successful large entrenched entrenched companies and it's very possible that snowflake could pull back moderate and then accelerate that growth even though people are concerned about the moderated guidance of 80 percent growth yeah that's that's the new definition of tepid i guess i look i like to look at other some other metrics the one that really called you know my my my attention was the remaining performance obligations this last quarter rpo snowflakes is up to something like 2.6 billion and that is a forward-looking indicator of of future revenues so i want to i'd like to see that growing and it's growing at a fast pace so you're going to see some ups and downs with snowflake i have no doubt but i think things are still looking pretty solid for the company growth companies like snowflake and octa and z scalar those other ones that i mentioned earlier have probably been repriced and refactored by investors while there's always going to be market and of course geopolitical risk especially in these times fundamentals matter you've got huge market well capitalized you got a leadership position great products and strong customer adoption you also have a great team team is something else that we look for we haven't touched on that but i'll leave you with this thought everyone knows about frank slootman mike scarpelli and what they've accomplished in their years of working together that's why the stock you know in ipo was was so overvalued they had seen these guys do it before slootman just documented in all this in his book amp it up which gives great insight into the history of of that though you know that pair and and the teams that they've built the companies that they've built how he thinks about building companies and markets and and how you know total available markets super important but the whole philosophy and culture that that he's building in his management style but you got to wonder right how long is this guy going to keep going what keeps him motivated you know i asked him that one time here's what he said why i mean are you in this for the sport what's the story here uh actually that that's not a bad way of characterizing it i think i am in it uh you know for the sport uh you know the only way to become the best version of yourself is to be uh to be under the gun and uh you know every single day and that's that's certainly uh what we are it sort of has its own rewards building great products building great companies uh you know regardless of you know uh what the spoils may be uh it has its own rewards and i i it's hard for people like us to get off the field and uh you know hang it up so here we are so there you have it he's in it for the sport how great is that he loves building companies and that my opinion that's how frank slootman thinks about success it's not about money money's the byproduct of success as earl nightingale would say success is the progressive realization of a worthy ideal i love that quote building great companies building products that change the world changing people's lives with data and insights creating jobs creating life-altering wealth opportunities not for himself but for thousands of employees and partners i'd say that's a pretty worthy ideal and i hope frank slootman sticks with it for a while okay that's it for today thanks to stephanie chan for the background research she does for breaking analysis alex meyerson on production kristen martin and cheryl knight on social with rob hoff on siliconangle and thanks to ivana delevska of spear invest and my friend chip symington for the angles from the money side of things remember all these episodes are available as podcasts just search breaking analysis podcast i publish weekly on wikibon.com and siliconangle.com and don't forget to check out etr.plus for all the survey data you can reach me at devolante or david.velante siliconangle.com and this is dave vellante for cube insights powered by etrbsafe stay well and we'll see you next time [Music] you

>>Hello, and welcome to this cubes presentation with unstoppable domains. It's a showcase we're featuring all the best content in web three. And with unstabled a showcase I'm John furrier, your host of the cube. We've got a great guest here, Matt Miscavige. Covich who's the chief revenue officer of unstoppable domains. Matt, welcome to the showcase. Appreciate it. >>Thank you for having me. So >>The theme of this segment is the potential of the web three marketplace with unstoppable domains, the chief revenue officer, you guys have a very intriguing, interesting concept. That's going extremely well. Congratulations, but you're using NFTs for access and domains. Of course, the, the metaverse is huge. People want their own domains, but it's not just like real estate in the sense of a website. It's bigger than that. It's a lot going on. So take us through what is the value proposition and what is the product? >>Absolutely. So for the past 20 years, most of us have been interacting on the internet. Using usernames issued to us by big corporations like Facebook, Google, Twitter, tech talks, Snapchat, et cetera. Whenever we get these usernames for free it's because we in our data are the product as some of the recent leaks. And the media has shown incentives. Individuals and companies are not always aligned. And most importantly, individuals are not in control of their own digital identity and the data, which means they can economically benefit from the value they create online. Think of Twitter as a two-sided marketplace with 0% revenue share back to its creators. We're now having in the creator economy and we believe that individuals should see the economic rewards of what they do in create online. That's all we're trying to do here at unstoppable domains is provide user own take control identity to four and a half billion internet users. >>It's interesting to see change that's happening with web three. And just in cultural terms, users are expecting to be part of the creative, the personality of the company. There's this almost this disintermediation of the middleman. You know, whether it's an ad network or a gatekeeper of any kind people going direct, right? So if I'm an artist, I can go direct to my fans. >>Exactly. So web through really shifts the power away from aggregators, aggregators and marketplaces have been some of the best business models. The last 20 years onto the internet, the web three is going to dramatically change that over the next decade, paying more power back in the hands of consumers. >>What type of companies do you guys work with and partner with that we see out there, what's give us some examples of the kinds of companies you're doing business with and partnering with. >>Yeah. So let's talk about use cases. First actually is the big use case that we identified initially for NFT domain names was around cryptocurrency transfers. Anyone who's ever bought cryptocurrency and tried to transfer it between the council while it's is familiar with these awkwardly long hexadecimal strings of random numbers and letters, where if you make a single type of money is lost forever. That's a pretty scary experience that exists today in our $2 trillion asset class with 250 million users. So the first set of partners that we worked on integrating with who actually cook the wilds and exchanges. So we will allow users to do is replace all their long hexadecimal wallet addresses with a single human readable name, like John dot NFT or Maxim needs give each dot crypto to allow for simple crypto transfers. >>And how did the exchange work with you guys on that as it is? Is it a plugin? Is it co-locating code together? What's the, what's the, what's the relationship between exchanges and unstoppable domains? >>Yeah, absolutely. A great question. So exchange has actually have to do a little bit of an engineering lift to work with us, and they can do that by either using our resolution libraries or using one of our API APIs or in order to look up an unstoppable name and figure out all the wallet addresses that's associated with that name. So today we work with dozens of the world's top exchanges and wallets ranging from Oko DX to Coinbase wallet, to trust wallet, to bread wallet, and many, many others. >>I got to ask you on the wallet side, is that a requirement in terms of having specific code and are there wallets that you work well with? Explain the wallet dynamic between unstoppable domains and wallets. >>Yeah. So while it's all have this huge usability problem for their users, because every single cryptocurrency held by every single one of their users has a different hexadecimal wallet address. And once again, every user is subject to the same human fallacies and errors, where they make a single type where their money can be lost forever. So we enable these wallets to do is to make crypto transfer as simple and as less scary than the current status code by giving the users on a sub well name that they can use to attach to all the waltz addresses on the backend. So companies like trust world, for example, which has 10 million users or Coinbase wallet. When you go to the crypto transfer fields, they can just type in an unstoppable name. They'll correctly, route the currency to the right person, to the right world, without any chance for human error. >>You know, when these big waves come, I gotta ask you this question. Cause a lot of people in the mainstream are getting into it. Now reminds me of the web wave that hit the big thing was how many people are coming online. It was one of the key metrics and how many web pages are being developed was another metric, which meant that people were building out web pages. And it's hard to look back and think, wow, that was actually a KPI. So internet users and webpages were the two proxies cause then search and just came out and everything else happened. So I'm going to ask you, there are people watching, they're seeing that on commercials on TV, they're seeing it everywhere stadiums are named after crypto companies. So the bottom line is people want to know how NFT domains take the fear out of working with crypto and sending crypto. >>Yeah, absolutely. So imagine if we had to navigate the web using IP addresses rather than typing in google.com, you'd have to type in a random string of words and numbers that you'd have to memorize. That would be super painful for users. And didn't, it wouldn't have gotten to where it is today with this, you know, almost 5 billion people online, the history of computer networks. We have human readable naming systems built on top. In every single instance. It's almost crazy that we got to a $2 trillion asset class with 250 million users worldwide 13 years after this, the Toshi white paper without a human readable naming system, other than supple domains and a few of our competitors, that's a fundamental problem that we need to solve in order to go from 250 million crypto users in 2022 to 5 billion crypto users, a decade from now. >>And just to point out and not to look back and maybe make a correlation, but I will, if you look at the naming system of DNS, what it did to IP addresses, that's one major innovation that enabled the web. Then you look at what keyword navigation has done on top of DNS, what that did for the industry. And that basically birthed Googled keywords, basically ads. So that's trillions and trillions of dollars again. Now shifting to you guys, is that how you see it? Obviously it's decentralized, so what's different. Okay. I get, so if you compare, Hey, Google was successful, you know, keyword advertising industry for less than 25 years or 20 years. >>Yeah. Yeah. What's different. Now is the technology inflection points. So blockchains have evolved to a point where they enable high throughput, high transaction volume and true decentralized ownership. The NFT standard, which is only a couple of years old know, has taken off massively around trading of profile pictures like crypto punks and the boy apes yacht club where they use cases extended much more than just, you know, a cool JPEG that goes up in value two or three X year over year. There is the true use case here around ownership of identity ownership over a data set, decentralized log-in authentication and permission data sharing. One of the sad things that happened in Jeanette on the internalized decade really was that the platforms built out have now allowed developers to built on top of them and a trustless permissionless way. Developers who build applications on top of some of the early monopolies in the last decade, got the rules changed on them. APIs, cutoff, new fees instituted. That's not going to happen in web three because all permissionless custody in a user's own wallet, we cannot take the way they will continue to exist in eternity, regardless of what happens to unstoppable domains, which gives developers a lot more confidence in building new products for the web three identity standard that we're building out. >>You guys amazing is that's a whole nother generational shift. I'm always been a big fan of abstractions when innovation is needed, when they're problems that need to be solved, messes to be cleaned up. Good abstraction layer on top of new architecture is really, really phenomenal. I guess the key question for I have for you is, you know, the queue, we have all this video where where's our NFT should, how should we implement NFTs? >>There's a couple of different ways you could think about it. You could do proof of attendance, protocol NFTs, which are really interesting way for users to show that they were at particular events. So just in the same way that people collect, t-shirts some conferences, people will be collecting. And if Ts to show, there were in person attending in person cultural moments, whether they were acquired an event online or offline, you could do NFTs for employees to show that they were at your company during certain periods of the company's growth. So think of replacing the resume with a cryptographically secure resume like this on the blockchain and perpetuity. Now more than half of all the resumes contain lies, which is a pretty gnarly problem as a hiring manager, or you constantly have to sort through as ways that this can impact that side of the market as well. >>I saw some, and I think it was a use case for everything. Appreciate that. And of course we can have the most favorite, cute moments. It could be a cube host NFT at 40 apes out there. Why not have a board cube host going on and, and >>Auction for charity on open? >>All right, great stuff. Now let's get into some of the cool tech nerd stuff, which is really the login piece, which I think is fascinating. The having NFTs be a login mechanism is another great innovation. Okay. So this is cool. Cause it's like think of it as one click and FTS, if you will. What's the response been on this? Log-in with unstoppable for that product? What some of the use gates is. Can you give some examples of the momentum and traction? >>Yeah, absolutely. So we launched the product less than 90 days ago. We already have 90 committed or integrated partners live today with a login product. And this replaces login with Google login with Facebook, with a way that's user owned and user controlled. And over time, people will be capturing additional information back to their NFP domain names, such as their reputation, their history, things they've done online and be able to permission to share that with applications that they interact with in order to get any rewards, once you own all your data and you can choose to share it with companies or incentivize you to share data. For example, imagine you just bought a new house and you have 3000 square feet to furnish. You could tell that fact and prove it to a company like Wayfair. Would they be incentivized to give you discounts? We're spending 10, 20, $30,000 and you'll do all of your purchasing there rather than spread across other e-commerce retailers. For sure they would. But right now, when you go to that website, you're just another random email address. They have no idea who you are, what you've done, what your credit score is, whether you house buyer or not. But if you could permission to share that to using a log-in open software product, I mean the web would just be much, much different. >>And I think one of the things too, as these, I call them analog old school companies, old guard companies is referred to in the cube talk here, but we were still always called that old guard is the people who aren't innovating. You could think about companies having more community too, because if you have more sharing and you have this marketplace concept and you have these new dynamics of how people are working together, sharing will provide more transparency, but yet security on identity. Therefore things are going to be happening organically. That's a community dynamic. What's your view on that? And what's your reaction >>Communities are such an important part of web three and the cryptos ecosystem in general, people are very tightly knit and they all support each other. There's a huge amount of collaboration in this space because we're all trying to onboard the next billion users into the ecosystem. And we know we have some fundamental challenges and problems to solve, whether it's complex wallet addresses, whether it's the lack of portable data sharing, whether it's just simple education, right? I'm sure, you know, tens of millions of people got into crypto for the first time during the super bowl face on some of those awesome ads that ran. >>Yeah. Love the QR code. That's a direct response. I remember when the QR code has been around for a long time. I remember in the nineties, late nineties, it was a thing, a device at red QR codes that did navigation to a webpage. So I mean, QR codes are super cool, great way to get, and we all using it to, with the pandemic to ordering food. So I think QR codes are here to stay. In fact, we should have a QR code on all of our images here on the screen too. So we'll work on that, but I gotta ask you on the project side, now let's get into the devs and kind of the applications, the users that are adopting unstoppable and this new way of doing things, why are they gravitating towards this login concepts? Can you give some examples and put, give some color commentary to why are these D application distribute application guys and gals programming and with you guys? >>Yeah. They all believe that the potential for why we're trying to create a round user own the controlled identity. We're the only company in the market right now with a product that's live and working today. There's been a lot of promises made and we're the first ones to actually deliver to companies like cook finance, for example, are seeing the benefit of being able to have their users go through a simple process to check in and authenticate into the application, using your NFT domain name, rather than having to create an email address and password combination as a login, which inevitably leads to problems such as lost passwords, password resets, all those fun things that we used to deal with on a daily basis. >>Okay. So now I got to ask you the kind of partnerships you guys are looking at doing. I can only imagine the old, old school days you had a registry and you had registrars, you had a sales mechanism. I noticed you guys are selling NFT kind of like domain names on your website. Is that a kind of a current situation? Is that going to be ongoing? How do you envision your business model evolving and what kind of partnerships do you see coming along? >>Yeah, absolutely. So we're working with a lot of different companies from browsers that took changes to wallets, to individual NFT projects, to more recently even exploring partnership, partnership opportunities with fashion brands. For example, the Tyree market is moving so so fast. And what we're trying to essentially do here is create the standard naming system for web three. So a big part of that for us, we'll be working with partners like blockchain.com and with circle who's behind the DC coin on creating registries, such as dot blockchain and dot coin and making those available to tens of millions and ultimately hundreds of millions and billions of users worldwide. We want an ensemble domain name to be the first asset that every user in crypto gets, even before they buy their Bitcoin Ethereum or dovish coin. >>It makes a lot of sense obstruct the way the long hexadecimal string. We all know that we all write down putting a safe, hopefully you don't forget about it. You know, I always say, make sure you tell someone where your addresses. So in case something happens, you don't lose all that crypto. All good stuff. I got to ask the question around the ecosystem. Okay, can you share your view and vision of either your purse, yourself or the company when you have this kind of new market, you have all kinds of, and we meant the web was a good example, right? Web pages, you need web development tools. You had HTML by hand. Then you had all these tools. So you had tools and platforms and things kind of came well, grew together. How was the web three stakeholder ecosystem space evolving? What's what are some of the white spaces? What are some of the clearly defined areas that are developing? >>Yeah, I mean, we've seen an explosion in new smart contract blockchains and the past couple of years actually going live, which is really interesting because they support a huge number of different use cases, different trade-offs on each. We recently partnered and moved over a primary infrastructure to polygon, which is a leading EVM compatible smart chain, which allows us to provide free gas fees to users for maintaining and managing their domain name. So we're trying to move all obstacles around user adoption. Here. We all need to have Ethereum in your wallet. You know, it'd be an unstoppable domains customer or user. You don't have to worry about paying transaction fees. Every time you want to update the wallet, addresses associated with your domain name. We want to make this really big and accessible for everybody. And that means driving down costs as much as possible. Yeah, >>It's a whole nother wave. It's a wave that's built on the shoulders of others. It's a shift and infrastructure, new capabilities, new new applications. I think it's a, it's a great thing. You guys doing the naming system makes a lot of sense. This abstraction layer creates that ease of use. It simplifies things makes things easier. I mean, this is, was the promise of, of these abstraction layers. Final question. If I want to get involved, say we want to do a cube NFT with unstoppable. How do we work with you? How do we engage? Can you give a quick plug on what companies can do to engage with you guys on a business level? >>Yeah, absolutely. So we're looking to partner with wallets, exchanges, browsers, and companies who are in the crypto space already and realize they have a huge problem around usability with crypto transfers and wild addresses. Additionally, we're looking to partner with decentralized applications as well as web to companies who perhaps want to offer log-in with unstoppable domain functionality. In addition to, or in replacement of the login with Google and log-in with Facebook buttons that we all know and love. And we're looking to work with fashion brands and companies in the sports sector who perhaps want to claim their unstoppable names, free of charge from us. I might add in order to use that on Twitter or other marketing materials that they may have out there in the world to signal that they're not only forward looking, but that they're supportive of this huge wave that we're all riding at the most. >>May I great insight, chief revenue officer ensemble domains. Thanks for coming on the showcase, the cube and unstoppable domain share in the insights. Thanks for coming on. Okay. This cubes coverage here with the unstoppable domain showcase. I'm John furrier, your host. Thanks for watching.

