>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo background tingles) >> Hey everyone, it's so good to see you, welcome back to theCube's day two coverage of MWC 23. We are live in Barcelona, Lisa Martin with Dave Nicholson, Dave we have had no signage of people dropping out, this conference is absolutely jam packed. There's so much interest in the industry, you've had a lot of interviews this morning, before we introduce our guests and have a great conversation about the industry and challenges and how they're being solved, what are some of the things that stuck out to you in conversations today? >> Well, I think the interesting, kind of umbrella conversation, that seems to be overlapping you know, overlying everything is this question about Open RAN and open standards in radio access network technology and where the operators of networks and the providers of technology come together to chart a better path forward. A lot of discussion of private 5G networks, it's very interesting, I think I've said this a few times, from a consumer's perspective, we feel like 5G has been with us for a long time- >> We do. >> But it's very clear that this, that we're really at the beginning of stages of this and I'm super excited for our guests that we have here because we're going to be able to talk to an actual operator- >> Yes. >> And hear what they have to say, we've heard a lot of people talking about the cool stuff they build, but we're going to get to hear from someone who actually works with this stuff, so- >> Who actually built it, absolutely. Please welcome our two guests, we have Ihab Tarazi CTO and SVP at Dell Technologies, and Juan Carlos Garcia SVP Technology Innovation and Ecosystems at Telephonica, it's great to have you guys on the program. >> So, thank you very much. >> So the buzz around this conference is incredible, 80,000 plus people, 2000 exhibitors, it's standing room only. Lot of opportunity in the industry, a lot of challenges though, Juan Carlos we'd love to get your perspective on, what are some of the industry challenges that Telephonica has faced that your peers are probably facing as well? >> Well we have two kinds of challenges, one is a business challenge, I would say that we may find in other industries, like profitability and growth and I will talk about it. And the second challenge is our technology challenge, we need the network to be ready to embrace a new wave of technologies and applications that are, you know, very demanding in terms of network characteristics and features. On the efficiency and profitability and growth, the solution comes as a challenge from changing the way networks are built and operated, from the traditional way to make them become software platforms. And this is not just at the knowledge challenge, it's also changing the mindset of network operators from a network and service provider to a digital service provider, okay? And this means several things, your network needs to become software-based so that you can manage it digitally and on top of it, you need to be able to deliver detail services digitally, okay? So there are three aspects, making your network so (indistinct) and cloud and cloud waste and then be able to sell in a different way to our customers. >> So some pretty significant challenges, but to your point, Juan Carlos, you share some of those challenges with other industries so there's some commonality there. I wanted to bring Ihab into the conversation, from Dell's perspective, we're seeing, you know, the explosion of data. Every company has to be a data company, we expect to have access to data in real time, if it's a new app, whatever it is. What are some of the challenges that you're seeing from your seat at Dell? >> Yeah, I think Juan Carlos explained that really well, what all the operators are talking about here between new applications, think metaverse, think video streaming, going all the way to the edge, think all the automation of factories and everything that's happening. It's not only requiring a whole new model for delivery and for building networks, but it's throwing out enormous amount of data and the data needs to be acted on to get the value of it. So the challenge is how do I collect the data? How do I catalog it? How do I make it usable? And then how do I make it persistent? So you know, it's high performance data storage and then after that, how do I move it to where I want to and be able to use it. And for many applications that has to happen in milliseconds for the value to come out. So now we've seen this before with enterprise but now I would say this digital transformation is happening at very large scale for all the telcos and starting to deal with very familiar themes we've seen before. >> So Juan Carlos, Telephonica, you hear from partners, vendors that they've done this before, don't worry, you're in good hands. >> Juan Carlos: Yeah, yeah. >> But as a practical matter, when you look at the challenges that you have and you think about the things you'll do to address them as you move forward, what are the immediate short term priorities? >> Okay. >> Versus the longer term priorities? What's realistic? You have a network to operate- >> Yeah. >> You're not just building something out of nothing, so you have to keep the lights on. >> Yeah. >> And you have to innovate, we call that by the way, in the CTO trade, ambidextrous, management using both hands, so what's your order of priorities? >> Well, the first thing, new technologies you are getting into the network need to come with a detail shape, so being cloud native, working by software. On the legacies that you need to keep alive, you need to go for a program to switch (indistinct) off progressively, okay? In fact, in Spain we are going to switch up the copper network in two years, so in 2024, Telephonica will celebrate 100 years and the celebration will be switching up the copper network and we'll have on the fixed access only fiber, okay. So more than likely, the network is necessary, all this digitalization may happen only on the new technologies because the new technologies are cloud-based, cloud native, become already ready for this digitalization process. And not only that, so you need also to build new things, we need an abstraction layer on top of the physical infrastructure to be able to manage the network by software, okay. This is something that happened in the computing world, okay, where the servers, you know, were covered with a cloud stack layer and we are doing the same thing in the network. We are trained to abstract the network services and capabilities and be able to offer them digitally to our customers. And this is a process that we are ongoing with many initiatives in the market, so one was the CAMARA community that was opened in Linux Foundation and the other one was the announcement we made yesterday of the open gateway initiative here at Mobile World Congress where all telecom operators have agreed to launch in this year a set of service APIs that are common worldwide, okay. This is a similar thing to what we did with 2G 35 years ago, to agree on a standard way of delivering a service and in this case is digital services based on APIs. >> What's the net result of? What are the benefits of having those open standards? Is it a benefit that myself as a consumer would enjoy? It seems, I mean, I've been, I'm old enough to remember, you know, a time before cellular telephones and I remember a time when it was very, very difficult to travel from North America to Europe with a cell phone. Now I land and my provider says, "Hey, welcome-" >> Juan Carlos: Yes. >> "Welcome, we're going to charge you a little extra money." And I say, "Hallelujah, awesome." So is part of that interoperability a benefit to consumers or, how, what? >> Yeah, you touch the right point. So in the same way you travel anywhere and you want to still make a call and send an SMS and connect to the internet, you will like your applications in your smartphone to work being them edge applications, okay, and these applications, each application will have to work to be executed very close to where you are, in a way that if you travel abroad the visitor network is serving you, okay. So this means that we are somehow extending the current interconnection and roaming agreements between operators to be able also to deliver edge applications wherever you are, in whatever network, with whatever technology. >> We have that expectation on the consumer side, that it's just going to work no matter where we are, we want apps to be updated, whether I'm banking or I'm shopping for groceries, I want to make sure that they know who I am, the data's got to be there, it's got to be real time, it's got to be right, it's got to serve me personally, but it just has to work. You guys talked about some of the big challenges, but also the opportunities in terms of the future of networking, the data turning companies in the data companies. Walk us through the future of networking from Telephonica's lens, you talked about some of the big initiatives that you have by 2024. >> Yes. >> But if you had a crystal ball and you could look in there and go it looks like this for operators, what would you say? And I'd love to get your feedback too. >> Yeah, I liked how Juan Carlos talked about how the future is, I think I want to add one thing to it, to say, a lot of times the user is no longer a consumer, it's an automated thing, you know, AI think robots, so a lot of times, more and more the usage is happening by some autonomous thing and it needs to always connect. And more and more these things are extending to places where even cellular coverage doesn't exist today, so you have edge compute show up. So, and when you think about it, the things we have to solve as a community here and this is all the discussions is, number one, how you make it a fully open standard model, so everything plugs and play, more and more, there's so many pieces coming, software, hardware, from different components and the integration of all of that is probably one of the biggest challenges people want solved. You know, how it's no longer one box, you buy from one person and put it away, now you have a complex combination of hardware and software. Also the operational model is very important and that is one of the areas we're focused on at Dell, is that while the operational model works inside the data centers for certain application, for telcos, it looks different when you're out at the cell tower and you're going to have these extended temperature changes. And sometimes this may not be inside a cabinet, maybe outside and the person servicing it is not an IT technician. This is somebody that needs to know exactly how to plug it, to be able to place equipment quickly and add capacity, those are just two of the areas, the cloud, making it work like a cloud, where it's intuitive, automated and you can easily add capacity, you can, you know, get a lot of monitoring, a lot of metrics, those are some of the things that we're all solving in this community. >> Let's talk about exactly how you're achieving this, Telephonica and Dell have been working together for a couple of years, you said before we went live. Talk about, you're doing this, you talked about the challenges, the opportunities how are you solving them and why with Dell? >> Okay, well you need to go with the right partners, not to this kind of process of transforming your network into a digital platform. There are big challenges on creating the cloud infrastructure that you need to support the complex, functionality and network requires. And I think you need to have with you, companies that know about the processors, that know about the hardware, the server, that know about how to make an abstraction of that hardware layer so that you can manage that digitally and this is not something any company can do, so you need companies that are very specialized. Telecom operators are changing the way to work, we work in the past with traditionally, with network equipment vendors, now we need to start working with technology providers, hardware (indistinct) providers with cloud providers with an ecosystem that is probably wider than what we had in the past. >> Yes. >> So I come from a background, I call myself a "knuckle dragging hardware engineer" sort of guy, so I'm almost fascinated by the physical part of this. You have a network, part of that network includes towers that have transmitters, receivers, at the base of those towers and like you mentioned, they're not all necessarily in urban areas or easy to access. There's equipment there, let's say that, that tower has been there for 5 years, 10 years, in the traditional world of IT, we have this this concept of the "refresh cycle" >> Juan Carlos: Yeah. >> Where a server may have a useful life of 36 months before it's consuming more power than it should based on the technology. How do you move from, kind of a legacy more proprietary, all-inclusive stack to an open system? I mean, is this a, "Okay, we're planning for an outage for the tower and you're wheeling out old equipment and wheeling in new equipment?" >> Juan Carlos: Yeah. >> I mean that's not, that's what we say as a non-trivial exercise, it's something that isn't, it's not something that's just easy to do, but is that what progress looks like? Sort of, methodically one site at a time? >> Yeah, well, I mean, you have touched an important point. In the technology renewal cycles, we were taking an appliance and replacing that by another one. Now with the current technology, you have the couple, the hardware from the software and the hardware, you need to replace it only when you run out of processing capacity to do what you want, okay? So then we'll be there 2, 3, 4, 5 years, whatever, when you need additional capacity, you replace it, but on the software side you can make the replacement every hour, every week. And this is something that the new technologies are bringing, a flexibility for the telecom operator to introduce a new feature without having to be physically there in the place, okay, by software remotely and this is the kind of software network we want to build. >> Lisa Martin: You know- >> Yeah, I want to add to that if I can- >> Please. >> Yeah. >> I think this is one of the biggest benefits of the open model. If the stack is all integrated as one appliance, when a new technology, we all know how quickly selecon technology comes out and now we have GPU's coming out for AI more increasingly, in an appliance model it may take you two years to take advantage of some new selecon that just came out. In this new open model, as Juan Carlos was saying, you just swap out, you know, you have time to market CPUs launched, it can be put out there at the cell tower and it could double capacity instantly and we're going to need that in that world, that easily going to be AI enabled- >> Lisa Martin: Right. >> So- >> So my last question to you, we only got a minute left or so, is given everything that we've talked about, the challenges, the opportunities, what you're doing together, how would you Juan Carlos summarize how the business is benefiting from the Dell partnership and the technologies that you're enabling with this new future network? >> Well, as I said before, we will need to be able to cover all the characteristics and performance of our network. We will need the right kind of processing capacity, the right kind of hardware solutions. We know that the functionality of the network is a very demanding one, we need hardware acceleration, we need a synchronization, we need time-sensitive solutions and all these can only done by hardware, so you need a good hardware partner, that ensures that you have the processing capacity you need to be able then to run your software, you know, with the confidence that it will work and with the performance that you need. >> That confidence is key. Well it sounds like what Telephonica and Dell have achieved together has been quite successful. Congratulations on the first couple of years, sounds like it's really helping Telephonica's business move in the strategic direction that it wants. We appreciate you joining us on the program today, describing all this, thank you both so much for your time. >> Thank you very much. >> Thank you, this was fun. >> A pleasure. >> Good, our pleasure. For our guests and for Dave Nicholson, I'm Lisa Martin, you're watching theCUBE live day two from Barcelona, MWC 23. Don't go anywhere, Dave and I will be right back with our next guests. (cheerful bouncy music)

(lively music) >> Welcome back to our coverage of Cloud Native Security Con. I'm Dave Vellante, here in our Boston studio. We're connecting today, throughout the day, with Palo Alto on the ground in Seattle. And right now I'm here with Michael Foster with Red Hat. He's on the ground in Seattle. We're going to discuss the trends and containers and security and everything that's going on at the show in Seattle. Michael, good to see you, thanks for coming on. >> Good to see you, thanks for having me on. >> Lot of market momentum for Red Hat. The IBM earnings call the other day, announced OpenShift is a billion-dollar ARR. So it's quite a milestone, and it's not often, you know. It's hard enough to become a billion-dollar software company and then to have actually a billion-dollar product alongside. So congratulations on that. And let's start with the event. What's the buzz at the event? People talking about shift left, obviously supply chain security is a big topic. We've heard a little bit about or quite a bit about AI. What are you hearing on the ground? >> Yeah, so the last event I was at that I got to see you at was three months ago, with CubeCon and the talk was supply chain security. Nothing has really changed on that front, although I do think that the conversation, let's say with the tech companies versus what customers are actually looking at, is slightly different just based on the market. And, like you said, thank you for the shout-out to a billion-dollar OpenShift, and ACS is certainly excited to be part of that. We are seeing more of a consolidation, I think, especially in security. The money's still flowing into security, but people want to know what they're running. We've allowed, had some tremendous growth in the last couple years and now it's okay. Let's get a hold of the containers, the clusters that we're running, let's make sure everything's configured. They want to start implementing policies effectively and really get a feel for what's going on across all their workloads, especially with the bigger companies. I think bigger companies allow some flexibility in the security applications that they can deploy. They can have different groups that manage different ones, but in the mid to low market, you're seeing a lot of consolidation, a lot of companies that want basically one security tool to manage them all, so to speak. And I think that the features need to somewhat accommodate that. We talk supply chain, I think most people continue to care about network security, vulnerability management, shifting left and enabling developers. That's the general trend I see. Still really need to get some hands on demos and see some people that I haven't seen in a while. >> So a couple things on, 'cause, I mean, we talk about the macroeconomic climate all the time. We do a lot of survey data with our partners at ETR, and their recent data shows that in terms of cost savings, for those who are actually cutting their budgets, they're looking to consolidate redundant vendors. So, that's one form of consolidation. The other theme, of course, is there's so many tools out in the security market that consolidating tools is something that can help simplify, but then at the same time, you see opportunities open up, like IOT security. And so, you have companies that are starting up to just do that. So, there's like these countervailing trends. I often wonder, Michael, will this ever end? It's like the universe growing and tooling, what are your thoughts? >> I mean, I completely agree. It's hard to balance trying to grow the company in a time like this, at the same time while trying to secure it all, right? So you're seeing the consolidation but some of these applications and platforms need to make some promises to say, "Hey, we're going to move into this space." Right, so when you have like Red Hat who wants to come out with edge devices and help manage the IOT devices, well then, you have a security platform that can help you do that, that's built in. Then the messaging's easy. When you're trying to do that across different cloud providers and move into IOT, it becomes a little bit more challenging. And so I think that, and don't take my word for this, some of those IOT startups, you might see some purchasing in the next couple years in order to facilitate those cloud platforms to be able to expand into that area. To me it makes sense, but I don't want to hypothesize too much from the start. >> But I do, we just did our predictions post and as a security we put up the chart of candidates, and there's like dozens, and dozens, and dozens. Some that are very well funded, but I mean, you've seen some down, I mean, down rounds everywhere, but these many companies have raised over a billion dollars and it's like uh-oh, okay, so they're probably okay, maybe. But a lot of smaller firms, I mean there's just, there's too many tools in the marketplace, but it seems like there is misalignment there, you know, kind of a mismatch between, you know, what customers would like to have happen and what actually happens in the marketplace. And that just underscores, I think, the complexities in security. So I guess my question is, you know, how do you look at Cloud Native Security, and what's different from traditional security approaches? >> Okay, I mean, that's a great question, and it's something that we've been talking to customers for the last five years about. And, really, it's just a change in mindset. Containers are supposed to unleash developer speed, and if you don't have a security tool to help do that, then you're basically going to inhibit developers in some form or another. I think managing that, while also giving your security teams the ability to tell the message of we are being more secure. You know, we're limiting vulnerabilities in our cluster. We are seeing progress because containers, you know, have a shorter life cycle and there is security and speed. Having that conversation with the C-suites is a little different, especially when how they might be used to virtual machines and managing it through that. I mean, if it works, it works from a developer's standpoint. You're not taking advantage of those containers and the developer's speed, so that's the difference. Now doing that and then first challenge is making that pitch. The second challenge is making that pitch to then scale it, so you can get onboard your developers and get your containers up and running, but then as you bring in new groups, as you move over to Kubernetes or you get into more container workloads, how do you onboard your teams? How do you scale? And I tend to see a general trend of a big investment needed for about two years to make that container shift. And then the security tools come in and really blossom because once that core separation of responsibilities happens in the organization, then the security tools are able to accelerate the developer workflow and not inhibit it. >> You know, I'm glad you mentioned, you know, separation of responsibilities. We go to a lot of shows, as you know, with theCUBE, and many of them are cloud shows. And in the one hand, Cloud has, you know, obviously made the world, you know, more interesting and better in so many different ways and even security, but it's like new layers are forming. You got the cloud, you got the shared responsibility model, so the cloud is like the first line of defense. And then you got the CISO who is relying heavily on devs to, you know, the whole shift left thing. So we're asking developers to do a lot and then you're kind of behind them. I guess you have audit is like the last line of defense, but my question to you is how can software developers really ensure that cloud native tools that they're using are secure? What steps can they take to improve security and specifically what's Red Hat doing in that area? >> Yeah, well I think there's, I would actually move away from that being the developer responsibility. I think the job is the operators' and the security people. The tools to give them the ability to see. The vulnerabilities they're introducing. Let's say signing their images, actually verifying that the images that's thrown in the cloud, are the ones that they built, that can all be done and it can be done open source. So we have a DevSecOps validated pattern that Red Hat's pushed out, and it's all open source tools in the cloud native space. And you can sign your builds and verify them at runtime and make sure that you're doing that all for free as one option. But in general, I would say that the hope is that you give the developer the information to make responsible choices and that there's a dialogue between your security and operations and developer teams but security, we should not be pushing that on developer. And so I think with ACS and our tool, the goal is to get in and say, "Let's set some reasonable policies, have a conversation, let's get a security liaison." Let's say in the developer team so that we can make some changes over time. And the more we can automate that and the more we can build and have that conversation, the better that you'll, I don't say the more security clusters but I think that the more you're on your path of securing your environment. >> How much talk is there at the event about kind of recent high profile incidents? We heard, you know, Log4j, of course, was mentioned in the Keynote. Somebody, you know, I think yelled out from the audience, "We're still dealing with that." But when you think about these, you know, incidents when looking back, what lessons do you think we've learned from these events? >> Oh, I mean, I think that I would say, if you have an approach where you're managing your containers, managing the age and using containers to accelerate, so let's say no images that are older than 90 days, for example, you're going to avoid a lot of these issues. And so I think people that are still dealing with that aspect haven't set up the proper, let's say, disclosure between teams and update strategy and so on. So I don't want to, I think the Log4j, if it's still around, you know, something's missing there but in general you want to be able to respond quickly and to do that and need the tools and policies to be able to tell people how to fix that issue. I mean, the Log4j fix was seven days after, so your developers should have been well aware of that. Your security team should have been sending the messages out. And I remember even fielding all the calls, all the fires that we had to put out when that happened. But yeah. >> I thought Brian Behlendorf's, you know, talk this morning was interesting 'cause he was making an attempt to say, "Hey, here's some things that you might not be thinking about that are likely to occur." And I wonder if you could, you know, comment on them and give us your thoughts as to how the industry generally, maybe Red Hat specifically, are thinking about dealing with them. He mentioned ChatGPT or other GPT to automate Spear phishing. He said the identity problem is still not fixed. Then he talked about free riders sniffing repos essentially for known vulnerabilities that are slow to fix. He talked about regulations that might restrict shipping code. So these are things that, you know, essentially, we can, they're on the radar, but you know, we're kind of putting out, you know, yesterday's fire. What are your thoughts on those sort of potential issues that we're facing and how are you guys thinking about it? >> Yeah, that's a great question, and I think it's twofold. One, it's brought up in front of a lot of security leaders in the space for them to be aware of it because security, it's a constant battle, constant war that's being fought. ChatGPT lowers the barrier of entry for a lot of them, say, would-be hackers or people like that to understand systems and create, let's say, simple manifests to leverage Kubernetes or leverage a misconfiguration. So as the barrier drops, we as a security team in security, let's say group organization, need to be able to respond and have our own tools to be able to combat that, and we do. So a lot of it is just making sure that we shore up our barriers and that people are aware of these threats. The harder part I think is educating the public and that's why you tend to see maybe the supply chain trend be a little bit ahead of the implementation. I think they're still, for example, like S-bombs and signing an attestation. I think that's still, you know, a year, two years, away from becoming, let's say commonplace, especially in something like a production environment. Again, so, you know, stay bleeding edge, and then make sure that you're aware of these issues and we'll be constantly coming to these calls and filling you in on what we're doing and make sure that we're up to speed. >> Yeah, so I'm hearing from folks like yourself that the, you know, you think of the future of Cloud Native Security. We're going to see continued emphasis on, you know, better integration of security into the DevSecOps. You're pointing out it's really, you know, the ops piece, that runtime that we really need to shore up. You can't just put it on the shoulders of the devs. And, you know, using security focused tools and best practices. Of course you hear a lot about that and the continued drive toward automation. My question is, you know, automation, machine learning, how, where are we in that maturity cycle? How much of that is being adopted? Sometimes folks are, you know, they embrace automation but it brings, you know, unknown, unintended consequences. Are folks embracing that heavily? Are there risks associated around that, or are we kind of through that knothole in your view? >> Yeah, that's a great question. I would compare it to something like a smart home. You know, we sort of hit a wall. You can automate so much, but it has to actually be useful to your teams. So when we're going and deploying ACS and using a cloud service, like one, you know, you want something that's a service that you can easily set up. And then the other thing is you want to start in inform mode. So you can't just automate everything, even if you're doing runtime enforcement, you need to make sure that's very, very targeted to exactly what you want and then you have to be checking it because people start new workloads and people get onboarded every week or month. So it's finding that balance between policies where you can inform the developer and the operations teams and that they give them the information to act. And that worst case you can step in as a security team to stop it, you know, during the onboarding of our ACS cloud service. We have an early access program and I get on-calls, and it's not even security team, it's the operations team. It starts with the security product, you know, and sometimes it's just, "Hey, how do I, you know, set this policy so my developers will find this vulnerability like a Log4Shell and I just want to send 'em an email, right?" And these are, you know, they have the tools and they can do that. And so it's nice to see the operations take on some security. They can automate it because maybe you have a NetSec security team that doesn't know Kubernetes or containers as well. So that shared responsibility is really useful. And then just again, making that automation targeted, even though runtime enforcement is a constant thing that we talk about, the amount that we see it in the wild where people are properly setting up admission controllers and it's acting. It's, again, very targeted. Databases, cubits x, things that are basically we all know is a no-go in production. >> Thank you for that. My last question, I want to go to the, you know, the hardest part and 'cause you're talking to customers all the time and you guys are working on the hardest problems in the world. What is the hardest aspect of securing, I'm going to come back to the software supply chain, hardest aspect of securing the software supply chain from the perspective of a security pro, software engineer, developer, DevSecOps Pro, and then this part b of that is, is how are you attacking that specifically as Red Hat? >> Sure, so as a developer, it's managing vulnerabilities with updates. As an operations team, it's keeping all the cluster, because you have a bunch of different teams working in the same environment, let's say, from a security team. It's getting people to listen to you because there are a lot of things that need to be secured. And just communicating that and getting it actionable data to the people to make the decisions as hard from a C-suite. It's getting the buy-in because it's really hard to justify the dollars and cents of security when security is constantly having to have these conversations with developers. So for ACS, you know, we want to be able to give the developer those tools. We also want to build the dashboards and reporting so that people can see their vulnerabilities drop down over time. And also that they're able to respond to it quickly because really that's where the dollars and cents are made in the product. It's that a Log4Shell comes out. You get immediately notified when the feeds are updated and you have a policy in action that you can respond to it. So I can go to my CISOs and say, "Hey look, we're limiting vulnerabilities." And when this came out, the developers stopped it in production and we were able to update it with the next release. Right, like that's your bread and butter. That's the story that you want to tell. Again, it's a harder story to tell, but it's easy when you have the information to be able to justify the money that you're spending on your security tools. Hopefully that answered your question. >> It does. That was awesome. I mean, you got data, you got communication, you got the people, obviously there's skillsets, you have of course, tooling and technology is a big part of that. Michael, really appreciate you coming on the program, sharing what's happening on the ground in Seattle and can't wait to have you back. >> Yeah. Awesome. Thanks again for having me. >> Yeah, our pleasure. All right. Thanks for watching our coverage of the Cloud Native Security Con. I'm Dave Vellante. I'm in our Boston studio. We're connecting to Palo Alto. We're connecting on the ground in Seattle. Keep it right there for more coverage. Be right back. (lively music)

>>The cube presents Ignite 22, brought to you by Palo Alto Networks. >>Good morning. Live from the MGM Grand. It's the cube at Palo Alto Networks Ignite 2022. Lisa Martin here with Dave Valante, day two, Dave of our coverage, or last live day of the year, which I can't believe, lots of good news coming out from Palo Alto Networks. We're gonna sit down with its Chief product officer next and dissect all of that. >>Yeah. You know, oftentimes in, in events like this, day two is product day. And look, it's all about products and sales. Yeah, I mean those, that's the, the, the golden rule. Get the product right, get the sales right, and everything else will take care of itself. So let's talk product. >>Yeah, let's talk product. Lee Claridge joins us, the Chief Product Officer at Palo Alto Networks. Welcome Lee. Great to have >>You. Thank you so much. >>So we didn't get to see your keynote yesterday, but we heard one of the things, you know, we've been talking about the threat landscape, the challenges. We had Unit 42, Wendy on yesterday. We had Nash on and near talking about the massive challenges in the threat landscape. But we understand, despite that you are optimistic. I am. Talk about your optimism given the massive challenges that every organization is facing today. >>Look, cybersecurity's hard and often in cybersecurity in the industry, a lot of people get sort of really focused on what the threat actors are doing, why they're successful. We investigate breaches and we think of it, it just starts to feel somewhat overwhelming for a lot of folks. And I just happen to think a little bit differently. I, I look at it and I think it's actually a solvable problem. >>Talk about cyber resilience. How does Palo Alto Networks define that and how does it help customers achieve that? Cuz that's the, that's the holy grail these days. >>Yes. Look, the, the way I think about cyber resilience is basically in two pieces. One, it's all about how do we prevent the threat actors from actually being successful in the first place. Second, we also have to be prepared for what happens if they happen to find a way to get through, and how do we make sure that that happens? The blast radius is, is as narrowly contained as possible. And so the, the way that we approach this is, you know, I, I kind of think in terms of like threes three core principles. Number one, we have to have amazing technology and we have to constantly be, keep keeping up with and ideally ahead of what attackers are doing. It's a big part of my job as the chief product officer, right? Second is we, you know, one of the, the big transformations that's happened is the advent of, of AI and the opportunity, as long as we can do it, a great job of collecting great data, we can drive AI and machine learning models that can start to be used for our advantage as defenders, and then further use that to drive automation. >>So we take the human out of the response as much as possible. What that allows us to do is actually to start using AI and automation to disrupt attackers as it's happening. The third piece then becomes natively integrating these capabilities into a platform. And when we do that, what allows us to do is to make sure that we are consistently delivering cybersecurity everywhere that it needs to happen. That we don't have gaps. Yeah. So great tech AI and automation deliver natively integrated through platforms. This is how we achieve cyber resilience. >>So I like the positivity. In fact, Steven Schmidt, who's now the CSO of, of Amazon, you know, Steven, and it was the CSO at AWS at the time, the first reinforced, he stood up on stage and said, listen, this narrative that's all gloom and doom is not the right approach. We actually are doing a good job and we have the capability. So I was like, yeah, you know, okay. I'm, I'm down with that. Now when I, my question is around the, the portfolio. I, I was looking at, you know, some of your alternatives and options and the website. I mean, you got network security, cloud security, you got sassy, you got capp, you got endpoint, pretty much everything. You got cider security, which you just recently acquired for, you know, this whole shift left stuff, you know, nothing in there on identity yet. That's good. You partner for that, but, so could you describe sort of how you think about the portfolio from a product standpoint? How you continue to evolve it and what's the direction? Yes. >>So the, the, the cybersecurity industry has long had this, I'm gonna call it a major flaw. And the major flaw of the cybersecurity industry has been that every time there is a problem to be solved, there's another 10 or 20 startups that get funded to solve that problem. And so pretty soon what you have is you're, if you're a customer of this is you have 50, a hundred, the, the record is over 400 different cybersecurity products that as a customer you're trying to operationalize. >>It's not a good record to have. >>No, it's not a good record. No. This is, this is the opposite of Yes. Not a good personal best. So the, so the reason I start there in answering your question is the, the way that, so that's one end of the extreme, the other end of the extreme view to say, is there such a thing as a single platform that does everything? No, there's not. That would be nice. That was, that sounds nice. But the reality is that cybersecurity has to be much broader than any one single thing can do. And so the, the way that we approach this is, is three fundamental areas that, that we, Palo Alto Networks are going to be the best at. One is network security within network security. This includes hardware, NextGen, firewalls, software NextGen, firewalls, sassy, all the different security services that tie into that. All of that makes up our network security platforms. >>So everything to do with network security is integrated in that one place. Second is around cloud security. The shift to the cloud is happening is very real. That's where Prisma Cloud takes center stage. C a P is the industry acronym. If if five letters thrown together can be called an acronym. The, so cloud native application protection platform, right? So this is where we bring all of the different cloud security capabilities integrated together, delivered through one platform. And then security, security operations is the third for us. This is Cortex. And this is where we bring together endpoint security, edr, ndr, attack, surface management automation, all of this. And what we had, what we announced earlier this year is x Im, which is a Cortex product for actually integrating all of that together into one SOC transformation platform. So those are the three platforms, and that's how we deliver much, much, much greater levels of native integration of capabilities, but in a logical way where we're not trying to overdo it. >>And cider will fit into two or three >>Into Prisma cloud into the second cloud to two. Yeah. As part of the shift left strategy of how we secure makes sense applications in the cloud >>When you're in customer conversations. You mentioned the record of 400 different product. That's crazy. Nash was saying yesterday between 30 and 50 and we talked with him and near about what's realistic in terms of getting organizations to, to be able to consolidate. I'd love to understand what does cybersecurity transformation look like for the average organization that's running 30 to 50 point >>Solutions? Yeah, look, 30 to 50 is probably, maybe normal. A hundred is not unusual. Obviously 400 is the extreme example. But all of those are, those numbers are too big right now. I think, I think realistic is high. Single digits, low double digits is probably somewhat realistic for most organizations, the most complex organizations that might go a bit above that if we're really doing a good job. That's, that's what I think. Now second, I do really want to point out on, on the product guy. So, so maybe this is just my way of thinking, consolidation is an outcome of having more tightly and natively integrated capabilities. Got you. And the reason I flip that around is if I just went to you and say, Hey, would you like to consolidate? That just means maybe fewer vendors that that helps the procurement person. Yes. You know, have to negotiate with fewer companies. Yeah. Integration is actually a technology statement. It's delivering better outcomes because we've designed multiple capabilities to work together natively ourselves as the developers so that the customer doesn't have to figure out how to do it. It just happens that by, by doing that, the customer gets all this wonderful technical benefit. And then there's this outcome sitting there called, you've just consolidated your complexity. How >>Specialized is the customer? I think a data pipelines, and I think I have a data engineer, have a data scientists, a data analyst, but hyper specialized roles. If, if, let's say I have, you know, 30 or 40, and one of 'em is an SD wan, you know, security product. Yeah. I'm best of breed an SD wan. Okay, great. Palo Alto comes in as you, you pointed out, I'm gonna help you with your procurement side. Are there hyper specialized individuals that are aligned to that? And how that's kind of part A and B, how, assuming that's the case, how does that integration, you know, carry through to the business case? So >>Obviously there are specializations, this is the, and, and cybersecurity is really important. And so there, this is why there had, there's this tendency in the past to head toward, well I have this problem, so who's the best at solving this one problem? And if you only had one problem to solve, you would go find the specialist. The, the, the, the challenge becomes, well, what do you have a hundred problems to solve? I is the right answer, a hundred specialized solutions for your a hundred problems. And what what I think is missing in this approach is, is understanding that almost every problem that needs to be solved is interconnected with other problems to be solved. It's that interconnectedness of the problems where all of a sudden, so, so you mentioned SD wan. Okay, great. I have Estee wan, I need it. Well what are you connecting SD WAN to? >>Well, ideally our view is you would connect SD WAN and branch to the cloud. Well, would you run in the cloud? Well, in our case, we can take our SD wan, connect it to Prisma access, which is our cloud security solution, and we can natively integrate those two things together such that when you use 'em together, way easier. Right? All of a sudden we took what seemed like two separate problems. We said, no, actually these problems are related and we can deliver a solution where those, those things are actually brought together. And that's just one simple example, but you could, you could extend that across a lot of these other areas. And so that's the difference. And that's how the, the, the mindset shift that is happening. And, and I I was gonna say needs to happen, but it's starting to happen. I'm talking to customers where they're telling me this as opposed to me telling them. >>So when you walk around the floor here, there's a visual, it's called a day in the life of a fuel member. And basically what it has, it's got like, I dunno, six or seven different roles or personas, you know, one is management, one is a network engineer, one's a coder, and it gives you an X and an O. And it says, okay, put the X on things that you spend your time doing, put the o on things that you wanna spend your time doing a across all different sort of activities that a SecOps pro would do. There's Xs and O's in every one of 'em. You know, to your point, there's so much overlap going on. This was really difficult to discern, you know, any kind of consistent pattern because it, it, it, unlike the hyper specialization and data pipelines that I just described, it, it's, it's not, it, it, there's way more overlap between those, those specialization roles. >>And there's a, there's a second challenge that, that I've observed and that we are, we've, we've been trying to solve this and now I'd say we've become, started to become a lot more purposeful in, in, in trying to solve this, which is, I believe cybersecurity, in order for cyber security vendors to become partners, we actually have to start to become more opinionated. We actually have to start, guys >>Are pretty opinionated. >>Well, yes, but, but the industry large. So yes, we're opinionated. We build these products, but that have, that have our, I'll call our opinions built into it, and then we, we sell the, the product and then, and then what happens? Customer says, great, thank you for the product. I'm going to deploy it however I want to, which is fine. Obviously it's their choice at the end of the day, but we actually should start to exert an opinion to say, well, here's what we would recommend, here's why we would recommend that. Here's how we envisioned it providing the most value to you. And actually starting to build that into the products themselves so that they start to guide the customer toward these outcomes as opposed to just saying, here's a product, good luck. >>What's, what's the customer lifecycle, not lifecycle, but really kind of that, that collaboration, like it's one thing to, to have products that you're saying that have opinions to be able to inform customers how to deploy, how to use, but where is their feedback in this cycle of product development? >>Oh, look, my, this, this is, this is my life. I'm, this is, this is why I'm here. This is like, you know, all day long I'm meeting with customers and, and I share what we're doing. But, but it's, it's a, it's a 50 50, I'm half the time I'm listening as well to understand what they're trying to do, what they're trying to accomplish, and how, what they need us to do better in order to help them solve the problem. So the, the, and, and so my entire organization is oriented around not just telling customers, here's what we did, but listening and understanding and bringing that feedback in and constantly making the products better. That's, that's the, the main way in which we do this. Now there's a second way, which is we also allow our products to be customized. You know, I can say, here's our best practices, we see it, but then allowing our customer to, to customize that and tailor it to their environment, because there are going to be uniquenesses for different customers in parti, we need more complex environments. Explain >>Why fire firewalls won't go away >>From your perspective. Oh, Nikesh actually did a great job of explaining this yesterday, and although he gave me credit for it, so this is like a, a circular kind of reference here. But if you think about the firewalls slightly more abstract, and you basically say a NextGen firewalls job is to inspect every connection in order to make sure the connection should be allowed. And then if it is allowed to make sure that it's secure, >>Which that is the definition of an NextGen firewall, by the way, exactly what I just said. Now what you noticed is, I didn't describe it as a hardware device, right? It can be delivered in hardware because there are environments where you need super high throughput, low latency, guess what? Hardware is the best way of delivering that functionality. There's other use cases cloud where you can't, you, you can't ship hardware to a cloud provider and say, can you install this hardware in front of my cloud? No, no, no. You deployed in a software. So you take that same functionality, you instantly in a software, then you have other use cases, branch offices, remote workforce, et cetera, where you say, actually, I just want it delivered from the cloud. This is what sassy is. So when I, when I look at and say, the firewall's not going away, what, what, what I see is the functionality needed is not only not going away, it's actually expanding. But how we deliver it is going to be across these three form factors. And then the customer's going to decide how they need to intermix these form factors for their environment. >>We put forth this notion of super cloud a while about a year ago. And the idea being you're gonna leverage the hyperscale infrastructure and you're gonna build a, a, you're gonna solve a common problem across clouds and even on-prem, super cloud above the cloud. Not Superman, but super as in Latin. But it turned into this sort of, you know, superlative, which is fun. But the, my, my question to you is, is, is, is Palo Alto essentially building a common cross-cloud on-prem, presumably out to the edge consistent experience that we would call a super cloud? >>Yeah, I don't know that we've ever used the term surfer cloud to describe it. Oh, you don't have to, but yeah. But yes, based on how you describe it, absolutely. And it has three main benefits that I describe to customers all the time. The first is the end user experience. So imagine your employee, and you might work from the office, you might work from home, you might work while from, from traveling and hotels and conferences. And, and by the way, in one day you might actually work from all of those places. So, so the first part is the end user experience becomes way better when it doesn't matter where they're working from. They always get the same experience, huge benefit from productivity perspective, no second benefit security operations. You think about the, the people who are actually administering these policies and analyzing the security events. >>Imagine how much better it is for them when it's all common and consistent across everywhere that has to happen. Cloud, on-prem branch, remote workforce, et cetera. So there's a operational benefit that is super valuable. Third, security benefit. Imagine if in this, this platform-based approach, if we come out with some new amazing innovation that is able to detect and block, you know, new types of attacks, guess what, we can deliver that across hardware, software, and sassi uniformly and keep it all up to date. So from a security perspective, way better than trying to figure out, okay, there's some new technology, you know, does my hardware provider have that technology or not? Does my soft provider? So it's bringing that in to one place. >>From a developer perspective, is there a, a, a PAs layer, forgive me super PAs, that a allows the developers to have a common experience across irrespective of physical location with the explicit purpose of serving the objective of your platform. >>So normally when I think of the context of developers, I'm thinking of the context of, of the people who are building the applications that are being deployed. And those applications may be deployed in a data center, increasing the data centers, depending private clouds might be deployed into, into public cloud. It might even be hybrid in nature. And so if you think about what the developer wants, the developer actually wants to not have to think about security, quite frankly. Yeah. They want to think about how do I develop the functionality I need as quickly as possible with the highest quality >>Possible, but they are being forced to think about it more and more. Well, but anyway, I didn't mean to >>Interrupt you. No, it's a, it is a good, it's a, it's, it's a great point. The >>Well we're trying to do is we're trying to enable our security capabilities to work in a way that actually enables what the developer wants that actually allows them to develop faster that actually allows them to focus on the things they want to focus. And, and the way we do that is by actually surfacing the security information that they need to know in the tools that they use as opposed to trying to bring them to our tools. So you think about this, so our customer is a security customer. Yet in the application development lifecycle, the developer is often the user. So we, we we're selling, we're so providing a solution to security and then we're enabling them to surface it in the developer tools. And by, by doing this, we actually make life easier for the developers such that they're not actually thinking about security so much as they're just saying, oh, I pulled down the wrong open source package, it's outdated, it has vulnerabilities. I was notified the second I did it, and I was told which one I should pull down. So I pulled down the right one. Now, if you're a developer, do you think that's security getting your way? Not at all. No. If you're a developer, you're thinking, thank god, thank you, thank, thank you. Yeah. You told me at a point where it was easy as opposed to waiting a week or two and then telling me where it's gonna be really hard to fix it. Yeah. Nothing >>More than, so maybe be talking to Terraform or some other hash corp, you know, environment. I got it. Okay. >>Absolutely. >>We're 30 seconds. We're almost out of time. Sure. But I'd love to get your snapshot. Here we are at the end of calendar 2022. What are you, we know you're optimistic in this threat landscape, which we're gonna see obviously more dynamics next year. What kind of nuggets can you drop about what we might hear and see in 23? >>You're gonna see across everything. We do a lot more focus on the use of AI and machine learning to drive automated outcomes for our customers. And you're gonna see us across everything we do. And that's going to be the big transformation. It'll be a multi-year transformation, but you're gonna see significant progress in the next 12 months. All >>Right, well >>What will be the sign of that progress? If I had to make a prediction, which >>I'm better security with less effort. >>Okay, great. I feel like that's, we can measure that. I >>Feel, I feel like that's a mic drop moment. Lee, it's been great having you on the program. Thank you for walking us through such great detail. What's going on in the organization, what you're doing for customers, where you're meeting, how you're meeting the developers, where they are. We'll have to have you back. There's just, just too much to unpack. Thank you both so much. Actually, our pleasure for Lee Cler and Dave Valante. I'm Lisa Martin. You're watching The Cube Live from Palo Alto Networks Ignite 22, the Cube, the leader in live, emerging and enterprise tech coverage.