>> Welcome back to Los Angeles. The cube is live. It feels so good to say that. I'm going to say that again. The cube is alive in Los Angeles. We are a coop con cloud native con 21. Lisa Martin with Dave Nicholson. We're talking to storm forge next. Cool name, right? We're going to get to the bottom of that. Please welcome Matt Provo, the founder and CEO of storm forge and Tom Ellery, the SVP of revenue storm forge, guys, welcome to the program. Thanks for having us. So storm forge, you have to say it like that. Like I feel like do you guys wear Storm trooper outfits on Halloween. >> Sometimes Storm trooper? The colors are black. You know, we hit anvils from time to time. >> I thought I, I thought they, that I saw >> Or may not be a heavy metal band that might be infringing on our name. It's all good. That's where we come from. >> I see. So you, so you started the company in 2015. Talk to me about the Genesis of the company. What were some of the gaps in the market that you saw that said we got to come in here and solve this? >> Yeah, so I was fortunate to always know. I think when you start a company, sometimes you, you know exactly the set of problems that you want to go after and potentially why you might be uniquely set up to solve it. What we knew at the beginning was we had a number of really talented data scientists. I was frustrated by the buzzwords around AI and machine learning when under the hood, this really a lot of vaporware. And so at the outset, really the, the point was build something real at the core, connect that to a set of problems that could drive value. And when we looked at really the beginnings of Kubernetes and containerization five, six years ago at its Genesis, we saw just a bunch of opportunity for machine learning, to play the right kind of role if we could build it correctly. And so at the outset it was what's going on. Why are people are people moving content workloads over to containers in the first place? And, you know, because of the flexibility and the portability around Kubernetes, we then ran into quickly its complexity. And within that complexity was really the foundation to set up the company and the solution for prob a set of problems uniquely and most beneficially solved by using machine learning. And so when we sort of brought that together and designed out some ideas, we, we did what any, any founder with a product background would do. We went and talked to a bunch of potential users and kind of tried to validate the problems themselves and, and got a really positive response. So. >> So Tom, from a business perspective, what, what attracted you to this? >> Well, initially I wasn't attracted just, I'll say that just from a startup standpoint. So I've been in the industry for 30 years, I've done six or seven pre IPO companies. I was exiting a private company. I did not want to go do another startup company, but being in the largest enterprise companies for the last 20 years, you see Kubernetes like wildfire in these places. And you knew there was huge amount of complexity and sophistication when they deployed it. So I started talking to Matt early on. He explained what they were doing and how unique the offer was around machine learning. I already knew the problems that customers had at scale with Kubernetes. So it was for me, I said, all right, I'm going to take one more run at this with Matt. I think we're, we're in a great position to differentiate ourselves. So that was really the launch pad for me, was really the technology and the market space. Those, those two things in combination are very exciting for us as a business. >> And, you know, a couple of bottles of amazing wine and a number of dinners that. >> Helps as well. >> That definitely helped twist his arm? >> Now tell us, just really kind of get into the technology. What does it do? How does it help facilitate the Kubernetes environment? >> Yeah, absolutely. So when organizations start moving workloads over to Kubernetes and get their applications up and running, there's a number of amazing organizations, whether it's through cloud providers or otherwise that that sort of solved that day one problem, those challenges. And as I was mentioning, you know, they moved because of flexibility and so developers love it and it starts to create a great experience, but there's these set of expectations. >> Where, where typically are these moving from? What you, what, what are the, what are the top three environments these are, that these are moving out of? >> Yeah. I mean, of course, non containerized environments, more generally. They could be coming from, you know, bare metal environment and it could be coming from kind of a VM driven environment. >> Okay. >> So when you look back at kind of the, the growth and Genesis and of VMs, you see a lot of parallels to what we're seeing now with, with containerization. And so as you move, it's, it's exciting. And then you get smacked in the face with the complexity, for all of the knobs that are able to be turned within a Kubernetes environment. It gives developers a lot of flexibility. These knobs, as you turn them, you have no visibility into how into the impact on the application itself. And so often organizations are become, you know, becoming more agile shipping, you know, shipping code more quickly, but then all of a sudden the, the cloud bill comes and they've, over-provisioned by 80, 90%, the, they didn't need nearly as many resources. And so what we do is we help understand the unique goals and requirements for each of the applications that are running in Kubernetes. And we have machine learning capabilities that can predict very accurately what organizations will need from a resource standpoint, in order to meet their goals, not just from a cost standpoint, but also from a performance standpoint. And so we allow organizations to typically save usually between 40 and 60% off their cloud bill and usually increased performance between 30 and 50%. Historically developers had to choose between cost and performance and their worldview on the application environment was very limited to a small set of what we would call parameters or metrics that they could choose from. And machine learning allows that world to just be blown open and not many humans are, are sophisticated in the way we think about multidimensional math to be able to make those kinds of predictions. You're talking about billions and billions of combinations, not just in a static environment, but an ongoing basis. So our technology sits in the middle of all that chaos and, and allows it to allows organizations just to re reap a whole lot of benefits that they otherwise may not ever find. >> Those numbers that you mentioned were, were big from a cost savings perspective than a performance increased perspective, which is so critical these days is in the last 18 months, we've seen so much change. We've seen massive pivots from companies in every industry to survive first of all, and then to be able to thrive and be able to iterate quickly enough to develop new products and services and get them to market to be competitive. >> Yeah. >> Yeah. Sorry. I mean, the thing that's interesting, there was an article by Andreessen Horowitz. I don't know if you've taken to the cloud paradox. So we actually, if you start looking at that great example would be some of these cloud companies that are growing like astronomical rates, snowflakes, like phenomenal what they're doing, but go look at their cogs and what it's doing. Also, it's growing almost proportionately as the revenues growing. So you need to be able to solve that problem in a way that is sophisticated enough with machine learning algorithms, that people don't have to be in the loop to do it. And that the math can prove out the solution as you go out and scale your environments. And a lot of companies now are all transitioning over SAS based platforms, and they're going to start running into these problems that they go as they go to scale. And those are the areas that we're really focused and concentrating on as an organization. >> As the leader of sales, talk to me about the voice of the customer. What are some- you've been there six months or so we heard, we heard about the wine and the dinners is obvious. >> We haven't done a lot of that over the last 18 months. >> You'll have to make for lost time then >> As soon as he closes more business. >> Oh, oh there we go, we got that on camera! >> There's, there's been three, a market spaces that we've had some really good success in that. So we talked about a SAS marketplace. So there's a company that does Drupal and Matt knows very well up in Boston, Aquia. And they have every customer is a unique snowflake customer. So they need to optimize each of their customers in order to ensure the cost as well as performance for that customer on their site works appropriately. So that's one example of a SAS based company that where we can go in and help them optimize without humans doing the optimization and the math and the machine learning from storm forge doing that. So that's an area, the other area that we've seen some really good traction Cantonese with GSI. So part of our go to market model is with GSI. So if you think about what a GSI does, a lot of times customers are struggling either initially deploying Kubernetes or putting it in for 12, 18 months and realizing we're starting to scale, we got all kinds of performance issues. How do I solve it? A lot of these people go to the Accentures, the cognizance and other ones, and start flying their ninjas into kind of solve the problem. So we're getting a lot of traction with them because they're using our tool as a way to help solve the customer's problems. And they're in the largest enterprise customers as possible. >> So if I'm hearing what you're saying correctly, you're saying that when I deploy server less applications, I may in fact, get a bill for servers that are being used? Is it, is that what you're telling us? >> They're there in fact may be a bill for what was coined as server less. That is very difficult to understand, by the way, >> That's crazy talk, Matt. >> And connect back. >> Yeah. But absolutely we deal with that all the time. It's a, it's a painful process from time to time. >> Have you, have you, have you seen the statistics that's going on with how people, I mean, there was huge inertia from every CIO that you had have a cloud strategy in place. Everyone ran out and had a cloud strategy in place. And then they started deploying on Kubernetes. Now they're realizing, oh wow, we can run it, but it's costing us more than it ever costs us on prem and the operational complexity associated with that. So there's not enough people in the industry to help solve that problem, especially at the grass roots, that's where you need sophisticated solutions like storm forge and machine learning to help solve this at scale problem in a way that humans could never solve. >> And I would, I would just add to that, that the, the same humans managing the Kubernetes application environments today are likely the same humans that we're managing it in a, in a BM world. So there's a huge skills gap. I love what Castin announced at KU KU con this year around their learning environment where it's free. Come learn Kubernetes and this, and we need more of that. There's an enormous skills gap and, and the problems are complex enough in and of themselves. But when we have, when you add that to the skills gap, it it's, it presents a lot of challenges for organizations. >> What are some the ways in which you think that gap can start to be made smaller. >> Yeah. I mean, I think as more workloads get moved over, over, you know, over time, you see, you see more and more people becoming comfortable in an environment where scale is a part of what they have to manage and take care of. I love what the Linux foundation and the CNCF are doing around Kubernetes certifications, you know, more and more training. I think you're going to see training, you know, availability for more and more developers and practitioners be adopted more widely. You know, and I think that, you know, as the tool chain itself hardens within a CCD world in a containerized world, as that hardens, you're going to, you're going to start seeing more and more individuals who are comfortable across all these different tools. If you look at the CNCF landscape, I mean, today compared to four or five years ago, it's growing like crazy. And so, but, but there's also consolidation taking place within the tools. And people have an opportunity to, to learn and gain expertise within us. Which is very marketable by the way, >> Absolutely >> My employees often show me their LinkedIn profiles and remind me of how , how much they're getting recruited, but they've been loyal. So it's been a fantastic. >> Are there are so many parallels when you look at a VM in virtualization and what's happening with covers, obviously all the abstractions and stuff, but there was this whole concept of VM sprawl, you know, maybe 10 years in, if you think about the Kubernetes environment, that is exponentially bigger problem because of how many they're spitting up versus how, how many you spun up in VM. So those things ultimately need to be solved. It's not just going to be solved with people. It needs to be solved with sophisticated software. That's the only way you're going to solve a problem at scale like that. No matter how many people you have in the industry, it's just never going to solve the problem. >> So when you're in customer conversations, Tom, what are you say are like the top three differentiators that really set storm forage apart? >> Well, so the first one is we're very focused on Kubernetes only. So that's all we do is just Kubernetes environment. So we understand not just the applications that run in Kubernetes, but we understand the underlying architectures and techniques, which we think is really important. From a solution standpoint, >> So you're specialists? >> We are absolutely specialists. The other areas obviously are machine learning and the sophistication of our machine learning. And Matt said this really well, early on, I mean, the buzzwords are all out there. You can read them all up, all over the place for the last five to seven year AI and ML. And a lot of them are very hollow, but our whole foundation was based on machine learning and PhDs from Harvard. That's where we came out of from a technology background. So we were solving more, we weren't just solving the Kubernetes problems. We were solving machine learning problems. And so that's another really big area of differential for us. And I think the ability to actually scale and not just deal with small problems, but very large problems, because our focus is the fortune 2000 companies. And most of them have been deploying like financial services and stuff, Kubernetes for three, four or five years. And so they have had scale challenges that they're trying to solve. >> Yeah. It's Lisa and I talk about this concept of machine learning and looking under the covers and trying to find out is the machine really learning? Is it really learning or is it people are telling the machine, you need to do this. If you see that Where's the machine actually making those correlations and doing something intelligently. So can you give us an example of something that is actually happening that's intelligent? >> Well, so the, the, if this, then that problem is actually a huge source of my original frustration for starting the company, because you, you, you tag AI as a buzzword onto a lot of stuff. And we see that growing like crazy. And so I literally at the beginning said, if we can't actually build something real, that solves problems, like we're going to hang it up. And, you know, as Tom said, we came out of Harvard and, you know, there was a challenge initially of, are we just going to build like a really amazing algorithm? That's so heavy, it can never be productized or commercialized and it really should have just stayed in academia. And, you know, I the I, I will say a couple of things. One is I do not believe that that black box AI is a thing. We believe in what we would call human, augmented AI. So we want to empower practitioners and developers into the process instead of automate them out. We just want to give them the information and we want to save time for them and make their lives easier. But there's a kill switch on the technology. They can intervene at any point in time. They can direct the technology as they see fit. And what's really, really interesting is because their worldview of this application environment gets opened up by all the predictions and all of the learning that actually is taking place and, you know, give it because that worldview is open, they then get into a kind of a tinkering or experimental mindset with the technology. And they start thinking about all these other scenarios that they never were able to explore previously with the application. And, and so the machine learning itself is on an ongoing basis. Understanding changes in traffic, understanding and changes, changes in workloads for the application or demand. If you thought about like surge pricing for Uber, you know, because of a, a big game that took place. And you know, that, that change in peaks and valleys in demand, our, our technology not only understands those reactively, but it starts to build models and predict proactively in advance of the events that are going to take place on, on what ne- what kind of resources need to be allocated. And why that's the other piece around it is often solutions are giving you a little bit of a what, but they certainly are not giving you any explanation of the why. So the holy grail really like in our world is kind of truly explainable AI, which we're not there yet. Nobody's there yet. But human augmented AI with, with actual intelligence that's taking place that also is relevant to business outcomes is, is pretty exciting. So that's why where try to operate. >> Very exciting guys. Thanks for joining us, talking to us about storm forage, to feel like we need some store in forge. T-shirts what do you think? >> (unintelligible) >> See, I'm not even asking for the bottle of wine. I liked that idea. I thank Matt and Tom, thank you so much for joining us exciting company. Congratulations on your success. And we look forward to seeing what great things are to come from storm forage. >> Thanks so much for the time. >> Our pleasure. For Dave Nicholson. I'm Lisa Martin. We are alive in Los Angeles, the cube covering Kube con and cloud native con 21 stick around. Dave and I will be right back with our next guest.