(upbeat music) >> Welcome back to Fal.Con 2022. My name is Dave Vallante. We're here with my co-host Dave Nicholson. On the last earnings call George Kurts made a really big emphasis on the relationship with managed service providers. CrowdStrike has announced a new service provider capability. The powered service provider program. Jason Cook is here. He is the president of cyber defense labs. He's joined by Mike Riolo. Who's the vice president of global system integrators and service providers at CrowdStrike gents. Welcome to TheCube. Good to see you. >> Thank you very much. >> Thank you >> Jason, tell us about cyber defense labs. What do you guys do? Give us the bumper sticker, please. >> Cyber defense labs uses the best technology in the world to put together services that help protect our clients >> Simple. Like it. What's XDR? (people laughing) >> I've not heard of that before, sorry. >> So Mike, we've seen the rise of service providers. I saw a stat, I don't know, six, seven months ago that 50% of us companies don't even have a SOC. We're talking about mid to large companies. So service providers are crucial. What's the CrowdStrike powered service provider program all about? >> Well, it's an evolution for us. We've been dealing with this market for some time. And the idea is, is like how do we expand the opportunity to stop reaches? I mean, that's what it's all about. Like how more routes to market, more partners like cyber defense labs that can really go in and bring our technology coupled with their services to power their offerings to their customers and just help us reach every end user out there, to stop reaches. >> So Jason, how do you guys differentiate? Cause I see, you know, as an analyst, I'll look back, I'll read the press releases and they'll see, okay. They just look so similar. So how do you differentiate from the competition? What do you tell customers? >> So when it comes to our selection of technology we test it, we work it, we literally put it into real world situations with our clients. And then we differentiate ourselves with expert services. It's a white glove service from us. We embed ourselves right in with our clients. That's why we call 'em our client partners. And they see us as part of their team and extension of their team. They don't have the time to play with technology and work out what's best. They don't know the time to select it or even then the expertise to use it effectively in the environment. So that's where the trust comes in with us. And then for us, likewise, we are the technology provider such as CrowdStrick, we need to know the technology works and it does what it says. >> I always ask CISOs; What's your number one challenge? And they'll say lack of talent. The only time I didn't get that answer was at... The Mongo DB CISO at reinforced. I'm like yeah, it's cause you're Mongo, I guess reinforced or AWS doesn't have the same problem, but do you... Obviously you see that problem. And you compliment that, is that a fair? >> Yeah, absolutely. Many, many companies mid-market enterprises are really struggling to find talent and then retain the talent. So for us where that's all we are about and then we are there to enable your business to do what your business does. It is just working and I think more and more so you're going to see an industry clearly CrowdStrike's going in that direction. That it's the service provider that becomes a critical element of that trusted circle. >> Does that translate into a market segment by size of organization typically or? You mentioned the ever never ending quest for talent which is critical regardless of size but what does your target market look like? >> So I, I think the biggest gap in the market frankly, is still the mid-market. Many smaller companies still are really just struggling with 'what is the problem.' At least in the mid-market, in the enterprises they really beginning to understand the problem and want to invest and lean in. And here's the irony. They now want to partner to solve the problem cause they recognize they can't do it on their own. >> So Mike, what are the critical aspects of this program? I mean, got the press release out there, but put some meat on the bone for us. >> So if you look at what we were doing to enable managed service providers to go in and, and be powered by CrowdStrike before it was in a corporate market segment it was a specific set of product from us to really enable MDR, you know, sort of that, that generation of services that a lot of customers looked at MSPs for. And what the big message about this is is we are now expanding that. We're taking it out of corporate, we're going upmarket, we're going enterprise. We can leverage partners like cyber defense labs to package our software into their offering and help them power them more than just endpoint. Right? We've had a lot of exciting announcements and probably more to come around identity, you know XDR, the new buzz, right? Like what does it mean? And in, if you look at our approach, it's a very platform centric approach and that's something that partners can monetize. That's something that partners can really help clients grow with is that it's not just about endpoint. It's more about how do I make sure that I'm in a position with a partner that allows me to grow as a market decides it's necessary. So things like identity, cloud on and on and on, that we're investing in and continuing to grow. We are making that available to the CrowdStrike powered service about our marketplace. >> So Jason, service providers historically outsourcing, okay. And it used to be a lot of; 'okay, you know, I'll take over your mess for less kind of thing.' Right? And so the pattern was you would have one of everything and then, that limited your scale. The bigger you got, you had this economies of scale. So am I hearing that, like how do you partner with CrowdStrike? Are you kind of standardizing on that platform or not necessarily cause you have to be agnostic. What's your posture on that? >> So there's a level of, you have to be technology agnostic. We pride ourselves in just using the best technology that's out there. But at the same time, very much with the Fal.Con platform they're building out and maturing in a way that's making significant risk mitigation abilities for a solution provider like us to say we'll take one of those, one of those and put our service around it because that's the best fit service to reduce the risk of this particular client. And having that flexibility for us to do that really allows us then to stay within the same sort of product suite rather than going outside when integration is still one of the biggest challenges that you have. >> So you're one of those organizations that's consolidating a bevy of point tools. Is that right? I mean, you're going through that transformation now. Have you already gone through that? What's your journey look like there? >> Oh, we help companies do that. That's how they mitigate and reduce their risk. >> Okay. But you're using tools as, as well. Are you not? So I mean, you've got to also I mean you're like an extension of those clients. >> Absolutely. So it comes down to a lot of the time do you have the right team? We have a team of experts that deliver expert services. You get to a level of skillset and experience, which goes what's just the best tool out there. And it becomes that's our insight. So one of the reasons why we like the Fal.Con product is because regardless of what the mess is, that's happening you can rapidly deploy stuff to make a difference. And then you then work out how to fix the mess which is quite a change from how traditionally things are done, which is let's analyze the problem. Let's look at options around it. And by the time you've done that time has passed and you can't afford to just allow time to pass these days. So having the right technology allows you to rapidly deploy. Of course, we use what we sell. So we are proud to say that we use a number of the Fal.Con products to protect ourselves and consolidate onto that technology as we then offer that out as a service to our clients. >> So Mike, I'm thinking about the program in general and specifically how you are implementing this program thinking about the path to bringing the customer on board. There are a finite number of strategic seats at any customer's table. So who is at the customer's table? Is it CDL saying; 'Hey, I'm going to bring in my folks from CrowdStrike to have a conversation with you.' Is it CrowdStrike saying; 'Hey, it looks like a service provider might be the best solution for you. Let's go talk to CDL.' How does that work? >> It's a great question. And I think we talk a lot about how there's a gap in people to support cyber efforts inside of companies. But we don't talk about the gap in like experts that can go in and actually sit down with CISOs, with CIOs, with CFOs. And so for us, like it's all about the flexibility. It's it's what do you need in the moment? Because at the end of the day, it comes down to the people. If Jason has a great trusted relationship, he's like; 'Hey I just need some content.' 'Help me push why we're powered by CrowdStrike in this moment.' Great, go run. If we have an opportunity where we know that cyber defense labs has a presence then we go in together, right? Like that flexibility is there. We've done a lot. When you build a program like this, like it's easy to tell the market what they need. It's easy to tell everybody, but it's also you're looking at a cultural shift and how CrowdStrike goes to market, right? Like this is all about how do we get every possible route to market to stop reaches for customers of all size. >> I would echo that. there's three ways that that's working for our two companies at the moment. Many times a lot of the relationships that we have are trusted advisor at the owner or board level of these mid-market and enterprise companies. They're looking to ask for a number of things. And one of the things that we then say is, Hey for your technology roadmap, hey we want to bring in co-present coded us, co-discuss co-strategize with you what your roadmap is. And so we often bring CrowdStrike into the conversations that cyber defense lab is having at the board level. Then on the other side, CrowdStrike obviously has a significant sales force and trusted advisors. They go in with the product and then it's apparent that the you know, the client wants way more than just the product. They say, this is great. I love it. I've made my decision, but I can't operate it effectively. And so we then get pulled in from that perspective >> You get to all the time from product companies, right? It's like, okay, now what? How do I do this? And you go, oh, I'll call somebody. So this is going to accelerate. You go to market. >> Well, and everybody looks at it like, you know how does your sales play with their sales, right? Everyone's going after the same thing. And I'm, you know, that's important, but you have to look at CrowdStrike as more than sales, right? We have an amazing threat intel group that are helping clients understand the risk factors and what bad people are trying to do to them. We can bring so many experts to the side of a cyber defense labs in, in that realm. You know, we've been doing this a long time. >> This is what's interesting to me when I think about your threat hunting, because you guys are experts and you guys are experts. But the... Correct me if I'm wrong. But the advantage I see at the CrowdStrike has is your cloud platform allows you to have such a huge observation space. You got a ton of data and you bring that to the relationship as well and then you benefit from that? >> It's two way. It's absolutely two way. CrowdStrike has a whole bunch of experts and expertise in this space. So do cyber defense labs. We call it for us because we're providing a service to multiple clients. Many of them have a global presence. We call it our global threat view. And absolutely we are exchanging real time threat telemetry data with, with our friends at CrowdStrike Which is impacting the value that we have and the ability to respond extremely quickly when something's happening to one of our clients. >> Well, I just add to that, you know if you look at all of our alliances, right? We've got solution providers, tech reliant, everything. The one thing that's really interesting about the CrowdStrike powered service provider program; it lives in alliances, It's a partnership program, but they're our customer. They have chosen to standardize on our platform, right. To help drive the best results for their customers. And so we treat them like a partner because it's not for internal use. There's unlimited aspect to it. And so as that treating like partnership we have to enable them with more than just product. Right? We want to bring the right experts. We want to bring the right, you know, vision of where the market's going the threats out there, things of that nature. And that's something that we do every day with you guys. >> And it was even expressed earlier with the keynote speech that George gave. Look there's an ecosystem of very good technologies, very good providers. And there there's that sort of friend-of-me view here. You put the best thing together for the client at the end of the day. And if we all acknowledge, which I think is the maturity of our partnership, that one plus one equals, I always say at 51 now, if you play it right, then the partner sees... That the client sees the value of the partnership. And so they want more of that. >> So it sounds like... We got to wrap, but I wonder if we could close on this. It sounds like this was happening just organically in the field. Now you've codified it. So my question to each of you is; What's your vision for the future? Where do you guys want to take this thing? >> What a wrap question right there. I love it. Honestly, like we look at it in... Look at what does it mean to be a CrowdStrike powered service provider. It is more than just the platform. It's the program in general, offering them tools to go in and do early assessments. One thing about service providers, they're in there before vendors, right? We're still a vendor at the end of the day. And so they have that relationship, like how do we enable them to leverage our platform leverage our tools, leverage our programs in order to help a client understand, like, what is your risk factor Could a breach come, things of that nature. And so it's really building in really enabling a partner like cyber defense labs to take on the full suite of programs, services, platform that we can provide to them as a customer, treated them like a partner. >> And Jason, from your perspective, bring us on if you would. >> So our partnership with CrowdStrike is really enabling cyber defense labs to increase our share of wallet, our presence in very specific market segments; The mid-market to enterprise especially around banking, financial services auto dealerships, healthcare, manufacturing, where last year we saw a significant progress there. And we think we're going to double it between this year and next year. >> Jason Cook, Mike Riolo. thanks for coming in TheCube. Great story. >> Thank you for having us >> Alright, thank you for watching. Keep it right there. Dave Vallante and Dave Nicholson will be back right after this short break from Fal.Con 22. You're watching TheCube. (soft electronic music)

>>Okay, welcome back everyone. There's the cubes coverage of VMware Explorer, 22 formerly world. We've been here since 2010 and world 2010 to now it's 2022. And it's VMware Explorer. We're here at the CEO, regular writer. Welcome back to the cube. Great to see you in person. >>Yeah. Great to be here in person, >>Dave and I are, are proud to say that we've been to 12 straight years of covering VMware's annual conference. And thank you. We've seen the change in the growth over time and you know, it's kind of, I won't say pinch me moment, but it's more of a moment of there's the VMware that's grown into the cloud after your famous deal with Andy jazzy in 2016, we've been watching what has been a real sea change and VMware since taking that legacy core business and straightening out the cloud strategy in 2016, and then since then an acceleration of, of cloud native, like direction under your leadership at VMware. Now you're the CEO take us through that because this is where we are right now. We are here at the pinnacle of VMware 2.0 or cloud native VMware, as you point out on your keynote, take us through that history real quick. Cuz I think it's important to know that you've been the architect of a lot of this change and it's it's working. >>Yeah, definitely. We are super excited because like I said, it's working, the history is pretty simple. I mean we tried running our own cloud cloud air. We cloud air didn't work so well. Right. And then at that time, customers really gave us strong feedback that the hybrid they wanted was a Amazon together. Right. And so that's what we went back and did and the andjay announcement, et cetera. And then subsequently as we were continue to build it out, I mean, once that happened, we were able to go work with the Satia and Microsoft and others to get the thing built out all over. Then the next question was okay, Hey, that's great for the workloads that are running on vSphere. What's the story for workloads that are gonna be cloud native and benefit a lot from being cloud native. So that's when we went the Tansu route and the Kubernetes route, we did a couple of acquisitions and then we started that started paying off now with the Tansu portfolio. And last but not the least is once customers have this distributed portfolio now, right. Increasingly everything is becoming multi-cloud. How do you manage and connect and secure. So that's what you start seeing that you saw the management announcement, networking and security and everything else is cooking. And you'll see more stuff there. >>Yeah know, we've been talking about super cloud. It's kinda like a multi-cloud on steroids kind a little bit different pivot of it. And we're seeing some use cases. >>No, no, it's, it's a very great, it's a, it's pretty close to what we talk about. >>Awesome. I mean, and we're seeing this kind of alignment in the industry. It's kind of open, but I have to ask you, when did you, you have the moment where you said multicloud is the game changer moment. When did you have, because you guys had hybrid, which is really early as well. When was the Raghu? When did you have the moment where you said, Hey, multicloud is what's happening. That's we're doubling down on that go. >>I mean, if you think about the evolution of the cloud players, right. Microsoft really started picking up around the 2018 timeframe. I mean, I'm talking about Azure, right? >>In a big way. >>Yeah. In a big way. Right. When that happened and then Google got really serious, it became pretty clear that this was gonna be looking more like the old database market than it looked like a single player cloud market. Right. Equally sticky, but very strong players all with lots of IP creation capability. So that's when we said, okay, from a supplier side, this is gonna become multi. And from a customer side that has always been their desire. Right. Which is, Hey, I don't want to get locked into anybody. I want to do multiple things. And the cloud vendors also started leveraging that OnPrem. Microsoft said, Hey, if you're a windows customer, your licensing is gonna be better off if you go to Azure. Right. Oracle did the same thing. So it just became very clear. >>I am, I have gone make you laugh. I always go back to the software mainframe because I, I think you were here. Right. I mean, you're, you're almost 20 years in. Yeah. And I, the reason I appreciate that is because, well, that's technically very challenging. How do you make virtualization overhead virtually non-existent how do you run any workload? Yeah. How do you recover from, I mean, that's was not trivial. Yeah. Okay. So what's the technical, you know, analog today, the real technical challenge. When you think about cross cloud services. >>Yeah. I mean, I think it's different for each of these layers, right? So as I was alluding to for management, I mean, you can go each one of them by themselves, there is one way of Mo doing multi-cloud, which is multiple clouds. Right. You could say, look, I'm gonna build a great product for AWS. And then I'm gonna build a great product for Azure. I'm gonna build a great product for Google. That's not what aria is. Aria is a true multi-cloud, which means it pulls data in from multiple places. Right? So there are two or three, there are three things that aria has done. That's I think is super interesting. One is they're not trying to take all the data and bring it in. They're trying to federate the data sources. And secondly, they're doing it in real time and they're able to construct this graph of a customer's cloud resources. >>Right. So to keep the graph constructed and pulling data, federating data, I think that's a very interesting concept. The second thing that, like I said is it's a real time because in the cloud, a container might come and go like that. Like that is a second technical challenge. The third it's not as much a technical challenge, but I really like what they have done for the interface they've used GraphQL. Right? So it's not about if you remember in the old world, people talk about single pan or glass, et cetera. No, this is nothing to do with pan or glass. This is a data model. That's a graph and a query language that's suited for that. So you can literally think of whatever you wanna write. You can write and express it in GraphQL and pull all sorts of management applications. You can say, Hey, I can look at cost. I can look at metrics. I can look at whatever it is. It's not five different types of applications. It's one, that's what I think had to do it at scale is the other problem. And, and >>The, the technical enable there is just it's good software. It's a protocol. It's >>No, no, it's, it's, it's it's software. It's a data model. And it's the Federation architecture that they've got, which is open. Right. You can pull in data from Datadog, just as well as from >>Pretty >>Much anything data from VR op we don't care. Right? >>Yeah. Yeah. So rego, I have to ask you, I'm glad you like the Supercloud cuz you know, we, we think multi-cloud still early, but coming fast. I mean, everyone has multiple clouds, but spanning this idea of spanning across has interesting sequences. Do you data, do you do computer both and a lot of good things happening. Kubernetes been containers, all that good stuff. Okay. How do you see the first rev of multi-cloud evolving? Like is it what happens? What's the sequence, what's the order of operations for a client standpoint? Customer standpoint of, of multicloud or Supercloud because we think we're seeing it as a refactoring of something like snowflake, they're a data base, they're a data warehouse on the cloud. They, they say data cloud they'd they like they'll tell us no, you, we're not a data. We're not a data warehouse. We're data cloud. Okay. You're a data warehouse refactored for the CapEx from Amazon and cooler, newer things. Yeah, yeah, yeah. That's a behavior change. Yeah. But it's still a data warehouse. Yeah. How do you see this multi-cloud environment? Refactoring? Is there something that you see that might be different? That's the same if you know what I'm saying? Like what's what, what's the ne the new thing that's happening with multi-cloud, that's different than just saying I'm I'm doing SAS on the cloud. >>Yeah. So I would say, I would point to a, a couple of things that are different. Firstly, my, the answer depends on which category you are in. Like the category that snowflake is in is very different than Kubernetes or >>Something or Mongo DB, right? >>Yeah. Or Mongo DB. So, so it is not appropriate to talk about one multi-cloud approach across data and compute and so, so on and so forth. So I'll talk about the spaces that we play. Right. So step one, for most customers is two application architectures, right? The cloud native architecture and an enterprise native architecture and tying that together either through data or through networks or through et cetera. So that's where most of the customers are. Right. And then I would say step two is to bring these things together in a more, in a closer fashion and that's where we are going. And that is why you saw the cloud universal announcement and that's already, you've seen the Tansu announcement, et cetera. So it's really, the step one was two distinct clouds. That is just two separate islands. >>So the other thing that we did, that's really what my, the other thing that I'd like to get to your reaction on, cause this is great. You're like a masterclass in the cube here. Yeah, totally is. We see customers becoming super clouds because they're getting the benefit of, of VMware, AWS. And so if I'm like a media company or insurance company, if I have scale, if I continue to invest in, in cloud native development, I do all these things. I'm gonna have a da data scale advantage, possibly agile, which means I can build apps and functionality very quick for customers. I might become my own cloud within the vertical. Exactly. And so I could then service other people in the insurance vertical if I'm the insurance company with my technology and create a separate power curve that never existed before. Cause the CapEx is off the table, it's operating expense. Yep. That runs into the income statement. Yep. This is a fundamental business model shift and an advantage of this kind of scenario. >>And that's why I don't think snowflakes, >>What's your reaction to that? Cuz that's something that, that is not really, talk's highly nuanced and situational. But if Goldman Sachs builds the biggest cloud on the planet for financial service for their own benefit, why wouldn't they >>Exactly. >>And they're >>Gonna build it. They sort of hinted at it that when they were up on stage on AWS, right. That is just their first big step. I'm pretty sure over time they would be using other clouds. Think >>They already are on >>Prem. Yeah. On prem. Exactly. They're using VMware technology there. Right? I mean think about it, AWS. I don't know how many billions of dollars they're spending on AWS R and D Microsoft is doing the same thing. Google's doing the same thing we are doing. Not as much as them that you're doing oral chair. Yeah. If you are a CIO, you would be insane not to take advantage of all of this IP that's getting created and say, look, I'm just gonna bet on one. Doesn't make any sense. Right. So that's what you're seeing. And then >>I think >>The really smart companies, like you talked about would say, look, I will do something for my industry that uses these underlying clouds as the substrate, but encapsulates my IP and my operating model that I then offer to other >>Partners. Yeah. And their incentive for differentiation is scale. Yeah. And capability. And that's a super cloud. That's a, or would be say it environment. >>Yeah. But this is why this, >>It seems like the same >>Game, but >>This, I mean, I think it environment is different than >>Well, I mean it advantage to help the business, the old day service, you >>Said snowflake guys out the marketing guys. So you, >>You said snowflake data warehouse. See, I don't think it's in data warehouse. It's not, that's like saying, you >>Know, I, over >>VMware is a virtualization company or service now is a help desk tool. I, this is the change. Yes. That's occurring. Yes. And that you're enabling. So take the Goldman Sachs example. They're gonna run OnPrem. They're gonna use your infrastructure to do selfer. They're gonna build on AWS CapEx. They're gonna go across clouds and they're gonna need some multi-cloud services. And that's your opportunity. >>Exactly. That's that's really, when you, in the keynote, I talked about cloud universal. Right? So think of a future where we can go to a customer and say, Mr. Customer buy thousand scores, a hundred thousand cores, whatever capacity you can use it, any which way you want on any application platform. Right. And it could be OnPrem. It could be in the cloud, in the cloud of their choice in multiple clouds. And this thing can be fungible and they can tie it to the right services. If they like SageMaker they could tie it to Sage or Aurora. They could tie it to Aurora, cetera, et cetera. So I think that's really the foundation that we are setting. Well, I think, I >>Mean, you're building a cloud across clouds. I mean, that's the way I look at it. And, and that's why it's, to me, the, the DPU announcement, the project Monterey coming to fruition is so important. Yeah. Because if you don't have that, if you're not on that new Silicon curve yep. You're gonna be left behind. Oh, >>Absolutely. It allows us to build things that you would not otherwise be able to do, >>Not to pat ourselves on the back Ragu. But we, in what, 2013 day we said, feel >>Free. >>We, we said with Lou Tucker when OpenStack was crashing. Yeah. Yeah. And then Kubernetes was just a paper. We said, this could be the interoperability layer. Yeah. You got it. And you could have inter clouding cuz there was no clouding. I was gonna riff on inter networking. But if you remember inter networking during the OSI model, TCP and IP were hardened after the physical data link layer was taken care of. So that enabled an entire new industry that was open, open interconnect. Right. So we were saying inter clouding. So what you're kind of getting at with cross cloud is you're kind of creating this routing model if you will. Not necessarily routing, but like connection inter clouding, we called it. I think it's kinda a terrible name. >>What you said about Kubernetes is super critical. It is turning out to be the infrastructure API so long. It has been an infrastructure API for a certain cluster. Right. But if you think about what we said about VSE eight with VSE eight Kubernetes becomes the data center API. Now we sort of glossed over the point of the keynote, but you could do operations storage, anything that you can do on vSphere, you can do using a Kubernetes API. Yeah. And of course you can do all the containers in the Kubernetes clusters and et cetera, is what you could always do. Now you could do that on a VMware environment. OnPrem, you could do that on EKS. Now Kubernetes has become the standard programming model for infrastructure across. It >>Was the great equalizer. Yeah. You, we used to say Amazon turned the data center through an API. It turns, turns of like a lot of APIs and a lot of complexity. Right. And Kubernetes changed. >>Well, the role, the role of defacto standards played a lot into the T C P I P revolution before it became a standard standard. What the question Raghu, as you look at, we had submit on earlier, we had tutorial on as well. What's the disruptive enabler from a defacto. What in your mind, what should, because Kubernetes became kind of defacto, even though it was in the CNCF and in an open source open, it wasn't really standard standard. There's no like standards, body, but what de facto thing has to happen in your mind's eye around