>>Mhm >>Welcome to this preview of couch based connect online 2021. My name is Dave Volonte with the cube and we're here with couch based ceo matt cain matt. Good to see you again. Welcome >>Thanks Dave. Great to be here. >>We are super excited at the Cube to partner with Couch Base this year to share the news, the analysis from connect online 21. What can attendees expect from the event this year? What's the theme? What can people really take away? >>They were fired up, you know, there is no different. Our theme this year is modernized now and it's something that we're hearing from our customers across the world is they think about leveraging technology to get closer to their customers and at the top of every one of their strategic agendas is figuring out how to build the best applications to service our needs as our personal lives and in our business lives and we're really focused on talking about the technology that we uniquely architected to enable this that stands aspects of relational database technology and new capabilities, leveraging those people technology, putting that into an integrated platform and really supporting customers. And we love talking about what we built Dave but we love even more when our customers share what they've been doing with our platform, customers like Pepsi and Amadeus and American greetings, you're going to hear them and their development meant teams talk about how they have leverage couch base to solve some of the most fundamental application challenges and how that's really opening up new businesses for them in their end markets. >>Let's talk a little bit more mad about that, the modernized now. I mean the trends that we're seeing in in the market place, they were in motion before the pandemic. But digital digitization and modernization has really become a high priority. Talk about why in your view now is the time to modernize and what's the mandate for enterprises? >>Well look, I think digital transformation has been a focus point for some time and I think that's going to continue as we go forward. But I think as enterprise think about the challenges they have in front of them to successfully transform digitally, they may be thinking about the problem a little bit differently in light of current circumstances. Uh and what we're seeing is enterprises have the desire to innovate, but they may not always have the resources or the capabilities to do it at the place they want to. And so how do they approach this challenge first and foremost, they need a platform that can help bridge the legacy world and the new one that they can safely evolve applications and modernize, you know, workloads that were dependent on relational databases while putting them into new platforms. At the same time, they need people to do this work. So if I'm an democrats, almost an insatiable demand to build new applications, but I don't necessarily have all the people and teams and capability and skill sets needed to support that. So as a technology company, we've got to think through how do we help provide the tools that will open up more people's ability to contribute to that digital transformation leveraging things like sequel is the fact of language in the database technology allowing enterprises to repurpose workforces free up investment dollars, free up people to really focus on the next generation of properties that are going to change their businesses. And so I think the current economic conditions haven't changed the fact that digital transformation is the top of the priority list. If anything, that reinforced the urge with which enterprises need to go after this, but also the way that they need to do it. But I can't just continue to throw niche technologies of problems. I've really got to think about what kind of platforms tonight and then in the future and a couch base as the modern database for enterprise applications. This is what we're going to spend time talking about and helping customers understand the value that we can unlock for them as they invest in the couch based platform. >>Super relevant now since we last talked matt, he made some big moves, not the least of which is you're now a public company. We've been following that. But what's changed what's new product wise and maybe one of the fundamentals of the market that that your your customers and your culture or driving. >>Yeah, well let's talk about first, what's not changed? We continue to be long term oriented couch basically believe we're in truly what we call a generational market transition and the challenges in front of enterprises unparalleled. So too are the opportunities for enterprises that get this right? They will innovate and thriving in their respective markets. And so as a company, we pride ourselves in being maniacally focused at solving unmet, underserved needs in the world of databases. And really thinking through what technological challenges do we need to innovate on store, customers can take that technology and successful. That's not, that hasn't changed that, that won't change. We continue to be insanely customer focused and really studying those problems and making sure that we're adding value in everything we do from a product perspective services, how we show up to help our customers and that's really important. Um certainly as you said, it's a big milestone for the company step in the public market. We're very proud of what we've accomplished over our first decade or so of existence. But we truly believe that we've been built for this moment and that market transition that ever have referred to um that that movement into the public markets allows us to talk more broadly about all that we've built and how customers are taking advantage of our technology case in point is probably the biggest release in company history couch based server seven oh, so while we were busy taking a step into the public market, we also continue to innovate as I said and are very pleased to be a market with couch base 70 which fundamentally bridges for enterprise customers to move from relational to modern databases and do that in a single integrated platform. And we're going to talk about that connect in more detail and how application developers can re platform applications in a much more seamless way and then start to innovate in a way, you know, that they never have. So a ton of work underway. We've got some really exciting announcements which I think we'll talk about here in the second at least plant the seeds on those. But we're going to be really focused on the innovation that we've delivered up to this point because it's so fundamentally valuable to the enterprise customers we serve and couldn't be more excited to share the benefits of that. That's actually what we're going to help customers do as we go forward. >>Well, we see a lot of companies and as as we evaluated, you've hit critical mass in terms of how we think about it successful I. P. O. Your surpassed $100 million in revenue 500 plus customers talk about the opportunity for couch based to continue to grow. What's in store. What's the focus? >>Well, as I mentioned, we're going to we're going to continue to innovate and so you know, ahead of the conference. We're going to talk about some really important upcoming innovations and I'm not gonna steal too much of the thunder from the show, people are really pumped and putting that material together? We we focus a lot on ensuring that we have the best database in the market, particularly for enterprise applications. Uh and really thinking through the architecture that will support applications today and going forward and we've been really successful with that date. As you mentioned, we have not only a lot of enterprise customers and we're really proud of those customers would support what were even more proud of though. Dave is the mission critical nature the enterprise nature of those applications. These companies are truly running their businesses on applications powered by pouches as we go forward. We have almost unlimited potential for new opportunity in acquiring new customers. Um and we're really focused on that and evangelizing what we've done successfully with our existing base to new customers and their respective markets and we continue to acquire those and you know will successfully expand because of the power of our platform. We've done a lot to invest in our partner ecosystem. So you know we have many I. S. V. S. That are taking our solutions to market. We have G. S. I. S. That are building practices around couch base because our database provides capabilities that others don't and they can run their businesses and help their end customers transform with the power of couch face. But Dave what we like to talk about a couch bases, we have opportunities to really help customers once we get in. We think about many factors of growth. So when we support a customer with an application, what often happens is that application growth because the enterprises successful and they put more users in or they deployed a new new geography at the same time, they realize, wow, if I can support highly interactive, highly scalable distributed applications in this particular area, I have hundreds, if not thousands of those in my enterprise, so I can use the platform for that. Then one of the things that we focus on is giving more and more capabilities to developers to enhance the performance and the personalization of their applications I mentioned, we support the sequel query language, we've got operational analytics, we've embedded full text search, we have things like eventing all of these are elegantly architected features that allow developers to build great applications and the more that were successful in helping developers do that, you know, the more, the more the company is going to grow. Um and then on top of all that we couldn't be more excited about about cloud and couch based cloud from the very outset has been a cloud, native platform, are enterprises are running this and multi and hybrid cloud deployments, but what we really have an opportunity to do is help them and run more of the service of, of that cloud solution and we're gonna be talking a lot more uh you know, come come the show about some specifics around that offering and could be more excited about augmenting or portfolio with some new capabilities there >>lot to learn at this event. Tons of meat on the bone. Okay. Matt, we're gonna leave it right there. Couch based, connect online. It's a two day event, october 20th to the 21st. More than 80 sessions geared for architects, developers, business users, open source advocates. Now the easiest way to register, all you gotta do is go to couch base dot com. You'll see the link there. There's a hackathon with prizes. So start developing and win. And while you're there, check out the free downloads with a number of different deployment options. Couch based, connect 2021 modernized. Now we'll see you there. >>Mhm mm.