making inter clouding or connecting clouds in a, in a way that's gonna create extensibility and growth. What do you see as a de facto thing that the industry should rally around? Obviously Kubernetes is one, is there something else that you see that's important for in an open way that the industry can discuss and, and get behind? >>Yeah. I mean, there are things like identity, right? Which are pretty critical. There is connectivity and networking. So these are all things that the industry can rally around. Right. And that goes along with any modern application infrastructure. So I would say those are the building blocks that need to happen on the data side. Of course there are so many choices as well. So >>How about, you know, security? I think about, you know, when after stuck net, the, the whole industry said, Hey, we have to do a better job of collaborating. And then when you said identity, it just sort of struck me. But then a lot of people tried to sort of monetize private reporting and things like that. So you do you see a movement within the technology industry to do a better job of collaborating to, to solve the acute, you know, security problems? >>Yeah. I think the customer pressure and government pressure right. Causes that way. Yeah. Even now, even in our current universe, you see, there is a lot of behind the scenes collaboration amongst the security teams of all of the tech companies that is not widely seen or known. Right. For example, my CISO knows the AWS CSO or the Microsoft CSO and they all talk and they share the right information about vulnerability attacks and so on and so forth. So there's already a certain amount of collaboration that's happening and that'll only increase. Do, >>Do you, you know, I was somewhat surprised. I didn't hear more in your face about security would, is that just because you had such a strong multi-cloud message that you wanted to get, get across, cuz your security story is very strong and deep. When you get into the DPU side of things, the, you know, the separation of resources and the encryption and I'll end to end >>I'm well, we have a phenomenal security story. Yeah. Yeah. Tell security story and yes. I mean I'll need guilty to the fact that in the keynote you have yeah, yeah, sure time. But what we are doing with NSX and you will hear about some NSX projects as you, if you have time to go to some of the, the sessions. Yeah. There's one called project, not star. Another is called project Watchman or watch, I think it's called, we're all dealing with this. That is gonna strengthen the security story even more. Yeah. >>We think security and data is gonna be a big part of it. Right. As CEO, I have to ask you now that you're the CEO, first of all, I'd love to talk about product with you cuz you're yeah. Yeah. We just great conversation. We want to kind of read thet leaves and ask pointed questions cuz we're putting the puzzle together in real time here with the audience. But as CEO, now you have a lot of discussions around the business. You, the Broadcom thing happening, you got the rename here, you got multi-cloud all good stuff happening. Dave and I were chatting before we came on this morning around the marketplace, around financial valuations and EBIDA numbers. When you have so much strategic Goodwill and investment in the oven right now with the, with the investments in cloud native multi-year investments on a trajectory, you got economies of scale there. >>It's just now coming out to be harvest and more behind it. Yeah. As you come into the Broadcom and or the new world wave that's coming, how do you talk about that value? Cuz you can't really put a number on it yet because there's no customers on it. I mean some customers, but you can't probably some for form. It's not like sales numbers. Yeah. Yeah. How do you make the argument to the PE type folks out there? Like EBIDA and then all the strategic value. What's the, what's the conversation like if you can share any, I know it's obviously public company, all the things going down, but like how do you talk about strategic value to numbers folks? >>Yeah. I mean, we are not talking to PE guys at all. Right. I mean the only conversation we have is helping Broadcom with >>Yeah. But, but number people who are looking at the number, EBIDA kind of, >>Yeah. I mean, you'd be surprised if, for, for example, even with Broadcom, they look at the business holistically as what are the prospects of this business becoming a franchise that is durable and could drive a lot of value. Right. So that's how they look at it holistically. It's not a number driven. >>They do. They look at that. >>Yeah. Yeah, absolutely. So I think it's a misperception to say, Hey, it's a numbers driven conversation. It's a business driven conversation where, I mean, and Hawk's been public about it. He says, look, I look at businesses. Can they be leaders in their market? Yeah. Because leaders get, as we all know a disproportionate share of the economic value, is it a durable franchise that's gonna last 10 years or more, right. Obviously with technology changes in between, but 10 years or more >>Or 10, you got your internal, VMware talent customers and >>Partners. Yeah. Significant competitive advantage. So that's, that's really where the conversation starts and the numbers fall out of it. Got it. >>Okay. So I think >>There's a track record too. >>That culture >>That VMware has, you've always had an engineering culture. That's turned, you know, ideas and problems into products that, that have been very successful. >>Well, they had different engineering cultures. They're chips. You guys are software. Right. You guys know >>Software. Yeah. Mean they've been very successful with Broadcom, the standalone networking company since they took it over. Right. I mean, it's, there's a lot of amazing innovation going on there. >>Yeah. Not, not that I'm smiling. I want to kind of poke at this question question. I'll see if I get an answer out of you, when you talk to Hawk tan, does he feel like he bought a lot more than he thought or does he, did he, does he know it's all here? So >>The last two months, I mean, they've been going through a very deliberate process of digging into each business and certainly feels like he got a phenomenal asset base. Yeah. He said that to me even today after the keynote, right. Is the amazing amount of product capability that he's seeing in every one of our businesses. And that's been the constant frame. >>But congratulations on that. >>I've heard, I've heard Hawk talk about the shift to, to Mer merchant Silicon. Yeah. From custom Silicon. But I wanted to ask you when you look at things like AWS nitro yeah. And graviton and train and the advantage that AWS has with custom Silicon, you see Google and Microsoft sort of Alibaba following suit. Would it benefit you to have custom Silicon for, for DPU? I mean, I guess you, you know, to have a tighter integration or do you feel like with the relationships that you have that doesn't buy you anything? >>Yeah. I mean we have pretty strong relationships with in fact fantastic relationships with the Invidia and Intel and AMD >>Benon and AMD now. >>Yeah. Yeah. I mean, we've been working with the Pendo team in their previous incarnations for years. Right, right. When they were at Cisco and then same thing with the, we know the Melanox team as well as the invi original teams and Intel is the collaboration right. From the get go of the company. So we don't feel a need for any of that. We think, I mean, it's clear for those cloud folks, right. They're going towards a vertical integration model and select portions of their stack, like you talked about, but there is always a room for horizontal integration model. Right. And that's what we are a part of. Right. So there'll be a number of DPU pro vendors. There'll be a number of CPU vendors. There'll be a number of other storage, et cetera, et cetera. And we think that is goodness in an alternative model compared to a vertically integr >>And yeah. What this trade offs, right. It's not one or the other, I mean I used to tell, talk to Al Shugar about this all the time. Right. I mean, if vertically integrated, there may be some cost advantages, but then you've got flexibility advantages. If you're using, you know, what the industry is building. Right. And those are the tradeoffs, so yeah. Yeah. >>Greg, what are you excited about right now? You got a lot going on obviously great event. Branding's good. Love the graphics. I was kind of nervous about the name changed. I likem world, but you know, that's, I'm kind of like it >>Doesn't readily roll off your phone. Yeah. >>I know. We, I had everyone miscue this morning already and said VMware Explorer. So >>You pay Laura fine. Yeah. >>Now, I >>Mean a quarter >>Curse jar, whatever I did wrong. I don't believe it. Only small mistake that's because the thing wasn't on. Okay. Anyway, what's on your plate. What's your, what's some of the milestones. Do you share for your employees, your customers and your partners out there that are watching that might wanna know what's next in the whole Broadcom VMware situation. Is there a timeline? Can you talk publicly about what? To what people can expect? >>Yeah, no, we, we talk all the time in the company about that. Right? Because even if there is no news, you need to talk about what is where we are. Right. Because this is such a big transaction and employees need to know where we are at every minute of the day. Right? Yeah. So, so we definitely talk about that. We definitely talk about that with customers too. And where we are is that the, all the processes are on track, right? There is a regulatory track going on. And like I alluded to a few minutes ago, Broadcom is doing what they call the discovery phase of the integration planning, where they learn about the business. And then once that is done, they'll figure out what the operating model is. What Broadcom is said publicly is that the acquisition will close in their fiscal 23, which starts in November of this year, runs through October of next year. >>So >>Anywhere window, okay. As to where it is in that window. >>All right, Raghu, thank you so much for taking valuable time out of your conference time here for the queue. I really appreciate Dave and I both appreciate your friendship. Congratulations on the success as CEO, cuz we've been following your trials and tribulations and endeavors for many years and it's been great to chat with you. >>Yeah. Yeah. It's been great to chat with you, not just today, but yeah. Over a period of time and you guys do great work with this, so >>Yeah. And you guys making, making all the right calls at VMware. All right. More coverage. I'm shot. Dave ante cube coverage day one of three days of world war cup here in Moscone west, the cube coverage of VMware Explorer, 22 be right back.

(electronic music) >> Hello everybody, welcome back to Boston. This is Dave Vellante and you're watching theCUBE's continuous coverage of AWS re:Inforce 2022. We're here at the convention center in Boston where theCUBE got started in May of 2010. I'm really excited. Lena Smart is here, she's the chief information security officer at MongoDB rocket ship company We covered MongoDB World earlier this year, June, down in New York. Lena, thanks for coming to theCUBE. >> Thank you for having me. >> You're very welcome, I enjoyed your keynote yesterday. You had a big audience, I mean, this is a big deal. >> Yeah. >> This is the cloud security conference, AWS, putting its mark in the sand back in 2019. Of course, a couple of years of virtual, now back in Boston. You talked in your keynote about security, how it used to be an afterthought, used to be the responsibility of a small group of people. >> Yeah. >> You know, it used to be a bolt on. >> Yep. >> That's changed dramatically and that change has really accelerated through the pandemic. >> Yep. >> Just describe that change from your perspective. >> So when I started at MongoDB about three and a half years ago, we had a very strong security program, but it wasn't under one person. So I was their first CISO that they employed. And I brought together people who were already doing security and we employed people from outside the company as well. The person that I employed as my deputy is actually a third time returnee, I guess? So he's worked for, MongoDB be twice before, his name is Chris Sandalo, and having someone of that stature in the company is really helpful to build the security culture that I wanted. That's why I really wanted Chris to come back. He's technically brilliant, but he also knew all the people who'd been there for a while and having that person as a trusted second in command really, really helped me grow the team very quickly. I've already got a reputation as a strong female leader. He had a reputation as a strong technical leader. So us combined is like indestructible, we we're a great team. >> Is your scope of responsibility, obviously you're protecting Mongo, >> Yeah. >> How much of your role extends into the product? >> So we have a product security team that report into Sahir Azam, our chief product officer. I think you even spoke to him. >> Yeah, he's amazing. >> He's awesome, isn't he? He's just fabulous. And so his team, they've got security experts on our product side who are really kind of the customer facing. I'm also to a certain extent customer facing, but the product folks are the absolute experts. They will listen to what our customers need, what they want, and together we can then work out and translate that. I'm also responsible for governance risk and compliance. So there's a large portion of our customers that give us input via that program too. So there's a lot of avenues to allow us to facilitate change in the security field. And I think that's really important. We have to listen to what our customers want, but also internally. You know, what our internal groups need as well to help them grow. >> I remember last year, Re:invent 2021, I was watching a talk on security. It was the, I forget his name, but it was the individual who responsible for data center security. And one of the things he said was, you know, look it's not at the end of the day, the technology's important but it's not the technology. It's how you apply the tools and the practices and the culture- >> Right. That you build in the organization that will ultimately determine how successful you are at decreasing the ROI for the bad guys. >> Yes. >> Let's put it that way. So talk about the challenges of building that culture, how you go about that, and how you sustain that cultural aspect. >> So, I think having the security champion program, so that's just, it's like one of my babies, that and helping underrepresented groups in MongoDB kind of get on in the tech world are both really important to me. And so the security champion program is purely voluntary. We have over a hundred members. And these are people, there's no bar to join. You don't have to be technical. If you're an executive assistant who wants to learn more about security, like my assistant does, you're more than welcome. Up to, we actually people grade themselves, when they join us, we give them a little tick box. Like five is, I walk in security water. One is, I can spell security but I'd like to learn more. Mixing those groups together has been game changing for us. We now have over a hundred people who volunteer their time, with their supervisors permission, they help us with their phishing campaigns, testing AWS tool sets, testing things like queryable encryption. I mean, we have people who have such an in-depth knowledge in other areas of the business that I could never learn, no matter how much time I had. And so to have them- And we have people from product as security champions as well, and security, and legal, and HR, and every department is recognized. And I think almost every geographical location is also recognized. So just to have that scope and depth of people with long tenure in the company, technically brilliant, really want to understand how they can apply the cultural values that we live with each day to make our security program stronger. As I say, that's been a game changer for us. We use it as a feeder program. So we've had five people transfer from other departments into the security and GRC teams through this Champions program. >> Makes a lot of sense. You take somebody who walks on water in security, mix them with somebody who really doesn't know a lot about it but wants to learn and then can ask really basic questions, and then the experts can actually understand better how to communicate. >> Absolutely. >> To that you know that 101 level. >> It's absolutely true. Like my mom lives in her iPad. She worships her iPad. Unfortunately she thinks everything on it is true. And so for me to try and dumb it down, and she's not a dumb person, but for me to try and dumb down the message of most of it's rubbish, mom, Facebook is made up. It's just people telling stories. For me to try and get that over to- So she's a one, and I might be a five, that's hard. That's really hard. And so that's what we're doing in the office as well. It's like, if you can explain to my mother how not everything on the internet is true, we're golden. >> My mom, rest her soul, when she first got a- we got her a Macintosh, this was years and years and years ago, and we were trying to train her over the phone, and said, mom, just grab the mouse. And she's like, I don't like mice. (Lena laughs) There you go. I know, I know, Lena, what that's like. Years ago, it was early last decade, we started to think about, wow, security really has to become a board level item. >> Yeah. >> And it really wasn't- 2010, you know, for certain companies. But really, and so I had the pleasure of interviewing Dr. Robert Gates, who was the defense secretary. >> Yes. >> We had this conversation, and he sits on a number, or sat on a number of boards, probably still does, but he was adamant. Oh, absolutely. Here's how you know, here. This is the criticality. Now it's totally changed. >> Right. >> I mean, it's now a board level item. But how do you communicate to the C-Suite, the board? How often do you do that? What do you recommend is the right regime? And I know there's not any perfect- there's got to be situational, but how do you approach it? >> So I am extremely lucky. We have a very technical board. Our chairman of the board is Tom Killalea. You know, Amazon alum, I mean, just genius. And he, and the rest of the board, it's not like a normal board. Like I actually have the meeting on this coming Monday. So this weekend will be me reading as much stuff as I possibly can, trying to work out what questions they're going to ask me. And it's never a gotcha kind of thing. I've been at board meetings before where you almost feel personally attacked and that's not a good thing. Where, at MongoDB, you can see they genuinely want us to grow and mature. And so I actually meet with our board four times a year, just for security. So we set up our own security meeting just with board members who are specifically interested in security, which is all of them. And so this is actually off cadence. So I actually get their attention for at least an hour once a quarter, which is almost unheard of. And we actually use the AWS memo format. People have a chance to comment and read prior to the meeting. So they know what we're going to talk about and we know what their concerns are. And so you're not going in like, oh my gosh, what what's going to happen for this hour? We come prepared. We have statistics. We can show them where we're growing. We can show them where we need more growth and maturity. And I think having that level of just development of programs, but also the ear of the board has has helped me mature my role 10 times. And then also we have the chance to ask them, well what are your other CISOs doing? You know, they're members of other boards. So I can say to Dave, for example, you know, what's so-and-so doing at Datadog? Or Tom Killelea, what's the CISO of Capital One doing? And they help me make a lot of those connections as well. I mean, the CISO world is small and me being a female in the world with a Scottish accent, I'm probably more memorable than most. So it's like, oh yeah, that's the Irish girl. Yeah. She's Scottish, thank you. But they remember me and I can use that. And so just having all those mentors from the board level down, and obviously Dev is a huge, huge fan of security and GRC. It's no longer that box ticking exercise that I used to feel security was, you know, if you heated your SOC2 type two in FinTech, oh, you were good to go. You know, if you did a HERC set for the power industry. All right, right. You know, we can move on now. It's not that anymore. >> Right. It's every single day. >> Yeah. Of course. Dev is Dev at the Chario. Dev spelled D E V. I spell Dave differently. My Dave. But, Lena, it sounds like you present a combination of metrics, so, the board, you feel like that's appropriate to dig into the metrics. But also I'm presuming you're talking strategy, potentially, you know, gaps- >> Road roadmaps, the whole nine yards. Yep. >> What's the, you know, I look at the budget scenario. At the macro level, CIOs have told us, they came into the year saying, hey we're going to grow spending at the macro, around eight percent, eight and a half percent. That's dialed down a little bit post Ukraine and the whole recession and Fed tightening. So now they're down maybe around six percent. So not dramatically lower, but still. And they tell us security is still the number one priority. >> Yes. >> That's been the case for many, many quarters, and actually years, but you don't have an unlimited budget. >> Sure >> Right. It's not like, oh, here is an open checkbook. >> Right. >> Lena, so, how does Mongo balance that with the other priorities in the organization, obviously, you know, you got to spend money on product, you got to spend money and go to market. What's the climate like now, is it, you know continuing on in 2022 despite some of the macro concerns? Is it maybe tapping the brakes? What's the general sentiment? >> We would never tap the breaks. I mean, this is something that's- So my other half works in the finance industry still. So we have, you know, interesting discussions when it comes to geopolitics and financial politics and you know, Dev, the chairman of the board, all very technical people, get that security is going to be taken advantage of if we're seeing to be tapping the brakes. So it does kind of worry me when I hear other people are saying, oh, we're, you know, we're cutting back our budget. We are not. That being said, you also have to be fiscally responsible. I'm Scottish, we're cheap, really frugal with money. And so I always tell my team: treat this money as if it's your own. As if it's my money. And so when we're buying tool sets, I want to make sure that I'm talking to the CISO, or the CISO of the company that's supplying it, and saying are you giving me the really the best value? You know, how can we maybe even partner with you as a database platform? How could we partner with you, X company, to, you know, maybe we'll give you credits on our platform. If you look to moving to us and then we could have a partnership, and I mean, that's how some of this stuff builds, and so I've been pretty good at doing that. I enjoy doing that. But then also just in terms of being fiscally responsible, yeah, I get it. There's CISOs who have every tool that's out there because it's shiny and it's new and they know the board is never going to say no, but at some point, people will get wise to that and be like, I think we need a new CISO. So it's not like we're going to stop spending it. So we're going to get someone who actually knows how to budget and get us what the best value for money. And so that's always been my view is we're always going to be financed. We're always going to be financed well. But I need to keep showing that value for money. And we do that every board meeting, every Monday when I meet with my boss. I mean, I report to the CFO but I've got a dotted line to the CTO. So I'm, you know, I'm one of the few people at this level that's got my feet in both camps. You know budgets are talked at Dev's level. So, you know, it's really important that we get the spend right. >> And that value is essentially, as I was kind of alluding to before, it's decreasing the value equation for the hackers, for the adversary. >> Hopefully, yes. >> Right? Who's the- of course they're increasingly sophisticated. I want to ask you about your relationship with AWS in this context. It feels like, when I look around here, I think back to 2019, there was a lot of talk about the shared responsibility model. >> Yes. >> You know, AWS likes to educate people and back then it was like, okay, hey, by the way, you know you got to, you know, configure the S3 bucket properly. And then, oh, by the way, there's more than just, it's not just binary. >> Right, right. >> There's other factors involved. The application access and identity and things like that, et cetera, et cetera. So that was all kind of cool. But I feel like the cloud is becoming the first line of defense for the CISO but because of the shared responsibility model, CISO is now the second line of defense >> Yes. Does that change your role? Does it make it less complicated in a way? Maybe, you know, more complicated because you now got to get your DevSecOps team? The developers are now much more involved in security? How is that shifting, specifically in the context of your relationship with AWS? >> It's honestly not been that much of a shift. I mean, these guys are very proactive when it comes to where we are from the security standpoint. They listen to their customers as much as we do. So when we sit down with them, when I meet with Steve Schmidt or CJ or you know, our account manager, its not a conversation that's a surprise to me when I tell them this is what we need. They're like, yep, we're on that already. And so I think that relationship has been very proactive rather than reactive. And then in terms of MongoDB, as a tech company, security is always at the forefront. So it's not been a huge lift for me. It's really just been my time that I've taken to understand where DevSecOps is coming from. And you know, how far are we shifting left? Are we actually shifting right now? It's like, you know, get the balance, right? You can't be too much to one side. But I think in terms of where we're teaching the developers, you know, we are a company by developers for developers. So, we get it, we understand where they're coming from, and we try and be as proactive as AWS is. >> When you obviously the SolarWinds hack was a a major mile- I think in security, there's always something in the headlines- >> Yes. But when you think of things like, you know, Stuxnet, you know, Log4J, obviously Solarwinds and the whole supply chain infiltration and the bill of materials. As I said before, the adversary is extremely capable and sophisticated and you know, much more automated. It's always been automated attacks, but you know island hopping and infiltrating and self-forming malware and really sophisticated techniques. >> Yep. >> How are you thinking about that supply chain, bill of materials from inside Mongo and ultimately externally to your customers? >> So you've picked on my third favorite topic to talk about. So I came from the power industry before, so I've got a lot of experience with critical infrastructure. And that was really, I think, where a lot of the supply chain management rules and regulations came from. If you're building a turbine and the steel's coming from China, we would send people to China to make sure that the steel we were buying was the steel we were using. And so that became the H bomb. The hardware bill of materials, bad name. But, you know, we remember what it stood for. And then fast forward: President Biden's executive order. SBOs front and center, cloud first front and center. It's like, this is perfect. And so I was actually- I actually moderated a panel earlier this year at Homeland Security Week in DC, where we had a sneak CISA, So Dr. Allen Friedman from CISA, and also Patrick Weir from OWASP for the framework, CISA for the framework as well, and just the general guidance, and Snake for the front end. That was where my head was going. And MongoDB is the back-end database. And what we've done is we've taken our work with Snake and we now have a proof of concept for SBOs. And so I'm now trying to kind of package that, if you like, as a program and get the word out that SBOs shouldn't be something to be afraid of. If you want to do business with the government you're going to have to create one. We are offering a secure repository to store that data, the government could have access to that repository and see that data. So there's one source of truth. And so I think SBOs is going to be really interesting. I know that, you know, some of my peers are like, oh, it's just another box to tick. And I think it's more than that. I definitely- I've just, there's something percolating in the back of my mind that this is going to be big and we're going to be able to use it to hopefully not stop things like another Log4j, there's always going to be another Log4j, we know that. we don't know everything, the unknown unknown, but at least if we're prepared to go find stuff quicker than we were then before Log4j, I think having SBOs on hand, having that one source of truth, that one repository, I think is going to make it so much easier to find those things. >> Last question, what's the CISO's number one challenge? Either yours or the CISO, generally. >> Keeping up with the fire hose that is security. Like, what do you pick tomorrow? And if you pick the wrong thing, what's the impact? So that's why I'm always networking and talking to my peers. And, you know, we're sometimes like meerkats, you know. there's meerkats, you see like this, it's like, what do we talk about? But there's always something to talk about. And you just have to learn and keep learning. >> Last question, part B. As a hot technology company, that's, you know, rising star, you know not withstanding the tech lash and the stock market- >> Yeah. >> But Mongo's growing, you know, wonderfully. Do you find it easier to attract talent? Like many CISOs will say, you know, lack of talent is my biggest, biggest challenge. Do you find that that's not the challenge for you? >> Not at all. I think on two fronts, one, we have the champions program. So we've got a whole internal ecosystem who love working there. So the minute one of my jobs goes on the board, they get first dibs at it. So they'd already phoning their friends. So we've got, you know, there's ripple effects out from over a hundred people internally. You know, I think just having that, that's been a game changer. >> I was so looking forward to interviewing you, Lena, thanks so much for coming. >> Thank you, this was a pleasure. >> It was really great to have you. >> Thank you so much. Thank you. >> You're really welcome. All right, keep it right there. This is Dave Villante for theCUBE. We'll be right back at AWS Re:inforce22 right after this short break.

(bright music) >> Hey, welcome back everyone, theCUBE coverage here at AWS re:Mars 2022. I'm John, your host of the theCUBE. re:Mars, part of the three re big events, re:Invent is the big one, re:Inforce the security, re:MARS is the confluence of industrial space, of automation, robotics and machine learning. Got a great guest here, Muhammad Faisal senior consultant solutions architect at Capgemini. Welcome to theCUBE. Thanks for coming on. >> Thank you. >> So we, you just we're hearing the classes we had with the professor from Okta ML from Washington. So he's in the weeds on machine learning. He's down getting dirty with all the hardcore, uncoupling it from hardware. Machine learning has gone really super nova in the past couple years. And this show points to the tipping point where machine learning's driving space, it's driving robotics industrial edge at unprecedented rates. So it's kind of moving from the old I don't want to say old, couple years ago and the legacy AI, I mean, old school AI is kind of the same new school with a twist it's just modernized and has faster, cheaper, smaller chips. >> Yeah. I mean, but there is a change also in the way it's working. So you had the classical AI, where you are detecting something and then you're making an action. You are perceiving something, making an action, you're detecting something, and you're assuming something that has been perceived. But now we are moving towards more deeper learning, deep. So AI, where you have to train your model to do things or to detect things and hope that it will work. And there's like, of course, a lot of research going on into explainable AI to help facilitate that. But that's where the challenges come into play. >> Well, Muhammad , first let's take, what do you do over there? Talk about your role specifically. You're doing a lot of student architecting around AI machine learning. What's your role? What's your focus. >> Yeah. So we basically are working in automotive to help OEMs and tier-one suppliers validate ADAS functions that they're working on. So advanced driving assistance systems, there are many levels that are, are when we talk about it. So it can be something simple, like, you know, a blind spot detection, just a warning function. And it goes all the way. So SAE so- >> So there's like the easy stuff and then the hard stuff. >> Muhammad : Exactly. >> Yeah. >> That's what you're getting at. >> Yeah. Yeah. And, and the easy stuff you can test validate quite easily because if you get it wrong. >> Yeah. >> The impact is not that high. The complicated stuff, if you have it wrong, then that can be very dangerous. (John laughs) >> Well, I got to say the automotive one was one was that are so fascinating because it's been so archaic and just in the past recent years, and Tesla's the poster child for this. You see that you go, oh my God, I love that car. I want to have a software driven car. And it's amazing. And I don't get a Tesla on now because that's, it's more like I should have gotten it earlier. Now I'm going to just hold my ground. >> Everyone has- >> Everyone's got it in Palo Alto. I'm not going to get another car, no way. So, but you're starting to see a lot of the other manufacturers, just in the past five years, they're leveling up. It may not be as cool and sexy as the Tesla, but it's, they're there. And so what are they dealing with when they talk about data and AI? What's the, what's some of the challenges that you're seeing that they're grappling with in terms of getting things integrated, developing pipelines, R and D, they wrangling data. Take us through some of the things. >> Muhammad: I mean, like when I think about the challenges that autonomous or the automakers are facing, I can think of three big ones. So first, is the amount of data they need to do their training. And more importantly, the validation. So we are talking about petabytes or hundred of petabytes of data that has to be analyzed, validated, annotated. So labeling to create gen, ground truth processed, reprocessed many times with every creation of a new software. So that is a lot of data, a lot of computational power. And you need to ensure that all of the processing, all of handling of the data allows you complete transparency of what is happening to the data, as well as complete traceability. So your, for home allocations, so approval process for these functions so that they can be released in cars that can be used on public roads. You need to have traceability. Like you can, you are supposed to be able to reproduce the data to validate your work that was done. So you can, >> John: Yeah >> Like, prove that your function is successful or working as expected. So this, the big data is the first challenge. I see that all the automotive makers are tackling. The second big one I see is understanding how much testing is enough. So with AI or with classical approach, you have certain requirements, how a function is supposed to work. You can test that with some test cases based on your architecture, and you have a successful or failed result. With deep learning, it gets more complicated. >> John: What are they doing with deep learning? Give an example of some of things. >> I mean, so you are, you need to then start thinking about statistics that I will test enough data with like a failure rate of potentially like 0.0, 0.1%. How much data do I need to test to make sure that I am achieving that rate. So then we are talking about, in terms of statistics, which requires a lot of data, because the failure rate that we want to have is so low. And it's not only like, failure in terms of that something is always detected, and if it's there, but it's also having like, a low false positive rate. So you are only detecting objects which are there and not like, phantom objects. >> What's some of the trends you're seeing across the client base, in terms of the patterns that they're all kind of, what, where's the state of their mindset and position with AI and some of the work they're doing, are they feeling, you feel like they're all crossed over across the chasm so to speak, in terms of executing, are they still in experimental mode in driving with the full capabilities is conservative or is it progressive? >> Muhammad: I mean, it's a mixture of both. So I'm in German automotive where I'm from, there is for functions, which are more complicated ones. There's definitely hesitancy to release them too early in the car, unless we are sure that they are safe. But of course, for functions which are assisting the drivers everyday usage they are widely available. Like one of the things like, so when we talk about this complex function. >> John: Highly available or available? >> Muhammad: I would say highly available. >> Higher? Is that higher availability and highly available. >> Okay. Yeah. (both laughing) >> Yeah, so. >> I know there's a distinction. >> Yeah. I mean >> I bring up as a joke cuz of the Jedi contract. (Muhammad laughs) >> I mean, in like, our architecture. So when we are developing our solution, high availability is one of our requirements. It is highly available, but the ADAS functions are now available in more and more cars. >> John: Well, latency, man. I mean, it's kind of a joke of storage, but it's a storage joke, but you know, it's latency, you got it, okay. (Muhammad laughs) But these are decisions that have to be made. >> Muhammad: They... >> I mean. >> Muhammad: I mean, they are still being made. >> So I mean, we are... >> John: Good. >> We haven't reached like, level five, which is the highest level of autonomous driving yet on public roads. >> John: That's hard. That's hard to do. >> Yeah. And I mean, the biggest difference, like, as you go above these levels is in terms of availability. So are they these functions? >> John: Yeah. >> Can they handle all possible scenarios or are they only available in certain scenarios? And of course the responsibility. So, it's, in the end, so with Tesla, you would be like, if you had a one you would be the person who is in control or responsible to monitor it. >> John: Yeah. But as we go >> John: Actually the reason I don't have a Tesla all my family would want one. I don't want to get anyone a Tesla. >> But I mean, but that's the sort the liabilities is currently on you, if like, you're not monitoring. >> Allright, so, talk about AWS, the relationship that Capgemini has with AWS, obviously, the partnerships there, you're here and this show is really a commitment to, this is a future to me, this is the future. >> Muhammad: Yeah. >> This is it. All right here, industrial, innovation's going to come massive. Back-office cloud, done deal. Data centers, hybrid somewhat multi-cloud, I guess. But hybrid is a steady state in the back-office cloud, game over. >> Muhammad: Yeah. >> Amazon, Azure, Google, Alibaba done. So super clouds underneath. Great. This is a digital transformation in the industrial area. >> Muhammad: Yeah. >> This is the big thing. What's your relationship with AWS >> Muhammad: So, as I mentioned, the first challenge, data, like, we have so much data, so much computational power and it's not something that is always needed. You need it like on demand. And this is where like a hyperscale or cloud provider, like AWS, can be the key to achieve, like, the higher, the acceleration that we are providing to our customers using our technology built on top of AWS services. We did a breakout session, this during re:MARS, where we demonstrated a couple of small tools that we have developed out of our offering. One of them was ability to stream data from the vehicle that is collecting data worldwide. So during the day when we did it from Vegas, driving on the strip, as well as from Germany, and while we are while this data is uploaded, it's at the same time real time anonymized to make sure it you're privacy aligned with the, the data privacy >> Of course. Yeah. That's hard to do right there. >> Yeah. And so the faces are blurred. The licenses are blurred. We also, then at the same time can run object detection. So we have real time monitoring of what our feed is doing worldwide. And... >> John: Do you, just curious, do you do that blurring? Is that part of a managed service, you call an API or is that built into the go? >> Muhammad: So from like part of our DSV, we have many different service offerings, so data production, data test strategy orchestration. So part of data production is worldwide data collection. And we can then also offer data management services, which include then anonymization data, quality check. >> John: And that's service you provide. >> Yeah. >> To the customer. Okay. Got it. Okay. >> So of course, like, in collaboration with the customer, so our like, platform is very modular. Microservices based the idea being if the customer already has a good ML model for anonymization, we can plug it into our platform, running on AWS. If they want to use it, we can develop one or we can use one of our existing ones or something off the shelf or like any other supplier can provide one as well. And we all integrate. >> So you are, you're tight with Amazon web services in terms of your cloud, your service. It's a cloud. >> Yeah. >> It's so Capgemini Super Cloud, basically. >> Exactly. >> Okay. So this we call we call it Super Cloud, we made that a thing and re:Invent Charles Fitzgerald would disagree but we will debate him. It's a Super Cloud, but okay. You got your Super Cloud. What's the coolest thing that you think you're doing right now that people should pay attention to. >> I mean, the cool thing that we are currently working on, so from the keynote today, we talked about also synthetic data for validation. >> John: Now That was phenomenal. So that was phenomenal. >> We are working on digital twin creation. So we are capturing data in real world creating a virtual identity of it. And that allows you the freedom to create multiple scenarios out of it. So that's also something where we are using machine learning to determine what are the parameters you need to change between, or so, you have one scenario, such as like, the cut-in scenario and you can change. >> John: So what scenario? >> A cut-in scenario. So someone is cutting in front of you or overtake scenario. And so, I mean, in real world, someone will do it in probably a nicer way, but of course, in, it is possible, at some point. >> Cognition to the cars. >> Yeah. >> It comes up as a vehicle. >> I mean, at some point some might, someone would be very aggressive with it. We might not record it. >> You might be able to predict too. I mean, the predictions, you could say this guy's weaving, he's a potential candidate. >> It it is possible. Yes. But I mean, but to, >> That's a future scenario. >> Ensure that we are testing these scenarios, we can translate a real world scenario into a digital world, change the parameters. So the distance between those two is different and use ML. So machine learning to change these parameters. So this is exciting. And the other thing we are... >> That is pretty cool. I will admit that's very cool. >> Yeah. Yeah. The other thing we like are trying to do is reduce the cost for the customer in the end. So we are collecting petabytes of data. Every time they make updates to the software, they have to re-simulate it or replay this data, so that they can- >> Petabytes? >> Petabytes of data. And, and physically sometimes on a physical hardware in loop device. And then this >> That's called a really heavy edge. You got to move, you don't want to be moving that around the Amazon cloud. >> Yeah. That that's, that's the challenge. And once we have replayed this or re-simulated it. we still have to calculate the KPIs out of it. And what we are trying to do is optimize this test orchestration, so that we are minimizing the REAP simulation. So you don't want the data to be going to the edge, >> Yeah. >> Unnecessarily. And once we get this data back to optimize the way we are doing the calculation, so you're not calculating- >> There's a huge data, integrity management. >> Muhammad: Yeah. >> New kind of thing going on here, it's kind of is it new or is it? >> Muhammad: I mean, it's- >> Sounds new to me. >> The scale is new, so- >> Okay, got it. >> The management of the data, having the whole traceability, that has been in automotive. So also Capgemini involved in aerospace. So in aerospace. >> Yeah. >> Having this kind of high, this validation be very strictly monitored is norm, but now we have to think about how to do it on this large scale. And that's why, like, I think that's the biggest challenge and hopefully what we are trying to, yeah, solve with our DSV offering. >> All right, Muhammad, thanks for coming on theCUBE. I really appreciate it. Great way to close out re:MARS, our last interview our the show. Thanks for coming on. Appreciate your time. >> I mean like just one last comment, like, so I think in automotive, like, so part of the automation the future is quite exciting, and I think that's where like- >> John: Yeah. >> It's, we have to be hopeful that like- >> John: Well, the show is all about hope. I mean, you had, you had space, moon habitat, you had climate change, potential solutions. You have new functionality that we've been waiting for. And, you know, I've watch every episode of Star Trek and SkyNet and kind of SkyNet going on air. >> The robots. >> Robots running cubes, robot cubes host someday. >> Yeah. >> You never know. Yeah. Thanks for coming on. Appreciate it. >> Thank you. Okay. That's theCUBE here. Wrapping up re:MARS. I'm John Furrier You're watching theCUBE, stay with us for the next event. Next time. Thanks for watching. (upbeat music)

>>Thanks. Hey, everyone, welcome back to the cubes. Continuing coverage of snowflakes. Summit 22 live from Caesars Forum in Las Vegas. Lisa Martin here. I have three guests here with me. We're gonna be talking about Snowflake Ventures and the snowflakes start up Challenge. That's in its second year. I've got Harry Glaser with me. Co founder and CEO of Model Bit Start Up Challenge finalist Damon Bryan joins us as well. The CTO and co founder of Hyper Affinity. Also a startup Challenge Finalists. And Stephane Williams to my left here, VP of Corporate development and snowflake Ventures. Guys, great to have you all on this little mini panel this morning. >>Thank you. >>Thank you. >>Let's go ahead, Harry, and we'll start with you. Talk to the audience about model. But what do you guys do? And then we'll kind of unpack the snowflake. The Snowflakes challenge >>Model bit is the easiest way for data scientists to deploy machine learning models directly into Snowflake. We make use of the latest snowflake functionality called Snow Park for python that allows those models to run adjacent to the data so that machine learning models can be much more efficient and much more powerful than they were before. >>Awesome. Damon. Give us an overview of hyper affinity. >>Yes, so hyper affinity were Decision Intelligence platform. So we helped. Specifically retailers and brands make intelligent decisions through the use of their own customer, data their product data and put data science in a I into the heart of the decision makers across their business. >>Nice Step seven. Tell us about the startup challenge. We talked a little bit about it yesterday with CMO Denise Pearson, but I know it's in its second year. Give us the idea of the impetus for it, what it's all about and what these companies embody. >>Yeah, so we This is the second year that we've done it. Um, we it was really out of, um Well, it starts with snowflake Ventures when we started to invest in companies, and we quickly realised that there's there's a massive opportunity for companies to be building on top of the Lego blocks, uh, of snowflake. And so, um, open up the competition. Last year it was the inaugural competition overlay analytics one, Um, and since then, you've seen a number of different functionalities and features as part of snowflakes snow part. Being one of them native applications is a really exciting one going forward. Um, the companies can really use to accelerate their ability to kind of deliver best in class applications using best in class technology to deliver real customer outcomes and value. Um, so we've we've seen tremendous traction across the globe, 250 applicants across 50. I think 70 countries was mentioned today, so truly global in nature. And it's really exciting to see how some of the start ups are taking snowflake to to to new and interesting use cases and new personas and new industries. >>So you had 200 over 250 software companies applied for this. How did you did you narrow it down to three? >>We did. Yeah, >>you do that. >>So, behind the scenes, we had a sub judging panel, the ones you didn't see up on stage, which I was luckily part of. We had kind of very distinct evaluation criteria that we were evaluating every company across. Um and we kind of took in tranches, right? We we took the first big garden, and we kind of try to get that down to a top 50 and top 50. Then we really went into the details and we kind of across, um, myself in ventures with some of my venture partners. Um, some of the market teams, some of the product and engineering team, all kind of came together and evaluated all of these different companies to get to the top 10, which was our semifinalists and then the semi finalists, or had a chance to present in front of the group. So we get. We got to meet over Zoom along the way where they did a pitch, a five minute pitch followed by a Q and A in a similar former, I guess, to what we just went through the startup challenge live, um, to get to the top three. And then here we are today, just coming out of the competition with with With folks here on the table. >>Wow, Harry talked to us about How did you just still down what model bit is doing into five minutes over Zoom and then five minutes this morning in person? >>I think it was really fun to have that pressure test where, you know, we've only been doing this for a short time. In fact model. It's only been a company for four or five months now, and to have this process where we pitch and pitch again and pitch again and pitch again really helped us nail the one sentence value proposition, which we hadn't done previously. So in that way, very grateful to step on in the team for giving us that opportunity. >>That helps tremendously. I can imagine being a 4 to 5 months young start up and really trying to figure out I've worked with those young start ups before. Messaging is challenging the narrative. Who are we? What do we do? How are we changing or chasing the market? What are our customers saying we are? That's challenging. So this was a good opportunity for you, Damon. Would you say the same as well for hyper affinity? >>Yeah, definitely conquer. It's really helped us to shape our our value proposition early and how we speak about that. It's quite complicated stuff, data science when you're trying to get across what you do, especially in retail, that we work in. So part of what our platform does is to help them make sense of data science and Ai and implement that into commercial decisions. So you have to be really kind of snappy with how you position things. And it's really helped us to do that. We're a little bit further down the line than than these guys we've been going for three years. So we've had the benefit of working with a lot of retailers to this point to actually identify what their problems are and shape our product and our proposition towards. >>Are you primarily working with the retail industry? >>Yes, Retail and CPG? Our primary use case. We have seen any kind of consumer related industries. >>Got it. Massive changes right in retail and CPG the last couple of years, the rise of consumer expectations. It's not going to go back down, right? We're impatient. We want brands to know who we are. I want you to deliver relevant content to me that if I if I bought a tent, go back on your website, don't show me more tense. Show me things that go with that. We have this expectation. You >>just explain the whole business. But >>it's so challenging because the brothers brands have to respond to that. How do you what is the value for retailers working with hyper affinity and snowflake together. What's that powerhouse? >>Yeah, exactly. So you're exactly right. The retail landscape is changing massively. There's inflation everywhere. The pandemic really impacted what consumers really value out of shopping with retailers. And those decisions are even harder for retailers to make. So that's kind of what our platform does. It helps them to make those decisions quickly, get the power of data science or democratise it into the hands of those decision makers. Um, so our platform helps to do that. And Snowflake really underpins that. You know, the scalability of snowflake means that we can scale the data and the capability that platform in tangent with that and snowflake have been innovating a lot of things like Snow Park and then the new announcements, announcements, uni store and a native APP framework really helping us to make developments to our product as quick as snowflakes are doing it. So it's really beneficial. >>You get kind of that tailwind from snowflakes acceleration. It sounds like >>exactly that. Yeah. So as soon as we hear about new things were like, Can we use it? You know, and Snow Park in particular was music to our ears, and we actually part of private preview for that. So we've been using that while and again some of the new developments will be. I'm on the phone to my guys saying, Can we use this? Get it, get it implemented pretty quickly. So yeah, >>fantastic. Sounds like a great aligned partnership there, Harry. Talk to us a little bit about model bit and how it's enabling customers. Maybe you've got a favourite customer example at model bit plus snowflake, the power that delivers to the end user customer? >>Absolutely. I mean, as I said, it allows you to deploy the M L model directly into snowflake. But sometimes you need to use the exact same machine learning model in multiple endpoints simultaneously. For example, one of our customers uses model bit to train and deploy a lead scoring model. So you know when somebody comes into your website and they fill out the form like they want to talk to a sales person, is this gonna be a really good customer? Do we think or maybe not so great? Maybe they won't pay quite as much, and that lead scoring model actually runs on the website using model bit so that you can deploy display a custom experience to that customer we know right away. If this is an A, B, C or D lead, and therefore do we show them a salesperson contact form? Do we just put them in the marketing funnel? Based on that lead score simultaneously, the business needs to know in the back office the score of the lead so that they can do things like routed to the appropriate salesperson or update their sales forecasts for the end of the quarter. That same model also runs in the in the snowflake warehouse so that those back office systems can be powered directly off of snowflake. The fact that they're able to train and deploy one model into two production environment simultaneously and manage all that is something they can only do with bottled it. >>Lead scoring has been traditionally challenging for businesses in every industry, but it's so incredibly important, especially as consumers get pickier and pickier with. I don't want I don't want to be measured. I want to opt out. What sounds like what model but is enabling is especially alignment between sales and marketing within companies, which is That's also a big challenge at many companies face for >>us. It starts with the data scientist, right? The fact that sales and marketing may not be aligned might be an issue with the source of truth. And do we have a source of truth at this company? And so the idea that we can empower these data scientists who are creating this value in the company by giving them best in class tools and resources That's our dream. That's our mission. >>Talk to me a little bit, Harry. You said you're only 4 to 5 months old. What were the gaps in the market that you and your co founders saw and said, Guys, we've got to solve this. And Snowflake is the right partner to help us do it. >>Absolutely. We This is actually our second start up, and we started previously a data Analytics company that was somewhat successful, and it got caught up in this big wave of migration of cloud tools. So all of data tools moved and are moving from on premise tools to cloud based tools. This is really a migration. That snowflake catalyst Snowflake, of course, is the ultimate in cloud based data platforms, moving customers from on premise data warehouses to modern cloud based data clouds that dragged and pulled the rest of the industry along with it. Data Science is one of the last pieces of the data industry that really hasn't moved to the cloud yet. We were almost surprised when we got done with our last start up. We were thinking about what to do next. The data scientists were still using Jupiter notebooks locally on their laptops, and we thought, This is a big market opportunity and we're We're almost surprised it hasn't been captured yet, and we're going to get in there. >>The other thing. I think it's really interesting on your business that we haven't talked about is just the the flow of data, right? So that the data scientist is usually taking data out of a of a of a day like something like Smoke like a data platform and the security kind of breaks down because then it's one. It's two, it's three, it's five, it's 20. Its, you know, big companies just gets really big. And so I think the really interesting thing with what you guys are doing is enabling the data to stay where it's at, not copping out keeping that security, that that highly governed environment that big companies want but allowing the data science community to really unlock that value from the data, which is really, really >>cool. Wonderful for small startups like Model Bit. Because you talk to a big company, you want them to become a customer. You want them to use your data science technology. They want to see your fed ramp certification. They want to talk to your C. So we're two guys in Silicon Valley with a dream. But if we can tell them the data is staying in snowflake and you have that conversation with Snowflake all the time and you trust them were just built on top. That is an easy and very smooth way to have that conversation with the customer. >>Would you both say that there's credibility like you got street cred, especially being so so early in this stage? Harry, with the partnership with With Snowflake Damon, we'll start with you. >>Yeah, absolutely. We've been using Snowflake from day one. We leave from when we started our company, and it was a little bit of an unknown, I guess maybe 23 years ago, especially in retail. A lot of retailers using all the legacy kind of enterprise software, are really starting to adopt the cloud now with what they're doing and obviously snowflake really innovating in that area. So what we're finding is we use Snowflake to host our platform and our infrastructure. We're finding a lot of retailers doing that as well, which makes it great for when they wanted to use products like ours because of the whole data share thing. It just becomes really easy. And it really simplifies it'll and data transformation and data sharing. >>Stephane, talk about the startup challenge, the innovation that you guys have seen, and only the second year I can. I can just hear it from the two of you. And I know that the winner is back in India, but tremendous amount of of potential, like to me the last 2.5 days, the flywheel that is snowflake is getting faster and faster and more and more powerful. What are some of the things that excite you about working on the start up challenge and some of the vision going forward that it's driving. >>I think the incredible thing about Snowflake is that we really focus as a company on the data infrastructure