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante recent earnings reports from key enterprise software and infrastructure players underscore that tech spending remains robust in the post isolation economy especially for those companies that have figured out a cloud strategy now despite covert variant uncertainties and component shortages and hardware most leading tech names outperformed expectations this past week that said investors were not in the mood to reward all names and any variability in product mix or earnings outlook or other nuances were met with a tepid response from the street hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll provide you with commentary and data points on key tech companies that announced this past week including snowflake salesforce workday splunk elastic palo alto networks vmware dell pure storage hp inc and netapp let's start by rolling back a week or so and look at how stocks that are priced to perfection get impacted by any negative news back on august 20th we saw this headline hit snowflake stock falls as analyst says signings growth has slowed the analyst report was put out by a boutique firm cleveland research the stock took a double-digit hit as you can see here i immediately got several texts from investors who know i follow the company asking me what i thought now as a disclaimer i don't give stock picking advice please do your own research but between the cube wikibon and etr we do see a lot of data and i'm happy to share that which i did with this tweet it said lots of talk ahead of snowflake's earnings some analysts have said their data suggests a slowdown etr data looks pretty encouraging and i tagged merv adrian he's a sharp analyst over at gartner who follows data and database he responded i don't speculate about revenues but there's no discernible shift in our client conversations though interest still seems high okay cool but let's let's dig into the etr data a bit and see why we remained positive this is a larger and more detailed version of the chart in the tweet it's a candlestick that shows a time series of the spending data on snowflake using etr's net score methodology the stacked bars represent the percent of customers in the survey that are newly adding the snowflake platform the forest green indicates the number of customers reporting that their spending is increasing by six percent or more the gray is flat spend that's plus or minus five percent the pinkish stack that's decreasing spend by six percent or more and the bright red is where chucking the platform we're leaving now you subtract the reds from the greens and that yields a net score which for snowflake last survey was a very elevated 81.3 percent we've highlighted the spending velocity line that's net score at the top put a picture of that blue line for snowflake in your mind because we're going to come back to it the yellow line down below is market share which is a measure of the pervasiveness in the survey i.e mention share if you will so looking at this chart one might conclude that the lime green i.e new account acquisition is compressing however in further analyzing the data back in january 2019 snowflake's presence in the survey was much lower only 35 accounts in subsequent quarters that number has jumped to over between 120 and 140 snowflake accounts so big much bigger n so while the percentage of respondents may be shrinking the absolute number of new accounts is growing on the snowflake earnings call snowflake said that new customers increased this past quarter to 458 up from 397 in the same period last year what's also telling is the forest green on its very first earnings call as a public company snowflake cfo mike scarpelli said very clearly the company's revenue growth in the near term will come from existing customers and the forest green i.e existing customers spending more is expanding in the etr survey so very strong confirmation of that trend and note the red is virtually non-existent for snowflake so it's no surprise that snowflake handily beat its earnings on the 25th of august which prompted a flurry of texts to me saying you were right thanks don't thank me do your own research we're just one data source okay so here's a snapshot of some of the major players that announced earnings this past week this chart is our popular xy view with net score or spending momentum on the vertical axis and market share or pervasiveness in the survey in the horizontal plane we talked about snowflake already but i'll emphasize they've held that roughly eighty percent net score for ten plus quarterly surveys now and they've continued to move steadily to the right on the horizontal axis let's make some comments on these other names and then dig in a bit more salesforce of course they're the big player amongst these names that we're showing and as we've said in previous breaking analysis segments they have become the next great software company showing 20 plus growth for five consecutive quarters which is quite impressive splunk as we've reported has struggled in the survey but you can see splunk has a great presence in the data set they have an awesome customer base and the acquisition of signal fx plotted on the left with an elevated next net score represents a really good opportunity to enter new markets like observability and pull signalfx to the right to the rest of splunk's customers and that can help accelerate splunk's move toward a subscription model then there's workday we're plotting the company's core hcm business as well as its emerging financial software suite the latter represents workday's tam expansion opportunity and the company appears to be back on track to show sustained growth now let's dig a little deeper into these names and we'll start with salesforce here's the etr spending profile for salesforce salesforce as we showed earlier has a huge and growing presence in the market and a consistently elevated net score in the etr data and while the chart shows much more green than red and a strong uptick in spending momentum from last october survey this doesn't really tell the whole story salesforce's stock price rocketed out of the march 2020 crash and ran up to a peak last august and is on its way back salesforce has made a number of strategic acquisitions including tableau slack mulesoft and several other billion dollar plus buys as well as a number of smaller acquisitions this past quarter saw 23 revenue growth relative to last year with 20 percent plus operating margins that's huge salesforce's acquisition strategy is beginning to demonstrate the company's promised operating leverage and slack in our view will only add to that benefit including continuous improvement and free cash flow sales force revenue will blow through 25 billion dollars this fiscal year it's a company with a 250 billion dollar market cap and appears to be one a name that has meaningful upside opportunity okay let's take a quick look at splunk we're finally seeing an uptick in splunk's spending momentum with within the etr data set eric bradley and i have discussed this in previous breaking analysis segments the key point as we've reported is we see splunk as a company that has been in transition from a traditional license to an arr subscription model and finally the company is showing clarity that there's light at the end of that tunnel investors don't like companies in transition and like salesforce splunk's stock price ran up to an all-time high last august but then came down hard and never fully recovered but it has come off its may lows and there were some real positives this past quarter cloud annual recurring revenue for splunk this past quarter grew 72 percent and its bookings grew 20 29 year on year the company was conservative in its guidance and there still seems to be some uncertainty around cash flow but more clear guidance by splunk on the top line is a welcome sign and now another name that we've been following that announced earnings this week is elastic and as you can see by the etr data that company has an elevated net score with very little red in the bars now note that blue line while it's slowly decelerating it remains very strong and elevated remember the comment earlier i made about freezing that snowflake blue line in your head the reason we said that is because for snowflake to hold its roughly 80 net score position firmly over the past 10 plus quarters is quite astounding and for the most part it's unprecedented in the etr data set in recent memory back to elastic the company grew its top line by 45 which is a healthy beat and that helped operating margins come in above expectations elastic has become the open source poster child for observability but customers often cite challenges related to complexity and scaling with the need often to seek professional services help which sometimes impacts adoption and cost obviously but overall very strong report especially in its cloud business which grew 89 relative to last year all right let's pivot to infrastructure we're going to do that with palo alto networks and then look at a broader more traditional hardware and software players in february of 2020 we reported the valuation of divergence between palo alto networks and fortinet and we cited the challenges that palo alto was having around its shift to cloud that was a clear headwind at the time especially with regard to some of its go to market challenges at the same time we said that we were confident that palo alto would work through these issues and the csos from the etr panels along with other anecdotal information from the cube community suggested that the company would power through these problems well it has palo alto has a huge presence in the market and consistently elevated net scores as you can see here palo alto stock is trading near all-time highs and it reacted very well to its uh to the earnings report this past week where revenue grew nicely at 20 28 year on year the company has consistently impressed despite some hiccups of the past and appears to be well positioned for the emerging hybrid work economy okay now let's take a look at some of the key infrastructure players that announced this past week this chart shows our popular xy view with netscore spending momentum on the vertical axis and market share and or pervasiveness on the horizontal axis we'll start with vmware it has the biggest presence in the market amongst these names vmware's revenue grew nine percent in the quarter which was in line with estimates the company had a solid quarter but only marginally beat expectations and the stock got hit hard it was down 8 percent midday on friday vmware cited stronger than expected perpetual license sales and somewhat softer sas subscription revenue now it's not surprising that we're going to see some lumpiness in those two lines as the company transitions to a subscription model but investors clearly want to see more growth in sas and subscriptions than they do in the traditional perpetual license model vmware cloud on aws grew 80 and that's confirmed in the data here compute was also strong one concern in the etr data is the vmware cloud which is the the core the vm vmr cloud foundation vcf which you can see here is well off its january net score highs now it's possible the etr is picking up some of the conservative clients that don't want to move to an ar or subscription model it's unclear but we'll continue to watch that trend overall vmware's business model is solid in our view and very very strong now let's talk about dell next dell in our view had a great quarter it grew top-line revenues by 15 year-on-year its client business grew 27 percent and you can see the elevated dell laptop net net scores in this chart the isg business was up three percent that comprises service and networking which was up six percent and storage which was off one percent the storage business contin continues to struggle but management reported that its mid-range storage revenue was up 17 now the challenge here is that high-end storage it's cyclical it's exposed sometimes you know somewhat to mainframe cycles but but but but the other thing is that a lot of the mid-range capability is eating away at the high end not the least which by the way is is pure storage competing at the higher end but also dell's own mid-range business so that continues to be a drag on revenue the the size of the traditional high-end business that that v-max power max business still is is is quite large and the the new is not growing fast enough to offset the decline in in the old but i mean i saw these numbers from dell i was surprised to see the stock down nearly five percent at midday on friday and i think what's happening is a couple things one is that hpq hp inc which we show here at a lower net score than dell's laptop business cited supply chain issues and component shortages now dell cited the same but maybe it's off on sympathy it's clear to us that dell is doing a much better job than hp with regard to managing component shortages the frustrating thing for these companies is it might be a 50 part holding up a server or in dell's case or a laptop in dell and hpq's case but demand is good which is a positive but the biggest factor in dell stock price we think is it's getting dragged down with vmware in a way if you think about it with vmware's value comprising so much of dell's market cap being down only four percent while vmware is down eight percent implies that the core dell business is viewed positively by the street but i thought with the vmware spin coming later this year investors might gravitate more aggressively toward dell but that didn't happen maybe over time now you see netapp on the chart netapp beat on top line revenue and earnings this past quarter however the company has not performed well in the etr surveys for several quarters and has a negative net score this is due when you tear apart the the math this is due to a low number of new adoptions and a fat middle very big fat middle of flat spending and a pretty high churn in the data set now the company claims they've picked up 1500 new customers in its cloud business so maybe maybe the etr survey is not picking that up or perhaps it's existing customers that are moving to netapp's cloud service that they're counting as new that's unclear but netapp claims that its public cloud business grew 155 in the quarter regardless the street likes netapp's story the stock has been acting very well this year out passing outpacing the s p 500. now you also see pure on the chart with a nicely elevated net score the company beat top and bottom lines this quarter and its ceo charlie giancarlo promised roughly 20 percent revenue growth going forward the street sure liked that that story and the stock shot up nearly 20 percent on that news and you can see here a little drill down the etr spending data trends in the right direction for pure to support this momentum pure's messaging is all around a modern data platform and it's clear from customer conversations that its storage products are easier to use than traditional storage offerings and it has a leg up on the as a service trend which we've been reporting on which pure has been pursuing for a number of years but it's still a much smaller player a couple billion dollars than the dells and the netapps of the storage world but if it can continue on a strong growth trajectory it will of course become a larger custom company the question will be how to continue to expand its total available market now the obvious path has been share gains which over the years it has accomplished and has served them well but that won't be as easy as it was last decade when pure caught emc and netapp flat-footed without strong flash array strategies pure's port works acquisition is something to watch as well as it tries to transition the market to a true cloud-like program programmable infrastructure model infrastructure as code and we'll leave you with this thought about the infrastructure space generally in storage specifically while cloud storage has exploded over the past several years on-prem storage has been extremely soft this in our view has been due to the double whammy that we've reported the combination of cloud stealing share from on-prem and the big flash injection in other words the latter suppressed the need to buy more spinning spindles and controllers for better performance and it hurt demand you don't need to do that when you have all this flash headroom but as we predicted last year we believe that there's pent up demand as people go back to work and headquarters need refresh there's only so much blood that it managers can squeeze from the stone moving storage around optimizing servers and and improving things like utilization while at the same time maintaining adequate performance and doing so within some kind of reasonable window of a day storage is no longer monolithic there are emerging use cases especially ones that are data intensive different storage types are emerging as satya nadella said recently we've reached peak centralization and as such that will create tailwinds for storage offerings that can accommodate cloud and on-prem because it pros understand that moving data is expensive and risky it's best to keep data where it belongs for reasons of performance and of course compliance so it looks like there's a decent chance that the long storage winter is over and the market could return to solid growth even the face of a continued cloud explosion now to circle back quickly to the enterprise software business there seems to be no end in sight to the shift to cloud-based offerings both sas and snowflake-like consumption models of which we're big believers digital transformation initiatives are real they're meaningful and software spending we believe is going to be robust and power these transformations for quite some time okay that's it for today remember these episodes are all available as podcasts all you got to do is search breaking analysis podcast we publish each week on wikibon.com and siliconangle.com you can reach me at divalante on twitter or my linkedin posts or email me at david.vellante siliconangle.com please do check check out the etr website at etr.plus and see their new data packages and offerings for all the survey data this is dave vellante for the cube insights powered by etr thanks for watching everybody be well and we'll see you next time [Music] you