and and we're hyper focused on enabling and incubating and encouraging partners to kind of stand on top of a best of breed platform, um, unlocked value across the different, either personas within I T organisations or industries like hypothermia is doing. And so it's it's it's really incredible to see kind of domain knowledge and subject matter expertise, able to kind of plug into best of breed underlying data infrastructure and really divide, drive, drive real meaningful outcomes for for for our customers in the community. Um, it's just been incredible to see. I mean, we just saw three today. Um, there was 250 incredible applications that past the initial. Like, do they check all the boxes and then actually, wow, they just take you to these completely different areas. You never thought that the technology would go and solve. And yet here we are talking about, you know, really interesting use cases that have partners are taking us to two >>150. Did that surprise you? And what was it last year. >>I think it was actually close to close to 2 to 40 to 50 as well, and I think it was above to 50 this year. I think that's the number that is in my head from last year, but I think it's actually above that. But the momentum is, Yeah, it's there and and again, we're gonna be back next year with the full competition, too. So >>awesome. Harry, what is what are some of the things that are next for model bed as it progresses through its early stages? >>You know, one thing I've learned and I think probably everyone at this table has internalised this lesson. Product market fit really is everything for a start up. And so for us, it's We're fortunate to have a set of early design partners who will become our customers, who we work with every day to build features, get their feedback, make sure they love the product, and the most exciting thing that happened to me here this week was one of our early design partner. Customers wanted us to completely rethink how we integrate with gets so that they can use their CI CD workflows their continuous integration that they have in their own get platform, which is advanced. They've built it over many years, and so can they back, all of model, but with their get. And it was it was one of those conversations. I know this is getting a little bit in the weeds, but it was one of those conversations that, as a founder, makes your head explode. If we can have a critical mass of those conversations and get to that product market fit, then the flywheel starts. Then the investment money comes. Then you're hiring a big team and you're off to the races. >>Awesome. Sounds like there's a lot of potential and momentum there. Damon. Last question for you is what's next for hyper affinity. Obviously you've got we talked about the street cred. >>Yeah, what's >>next for the business? >>Well, so yeah, we we've got a lot of exciting times coming up, so we're about to really fully launch our products. So we've been trading for three years with consultancy in retail analytics and data science and actually using our product before it was fully ready to launch. So we have the kind of main launch of our product and we actually starting to onboard some clients now as we speak. Um, I think the climate with regards to trying to find data, science, resources, you know, a problem across the globe. So it really helps companies like ours that allow, you know, allow retailers or whoever is to democratise the use of data science. And perhaps, you know, really help them in this current climate where they're struggling to get world class resource to enable them to do that >>right so critical stuff and take us home with your overall summary of snowflake summit. Fourth annual, nearly 10,000 people here. Huge increase from the last time we were all in person. What's your bumper sticker takeaway from Summit 22 the Startup Challenge? >>Uh, that's a big closing statement for me. It's been just the energy. It's been incredible energy, incredible excitement. I feel the the products that have been unveiled just unlock a tonne, more value and a tonne, more interesting things for companies like the model bit I profanity and all the other startups here. And to go and think about so there's there's just this incredible energy, incredible excitement, both internally, our product and engineering teams, the partners that we have spoke. I've spoken here with the event, the portfolio companies that we've invested in. And so there's there's there's just this. Yeah, incredible momentum and excitement around what we're able to do with data in today's world, powered by underlying platform, like snowflakes. >>Right? And we've heard that energy, I think, through l 30 plus guests we've had on the show since Tuesday and certainly from the two of you as well. Congratulations on being finalist. We wish you the best of luck. You have to come back next year and talk about some of the great things. More great >>things hopefully will be exhibited next year. >>Yeah, that's a good thing to look for. Guys really appreciate your time and your insights. Congratulations on another successful start up challenge. >>Thank you so much >>for Harry, Damon and Stefan. I'm Lisa Martin. You're watching the cubes. Continuing coverage of snowflakes. Summit 22 live from Vegas. Stick around. We'll be right back with a volonte and our final guest of the day. Mhm, mhm

(upbeat music) >> Hello everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California in our studios. Got a great guest here, Rachel Obstler, Vice President, Head of Product at heap.io or Heap is the company name, heap.io is URL. Rachel, thanks for coming on. >> Thanks for having me, John. Great to be here. >> So you guys are as a company is heavily backed with some big time VCs and funders. The momentum is pretty significant. You see the accolades in the industry. It's a hot market for anyone who can collect data easily and make sense of it relative to everything being measured, which is the Nirvana. You can measure everything, but then what do you do with it? So you're at the center of it. You're heading up product for heap. This is what you guys do. And there's a lot of solutions, so let's get into it. Describe the company. What's your mission and what you guys do? >> Yeah, so let me start maybe with how Heap was even started and where the idea came from. So Heap was started by Matin Movassate, someone who was working at Facebook. And this is important 'cause it gets right at the problem that we are trying to solve, which is that he was a product manager at Facebook and he was spending a lot of money on pizza. The reason why he was spending a lot of money on pizza is because he wanted to be able to measure what the users were doing in the product that he was responsible for, and he couldn't get the data. And in order to get the data, he would have to go beg his engineers to put in all sorts of tracking code to collect data. And every time he did so, he had to bribe him with pizza because it's no one's favorite work, number one, and then people want to build new things. They don't want to just constantly be adding tracking code. And then the other thing he found is that even when he did that then it took a couple weeks to get it done. And then he had to wait to collect the data to see what data is. It takes a while to build up the data, and he just thought there must be a better way. And so he founded, he with a couple other co-founders, and the idea was that we could automatically collect data all the time. So it didn't matter if you launched something new, you didn't have to do anything. The data would be automatically collected. And so Heap's mission is really to make it easy to create amazing digital experiences. And we do that by firstly, just making sure you have all the data of what your users are doing because you would think you want to create a new digital experience. You could just do that and it would be perfect the first time, but that's not how it works and users are not predictable. >> Yeah, remember back in the day, big data, Hadoop and that kind of fell flap, but the idea of a data lake started there. You saw the rise of Databricks, the Snowflakes. So this idea that you can collect is there. It's here now, state of the art. Now I see that market. Now the business model comes in. Okay, I can collect everything. How fast can I turn around the insights becomes the next question. So what is the business model of the company? What does the product do? Is it SaaS? Is it a as a package software? How do you guys deploy? How do your customers consume and pay for the service? >> Yeah, so we are a SaaS company and we sell largely to, it could be a product manager. It could be someone in marketing, but it's someone who is responsible for a digital service or a digital product. So they're responsible for making sure that that they're hitting whatever targets they have. It could be revenue, it could be just usage, getting more users adopted, making sure they stay in the product. So that's who we sell to. And so basically our model is just around sessions. So how many sessions do you have? How much data are you collecting? How much traffic do you have? And that's how we charge. I think you were getting at something else though that was really interesting, which is this proliferation of data and then how do you get to an insight. And so one of the things that we've done is first of all, okay, collecting all the data and making sure that you have everything that you need, but then you have a lot of data. So that is indeed an issue. And so we've also built on top of Heap a data science layer that will automatically surface interesting points. So for instance, let's say that you have a very common user flow. Maybe it's your checkout flow. Maybe it's a signup flow and you know exactly what the major milestones are. Like you first fill out a form, you sign up, like maybe you get to do the first thing in the trial. You configure it, you get some value. So we're collecting not only those major milestones, we're collecting every single thing that happens in between. And then we'll automatically surface when there is an important drop off point, for instance, between two milestones so that you know exactly where things are going wrong. >> So you have these indicators. So it's a data driven business. I can see that clearly. And the value proposition in the pitch to the customer is ease of use. Is it accelerated time to value for insights? Is it eliminating IT? Is it the 10X marketer? Or all of those things? What is the core contract with the customer, the brand promise? >> That's exactly. So it's the ability to get to insight. First of all, that you may never have found on your own, or that would take you a long time to keep trialing an error of collecting data until you found something interesting. So getting to that insight faster and being able to understand very quickly, how you can drive impact with your business. And the other thing that we've done recently that adds a lot to this is we recently joined forces with a company named Auryc so we just announced this on Monday. So now on top of having all the data and automatically surfacing points of interest, like this is where you're having drop off, this is where you have an opportunity, we now allow you to watch it. So not only just see it analytically, see it in the numbers, but immediately click a show me button, and then just watch examples of users getting stuck in that place. And it really gives you a much better or clearer context for exactly what's happening. And it gives you a much better way to come up with ideas as to how to fix it as one of those digital builders or digital owners. >> You know, kind of dating myself when I mention this movie "Contact" where Jodie foster finds that one little nugget that opens up so much more insight. This is what you're getting at where if you can find that one piece that you didn't see before and bring it in and open it up and bring in that new data, it could change the landscape and lens of the entire data. >> Yeah. I can give you an example. So we have a customer, Casper. Most are familiar with that they sell mattresses online. So they're really a digital innovator for selling something online that previously you had to like go into a store to do. And they have a whole checkout flow. And what they discovered was that users that at the very end of the flow chose same day delivery were much more likely to convert and ultimately buy a mattress. They would not necessarily have looked at this. They wouldn't necessarily have looked at or decided to track like delivery mechanism. Like that's just not the most front and center thing, but because he collects all the data, they could look at it and say, oh, people who are choosing this converted a much higher rate. And so then they thought, well, okay, this is happening at the very end of the process. Like they've already gone through choosing what they want and putting it in their card and then it's like the very last thing they do. What if we made the fact that you could get same day delivery obvious at the beginning of the whole funnel. And so they tried that and it improved their conversion rate considerably. And so these are the types of things that you wouldn't necessarily anticipate. >> I got to have a mattress to sleep on. I want it today. Come on. >> Yeah, exactly. Like there's a whole market of people who are like, oh no, I need a mattress right now. >> This is exactly the point. I think this is why I love this opportunity that you guys are in. Every company now is digitalizing their business, aka digital transformation. But now they're going to have applications, they're going to have cloud native developers, they're going to be building modern applications. And they have to think like an eCommerce company, but it's not about brick and mortars anymore. It's just digital. So this is the new normal. This is an imperative. This is a fact. And so a lot of them don't know what to do. So like, wait a minute, who do we call? This is like a new problem for the mainstream. >> Yeah, and think about it too. Actually e-commerce has been doing this for quite a while, but think about all the B2B companies and B2B SaaS, like all the things that today, you do online. And that they're really having to start thinking more like e-commerce companies and really think about how do we drive conversion, even if conversion isn't the same thing or doesn't mean the same thing, but it means like a successful retained user. It's still important to understand what their journey is and where you going to help them. >> Recently, the pandemic has pulled forward this digital gap that every company's seeing, especially the B2B, which is virtual events, which is just an indicator of the convergence of physical and online. But it brings up billions of signals and I know we have an event software that people do as well. But when you're measuring everything, someone's in a chat, someone hit a web page, I mean there are billions of signals that need to get stored, and this is what you guys do. So I want to ask you, you run the product team. What's under the covers? What's the secret sauce for you guys at Heap? Because you got to store everything. That's one challenge. That's one problem you got to solve. Then you got to make it fast because most of the databases can't actually roll up data fast enough. So you're waiting for the graph forever when some people say. What's under the covers? What's the secret sauce? >> Well, it's a couple different things. So one is we designed the system from the very beginning for that purpose. For the purpose of bringing in all those different signals and then being able to cut the data lots of different ways. And then also to be able to apply data science to it in real time to be able to surface these important points that you should be looking at. So a lot of it is just about designing the system for the very beginning for that purpose. It was also designed to be easy for everyone to use. So what was a really important principle for us is a democratization of data. So in the past, you have these central data teams. You still have them today. Central data teams that are responsible for doing complex analysis. Well, we want to bring as much of that functionality to the digital builders, the product managers, the marketers, the ones that are making decisions about how to drive impact for their digital products and make it super easy for them to find these insights without having to go through a central team that could again take weeks and months to get an answer back from. >> Well, that's what brings up a good point. I want to dig into, if you don't mind, Rachel, this data engineering challenge. There's not enough talent out there. When I call data engineer, I'm talking about like the specialist person. She could be a unique engineer, but not a data scientist. We're talking about like hardcore data engineering, pipelining, streaming data, hardcore. There's not many people that fit that bill. So how do you scale that? Is that what you guys help do? >> We can help with that. Because, again, like if you put the power in the hands of the product people or the marketers or the people that are making those decisions, they can do their own analysis. Then you can really offload some of those central teams and they can do some of the much more complex work, but they don't have to spend their time constantly serving maybe the easier questions to answer. You have data that's self-service for everyone. >> Okay, before I get into the quick customer side of it, quickly while I have you on the product side. What are some of your priorities? You look at the roadmap, probably got tons of people calling. I can only imagine the customer base is diverse in its feature requests. Everyone has the same need, but they all have different businesses. So they want a feature here. They want a feature there. What's the priorities? How do you prioritize? What are some of your priorities for how you're going to build out and keep continuing the momentum? >> Yeah, so I mentioned earlier that we just joined forces with a company name Auryc that has session replay capabilities, as well as voice of customer. So one of our priorities is that we've noticed in this market, there's a real, it's very broken up in a strange way. I shouldn't say it's strange. It's probably because this is the way markets form, startups start, and they pick a technology and they build on top of it. So as a result, the way the market has formed is that you have analytics tools like Heap, and they look at very quantitative data, collecting all sorts of data and doing all sorts of quantitative cuts on it. And then you have tools that do things like session replay. So I just want to record sessions and watch and see exactly what the user's doing and follow their path through one at a time. And so one is aggregating data and the other one is looking at individual user journeys, but they're solving similar jobs and they're used by the same people. So a product manager, for example, wants to find a point of friction, wants to find an opportunity in their product that is significant, that is happening to a lot of people, that if they make a change will drive impact like a large impact for the business. So they'll identify that using the quant, but then to figure out how to fix it, they need the qual. They need to be able to watch it and really understand where people are getting stuck. They know where, but what does that really look like? Like, let me visualize this. And so our priority is really to bring these things together to have one platform where someone can just, in seconds, find this point of opportunity and then really understand it with a show me button so that they can watch examples of it and be like, I see exactly what's happening here and I have ideas of how to fix this. >> Yeah, something's happening at that intersection. Let's put some cameras on. Let's get some eyes on that. Let's look at it. >> Exactly. >> Oh, hey, let's put something. Let's fix that. So it makes a lot of sense. Now, customer attraction has been strong. I know it's been a lot of press and accolades online with when you guys are getting review wise. I mean, I can see DevOps and app people just using this easily, like signing up and I can collect all the data and seeing value, so I get that. What are some of the customer value propositions that are coming out of that, that you can share? And for the folks watching that don't know Heap, what's their problem that they're facing that you can solve, and what pain are they in or what problem do they solve? So example of some success that's coming out of the platform, enablement, the disruptive enablement, and then what's the problem, what's the customer's pain point, and when they know to call you guys or sign up. >> Yeah, so there's a couple different ways to look at it. When I was talking about is really for the user. There's this individual person who owns an outcome and this is where the market is going that the product managers, the marketers, they're not just there to build new features, they're there to drive outcomes for the business. And so in order to drive these outcomes, they need to figure out what are the most impactful things to do? Where are the investments that they need to make? And so Heap really helps them narrow down on those high impact areas and then be able to understand quickly as I was mentioning how to fix them. So that's one way to look at it. Another use case is coming from the other side. So talking in about session replay, you may have a singular problem. You may have a single support ticket. You may have someone complaining about something and you want to really understand, not only what is the problem, like what were they experiencing that caused them to file this ticket, but is this a singular problem, or is this something that is happening to many different people? And therefore, like we should prioritize fixing it very quickly. And so that's the other use case is let's start, not with the group, like the biggest impact and go to like exactly some examples, let's start with the singular and figure out if that gives you a path to the group. But the other use case that I think is really interesting is if you think about it from a macro point of view or from a product leader or a marketing leader's point of view, they're not just trying to drive impact. They're trying to make it easy for their team to drive that impact. So they're thinking about how do they make their whole organization a lot more data driven or insights driven? How do they change the culture, the process, not just the tool, but all of those things together so that they can have a bigger business impact and enable their team to be able to do this on their own? >> You guys are like a data department for developers and product managers. >> Essentially, like we are the complete dataset and the easy analysis that really helps you figure out, where do I invest? How do I justify my investments? And how do I measure how well my investments are doing? >> And this is where the iteration comes in. This is the model everyone's doing. You see a problem, you keep iterating. Got to look at the data, get some insight and keep looking back and making that product, get that flywheel going. Rachel, great stuff. Coming out here, real quick question for you to end the segment. What's the culture like over at Heap? If people are interested in joining the company or working with you guys. Every company has their own kind of DNA. What's the Heap culture like? >> That's a great question. So Heap is definitely a unique company that I've worked at and in a really good way. We find it really important to be respectful to each other. So one of our values is respectful candor. So you may be familiar with radical candor. We've kind of softened it a bit and said, look, it's good to be truthful and have candor, but let's do it in a respectful way. We really find important that everyone has a growth mindset. So we're always thinking about how do we improve? How do we get better? How do we grow faster? How do we learn? And then the other thing that I'll mention, another one of our values that I love, we call it, "taste the soup". Some people use to call it dogfooding, but we are in Heap all the time. We call it Heap on Heap. We really want to experience what our customers experience and constantly use our product to also get better and make our product better. >> A little more salt on the sauce, keep the soup, taste it a little bit. Good stuff. Rachel, thanks for coming on. Great insights and congratulations on a great product opportunity. Again, as world goes digital transformation, developers, product, all people want to instrument everything to then start figuring out how to improve their offering. So really hot market and hot company. Thanks for coming on. >> Thanks, John. Thanks for having me. >> This is theCUBE conversation. I'm John Furrier here in Palo Alto, California. Thanks for watching. (gentle music)

>> Welcome back to the Seaport in Boston and this is theCUBE's coverage of Red Hat Summit 2022. I'm Dave Vellante with my co-host Paul Gillin. Rob Belson is here as the Developer Relations Lead at Verizon. Robbie great to see you. Thanks for coming on theCUBE. >> Thanks for having me. >> So Verizon and developer relations. Talk about your role there. Really interesting. >> Absolutely. If you think about our mobile edge computing portfolio in Verizon 5G Edge, suddenly the developer is a more important persona than ever for actually adopting the cloud itself and adopting the mobile edge. So the question then quickly became how do we go after developers and how do we tell stories that ultimately resonate with them? And so my role has been spearheading our developer relations and experience efforts, which is all about meeting developers in the channels where they actually are, building content that resonates with them. Building out architectures that showcase how do you actually use the technology in the wild? And then ultimately creating automation assets that make their lives easier in deploying to the mobile edge. >> So, you know, telcos get a bad rap, when you're thinking it's amazing what you guys do. You put out all this capital infrastructure, big outlays. You know, we use our phones to drop a call. People like, "Ah, freaking Verizon." But it's amazing what we can actually do too. You think about the pandemic, the shift that the telcos had to go through to landlines to support home, never missed a beat. And yet at the same time you're providing all this infrastructure for people to come over the top, the cost forbid is going down, right? Your cost are going up and yet now we're doing this big 5G buildup. So I feel like there's a renaissance about to occur in edge computing that the telcos are going to lead new forms of monetization new value that you're going to be able to add, new services, new applications. The future's got to be exciting for you guys and it's going to be developer-led, isn't it? >> Absolutely. I mean it's been such an exciting time to be a part of our mobile edge computing portfolio. If you think back to late 2019 we were really asking the question with the advent of high speed 5G mobile networks, how can you drive more immersive experiences from the cloud in a cloud native way without compromising on the tools you know and love? And that's ultimately what caused us to really work with the likes of AWS and others to think about what does a mobile edge computing portfolio look like? So we started with 5G Edge with AWS Wavelength. So taking the compute and storage services you know and love in AWS and bringing it to the edge of our 4G and 5G networks. But then we start to think, well, wait a minute. Why stop at public networks? Let's think about private networks. How can we bring the cloud and private networks together? So you turn back to late 2021 we announced Verizon 5G Edge with AWS Outposts but we didn't even stop there. We said, "Well, interest's cool, but what about network APIs? We've been talking about the ability and the programmability of the 5G network but what does that actually look like to the developers? And one great example is our Edge Discovery Service. So you think about the proliferation of the edge 17 Wavelength Zones today in the US. Well, what edge is the right edge? You think about maybe the airline industry if the closest exit might be behind you absolutely applies to service discovery. So we've built an API that helps answer that seemingly basic question but is the fundamental building block for everything to workload orchestration, workload distribution. A basic network building block has become so important to some of these new sources of revenue streams, as we mentioned, but also the ability to disintermediate that purpose built hardware. You think about the future of autonomous mobile robots either ground and aerial robotics. Well, you want to make those devices as cheap as possible but you don't want to compromise on performance. And that mobile edge layer is going to become so critical for that connectivity, but also the compute itself. >> So I just kind of gave my little narrative up front about telco, but that purpose built hardware that you're talking about is exceedingly reliable. I mean, it's hardened, it's fossilized and so now as you just disaggregate that and go to a more programmable infrastructure, how are you able to and what gives you confidence that you're going to be able to maintain that reliability that I joke about? Oh, but it's so reliable. The network has amazing reliability. How are you able to maintain that? Is that just the pace of technology is now caught up, I wonder if you can explain that? >> I think it's really cool as I see reliability and sort of geo distribution as inextricably linked. So in a world where to get that best in class latency you needed to go to one place and one place only. Well, now you're creating some form of single