>> Hi, I'm Natalie Ehrlich and welcome to the AWS startup showcase presented by The Cube. We have an amazing lineup of great guests who will share their insights on the latest innovations and solutions and leveraging cloud scale data in AI, security and life sciences. And now we're joined by the co-founders and co-CEOs of The Cube, Dave Vellante and John Furrier. Thank you gentlemen for joining me. >> Hey Natalie. >> Hey Natalie. >> How are you doing. Hey John. >> Well, I'd love to get your insights here, let's kick it off and what are you looking forward to. >> Dave, I think one of the things that we've been doing on the cube for 11 years is looking at the signal in the marketplace. I wanted to focus on this because AI is cutting across all industries. So we're seeing that with cybersecurity and life sciences, it's the first time we've had a life sciences track in the showcase, which is amazing because it shows that growth of the cloud scale. So I'm super excited by that. And I think that's going to showcase some new business models and of course the keynotes Ali Ghodsi, who's the CEO Data bricks pushing a billion dollars in revenue, clear validation that startups can go from zero to a billion dollars in revenues. So that should be really interesting. And of course the top venture capitalists coming in to talk about what the enterprise dynamics are all about. And what about you, Dave? >> You know, I thought it was an interesting mix and choice of startups. When you think about, you know, AI security and healthcare, and I've been thinking about that. Healthcare is the perfect industry, it is ripe for disruption. If you think about healthcare, you know, we all complain how expensive it is not transparent. There's a lot of discussion about, you know, can everybody have equal access that certainly with COVID the staff is burned out. There's a real divergence and diversity of the quality of healthcare and you know, it all results in patients not being happy, and I mean, if you had to do an NPS score on the patients and healthcare will be pretty low, John, you know. So when I think about, you know, AI and security in the context of healthcare in cloud, I ask questions like when are machines going to be able to better meet or make better diagnoses than doctors? And that's starting. I mean, it's really in assistance putting into play today. But I think when you think about cheaper and more accurate image analysis, when you think about the overall patient experience and trust and personalized medicine, self-service, you know, remote medicine that we've seen during the COVID pandemic, disease tracking, language translation, I mean, there are so many things where the cloud and data, and then it can help. And then at the end of it, it's all about, okay, how do I authenticate? How do I deal with privacy and personal information and tamper resistance? And that's where the security play comes in. So it's a very interesting mix of startups. I think that I'm really looking forward to hearing from... >> You know Natalie one of the things we talked about, some of these companies, Dave, we've talked a lot of these companies and to me the business model innovations that are coming out of two factors, the pandemic is kind of coming to an end so that accelerated and really showed who had the right stuff in my opinion. So you were either on the wrong side or right side of history when it comes to the pandemic and as we look back, as we come out of it with clear growth in certain companies and certain companies that adopted let's say cloud. And the other one is cloud scale. So the focus of these startup showcases is really to focus on how startups can align with the enterprise buyers and create the new kind of refactoring business models to go from, you know, a re-pivot or refactoring to more value. And the other thing that's interesting is that the business model isn't just for the good guys. If you look at say ransomware, for instance, the business model of hackers is gone completely amazing too. They're kicking it but in terms of revenue, they have their own they're well-funded machines on how to extort cash from companies. So there's a lot of security issues around the business model as well. So to me, the business model innovation with cloud-scale tech, with the pandemic forcing function, you've seen a lot of new kinds of decision-making in enterprises. You seeing how enterprise buyers are changing their decision criteria, and frankly their existing suppliers. So if you're an old guard supplier, you're going to be potentially out because if you didn't deliver during the pandemic, this is the issue that everyone's talking about. And it's kind of not publicized in the press very much, but this is actually happening. >> Well thank you both very much for joining me to kick off our AWS startup showcase. Now we're going to go to our very special guest Ali Ghodsi and John Furrier will seat with him for a fireside chat and Dave and I will see you on the other side. >> Okay, Ali great to see you. Thanks for coming on our AWS startup showcase, our second edition, second batch, season two, whatever we want to call it it's our second version of this new series where we feature, you know, the hottest startups coming out of the AWS ecosystem. And you're one of them, I've been there, but you're not a startup anymore, you're here pushing serious success on the revenue side and company. Congratulations and great to see you. >> Likewise. Thank you so much, good to see you again. >> You know I remember the first time we chatted on The Cube, you weren't really doing much software revenue, you were really talking about the new revolution in data. And you were all in on cloud. And I will say that from day one, you were always adamant that it was cloud cloud scale before anyone was really talking about it. And at that time it was on premises with Hadoop and those kinds of things. You saw that early. I remember that conversation, boy, that bet paid out great. So congratulations. >> Thank you so much. >> So I've got to ask you to jump right in. Enterprises are making decisions differently now and you are an example of that company that has gone from literally zero software sales to pushing a billion dollars as it's being reported. Certainly the success of Data bricks has been written about, but what's not written about is the success of how you guys align with the changing criteria for the enterprise customer. Take us through that and these companies here are aligning the same thing and enterprises want to change. They want to be in the right side of history. What's the success formula? >> Yeah. I mean, basically what we always did was look a few years out, the how can we help these enterprises, future proof, what they're trying to achieve, right? They have, you know, 30 years of legacy software and, you know baggage, and they have compliance and regulations, how do we help them move to the future? So we try to identify those kinds of secular trends that we think are going to maybe you see them a little bit right now, cloud was one of them, but it gets more and more and more. So we identified those and there were sort of three or four of those that we kind of latched onto. And then every year the passes, we're a little bit more right. Cause it's a secular trend in the market. And then eventually, it becomes a force that you can't kind of fight anymore. >> Yeah. And I just want to put a plug for your clubhouse talks with Andreessen Horowitz. You're always on clubhouse talking about, you know, I won't say the killer instinct, but being a CEO in a time where there's so much change going on, you're constantly under pressure. It's a lonely job at the top, I know that, but you've made some good calls. What was some of the key moments that you can point to, where you were like, okay, the wave is coming in now, we'd better get on it. What were some of those key decisions? Cause a lot of these startups want to be in your position, and a lot of buyers want to take advantage of the technology that's coming. They got to figure it out. What was some of those key inflection points for you? >> So if you're just listening to what everybody's saying, you're going to miss those trends. So then you're just going with the stream. So, Juan you mentioned that cloud. Cloud was a thing at the time, we thought it's going to be the thing that takes over everything. Today it's actually multi-cloud. So multi-cloud is a thing, it's more and more people are thinking, wow, I'm paying a lot's to the cloud vendors, do I want to buy more from them or do I want to have some optionality? So that's one. Two, open. They're worried about lock-in, you know, lock-in has happened for many, many decades. So they want open architectures, open source, open standards. So that's the second one that we bet on. The third one, which you know, initially wasn't sort of super obvious was AI and machine learning. Now it's super obvious, everybody's talking about it. But when we started, it was kind of called artificial intelligence referred to robotics, and machine learning wasn't a term that people really knew about. Today, it's sort of, everybody's doing machine learning and AI. So betting on those future trends, those secular trends as we call them super critical. >> And one of the things that I want to get your thoughts on is this idea of re-platforming versus refactoring. You see a lot being talked about in some of these, what does that even mean? It's people trying to figure that out. Re-platforming I get the cloud scale. But as you look at the cloud benefits, what do you say to customers out there and enterprises that are trying to use the benefits of the cloud? Say data for instance, in the middle of how could they be thinking about refactoring? And how can they make a better selection on suppliers? I mean, how do you know it used to be RFP, you deliver these speeds and feeds and you get selected. Now I think there's a little bit different science and methodology behind it. What's your thoughts on this refactoring as a buyer? What do I got to do? >> Well, I mean let's start with you said RFP and so on. Times have changed. Back in the day, you had to kind of sign up for something and then much later you're going to get it. So then you have to go through this arduous process. In the cloud, would pay us to go model elasticity and so on. You can kind of try your way to it. You can try before you buy. And you can use more and more. You can gradually, you don't need to go in all in and you know, say we commit to 50,000,000 and six months later to find out that wow, this stuff has got shelf where it doesn't work. So that's one thing that has changed it's beneficial. But the second thing is, don't just mimic what you had on prem in the cloud. So that's what this refactoring is about. If you had, you know, Hadoop data lake, now you're just going to have an S3 data lake. If you had an on-prem data warehouse now you just going to have a cloud data warehouse. You're just repeating what you did on prem in the cloud, architected for the future. And you know, for us, the most important thing that we say is that this lake house paradigm is a cloud native way of organizing your data. That's different from how you would do things on premises. So think through what's the right way of doing it in the cloud. Don't just try to copy paste what you had on premises in the cloud. >> It's interesting one of the things that we're observing and I'd love to get your reaction to this. Dave a lot** and I have been reporting on it is, two personas in the enterprise are changing their organization. One is I call IT ops or there's an SRE role developing. And the data teams are being dismantled and being kind of sprinkled through into other teams is this notion of data, pipelining being part of workflows, not just the department. Are you seeing organizational shifts in how people are organizing their resources, their human resources to take advantage of say that the data problems that are need to being solved with machine learning and whatnot and cloud-scale? >> Yeah, absolutely. So you're right. SRE became a thing, lots of DevOps people. It was because when the cloud vendors launched their infrastructure as a service to stitch all these things together and get it all working you needed a lot of devOps people. But now things are maturing. So, you know, with vendors like Data bricks and other multi-cloud vendors, you can actually get much higher level services where you don't need to necessarily have lots of lots of DevOps people that are themselves trying to stitch together lots of services to make this work. So that's one trend. But secondly, you're seeing more data teams being sort of completely ubiquitous in these organizations. Before it used to be you have one data team and then we'll have data and AI and we'll be done. ' It's a one and done. But that's not how it works. That's not how Google, Facebook, Twitter did it, they had data throughout the organization. Every BU was empowered. It's sales, it's marketing, it's finance, it's engineering. So how do you embed all those data teams and make them actually run fast? And you know, there's this concept of a data mesh which is super important where you can actually decentralize and enable all these teams to focus on their domains and run super fast. And that's really enabled by this Lake house paradigm in the cloud that we're talking about. Where you're open, you're basing it on open standards. You have flexibility in the data types and how they're going to store their data. So you kind of provide a lot of that flexibility, but at the same time, you have sort of centralized governance for it. So absolutely things are changing in the market. >> Well, you're just the professor, the masterclass right here is amazing. Thanks for sharing that insight. You're always got to go out of date and that's why we have you on here. You're amazing, great resource for the community. Ransomware is a huge problem, it's now the government's focus. We're being attacked and we don't know where it's coming from. This business models around cyber that's expanding rapidly. There's real revenue behind it. There's a data problem. It's not just a security problem. So one of the themes in all of these startup showcases is data is ubiquitous in the value propositions. One of them is ransomware. What's your thoughts on ransomware? Is it a data problem? Does cloud help? Some are saying that cloud's got better security with ransomware, then say on premise. What's your vision of how you see this ransomware problem being addressed besides the government taking over? >> Yeah, that's a great question. Let me start by saying, you know, we're a data company, right? And if you say you're a data company, you might as well just said, we're a privacy company, right? It's like some people say, well, what do you think about privacy? Do you guys even do privacy? We're a data company. So yeah, we're a privacy company as well. Like you can't talk about data without talking about privacy. With every customer, with every enterprise. So that's obviously top of mind for us. I do think that in the cloud, security is much better because, you know, vendors like us, we're investing so much resources into security and making sure that we harden the infrastructure and, you know, by actually having all of this infrastructure, we can monitor it, detect if something is, you know, an attack is happening, and we can immediately sort of stop it. So that's different from when it's on prem, you have kind of like the separated duties where the software vendor, which would have been us, doesn't really see what's happening in the data center. So, you know, there's an IT team that didn't develop the software is responsible for the security. So I think things are much better now. I think we're much better set up, but of course, things like cryptocurrencies and so on are making it easier for people to sort of hide. There decentralized networks. So, you know, the attackers are getting more and more sophisticated as well. So that's definitely something that's super important. It's super top of mind. We're all investing heavily into security and privacy because, you know, that's going to be super critical going forward. >> Yeah, we got to move that red line, and figure that out and get more intelligence. Decentralized trends not going away it's going to be more of that, less of the centralized. But centralized does come into play with data. It's a mix, it's not mutually exclusive. And I'll get your thoughts on this. Architectural question with, you know, 5G and the edge coming. Amazon's got that outpost stringent, the wavelength, you're seeing mobile world Congress coming up in this month. The focus on processing data at the edge is a huge issue. And enterprises are now going to be commercial part of that. So architecture decisions are being made in enterprises right now. And this is a big issue. So you mentioned multi-cloud, so tools versus platforms. Now I'm an enterprise buyer and there's no more RFPs. I got all this new choices for startups and growing companies to choose from that are cloud native. I got all kinds of new challenges and opportunities. How do I build my architecture so I don't foreclose a future opportunity. >> Yeah, as I said, look, you're actually right. Cloud is becoming even more and more something that everybody's adopting, but at the same time, there is this thing that the edge is also more and more important. And the connectivity between those two and making sure that you can really do that efficiently. My ask from enterprises, and I think this is top of mind for all the enterprise architects is, choose open because that way you can avoid locking yourself in. So that's one thing that's really, really important. In the past, you know, all these vendors that locked you in, and then you try to move off of them, they were highly innovative back in the day. In the 80's and the 90's, there were the best companies. You gave them all your data and it was fantastic. But then because you were locked in, they didn't need to innovate anymore. And you know, they focused on margins instead. And then over time, the innovation stopped and now you were kind of locked in. So I think openness is really important. I think preserving optionality with multi-cloud because we see the different clouds have different strengths and weaknesses and it changes over time. All right. Early on AWS was the only game that either showed up with much better security, active directory, and so on. Now Google with AI capabilities, which one's going to win, which one's going to be better. Actually, probably all three are going to be around. So having that optionality that you can pick between the three and then artificial intelligence. I think that's going to be the key to the future. You know, you asked about security earlier. That's how people detect zero day attacks, right? You ask about the edge, same thing there, that's where the predictions are going to happen. So make sure that you invest in AI and artificial intelligence very early on because it's not something you can just bolt on later on and have a little data team somewhere that then now you have AI and it's one and done. >> All right. Great insight. I've got to ask you, the folks may or may not know, but you're a professor at Berkeley as well, done a lot of great work. That's where you kind of came out of when Data bricks was formed. And the Berkeley basically was it invented distributed computing back in the 80's. I remember I was breaking in when Unix was proprietary, when software wasn't open you actually had the deal that under the table to get code. Now it's all open. Isn't the internet now with distributed computing and how interconnects are happening. I mean, the internet didn't break during the pandemic, which proves the benefit of the internet. And that's a positive. But as you start seeing edge, it's essentially distributed computing. So I got to ask you from a computer science standpoint. What do you see as the key learnings or connect the dots for how this distributed model will work? I see hybrids clearly, hybrid cloud is clearly the operating model but if you take it to the next level of distributed computing, what are some of the key things that you look for in the next five years as this starts to be completely interoperable, obviously software is going to drive a lot of it. What's your vision on that? >> Yeah, I mean, you know, so Berkeley, you're right for the gigs, you know, there was a now project 20, 30 years ago that basically is how we do things. There was a project on how you search in the very early on with Inktomi that became how Google and everybody else to search today. So workday was super, super early, sometimes way too early. And that was actually the mistake. Was that they were so early that people said that that stuff doesn't work. And then 20 years later you were invented. So I think 2009, Berkeley published just above the clouds saying the cloud is the future. At that time, most industry leaders said, that's just, you know, that doesn't work. Today, recently they published a research paper called, Sky Computing. So sky computing is what you get above the clouds, right? So we have the cloud as the future, the next level after that is the sky. That's one on top of them. That's what multi-cloud is. So that's a lot of the research at Berkeley, you know, into distributed systems labs is about this. And we're excited about that. Then we're one of the sky computing vendors out there. So I think you're going to see much more innovation happening at the sky level than at the compute level where you needed all those DevOps and SRE people to like, you know, build everything manually themselves. I can just see the memes now coming Ali, sky net, star track. You've got space too, by the way, space is another frontier that is seeing a lot of action going on because now the surface area of data with satellites is huge. So again, I know you guys are doing a lot of business with folks in that vertical where you starting to see real time data acquisition coming from these satellites. What's your take on the whole space as the, not the final frontier, but certainly as a new congested and contested space for, for data? >> Well, I mean, as a data vendor, we see a lot of, you know, alternative data sources coming in and people aren't using machine learning< AI to eat out signal out of the, you know, massive amounts of imagery that's coming out of these satellites. So that's actually a pretty common in FinTech, which is a vertical for us. And also sort of in the public sector, lots of, lots of, lots of satellites, imagery data that's coming. And these are massive volumes. I mean, it's like huge data sets and it's a super, super exciting what they can do. Like, you know, extracting signal from the satellite imagery is, and you know, being able to handle that amount of data, it's a challenge for all the companies that we work with. So we're excited about that too. I mean, definitely that's a trend that's going to continue. >> All right. I'm super excited for you. And thanks for coming on The Cube here for our keynote. I got to ask you a final question. As you think about the future, I see your company has achieved great success in a very short time, and again, you guys done the work, I've been following your company as you know. We've been been breaking that Data bricks story for a long time. I've been excited by it, but now what's changed. You got to start thinking about the next 20 miles stair when you look at, you know, the sky computing, you're thinking about these new architectures. As the CEO, your job is to one, not run out of money which you don't have to worry about that anymore, so hiring. And then, you got to figure out that next 20 miles stair as a company. What's that going on in your mind? Take us through your mindset of what's next. And what do you see out in that landscape? >> Yeah, so what I mentioned around Sky company optionality around multi-cloud, you're going to see a lot of capabilities around that. Like how do you get multi-cloud disaster recovery? How do you leverage the best of all the clouds while at the same time not having to just pick one? So there's a lot of innovation there that, you know, we haven't announced yet, but you're going to see a lot of it over the next many years. Things that you can do when you have the optionality across the different parts. And the second thing that's really exciting for us is bringing AI to the masses. Democratizing data and AI. So how can you actually apply machine learning to machine learning? How can you automate machine learning? Today machine learning is still quite complicated and it's pretty advanced. It's not going to be that way 10 years from now. It's going to be very simple. Everybody's going to have it at their fingertips. So how do we apply machine learning to machine learning? It's called auto ML, automatic, you know, machine learning. So that's an area, and that's not something that can be done with, right? But the goal is to eventually be able to automate a way the whole machine learning engineer and the machine learning data scientist altogether. >> You know it's really fun and talking with you is that, you know, for years we've been talking about this inside the ropes, inside the industry, around the future. Now people starting to get some visibility, the pandemics forced that. You seeing the bad projects being exposed. It's like the tide pulled out and you see all the scabs and bad projects that were justified old guard technologies. If you get it right you're on a good wave. And this is clearly what we're seeing. And you guys example of that. So as enterprises realize this, that they're going to have to look double down on the right projects and probably trash the bad projects, new criteria, how should people be thinking about buying? Because again, we talked about the RFP before. I want to kind of circle back because this is something that people are trying to figure out. You seeing, you know, organic, you come in freemium models as cloud scale becomes the advantage in the lock-in frankly seems to be the value proposition. The more value you provide, the more lock-in you get. Which sounds like that's the way it should be versus proprietary, you know, protocols. The protocol is value. How should enterprises organize their teams? Is it end to end workflows? Is it, and how should they evaluate the criteria for these technologies that they want to buy? >> Yeah, that's a great question. So I, you know, it's very simple, try to future proof your decision-making. Make sure that whatever you're doing is not blocking your in. So whatever decision you're making, what if the world changes in five years, make sure that if you making a mistake now, that's not going to bite you in about five years later. So how do you do that? Well, open source is great. If you're leveraging open-source, you can try it out already. You don't even need to talk to any vendor. Your teams can already download it and try it out and get some value out of it. If you're in the cloud, this pay as you go models, you don't have to do a big RFP and commit big. You can try it, pay the vendor, pay as you go, $10, $15. It doesn't need to be a million dollar contract and slowly grow as you're providing value. And then make sure that you're not just locking yourself in to one cloud or, you know, one particular vendor. As much as possible preserve your optionality because then that's not a one-way door. If it turns out later you want to do something else, you can, you know, pick other things as well. You're not locked in. So that's what I would say. Keep that top of mind that you're not locking yourself into a particular decision that you made today, that you might regret in five years. >> I really appreciate you coming on and sharing your with our community and The Cube. And as always great to see you. I really enjoy your clubhouse talks, and I really appreciate how you give back to the community. And I want to thank you for coming on and taking the time with us today. >> Thanks John, always appreciate talking to you. >> Okay Ali Ghodsi, CEO of Data bricks, a success story that proves the validation of cloud scale, open and create value, values the new lock-in. So Natalie, back to you for continuing coverage. >> That was a terrific interview John, but I'd love to get Dave's insights first. What were your takeaways, Dave? >> Well, if we have more time I'll tell you how Data bricks got to where they are today, but I'll say this, the most important thing to me that Allie said was he conveyed a very clear understanding of what data companies are outright and are getting ready. Talked about four things. There's not one data team, there's many data teams. And he talked about data is decentralized, and data has to have context and that context lives in the business. He said, look, think about it. The way that the data companies would get it right, they get data in teams and sales and marketing and finance and engineering. They all have their own data and data teams. And he referred to that as a data mesh. That's a term that is your mock, the Gany coined and the warehouse of the data lake it's merely a node in that global message. It meshes discoverable, he talked about federated governance, and Data bricks, they're breaking the model of shoving everything into a single repository and trying to make that the so-called single version of the truth. Rather what they're doing, which is right on is putting data in the hands of the business owners. And that's how true data companies do. And the last thing you talked about with sky computing, which I loved, it's that future layer, we talked about multi-cloud a lot that abstracts the underlying complexity of the technical details of the cloud and creates additional value on top. I always say that the cloud players like Amazon have given the gift to the world of 100 billion dollars a year they spend in CapEx. Thank you. Now we're going to innovate on top of it. Yeah. And I think the refactoring... >> Hope by John. >> That was great insight and I totally agree. The refactoring piece too was key, he brought that home. But to me, I think Data bricks that Ali shared there and why he's been open and sharing a lot of his insights and the community. But what he's not saying, cause he's humble and polite is they cracked the code on the enterprise, Dave. And to Dave's points exactly reason why they did it, they saw an opportunity to make it easier, at that time had dupe was the rage, and they just made it easier. They was smart, they made good bets, they had a good formula and they cracked the code with the enterprise. They brought it in and they brought value. And see that's the key to the cloud as Dave pointed out. You get replatform with the cloud, then you refactor. And I think he pointed out the multi-cloud and that really kind of teases out the whole future and landscape, which is essentially distributed computing. And I think, you know, companies are starting to figure that out with hybrid and this on premises and now super edge I call it, with 5G coming. So it's just pretty incredible. >> Yeah. Data bricks, IPO is coming and people should know. I mean, what everybody, they created spark as you know John and everybody thought they were going to do is mimic red hat and sell subscriptions and support. They didn't, they developed a managed service and they embedded AI tools to simplify data science. So to your point, enterprises could buy instead of build, we know this. Enterprises will spend money to make things simpler. They don't have the resources, and so this was what they got right was really embedding that, making a building a managed service, not mimicking the kind of the red hat model, but actually creating a new value layer there. And that's big part of their success. >> If I could just add one thing Natalie to that Dave saying is really right on. And as an enterprise buyer, if we go the other side of the equation, it used to be that you had to be a known company, get PR, you fill out RFPs, you had to meet all the speeds. It's like going to the airport and get a swab test, and get a COVID test and all kinds of mechanisms to like block you and filter you. Most of the biggest success stories that have created the most value for enterprises have been the companies that nobody's understood. And Andy Jazz's famous quote of, you know, being misunderstood is actually a good thing. Data bricks was very misunderstood at the beginning and no one kind of knew who they were but they did it right. And so the enterprise buyers out there, don't be afraid to test the startups because you know the next Data bricks is out there. And I think that's where I see the psychology changing from the old IT buyers, Dave. It's like, okay, let's let's test this company. And there's plenty of ways to do that. He illuminated those premium, small pilots, you don't need to go on these big things. So I think that is going to be a shift in how companies going to evaluate startups. >> Yeah. Think about it this way. Why should the large banks and insurance companies and big manufacturers and pharma companies, governments, why should they burn resources managing containers and figuring out data science tools if they can just tap into solutions like Data bricks which is an AI platform in the cloud and let the experts manage all that stuff. Think about how much money in time that saves enterprises. >> Yeah, I mean, we've got 15 companies here we're showcasing this batch and this season if you call it. That episode we are going to call it? They're awesome. Right? And the next 15 will be the same. And these companies could be the next billion dollar revenue generator because the cloud enables that day. I think that's the exciting part. >> Well thank you both so much for these insights. Really appreciate it. AWS startup showcase highlights the innovation that helps startups succeed. And no one knows that better than our very next guest, Jeff Barr. Welcome to the show and I will send this interview now to Dave and John and see you just in the bit. >> Okay, hey Jeff, great to see you. Thanks for coming on again. >> Great to be back. >> So this is a regular community segment with Jeff Barr who's a legend in the industry. Everyone knows your name. Everyone knows that. Congratulations on your recent blog posts we have reading. Tons of news, I want to get your update because 5G has been all over the news, mobile world congress is right around the corner. I know Bill Vass was a keynote out there, virtual keynote. There's a lot of Amazon discussion around the edge with wavelength. Specifically, this is the outpost piece. And I know there is news I want to get to, but the top of mind is there's massive Amazon expansion and the cloud is going to the edge, it's here. What's up with wavelength. Take us through the, I call it the power edge, the super edge. >> Well, I'm really excited about this mostly because it gives a lot more choice and flexibility and options to our customers. This idea that with wavelength we announced quite some time ago, at least quite some time ago if we think in cloud years. We announced that we would be working with 5G providers all over the world to basically put AWS in the telecom providers data centers or telecom centers, so that as their customers build apps, that those apps would take advantage of the low latency, the high bandwidth, the reliability of 5G, be able to get to some compute and storage services that are incredibly close geographically and latency wise to the compute and storage that is just going to give customers this new power and say, well, what are the cool things we can build? >> Do you see any correlation between wavelength and some of the early Amazon services? Because to me, my gut feels like there's so much headroom there. I mean, I was just riffing on the notion of low latency packets. I mean, just think about the applications, gaming and VR, and metaverse kind of cool stuff like that where having the edge be that how much power there. It just feels like a new, it feels like a new AWS. I mean, what's your take? You've seen the evolutions and the growth of a lot of the key services. Like EC2 and SA3. >> So welcome to my life. And so to me, the way I always think about this is it's like when I go to a home improvement store and I wander through the aisles and I often wonder through with no particular thing that I actually need, but I just go there and say, wow, they've got this and they've got this, they've got this other interesting thing. And I just let my creativity run wild. And instead of trying to solve a problem, I'm saying, well, if I had these different parts, well, what could I actually build with them? And I really think that this breadth of different services and locations and options and communication technologies. I suspect a lot of our customers and customers to be and are in this the same mode where they're saying, I've got all this awesomeness at my fingertips, what might I be able to do with it? >> He reminds me when Fry's was around in Palo Alto, that store is no longer here but it used to be back in the day when it was good. It was you go in and just kind of spend hours and then next thing you know, you built a compute. Like what, I didn't come in here, whether it gets some cables. Now I got a motherboard. >> I clearly remember Fry's and before that there was the weird stuff warehouse was another really cool place to hang out if you remember that. >> Yeah I do. >> I wonder if I could jump in and you guys talking about the edge and Jeff I wanted to ask you about something that is, I think people are starting to really understand and appreciate what you did with the entrepreneur acquisition, what you do with nitro and graviton, and really driving costs down, driving performance up. I mean, there's like a compute Renaissance. And I wonder if you could talk about the importance of that at the edge, because it's got to be low power, it has to be low cost. You got to be doing processing at the edge. What's your take on how that's evolving? >> Certainly so you're totally right that we started working with and then ultimately acquired Annapurna labs in Israel a couple of years ago. I've worked directly with those folks and it's really awesome to see what they've been able to do. Just really saying, let's look at all of these different aspects of building the cloud that were once effectively kind of somewhat software intensive and say, where does it make sense to actually design build fabricate, deploy custom Silicon? So from putting up the system to doing all kinds of additional kinds of security checks, to running local IO devices, running the NBME as fast as possible to support the EBS. Each of those things has been a contributing factor to not just the power of the hardware itself, but what I'm seeing and have seen for the last probably two or three years at this point is the pace of innovation on instance types just continues to get faster and faster. And it's not just cranking out new instance types because we can, it's because our awesomely diverse base of customers keeps coming to us and saying, well, we're happy with what we have so far, but here's this really interesting new use case. And we needed a different ratio of memory to CPU, or we need more cores based on the amount of memory, or we needed a lot of IO bandwidth. And having that nitro as the base lets us really, I don't want to say plug and play, cause I haven't actually built this myself, but it seems like they can actually put the different elements together, very very quickly and then come up with new instance types that just our customers say, yeah, that's exactly what I asked for and be able to just