source of failure whether it's the power, whether it's the compute itself, whether it's the networking, but with a more geo distributed footprint, particularly in the mobile edge more choices for where to deliver that immersive experience you're naturally driving an increase in reliability. But again, infra alone it's not going to do the job. You need the network APIs. So it's the convergence of the cloud and network and infra and the automation behind it that's been incredibly powerful. And as a great example, the work we've been doing in hybrid MEC the ability to converge within one single architecture, the private network, the public network, the AWS Outposts, the AWS Wavelength all in one has been such a fantastic journey and Red Hat has been a really important part in that journey. >> From the perspective of the developer when they're building a full cloud to edge application, where does Verizon pick up? Where do they start working primarily with you versus with their cloud provider? >> Absolutely. And I think you touched on a really important point. I think when you often think about the edge it's thought of as an either, or. Is it the edge? Is it the cloud? Is it both? It's an and I can't emphasize that enough. What we've seen from the customers greenfield or otherwise it's about extending an application or services that were never intended to live at the edge, to the edge itself, to deliver a more performant experience. And for certain control plane operations, metadata, backend operations analytics that can absolutely stay in the cloud itself. And so our role is to be a trusted partner in some of our enterprise customers' journeys. Of course, they can lean on the cloud provider in select cases, but we're an absolutely critical mode of support as you think about what are those architectures? How do you integrate the network APIs? And through our developer relations efforts, we've put a major role in helping to shape what those patterns really look like in the wild. >> When they're developing for 5G I mean, the availability of 5G of particularly you know, the high bandwidth 5G is pretty spotty right now. Mostly urban areas. How should they be thinking in the future developing an application roll out two years from now about where 5G will be at that point? >> Absolutely. I think one of the most important things in this case is the interoperability of our edge computing portfolio with both 4G and 5G. Whenever somebody asks me about the performance of 5G they ask how fast? Or for edge computing. It's always about benchmark. It's not an absolute value. It's always about benchmarking the performance to that next best alternative. What were you going to get if you didn't have edge computing in your back pocket? And so along that line of thought having the option to go either through 4G or 5G, having a mobile edge computing portfolio that works for both modes of connectivity even CAN-AM IoT is incredibly powerful. >> So it sounds like 4G is going to be with us for quite a while still? >> And I think it's an important part of the architecture. >> Yeah. >> Robert, tell us about the developer that's building these applications. Where does that individual come from? What's their persona? >> Oh, boy I think there's a number of different personas and flavors. I've seen everything from the startup in the back of a garage working hard to try to figure out what could I do for a next generation media and entertainment experience but also large enterprises. And I think a great area where we saw this was our 5G Edge Computing Challenge that we hosted last year. Believe it or not 100 submissions from over 22 countries, all building on Verizon 5G Edge. It was so exciting to see because so many different use cases across public safety, healthcare, media and entertainment. And what we found was that education is so important. A lot of developers have great ideas but if you don't understand the fundamentals of the infrastructure you get bogged down in networking and setting up your environment. And that's why we think that developer education is so important. We want to make it easy and in fact, the 5G Edge portfolio was designed in such a way that we'll abstract the complexities of the network away so you can focus on building your application and that's such a central theme and focus for how we approach the development. >> So what kind of services are you exposing via APIs? >> Absolutely, so first and foremost, as you think about 5G Edge with say AWS Wavelength, the infra there are APIs that are exposed by AWS to launch your infra, to patch your infrastructure, to automate your infrastructure. Specifically that Verizon has developed that's our network APIs. And a great example is our Edge Discovery Service. So think of this as like a service registry you've launched an application in all 17 edge zones. You would take that information, you would send it via API to the Edge Discovery Service so that for any mobile client say, you wake up one morning in Boston, you can ask the API or query, "Hey, what's the closest edge zone?" DNS isn't going to be able to figure it out. You need knowledge of the actual topology of the mobile network itself. So the API will answer. Let's say you take a little road trip 1,000 miles south to say Miami, Florida you ask that question again. It could change. So that's the workflow and how you would use the network API today. >> How'd you get into this? You're an engineer it's obvious how'd you stumble into this role? >> Well, yeah, I have a background in networks and distributed systems so I always knew I wanted to stay in the cloud somewhere. And there was a really unique opportunity at Verizon as the portfolio was being developed to really think about what this developer community looked like. And we built this all from scratch. If you look at say our Verizon 5G Edge Blog we launched it just along the timing of the actual GA of Wavelength. You look at our developer newsletter also around the time of the launch of Wavelength. So we've done a lot in such a short period and it's all been sort of organic, interacting with developers, working backwards from the customer. And so it's been a fairly new, but incredibly exciting journey. >> How will your data, architecture, data flow what will that look like in the future? How will that be different than it is sort of historically? >> When I think about customer workloads real time data architecture is an incredibly difficult thing to do. When you overlay the edge, admittedly, it gets more complicated. More places that produce the data, more places that consume data. How do you reconcile all of these environments? Maintain consistency? This is absolutely something we've been working on with the ecosystem at large. We're not going to solve this alone. We've looked at architecture patterns that we think are successful. And some of the things that we found that we believe are pretty cool this idea of taking that embedded mobile database, virtualizing it to the edge, even making it multi-tenant. And then you're producing data to one single source and simplifying how you organize and share data because all of the data being produced to that one location will be relevant to that topology. So Boston, as an example, Boston data being produced to that edge zone will only service Boston clients. So having a geo distributed footprint really does help data architectures, but at the core of all of this database, architectures, you need a compute environment that actually makes sense. That's performant, that's reliable. That's easy to use that you understand how to manage and that the edge doesn't make it any more difficult to manage. >> So are you building that? >> That's exactly what we're doing. So here at Red Hat Summit we've had the unique opportunity to continue to collaborate with our partners at Red Hat to think about how you actually use OpenShift in the context of hybrid MEC. So what have done is we've used OpenShift as is to extend what already exists to some of these new edge zones without adding in an additional layer of complexity that was unmanageable. >> So you use OpenShift so you don't have to cobble this together on your own as a full development environment and that's the role really that OpenShift plays here? >> That's exactly right. And we presented pieces of this at our re:Invent this past year and what we basically did is we said the edge needs to be inextricably linked with the cloud. And you want to be able to manage it from some seamless central pane of glass and using that OpenShift console is a great way. So what we did is we wanted to show a really geo-distributed footprint in action. We started with a Wavelength zone in Boston, the region in Northern Virginia, an outpost in the Texas area. We cobbled it all together in one cluster. So you had a whole compute mesh separated by thousands of miles all within a single cluster, single pane of glass. We take that and are starting to expand on the complexity of these architectures to overlay the network APIs we mentioned, to overlay multi-region support. So when we say you can use all 17 zones at once you actually can. >> So you've been talking about Wavelength and Outposts which are AWS products, but Microsoft and Google both have their distributed architectures as well. Where do you stand with those? Will you support those? Are you working with them? >> That's a great question. We have made announcements with Microsoft and Google but today I focus a lot on the work we do with AWS Wavelength and Outposts and continuing to work backwards from the customer and ultimately meet their needs. >> Yeah I mean, you got to start with an environment that the developers know that obviously a great developer community, you know, you see it at re:Invent. What was the reaction at re:Invent when you showed this from a developer community? >> Absolutely. Developers are excited and I think the best part is we're not the only ones talking about Wavelength not even AWS are the only ones talking about Wavelength. And to me from a developer ecosystem perspective that's when you know it's working. When you're not the one telling the best stories when others are evangelizing the power of your technology on your behalf that's when the ecosystem's starting to pick up. >> Speaking of making a bet on Outposts you know, it's somewhat limited today. I'll say it it's limited today in terms of we think it supports RDS and there's a few storage players. Is it your expectation that Outposts is going to be this essentially the cloud environment on your premises is that? >> That's a great question. I see it more as we want to expand customer choice more than ever and ultimately let the developers and architects decide. That's why I'm so bullish on this idea of hybrid MEC. Let's provide all of the options the most complicated geo distributed hybrid deployment you can imagine and automate it, make it easy. That way if you want to take away components of this architecture all you're doing is simplifying something that's already automated and fairly simple to begin with. So start with the largest problem to solve and then provide customers choice for what exactly meets their requirements their SLAs, their footprint, their network and work backwards from the customer. >> Exciting times ahead. Rob, thanks so much for coming on theCUBE. It's great to have you. >> Appreciate it, thanks for your time. >> Good luck. All right, thank you for watching. Keep it right there. This is Dave Vellante for Paul Gillin. We're live at Red Hat Summit 2022 from the Seaport in Boston. We'll be right back.

(upbeat music) >> Welcome to theCUBE coverage of women in tech. International Women's Day 2022. I'm your host, Lisa Martin. Karla Wong joins me next. Country Sales Leader for the Commercial Sector in Peru at AWS. Karla, welcome to theCUBE. >> Thank you so much Lisa and thank you for having me. It's a pleasure to be with you today. >> I'm looking forward to chatting with you. You've been in the tech industry for more than 20 years, you've been a leader in tech and sales and customer service, partners, organizations. Talk to me a little bit about your background. >> I am a system engineer. I have some studies from enterprise direction with a university in Savannah, Columbia and I have a digital transformation certified with MIT in Boston. >> Fantastic, were you always interested in technology or STEM or was it something that you pivoted into somewhere during your career? >> Yes, you know what? Since I was little, I was just fascinated with the technology and all the time I was just trying to figure out how to do things and how to build that things and I remember once I was just, of course many time long ago, I was with this BHS, right? An equipment and I tried to do and tried to understand how this works and just figure out I was with many parts of that equipment and then I didn't realize how to join that parts but it was really funny because all the time I was trying to understand what is behind that kind of equipment, how this works and all the time I was asking and my dad said, I was just feeling so curiosity about that and asking many questions and I have uncles that they are engineers. So I was just all the time asking about that and they said, you know what? You are good in math, maybe you can just decide for an engineering career. They were encouraged me for doing that. So I guess that was my first clue that I'm interested in technology. >> Well, you sounds like you have a natural curiosity that you had great role models in your parents and probably others along your educational route and your career route that kind of encouraged that curiosity and being curious is one of the things that's important to being at AWS. Am I right? >> Yes, it's really important because we promote, you know, our, one of the main leadership principles that you read is learn to be curious and they promote that one, right? They're encouraging you to innovate, to learn more, to try to understand more about our solutions, our customers, how to make the things better and you have the space to propose new things, to do the things better. So they encourage you and they empower you to do that and you feel like your curiosity that you have very natural here's improved and they just promote that you continue to do that. >> That curiosity is so important. I mean, when we think about women in technology and we think about bringing in more thought diversity and DEI, it's important to be curious, to be able to bring different thoughts in so that the organization can be more well rounded, it can learn, you also not only do you lead the sales organization, but you are someone that's very active in volunteering. Tell me a little bit about that and how do you balance leading a sales organization and volunteering at the same time? >> You know, when you talk about this is more like work life balance, right? And when we talk about that you can feel like you need it, right? You need to work on that. It's more like an attitude of it's extremely important to think about mental health for everyone because that of course have impact in your physical health and when you talk about this, it not only matters in terms of attitude, it's action and disciplines as well and you have to keep in mind that. The first thing I believe and all the time I do it give the right value for this balance because it's something that a lot of people want more than anything and I have more than some professional decision thinking about this precisely and I have to thinking of me as a person, my family, how to help the community and you cannot imagine the impact when you decide to go for a volunteering activities how can benefit you and not in only the personal way, in your professional way. Even though you didn't start a volunteering, trying to figure out how this help you in your professional life, you receive a lot of benefits from the volunteering activities and it's amazing how that one's impacting your professional life also. When you are a volunteer, you'll receive new and meaningful experiences. Volunteering can be an excellent getaway to find unique and valuable experiences that you are very difficult to find in a day to day basis, right? And you develop your real life skills, openness to criticism, responsibility, humility, commitment, service, attitude, many things that you can proactively include in your job with your team and you can join with them in teamwork and try to figure out how to engage with them in your activities. This is another way to motivate your team, to build your team, right? Talking with this very valuable experiences and also I find out that that improves your health and mood. >> Sounds very-- >> We talk having-- >> Sorry. >> I'm sorry, no don't worry. >> That's very complimentary, that the volunteer work with leading the sales organization that there's so much value that you're bringing into your sales leadership role from the volunteering that you do. I'm just curious, can you describe some of the volunteer organizations that you work with? I think it's pretty impressive. >> Yes, I started my volunteering 14 years ago I guess but I was in the volunteering activities from the school and my dad was a really strong influence for that because I joined, I remember joining with him and go to do some volunteering activities that he led and I start 14 years I went with Operation and Smile group and then in the last two or three years I start with Project of Love. We are focused on kids with cancer and try to help them to build the last wishes they have because they pass away and at the end of this, this two years ago, I start with local activity that we do for patients with rare diseases and we just try to join two great passion that I have. One is the dance that we have here. The name of our national dance is Marinera Norteña and we are just doing this with a group that they are passion at the same time with this volunteering activities and the dance and we just trying to be the ambassador for and the voice for these patients, try to share with the community, the hard health journey that they have trying to obtain a fair treatment, a fair diagnostic, because they are rare disease and here is very difficult that they investigate about that. So that's why we are just doing this using dance as a way to broadcast our voice and just share happiness and hope and health. >> Happiness and hope. Those are two great things. So as the female leader in the tech industry, what are some of the main challenges that you have found regarding cultural aspects, regarding geographical aspects and LATAM? Talk to me about some of those challenges. >> Let me share with you my personal journey. My challenges started with the moment I decided to start engineering. A career that is traditional considered for men only, although this changes over the time, you will realize that the stereotype remains in many people minds right? It happens not only in Peru I can see it in Latin America. Someone once asked me if I wouldn't like to study something easier for a woman, right? And I just, when I received that question, that helping me to reaffirm that it was taking the right decision and I have the fortune to work with companies that believe in female leadership and the importance of our contribution and empower me to do things differently. Although I must confess that this was not always like this. I experienced the situation when I have to show that I'm so much and more capable and prepared than a man to take a major challenge. So despite the fact in the recent years you have had the great advances in integration of women in the field of science and technology, the gap in equality in equality in this sector still continues and many times the attitude towards women is discriminatory considering that we don't have enough knowledge and we don't have enough strength to overcome challenge without the ability to give the extra mile that is often required, or simply because of a gender issue. And generally speaking, opportunities that they're not equal. Neither in salaries. Several studies have revealed that in the same position since at position level within company, men's salary or benefits are higher than the woman. In addition, sometimes the position for a woman is not necessarily for merit it's just to feel fulfill a gender quota and when it's fulfilled, there's no more opportunities. So it's still a long way to go. We are working in that, we are trying to inspire more women to be part of this world. This is an amazing world and this world needs our leadership, judgment, ambition, as a woman. So that's why we try to inspire and try to be a role model for some young ladies that they are thinking about this career in technology. >> Right, you bring up a great point though about one of the things in terms of hiring for quotas. And as we think about this International Women's Day, this year's theme is Breaking the Bias. Where do you think we are with that? >> I think we have a lot long, long way to go to. Today we don't see that we have more women in some leadership roles in technology. We see more young ladies studying engineering but you know what, when you talk about stereotypes we need to understand, or the bias, the bias is not only what the society it's giving you, it's also your own bias because we need to understand that technology careers is not only for men it's also for a woman. And we need to understand and change the perspective that we see the challenges that we have in our life because sometimes that could be a really stopper in your professional life. And for me, we don't, we really need to understand that it's important. We cannot stop believing in ourself and we can achieve whatever we want. So we never stop pursuing our goals and achieve what you really need to achieve and as I said all the time, get inspired by women with great achievements who have changed this world technology. We have many examples of that for many years. We have Eva Maria Kiesler, the core inventor of Wi-Fi, Radia Joy Perlman, known as the the mother of the internet and Ada Lovelace who became the first female computer programmer. So we have many examples in this story to understand that the limit is on you. So the bias we need to break the first one is the bias that you have of yourself. >> That's a good point. That's a really good point there. I'm curious, what would your recommendation be? You obviously had, you had that natural curiosity that we talked about. You also seems like you had great parents who were very encouraging of all of the different things that you were interested in. What do you recommend for women maybe starting out in the STEM area or in tech in particular? How do they get that courage to just try? >> You know what, the main thing I guess as I mentioned before, is to put aside the stereotypes, right? And get out of your head, the standing out career like science, technology and engineering is only for a man. All the time I have this list for me, that is lesson learned. And my lesson learned is please don't think that you cannot do it. Try it. If you go and the things do not work well, try it again and try it again. So don't feel stopped because you face your first challenge and the challenge it's very difficult, because we have the courage to do that and you know what? It is very and interesting to understand that women has resilience, we have the courage to do anything, we are multi tasking all the time they say women can do many things at the same time and we have this particular way to communicate. We are very inclusive. We make empathy. We're just leading with a cohesion concept of a team. So we need to explore more about our strengths and try to encourage from them. And one of the main things for me is don't feel afraid and transform, you know, when you feel like that, transfer that as your power, you're encouraged to continue. So we need to transform our fears in our, I always said our gasoline to continue and then your motive to be successful. So transform your fears. >> I love that. >> That's my main focus. >> Transform your fear. That's great advice there is. And I will say no, don't be afraid to raise your hand and ask a question 'cause I guarantee you, many people in the room whether it's a physical room these days or it's a virtual video conferencing room, probably have the same question. Be the one to raise your hand and ask. But I love how you're saying transform that fear 'cause it's there. Don't be afraid to fail but also we need to have those female role models, mentors and sponsors that we can see that can have help us kind of in that transformation process, that mentorship is really critical to help guide that along. >> Yes, yes, yes, that's correct and I will, I am, I was really fortunate because I have real role models in my life not only, as I mentioned my dad and also one of the things that I recognize in this company that I work for that empower leadership from women and I identify some role models I want to follow and I ask her in each particular company to be my coach and to be my mentor, because of course you are starting in the technology side and you need more from others that they can share with you her wisdom, right? And try to give you advice, how to work on that. And I always said, and I will always repeat because I sometimes I have the opportunity to mentor young ladies that they are very curious about the technology side and I share with them my experience, my lesson learned so they can build their own story to do this and I share all the time don't compete in a male environment in a gray suit. You have your own personality, you have your own strengths, you're a woman and you have your strength as a woman. Show that, be, you know, the black point in the middle of the white environment because you're different, your leadership is different. You have to understand that, value that and explore more about that so you can inspire others and you can inspire yourself and it's fair to say, please identify your achievements and value them because you deserve that, you fight for them and you have to be celebrate for that. >> Right. >> So that's the main, you know, the main idea when I share with these ladies but it's right, it's fair to be recognized for that. It's your effort, it's your way to do the things differently and it's very appreciated. >> Very appreciated and very inspiring. Thank you so much Karla for sharing your story, how you are balancing work life volunteerism, how it's complimentary. I found this conversation very inspiring so thank you so much for joining me today. >> Thank you. No, thank you so much Lisa. It was really a pleasure for me to be with you today. >> Excellent, likewise. For Karla Wong, I'm Lisa Martin. You're watching theCUBE's coverage of women in tech, International Women's Day 2022. 