do this entire range of from like micro and nano sized all the way up to incredibly large with incredible just to me like, when we talk about terabytes of memory that are just like actually just RAM memory. It's like, that's just an inconceivably large number by the standards of where I started out in my career. So it's all putting this power in customer hands. >> You used the term plug and play, but it does give you that nitro gives you that optionality. And then other thing that to me is really exciting is the way in which ISVs are writing to whatever's underneath. So you're making that, you know, transparent to the users so I can choose as a customer, the best price performance for my workload and that that's just going to grow that ISV portfolio. >> I think it's really important to be accurate and detailed and as thorough as possible as we launch each one of these new instance types with like what kind of processor is in there and what clock speed does it run at? What kind of, you know, how much memory do we have? What are the, just the ins and outs, and is it Intel or arm or AMD based? It's such an interesting to me contrast. I can still remember back in the very very early days of back, you know, going back almost 15 years at this point and effectively everybody said, well, not everybody. A few people looked and said, yeah, we kind of get the value here. Some people said, this just sounds like a bunch of generic hardware, just kind of generic hardware in Iraq. And even back then it was something that we were very careful with to design and optimize for use cases. But this idea that is generic is so, so, so incredibly inaccurate that I think people are now getting this. And it's okay. It's fine too, not just for the cloud, but for very specific kinds of workloads and use cases. >> And you guys have announced obviously the performance improvements on a lamb** does getting faster, you got the per billing, second billings on windows and SQL server on ECE too**. So I mean, obviously everyone kind of gets that, that's been your DNA, keep making it faster, cheaper, better, easier to use. But the other area I want to get your thoughts on because this is also more on the footprint side, is that the regions and local regions. So you've got more region news, take us through the update on the expansion on the footprint of AWS because you know, a startup can come in and these 15 companies that are here, they're global with AWS, right? So this is a major benefit for customers around the world. And you know, Ali from Data bricks mentioned privacy. Everyone's a privacy company now. So the huge issue, take us through the news on the region. >> Sure, so the two most recent regions that we announced are in the UAE and in Israel. And we generally like to pre-announce these anywhere from six months to two years at a time because we do know that the customers want to start making longer term plans to where they can start thinking about where they can do their computing, where they can store their data. I think at this point we now have seven regions under construction. And, again it's all about customer trice. Sometimes it's because they have very specific reasons where for based on local laws, based on national laws, that they must compute and restore within a particular geographic area. Other times I say, well, a lot of our customers are in this part of the world. Why don't we pick a region that is as close to that part of the world as possible. And one really important thing that I always like to remind our customers of in my audience is, anything that you choose to put in a region, stays in that region unless you very explicitly take an action that says I'd like to replicate it somewhere else. So if someone says, I want to store data in the US, or I want to store it in Frankfurt, or I want to store it in Sao Paulo, or I want to store it in Tokyo or Osaka. They get to make that very specific choice. We give them a lot of tools to help copy and replicate and do cross region operations of various sorts. But at the heart, the customer gets to choose those locations. And that in the early days I think there was this weird sense that you would, you'd put things in the cloud that would just mysteriously just kind of propagate all over the world. That's never been true, and we're very very clear on that. And I just always like to reinforce that point. >> That's great stuff, Jeff. Great to have you on again as a regular update here, just for the folks watching and don't know Jeff he'd been blogging and sharing. He'd been the one man media band for Amazon it's early days. Now he's got departments, he's got peoples on doing videos. It's an immediate franchise in and of itself, but without your rough days we wouldn't have gotten all the great news we subscribe to. We watch all the blog posts. It's essentially the flow coming out of AWS which is just a tsunami of a new announcements. Always great to read, must read. Jeff, thanks for coming on, really appreciate it. That's great. >> Thank you John, great to catch up as always. >> Jeff Barr with AWS again, and follow his stuff. He's got a great audience and community. They talk back, they collaborate and they're highly engaged. So check out Jeff's blog and his social presence. All right, Natalie, back to you for more coverage. >> Terrific. Well, did you guys know that Jeff took a three week AWS road trip across 15 cities in America to meet with cloud computing enthusiasts? 5,500 miles he drove, really incredible I didn't realize that. Let's unpack that interview though. What stood out to you John? >> I think Jeff, Barr's an example of what I call direct to audience a business model. He's been doing it from the beginning and I've been following his career. I remember back in the day when Amazon was started, he was always building stuff. He's a builder, he's classic. And he's been there from the beginning. At the beginning he was just the blog and it became a huge audience. It's now morphed into, he was power blogging so hard. He has now support and he still does it now. It's basically the conduit for information coming out of Amazon. I think Jeff has single-handedly made Amazon so successful at the community developer level, and that's the startup action happened and that got them going. And I think he deserves a lot of the success for AWS. >> And Dave, how about you? What is your reaction? >> Well I think you know, and everybody knows about the cloud and back stop X** and agility, and you know, eliminating the undifferentiated, heavy lifting and all that stuff. And one of the things that's often overlooked which is why I'm excited to be part of this program is the innovation. And the innovation comes from startups, and startups start in the cloud. And so I think that that's part of the flywheel effect. You just don't see a lot of startups these days saying, okay, I'm going to do something that's outside of the cloud. There are some, but for the most part, you know, if you saw in software, you're starting in the cloud, it's so capital efficient. I think that's one thing, I've throughout my career. I've been obsessed with every part of the stack from whether it's, you know, close to the business process with the applications. And right now I'm really obsessed with the plumbing, which is why I was excited to talk about, you know, the Annapurna acquisition. Amazon bought and a part of the $350 million, it's reported, you know, maybe a little bit more, but that isn't an amazing acquisition. And the reason why that's so important is because Amazon is continuing to drive costs down, drive performance up. And in my opinion, leaving a lot of the traditional players in their dust, especially when it comes to the power and cooling. You have often overlooked things. And the other piece of the interview was that Amazon is actually getting ISVs to write to these new platforms so that you don't have to worry about there's the software run on this chip or that chip, or x86 or arm or whatever it is. It runs. And so I can choose the best price performance. And that's where people don't, they misunderstand, you always say it John, just said that people are misunderstood. I think they misunderstand, they confused, you know, the price of the cloud with the cost of the cloud. They ignore all the labor costs that are associated with that. And so, you know, there's a lot of discussion now about the cloud tax. I just think the pace is accelerating. The gap is not closing, it's widening. >> If you look at the one question I asked them about wavelength and I had a follow up there when I said, you know, we riff on it and you see, he lit up like he beam was beaming because he said something interesting. It's not that there's a problem to solve at this opportunity. And he conveyed it to like I said, walking through Fry's. But like, you go into a store and he's a builder. So he sees opportunity. And this comes back down to the Martine Casada paradox posts he wrote about do you optimize for CapEx or future revenue? And I think the tell sign is at the wavelength edge piece is going to be so creative and that's going to open up massive opportunities. I think that's the place to watch. That's the place I'm watching. And I think startups going to come out of the woodwork because that's where the action will be. And that's just Amazon at the edge, I mean, that's just cloud at the edge. I think that is going to be very effective. And his that's a little TeleSign, he kind of revealed a little bit there, a lot there with that comment. >> Well that's a to be continued conversation. >> Indeed, I would love to introduce our next guest. We actually have Soma on the line. He's the managing director at Madrona venture group. Thank you Soma very much for coming for our keynote program. >> Thank you Natalie and I'm great to be here and will have the opportunity to spend some time with you all. >> Well, you have a long to nerd history in the enterprise. How would you define the modern enterprise also known as cloud scale? >> Yeah, so I would say I have, first of all, like, you know, we've all heard this now for the last, you know, say 10 years or so. Like, software is eating the world. Okay. Put it another way, we think about like, hey, every enterprise is a software company first and foremost. Okay. And companies that truly internalize that, that truly think about that, and truly act that way are going to start up, continue running well and things that don't internalize that, and don't do that are going to be left behind sooner than later. Right. And the last few years you start off thing and not take it to the next level and talk about like, not every enterprise is not going through a digital transformation. Okay. So when you sort of think about the world from that lens. Okay. Modern enterprise has to think about like, and I am first and foremost, a technology company. I may be in the business of making a car art, you know, manufacturing paper, or like you know, manufacturing some healthcare products or what have you got out there. But technology and software is what is going to give me a unique, differentiated advantage that's going to let me do what I need to do for my customers in the best possible way [Indistinct]. So that sort of level of focus, level of execution, has to be there in a modern enterprise. The other thing is like not every modern enterprise needs to think about regular. I'm competing for talent, not anymore with my peers in my industry. I'm competing for technology talent and software talent with the top five technology companies in the world. Whether it is Amazon or Facebook or Microsoft or Google, or what have you cannot think, right? So you really have to have that mindset, and then everything flows from that. >> So I got to ask you on the enterprise side again, you've seen many ways of innovation. You've got, you know, been in the industry for many, many years. The old way was enterprises want the best proven product and the startups want that lucrative contract. Right? Yeah. And get that beach in. And it used to be, and we addressed this in our earlier keynote with Ali and how it's changing, the buyers are changing because the cloud has enabled this new kind of execution. I call it agile, call it what you want. Developers are driving modern applications, so enterprises are still, there's no, the playbooks evolving. Right? So we see that with the pandemic, people had needs, urgent needs, and they tried new stuff and it worked. The parachute opened as they say. So how do you look at this as you look at stars, you're investing in and you're coaching them. What's the playbook? What's the secret sauce of how to crack the enterprise code today. And if you're an enterprise buyer, what do I need to do? I want to be more agile. Is there a clear path? Is there's a TSA to let stuff go through faster? I mean, what is the modern playbook for buying and being a supplier? >> That's a fantastic question, John, because I think that sort of playbook is changing, even as we speak here currently. A couple of key things to understand first of all is like, you know, decision-making inside an enterprise is getting more and more de-centralized. Particularly decisions around what technology to use and what solutions to use to be able to do what people need to do. That decision making is no longer sort of, you know, all done like the CEO's office or the CTO's office kind of thing. Developers are more and more like you rightly said, like sort of the central of the workflow and the decision making process. So it'll be who both the enterprises, as well as the startups to really understand that. So what does it mean now from a startup perspective, from a startup perspective, it means like, right. In addition to thinking about like hey, not do I go create an enterprise sales post, do I sell to the enterprise like what I might have done in the past? Is that the best way of moving forward, or should I be thinking about a product led growth go to market initiative? You know, build a product that is easy to use, that made self serve really works, you know, get the developers to start using to see the value to fall in love with the product and then you think about like hey, how do I go translate that into a contract with enterprise. Right? And more and more what I call particularly, you know, startups and technology companies that are focused on the developer audience are thinking about like, you know, how do I have a bottom up go to market motion? And sometime I may sort of, you know, overlap that with the top down enterprise sales motion that we know that has been going on for many, many years or decades kind of thing. But really this product led growth bottom up a go to market motion is something that we are seeing on the rise. I would say they're going to have more than half the startup that we come across today, have that in some way shape or form. And so the enterprise also needs to understand this, the CIO or the CTO needs to know that like hey, I'm not decision-making is getting de-centralized. I need to empower my engineers and my engineering managers and my engineering leaders to be able to make the right decision and trust them. I'm going to give them some guard rails so that I don't find myself in a soup, you know, sometime down the road. But once I give them the guard rails, I'm going to enable people to make the decisions. People who are closer to the problem, to make the right decision. >> Well Soma, what are some of the ways that startups can accelerate their enterprise penetration? >> I think that's another good question. First of all, you need to think about like, Hey, what are enterprises wanting to rec? Okay. If you start off take like two steps back and think about what the enterprise is really think about it going. I'm a software company, but I'm really manufacturing paper. What do I do? Right? The core thing that most enterprises care about is like, hey, how do I better engage with my customers? How do I better serve my customers? And how do I do it in the most optimal way? At the end of the day that's what like most enterprises really care about. So startups need to understand, what are the problems that the enterprise is trying to solve? What kind of tools and platform technologies and infrastructure support, and, you know, everything else that they need to be able to do what they need to do and what only they can do in the most optimal way. Right? So to the extent you are providing either a tool or platform or some technology that is going to enable your enterprise to make progress on what they want to do, you're going to get more traction within the enterprise. In other words, stop thinking about technology, and start thinking about the customer problem that they want to solve. And the more you anchor your company, and more you anchor your conversation with the customer around that, the more the enterprise is going to get excited about wanting to work with you. >> So I got to ask you on the enterprise and developer equation because CSOs and CXOs, depending who you talk to have that same answer. Oh yeah. In the 90's and 2000's, we kind of didn't, we throttled down, we were using the legacy developer tools and cloud came and then we had to rebuild and we didn't really know what to do. So you seeing a shift, and this is kind of been going on for at least the past five to eight years, a lot more developers being hired yet. I mean, at FinTech is clearly a vertical, they always had developers and everyone had developers, but there's a fast ramp up of developers now and the role of open source has changed. Just looking at the participation. They're not just consuming open source, open source is part of the business model for mainstream enterprises. How is this, first of all, do you agree? And if so, how has this changed the course of an enterprise human resource selection? How they're organized? What's your vision on that? >> Yeah. So as I mentioned earlier, John, in my mind the first thing is, and this sort of, you know, like you said financial services has always been sort of hiring people [Indistinct]. And this is like five-year old story. So bear with me I'll tell you the firewall story and then come to I was trying to, the cloud CIO or the Goldman Sachs. Okay. And this is five years ago when people were still like, hey, is this cloud thing real and now is cloud going to take over the world? You know, am I really ready to put my data in the cloud? So there are a lot of questions and conversations can affect. The CIO of Goldman Sachs told me two things that I remember to this day. One is, hey, we've got a internal edict. That we made a decision that in the next five years, everything in Goldman Sachs is going to be on the public law. And I literally jumped out of the chair and I said like now are you going to get there? And then he laughed and said like now it really doesn't matter whether we get there or not. We want to set the tone, set the direction for the organization that hey, public cloud is here. Public cloud is there. And we need to like, you know, move as fast as we realistically can and think about all the financial regulations and security and privacy. And all these things that we care about deeply. But given all of that, the world is going towards public load and we better be on the leading edge as opposed to the lagging edge. And the second thing he said, like we're talking about like hey, how are you hiring, you know, engineers at Goldman Sachs Canada? And he said like in hey, I sort of, my team goes out to the top 20 schools in the US. And the people we really compete with are, and he was saying this, Hey, we don't compete with JP Morgan or Morgan Stanley, or pick any of your favorite financial institutions. We really think about like, hey, we want to get the best talent into Goldman Sachs out of these schools. And we really compete head to head with Google. We compete head to head with Microsoft. We compete head to head with Facebook. And we know that the caliber of people that we want to get is no different than what these companies want. If you want to continue being a successful, leading it, you know, financial services player. That sort of tells you what's going on. You also talked a little bit about like hey, open source is here to stay. What does that really mean kind of thing. In my mind like now, you can tell me that I can have from given my pedigree at Microsoft, I can tell you that we were the first embraces of open source in this world. So I'll say that right off the bat. But having said that we did in our turn around and said like, hey, this open source is real, this open source is going to be great. How can we embrace and how can we participate? And you fast forward to today, like in a Microsoft is probably as good as open source as probably any other large company I would say. Right? Including like the work that the company has done in terms of acquiring GitHub and letting it stay true to its original promise of open source and community can I think, right? I think Microsoft has come a long way kind of thing. But the thing that like in all these enterprises need to think about is you want your developers to have access to the latest and greatest tools. To the latest and greatest that the software can provide. And you really don't want your engineers to be reinventing the wheel all the time. So there is something available in the open source world. Go ahead, please set up, think about whether that makes sense for you to use it. And likewise, if you think that is something you can contribute to the open source work, go ahead and do that. So it's really a two way somebody Arctic relationship that enterprises need to have, and they need to enable their developers to want to have that symbiotic relationship. >> Soma, fantastic insights. Thank you so much for joining our keynote program. >> Thank you Natalie and thank you John. It was always fun to chat with you guys. Thank you. >> Thank you. >> John we would love to get your quick insight on that. >> Well I think first of all, he's a prolific investor the great from Madrona venture partners, which is well known in the tech circles. They're in Seattle, which is in the hub of I call cloud city. You've got Amazon and Microsoft there. He'd been at Microsoft and he knows the developer ecosystem. And reason why I like his perspective is that he understands the value of having developers as a core competency in Microsoft. That's their DNA. You look at Microsoft, their number one thing from day one besides software was developers. That was their army, the thousand centurions that one won everything for them. That has shifted. And he brought up open source, and .net and how they've embraced Linux, but something that tele before he became CEO, we interviewed him in the cube at an Xcel partners event at Stanford. He was open before he was CEO. He was talking about opening up. They opened up a lot of their open source infrastructure projects to the open compute foundation early. So they had already had that going and at that price, since that time, the stock price of Microsoft has skyrocketed because as Ali said, open always wins. And I think that is what you see here, and as an investor now he's picking in startups and investing in them. He's got to read the tea leaves. He's got to be in the right side of history. So he brings a great perspective because he sees the old way and he understands the new way. That is the key for success we've seen in the enterprise and with the startups. The people who get the future, and can create the value are going to win. >> Yeah, really excellent point. And just really quickly. What do you think were some of our greatest hits on this hour of programming? >> Well first of all I'm really impressed that Ali took the time to come join us because I know he's super busy. I think they're at a $28 billion valuation now they're pushing a billion dollars in revenue, gap revenue. And again, just a few short years ago, they had zero software revenue. So of these 15 companies we're showcasing today, you know, there's a next Data bricks in there. They're all going to be successful. They already are successful. And they're all on this rocket ship trajectory. Ali is smart, he's also got the advantage of being part of that Berkeley community which they're early on a lot of things now. Being early means you're wrong a lot, but you're also right, and you're right big. So Berkeley and Stanford obviously big areas here in the bay area as research. He is smart, He's got a great team and he's really open. So having him share his best practices, I thought that was a great highlight. Of course, Jeff Barr highlighting some of the insights that he brings and honestly having a perspective of a VC. And we're going to have Peter Wagner from wing VC who's a classic enterprise investors, super smart. So he'll add some insight. Of course, one of the community session, whenever our influencers coming on, it's our beat coming on at the end, as well as Katie Drucker. Another Madrona person is going to talk about growth hacking, growth strategies, but yeah, sights Raleigh coming on. >> Terrific, well thank you so much for those insights and thank you to everyone who is watching the first hour of our live coverage of the AWS startup showcase for myself, Natalie Ehrlich, John, for your and Dave Vellante we want to thank you very much for watching and do stay tuned for more amazing content, as well as a special live segment that John Furrier is going to be hosting. It takes place at 12:30 PM Pacific time, and it's called cracking the code, lessons learned on how enterprise buyers evaluate new startups. Don't go anywhere.

>> Welcome to today's session of theCUBE's presentation of the AWS Startup Showcase, The Next Big Thing in AI, Security and Life Sciences. Today featuring Lacework for the security track. I'm your host Natalie Erlich. Thank you for joining us. And we will discuss today how LendingTree automates AWS security for DevOps teams and stays compliant with Lacework. Now we're joined by Adam Leftik the VP of Product at Lacework as well as a Arun Sankaran, CISO of LendingTree. Thank you both very much for joining us today. >> Thank you for having us. >> Well, wonderful. Adam, let's start with you. Lacework positions itself as, "cloud security at the speed of cloud innovation." What does that mean to you and how are you helping your customers? >> Great question, Natalie. I think one of the things that's really important to understand about Lacework really comes back to essentially what's happening at cloud speed, which is customers are aggressively moving more and more of their applications to the cloud, but they're doing so with the same number of resources to secure that environment. And as the cloud continues to grow, both in terms of complexity, as well as overall ability to unlock new styles of applications that were never before even possible without this new technology landscape. Fundamentally, Lacework is designed to enable those builders to go faster without worrying about all the different intricacies and threats that they face out there on the internet. And so the core mission of Lacework is really about enabling builders to build those applications and leverage those cloud resources and new cloud technologies to move quicker and quicker. >> Natalie: Fascinating. >> Yeah, thanks. If you go back to the sort of foundation of the company there we took a very different approach to how we think about security. Often, you know, security approaches in the past have been a rules driven model where you try and think of all the different vectors that attacks can come at. And fundamentally, you end up writing a series of these rules that are impossible to maintain, they atrophy over time, and that you can't possibly think ahead of all these nefarious actors. So one of the things that Lacework did from the very beginning was take a very different approach which is leveraging security as a data problem. And the way we do this is through what we refer to as our polygraph. And the polygraph essentially looks at all the exhaust telemetry that we're able to ingest both from your cloud accounts as well as the underlying infrastructure. And we take that and we build a baseline and a behavioral model for how the application should behave when it's normal. And this baseline represents the state of normalcy. And so then we leverage modern data science techniques to essentially build a model that can identify potential threats without requiring our users to build rules and ultimately play catch up to all the different threats that they face. And this is a really, really powerful capability because it allows our customers both to identify misconfigurations and remediate them, monitor all the activity to reduce the overall overhead on their security organization, and of course help them build faster and identify threats as they come into the system. And we differentiate in lots of different ways as well. So one of the things we're looking to do as part of the overall cloud transformation is really meet the DevOps teams and the security teams where they are. And so all of the information that Lacework captures, synthesizes, and produce through our automation ultimately feed into the different channels that our users are really leveraging that skill today. Whether that's through their ChatOps windows or ultimately into their CICD pipeline so that we give broad coverage both at build time as well as run time and give them full visibility and insights and the ability to remediate those quickly. You know, one of the other things that we're really proud of and this is core to our product philosophy is building more and more partnerships with our customers and LendingTree is really at the forefront of that partnership and we're super excited to be partnering with them. And that's certainly something that we've done to differentiate our product offering and I'd love to hear from Arun, how have you been working with Lacework and how has that been going so far? >> Yeah, thank you, Adam. You know, frankly I think that's a huge differentiator for us. There's a lot of players that can solve technology problems but what we've really appreciated is that as a smaller shop and a smaller organization, the level of connectedness that we feel with the development teams at Lacework. We raise a opportunity. You know, this can make things more efficient for us or this can reduce our time to triage, or this visualization or this UI could be modified to support certain security operations center use cases, maybe that's not what it's designed for. And we've enjoyed just a lot of success in kind of shaping the product in order to meet all the different use cases. And as Adam mentioned, you know, as a CISO, my primary responsibility is security, but frankly there's a lot of DevOps and tech use cases within the polygraph visualization tool, and understanding our environment and troubleshooting has frankly it saved us quite a bit of time and we're looking forward to the partnership to continue to grow out the tool. As we, as a company, scale in today's world, it's very important that we're able to scale our capability 2-3X without a corresponding 2-3X in staff and resources. I think this is the kind of tool that's going to help us get there. >> Well, speaking to you Arun, Lacework has recently grown tremendously and gotten a lot of industry attention but you saw something before everyone else. Can you tell us what really caught your attention? What stood out to you and why you decided to become an early adopter? >> Yeah, great question. Honestly, I wish it was a super tricky kind of answer but the real honest answer is it was a very easy decision because we had a need. We knew that we needed robust monitoring capability and detection of threats within containerized environments. And, you know, there are other players in the space but we have a very diverse environment. We're a combination of multiple container technologies and multiple cloud platforms. And we needed something that had the greatest diversity of coverage across our environments. And this was really the only solution that would work for us. I'd love to be able to say that it was like an aggressive bake-off and there's all these different options. But really, from a capability, and scope, and coverage, it was a fairly easy decision for us. >> And how has your threat detection and investigation process changed since you brought on Lacework? >> Yeah, it certainly has. Our environment within 24 hour period, it might generate 300, 400 million events and that's process level data from hosts and network data access. It's just a very noisy amount of alerts. With the Lacework's platform, those 300, 400 million get reduced to about a hundred alerts a day that we see and of those, five are critical and those tend to all be very actionable. So from an alert fatigue perspective, we really rely on this to give us actionable data, actionable alerts that teams can really focus on and reduces that noise. So I would say that's probably the number one way that our detection process has changed and frankly, a lot of it is what Adam mentioned as far as the underlying self-learning, self-tuning engine. There's not a whole lot of active rules that we had to create or configuration that we had to do. It's kind of a learning system and I think it's really, probably, I would estimate maybe 50-60% reduction in triage and response time for alerts as well. >> And Adam, now going to you, while 2020 was a really rough year for a lot of people, a lot of businesses, Lacework realized 300% revenue growth. So now that the economy is bouncing back and seemingly so in full force, what are your expectations for Lacework in the next year? >> Great question. I think one of the things we're seeing broadly across the industry is an acceleration, a realization that companies that are going through digital transformations have accelerated their pace and so we anticipate even faster growth. Additionally, you know, the companies that may have not been on that trajectory are now realizing that they need to move to the cloud. There's not a lot of folks right now thinking that they're going to be racking and stacking in physical data centers going forward. So we fully expect a continuation of massive growth. And increasingly as customers are moving into the cloud, they're looking for tools to help them build a secure footprint but also enable them to go faster. So, we have a point of view that we're going to continue to see this massive growth and if not, how to accelerate from here. >> Well, you're also the man behind the product. So could you go behind some of the key features that it offers? >> Sure. So, if you think about our overall product portfolio, we really have both breadth and depth. So, first and foremost, most customers who are moving to the cloud or have a large cloud footprint, the first concern they have is, do I have a series of misconfigurations? We really help our customers both identify best practices with those configurations in the cloud, and then also help them move quickly towards potential compliance standards that they need to adhere to. Everyone's operating in a regulated environment these days. And then of course, once you've got that footprint to a place where it's healthy, you really, really want to be able to monitor and track the changes to the configurations over time to ensure you're continuing to maintain that footprint. And so we provide a polygraph based model that essentially identifies potential behavioral risks that we're observing through our data clustering algorithms to help you identify potential holes that you may have created over time and help you remediate those things. And then of course, you know, every customer faces a significant challenge when it comes to just keeping up with the overall landscape changes in terms of overall vulnerability footprint in their environments. And so we have a great capability with what we call vulnerability discovery, which enables our customers to understand where they're vulnerable and not simply tell them how many vulnerabilities they have, but help them isolate, leveraging all the run time and bill time contexts we have so that they can really prioritize what's important to them and what represents the highest risk. And then of course, lastly, you know, where the company really got started is in helping customers protect their cloud workloads. And we do this by identifying threats that we're able to leverage our machine learning and data clustering algorithms so that once we have those baseline behaviors identified and modeled, we can leverage all of our threat intelligence to identify anomalies in that system and help customers really identify those risks as they're coming into the system and deal with those in a really timely manner. So those are kind of the overall key capabilities that they really help teams scale and drive their overall cloud security programs. >> And Arun, really quickly from your perspective, what is a key feature that is really beneficial to LendingTree? >> It's kind of what Adam mentioned with the kind of the self-tuning capability, the reduction of alerts and data based on behavioral-based detection versus rule-based. A lot of people have, you have fancy words, they call AI and machine learning, this and that, but I've rarely seen it work effectively. I think this is a situation where it does work really effectively and does free up time and resources on our side that we can apply to other problems we're trying to solve so I think that's the number one. >> Okay, terrific. Well, I'm really curious Adam. Got to ask you this question. I mean, we saw a really big software IPO last year. What do you think is in store for Lacework? >> Yeah, well, you know, the IPO is just a point in time as opposed to it's part of the journey. Lacework's continuing to invest and really focus on fundamentally changing the security landscape. One of the reasons why I joined Lacework and continue to be really excited about the opportunity comes back to the fundamental challenge that all security tools have. We do not want to create a platform that drives wet blanket behavior, but really fundamentally enables teams like Arun's to move faster and enable the builders to build the applications that fundamentally drive great business outcomes for our customers. And so that's what gets me out of bed. And I think everyone at Lacework is really focused on helping drive great outcomes for our customers. >> Fascinating to hear how Lacework is securing cloud around the world. Lovely to have you on the show. Adam Leftik, the VP of Lacework, as well Arun Sankaran, the CISO of LendingTree. I'm your host for the AWS Startup Network here on theCUBE. Thank you very much for watching.