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(upbeat music) >> Hey, everyone. Welcome back to theCUBE's live coverage of Women in Data Science Worldwide Conference, WiDS 2022, live from Stanford Uni&versity. I'm Lisa Martin. I have a guest next here with me. Maggie Wang is here, Autonomy Engineer at Skydio. Maggie, welcome to the program. >> Thanks so much. I'm so happy to be here. >> Excited to talk to you. You are one of the event speakers, but this is your first WiDS. What's your take so far? >> I'm really excited that there's a conference dedicated to getting more women in STEM. I think it's extremely important, and I'm so happy to be here. >> Were you always interested in STEM subjects when you were growing up? >> I think I've always been drawn to STEM, but not only STEM, but I've always been interested in arts, humanities. I'm getting more interested in the science as well. And I think STEM robotics was really my way to express myself and make things move in the real world. >> Nice. So you've got interests, I was reading about you, interests in motion planning, control theory, computer vision and deep learning. Talk to me about those interests. It sounds very fascinating. >> Yeah. So I think what really drew me into robotics was just how interdisciplinary the subject is. So I think a lot goes into creating a robot. So not only is it about actually understanding where you are in the world, it's also about seeing where you are in the world. And it's so interesting, because I feel like humans, you know, we take this all for granted, but it's actually so difficult to do that in an actual robot. So I'm excited about the possibilities of robotics now and in the future. >> Lots of possibilities. And you only graduated from Harvard last May, with a Bachelor's and a Masters? >> Yeah. >> Tell me a little bit about what you studied at Harvard. >> Yeah, so I studied Physics as my undergrad degree. And that was really interesting, because I've always been interested in science. And, actually, part of what got me interested in STEM was just learning about the universe and astrophysics. And that's what gets me excited. And I think I also wanted to supplement that with computer science and building things in the real world. And so that's why I got my Masters in that. And I always knew that I wanted to kind of blend a lot of different disciplines and study them. >> There's so much benefit from blending disciplines, in terms of even the thought diversity alone, which just opens up the opportunities to be almost endless. So you graduated in May. You're now at Skydio. Autonomy Engineer. Talk to me a little bit, first of all, tell me a bit about Skydio as a company, the products, what differentiates it, and then talk to me about what you're doing there specifically. >> So Skydio is a really amazing company. I'm super-fortunate to work there. So what they do is create autonomous drones, and what differentiates them is the autonomy. So in typical drones, it's very difficult to actually make sure that it has full understanding of the environment and obstacle avoidance. So what happens is we fly these drones manually, but we aren't able to harness the full potential of these drones because of lack of autonomy. So what we do is really push into this autonomous sphere, and make sure that we're able to understand the environment. We have deep learning algorithms on the drone, and we have really good planning and controls on the drone as well. So yeah, our company basically makes the most autonomous drones in the market. >> Nice. And tell me about your role specifically. >> Yeah. So as an autonomy engineer, I write algorithms that run on the drone, which is super-exciting. I can create some algorithms and design it, and then also fly it in simulation, and then fly it in the real world. So it's just really amazing to see the things I work with actually come to life. >> And talk to me about how you got involved in WiDS. You were saying it was your first WiDS, and Margot Gerritsen found you on LinkedIn, but what are some of the things that you've heard so far? I mean, I was in one of the panels this morning before we came out to the set, and I loved how they were talking about the importance of mentors and sponsors. Talk to me about some of your mentors along the way. >> Yeah, I had so many great mentors along the way. I definitely would not be here had it not been for them. Starting from my parents, they're immigrants from China, and they inspire me in so many ways. They're very hard-working, and they always encourage me to fail, and just be courageous, and, you know, follow my passions. And I think beyond that, like in high school, I had great mentors. One was an astrophysics professor. >> Wow. >> Yeah. So it was very amazing that I was able to have these opportunities at a young age. And even in high school, I was involved in all girls robotics team. And that really opened my eyes to how technology can be used and why more women should be in STEM. And that, you know, STEM should not be only for males. And it's really important for everyone to be involved. >> It is, for so many reasons. If we look at the data, and the workforce is about 50-50, but the number of women in STEM positions is less than 25%. It's something that's new to the tech industry. What are some of the things that... Do you see that, do you feel that, or are you just really excited to be able to focus on doing the autonomous engineering that you're doing? >> Well, I think that it's kind of easy to try to separate yourself and your identity from your work, but I don't necessarily agree with that. I think you need to, as best as possible, bring yourself to the table and bring your whole identity. And I think part of growing up for me was trying to understand who I was as a woman and also as an Asian American, and try to combine all of my identities into how I bring myself to the workplace. And I think as we become more vulnerable and try to understand ourselves and express ourselves to others, we're able to build more inclusive communities, in STEM and beyond. >> I agree. Very wise words. So you're going to be talking on the career panel today. What are some of the parts of wisdom are you going to leave the audience with this afternoon? >> Well, wisdom. I think everyone should be able to know, and have intuitive understanding of what they actually bring to the table. I think so many times women shy away from bringing themselves and showing up as themselves. And I think it's really important for a woman to understand that they hold a lot of power, that they have a voice that need to be heard. And I think I just want to encourage everyone to be passionate and show up. >> Be passionate and show up. That's great advice. One of the things that was talked about this morning, and we talk about this a lot when we talk about data or data science, is the inherent bias in data. Talk to me about the importance of data in robotics. Is there bias there? How do you navigate around that? >> Yeah, there's definitely bias in robotics. There's definitely a lot of data involved in robotics. So in many cases right now in robotics, we work in specialized fields, so you can see picking robots that will pick in specific factory locations. But if you bring them to other locations, like in your garage or something, and make it clean up, it's really difficult to do so. So I think having a lot of different streams of data and having very diverse sets of data is very important. And also being able to run these in the real world I think is also super-important, and something that Skydio addresses a lot. >> So you talked about Skydio, what you guys do there, and some of the differentiators. What are some of the technical challenges that you face in trying to do what you're doing? >> Well, first of all, Skydio's trying to run everything on board on the drone. So already there's a lot of technical challenges that goes into putting everything in a small form factor and making sure that we trade off between compute and all of these different resources. And yeah, making sure that we utilize all of our resources in the best possible way. So that's definitely one challenge. And making sure that we have these trade-offs, and understand the trade-offs that we make. >> That's a good point. Talk to me about why robotics researchers and industry practitioners, what should be some of the key things that they're focusing on? >> Yeah, so I think right now, as I said, a lot of robotics is in very specialized environments, and what we're trying to do in robotics is try to expand to more complex real world applications. And I think Skydio's at the forefront of this. And trying to get these drones in all different types of locations is very difficult, because you might not have good priors, you might not have good information on your data sources. So I think, yeah, getting good, diverse data and making sure that these robots can work in multiple environments can hopefully help us in the future when we use robots. >> Right. There's got to be so many real world a applications of that. >> Yeah, for sure. >> I imagine. Definitely. So talk to me about being a female in the drone industry. What's that like? Why do you think it's important to have the female voice in mind in the drone industry? >> Well, I think first of all, I think it's kind of sad to see not many women in the drone space, because I think there's a lot of potential for drones to be used for good in all the different areas that women care about. And for instance, like climate change, there's a lot of ways that drones can help in reducing waste in many different ways. Search and rescue, for instance. Those are huge issues, and potential solutions from drones. And I think that if women understand these solutions and understand how drones can be used for good, I think we could get more women in and excited about this. >> And how do you see your role in that, in helping to get more women excited, and maybe even just aware of it as a career opportunity? >> Yeah. So I think sometimes robotics can be a very niche subject, and a lot of people get into it from gaming or other things. But I think if we come to it as a way to solve humanity's greatest problems, I think that's what really inspires me. I think that's what would inspire a lot of young women, is to see that robotics is a way to help others. And also that it may not, if we don't consciously make it so that robotics helps others, and if we don't put our voices into the table, then potentially robotics will do harm. But we need to push it into the right direction. >> Do you feel it's going in the right direction? >> Yes, I think with more conferences like this, like WiDS, I think we're going in the right direction. >> Yeah, this is a great conference. It's one of my favorite shows to host. And you know, it only started back in 2015 as a one-day technical conference. And look at it now. It's a global movement. They found you. You're now part of the community. But there's hundreds of events going on in 60 countries. You have the opportunity there to really grow your network, but also reach a much bigger audience, just based on something like what Margot Gerritsen and the team have done with WiDS. What does that mean to you? >> It means a lot. I think it's so amazing that we're able to spread the word of how technology can be used in many different fields, not just robotics, but in healthcare, in search and rescue, in environmental protection. So just seeing the power that technology can bring, and spreading that to underserved communities, not just in the United States, I love how WiDS is a global community and there's regional chapters everywhere. And I think there should be more of this global collaboration in technology. >> I agree. You know, every company these days is a technology company, or a data company, or both. You think of even your local retailer or grocery store that has to be a technology company. So for women to get involved in technology, there's so many different applications of that. It doesn't have to be just coding, for example. You're doing work with drones. There's so much potential there. I think the more that we can do events like this, and leverage platforms like theCUBE, the more we can get that word out there. >> I agree. >> So you have the career panel. And then you're also doing a tech vision talk. >> Yeah, a tech talk. >> What are some of the things you're going to talk about there? >> Yeah, so I'm going to talk about... So at the career panel, just advice in general to young people who may be as confused and starting off their career, just like I am. And at the tech talk, I'll be talking about some different aspects of Skydio, and a specific use case, which is 3D scanning any physical object and putting that into a digital model. >> Ooh, wow. Tell me a little bit more about that. >> Yeah, so 3D scan is one of our products, and it allows for us to take pictures of anything in the physical world and make sure that we can put it into a digital form. So we can create digital twins into digital form, which is very cool. >> Very cool. So we're talking any type of physical object. >> Mm hm. So if you want to inspect a building, or any crumbling infrastructure, a lot of the times right now we use helicopters, or big snooper trucks, or just things that could be expensive or potentially dangerous. Instead, we can use a drone. So this is just one example of how drones can be used to help save lives, potentially. >> Tremendous amount of opportunity that drones provide. It's very exciting. What are some of the things that you're looking forward to this year? We are very early in calendar year 2022, but what are you excited about as the year progresses? >> Hmm. What am I excited about? I think there's a lot of really interesting drone-related companies, and also a lot of robotics companies in general, a lot of startups, and there's a lot of excitement there. And I think as the robotics community grows and grows, we'll be seeing more robots in real life. And I think that's just extremely exciting to me. >> It is. And you're at the forefront of that. Maggie, it's great to have you on the program. Thank you for sharing what you're doing at Skydio, your history, your past, and what you're going to be encouraging the audience to be able to go and achieve. We appreciate your time. >> Thanks so much. >> All right. From Maggie Wang. I'm Lisa Martin. You're watching theCUBE's coverage of Women in Data Science Worldwide Conference, WiDS 2022. Stick around. I'll be right back with my next guest. (upbeat music)

>>Alteryx is a company with a long history that goes all the way back to the late 1990s. Now the one consistent theme over 20 plus years has been that Ultrix has always been a data company early in the big data and Hadoop cycle. It saw the need to combine and prep different data types so that organizations could analyze data and take action Altrix and similar companies played a critical role in helping companies become data-driven. The problem was the decade of big data, brought a lot of complexities and required immense skills just to get the technology to work as advertised this in turn limited, the pace of adoption and the number of companies that could really lean in and take advantage of the cloud began to change all that and set the foundation for today's theme to Zuora of digital transformation. We hear that phrase a ton digital transformation. >>People used to think it was a buzzword, but of course we learned from the pandemic that if you're not a digital business, you're out of business and a key tenant of digital transformation is democratizing data, meaning enabling, not just hypo hyper specialized experts, but anyone business users to put data to work. Now back to Ultrix, the company has embarked on a major transformation of its own. Over the past couple of years, brought in new management, they've changed the way in which it engaged with customers with the new subscription model and it's topgraded its talent pool. 2021 was even more significant because of two acquisitions that Altrix made hyper Ana and trifecta. Why are these acquisitions important? Well, traditionally Altryx sold to business analysts that were part of the data pipeline. These were fairly technical people who had certain skills and were trained in things like writing Python code with hyper Ana Altryx has added a new persona, the business user, anyone in the business who wanted to gain insights from data and, or let's say use AI without having to be a deep technical expert. >>And then Trifacta a company started in the early days of big data by cube alum, Joe Hellerstein and his colleagues at Berkeley. They knocked down the data engineering persona, and this gives Altryx a complimentary extension into it where things like governance and security are paramount. So as we enter 2022, the post isolation economy is here and we do so with a digital foundation built on the confluence of cloud native technologies, data democratization and machine intelligence or AI, if you prefer. And Altryx is entering that new era with an expanded portfolio, new go-to market vectors, a recurring revenue business model, and a brand new outlook on how to solve customer problems and scale a company. My name is Dave Vellante with the cube and I'll be your host today. And the next hour, we're going to explore the opportunities in this new data market. And we have three segments where we dig into these trends and themes. First we'll talk to Jay Henderson, vice president of product management at Ultrix about cloud acceleration and simplifying complex data operations. Then we'll bring in Suresh Vetol who's the chief product officer at Altrix and Adam Wilson, the CEO of Trifacta, which of course is now part of Altrix. And finally, we'll hear about how Altryx is partnering with snowflake and the ecosystem and how they're integrating with data platforms like snowflake and what this means for customers. And we may have a few surprises sprinkled in as well into the conversation let's get started. >>We're kicking off the program with our first segment. Jay Henderson is the vice president of product management Altryx and we're going to talk about the trends and data, where we came from, how we got here, where we're going. We get some launch news. Well, Jay, welcome to the cube. >>Great to be here, really excited to share some of the things we're working on. >>Yeah. Thank you. So look, you have a deep product background, product management, product marketing, you've done strategy work. You've been around software and data, your entire career, and we're seeing the collision of software data cloud machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or data executive in an organization, w J what's your north star, where are you trying to take your company from a data and analytics point of view? >>Yeah, I mean, you know, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust, creating large volumes of data storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's, you know, drowning in data, but somehow still starving for insights. And so I think, uh, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics, um, and, you know, let the, the business users and the whole organization get value out of all that data they have. >>And we're going to dig into that throughout this program data, I like to say is plentiful insights, not always so much. Tell us about your launch today, Jay, and thinking about the trends that you just highlighted, the direction that your customers want to go and the problems that you're solving, what role does the cloud play in? What is what you're launching? How does that fit in? >>Yeah, we're, we're really excited today. We're launching the Altryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, um, and to take advantage of things like based access. So that it's really easy to give anyone access, including folks on a Mac. Um, it, you know, it also lets you take advantage of elastic compute so that you can do, you know, in database processing and cloud native, um, solutions that are gonna scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud, but we've got ultra to machine learning, which helps up-skill regular old analysts with advanced machine learning capabilities. We've got auto insights, which brings a business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition, which is Trifacta that helps data engineers do data pipelining and really, um, you know, create a lot of the underlying data sets that are used in some of this, uh, downstream analytics. >>Let's dig into some of those roles if we could a little bit, I mean, you've traditionally Altryx has served the business analysts and that's what designer cloud is fit for, I believe. And you've explained, you know, kind of the scope, sorry, you've expanded that scope into the, to the business user with hyper Anna. And we're in a moment we're going to talk to Adam Wilson and Suresh, uh, about Trifacta and that recent acquisition takes you, as you said, into the data engineering space in it. But in thinking about the business analyst role, what's unique about designer cloud cloud, and how does it help these individuals? >>Yeah, I mean, you know, really, I go back to some of the feedback we've had from our customers, which is, um, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product, you know, really, as they look to take the next step, they're trying to figure out how do I give access to that? Those types of analytics to thousands of people within the organization and designer cloud is, is really great for that. You've got the browser-based interface. So if folks are on a Mac, they can really easily just pop, open the browser and get access to all of those, uh, prep and blend capabilities to a lot of the analysis we're doing. Um, it's a great way to scale up access to the analytics and then start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >>Okay, great. So now then you add in the hyper Anna acquisition. So now you're targeting the business user Trifacta comes into the mix that deeper it angle that we talked about, how does this all fit together? How should we be thinking about the new Altryx portfolio? >>Yeah, I mean, I think it's pretty exciting. Um, you know, when you think about democratizing analytics and providing access to all these different groups of people, um, you've not been able to do it through one platform before. Um, you know, it's not going to be one interface that meets the, of all these different groups within the organization. You really do need purpose built specialized capabilities for each group. And finally, today with the announcement of the alternates analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single in the end application. So really finally delivering on the promise of providing analytics to all, >>How much of this you've been able to share with your customers and maybe your partners. I mean, I know OD is fairly new, but if you've been able to get any feedback from them, what are they saying about it? >>Uh, I mean, it's, it's pretty amazing. Um, we ran a early access, limited availability program that led us put a lot of this technology in the hands of over 600 customers, um, over the last few months. So we have gotten a lot of feedback. I tell you, um, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data. They've got, they're excited to be able to use analytics in every decision that they're making so that the decisions they have or more informed and produce better business outcomes. Um, and, and this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >>Yeah, those are good. Good, good numbers for, for preview mode. Let's, let's talk a little bit about vision. So it's democratizing data is the ultimate goal, which frankly has been elusive for most organizations over time. How's your cloud going to address the challenges of putting data to work across the entire enterprise? >>Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes, you know, in the, and these are really kind of enduring themes that you're going to see us making investments in over the next few years, the first is having cloud centricity. You know, the data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it, to provide cloud solution. So the first one is really around cloud centricity. The second is around big data fluency. Once you have all of the data, you need to be able to manipulate it in a performant manner. So having the elastic cloud infrastructure and in database processing is so important, the third is around making AI a strategic advantage. >>So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. Um, and then the fourth thing is really providing access across the entire organization. You know, it and data engineers, uh, as well as business owners and analysts. So, um, cloud centricity, big data fluency, um, AI is a strategic advantage and, uh, personas across the organization are really the four big themes you're going to see us, uh, working on over the next few months and, uh, coming coming year. >>That's good. Thank you for that. So, so on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know, monolithic organizations, uh, very specialized or I might even say hyper specialized roles and, and your, your mission of course is the customer. You, you, you, you and your customers, they want to democratize the data. And so it seems logical that domain leaders are going to take more responsibility for data, life cycles, data ownerships, low code becomes more important. And perhaps this kind of challenges, the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving and, and, and what role will Altryx play? >>Yeah. Um, you know, I think we'll see sort of a more federated systems start to emerge. Those centralized groups are going to continue to exist. Um, but they're going to start to empower, you know, in a much more de-centralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on, uh, problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model results in millions of dollars a day for the business. And then by pushing some of the analytics out to, uh, closer to the edge and closer to the business, you'll be able to apply those analytics in every single decision. So I think you're going to see, you know, both the decentralized and centralized models start to work in harmony and a little bit more about almost a federated sort of a way. And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, um, and drive business outcomes with the analytics they're using. >>Yeah. I mean, I think my take on another one, if you could comment is to me, the technology should be an operational detail and it has been the, the, the dog that wags the tail, or maybe the other way around, you mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operationals systems that then somehow, eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, users, those, those line of business experts get more access. That's your goal. And then even go beyond analytics, start to build data products that could be monetized, and that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >>Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications and to enable somebody who's an analyst or business user to create an application on top of the data and analytics layers that they have, um, really to help democratize the analytics, to help prepackage some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more. >>Yeah. And to your point, if you can federate the governance and automate that, then that can happen. I mean, that's a key part of it, obviously. So, all right, Jay, we have to leave it there up next. We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson who led Trifacta for more than seven years. It's the recipe. Tyler is the chief product officer at Altryx to explain the rationale behind the acquisition and how it's going to impact customers. Keep it right there. You're watching the cube. You're a leader in enterprise tech coverage. >>It's go time, get ready to accelerate your data analytics journey with a unified cloud native platform. That's accessible for everyone on the go from home to office and everywhere in between effortless analytics to help you go from ideas to outcomes and no time. It's your time to shine. It's Altryx analytics cloud time. >>Okay. We're here with. Who's the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate their businesses with that in mind, you know, we know designer and are the products that Altrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyper Rana now kind of renamed, um, Altrix auto. We even speak with the business owner and the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so fact made so much sense for us. >>Yeah. Thank you for that. I mean, you, look, you could have built it yourself would have taken, you know, who knows how long, you know, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birth Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical? And, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So, so a broader set of, of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I could use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company and I think is, as we, um, saw over the course of the last 5, 6, 7 years that, um, you know, uh, real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push-down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making is, is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making, because we've looked, we've contextualized most of our operational systems, but the big data pipeline is hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform for analytics, automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely Alcon's has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics, for AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. Um, and so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's applied and so multiple personas. Um, and we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now at least three personas the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that? How is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market is not crack the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. >>And you're really, you're obviously writing the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just what Adam said resonates with me deeply. Um, analytics is one of those, um, massive disciplines inside an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was all drinks and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altrix it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? Yeah, >>I think, I think you should think about them. And, uh, um, as, as very complimentary right designer cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, the really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with, um, Trifacta, um, I think we have to get deeper inside to think about what does the data engineer really need? What's the business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the trifecta on the amazing Trifacta cloud platform. >>You know, >>I think we're just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but one of the reasons I always liked Altrix is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the organization said, wow, this big data stuff has taken off, but we need security. We need governance. And it's interesting because you've got, you know, ETL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? Uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Um, thanks for asking about our sales kickoff. So we met for the first time and you've got a two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was a, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we added a Trifacta to, um, the, the potty such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for other the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working out him and I will, when he's so hot on, on the deal and the core hypotheses and so on. And then you step back and you're going to share the vision with the field organization, and it blows you away, the energy that it creates among our sellers out of partners. >>And I'm sure Madam will and his team were mocked, um, every single day, uh, with questions and opportunities to bring them in. But Adam, maybe you should share. Yeah, no, it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended, the story that we told was just, you have this opportunity to really cater to what the end users care about, which is a lot about interactivity and self-service, and at the same time. >>And that's, and that's a lot of the goodness that, um, that Altryx is, has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that jets. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube you're leader in enterprise tech coverage. >>This is your data housed neatly insecurely in the snowflake data cloud. And all of it has potential the potential to solve complex business problems, deliver personalized financial offerings, protect supply chains from disruption, cut costs, forecast, grow and innovate. All you need to do is put your data in the hands of the right people and give it an opportunity. Luckily for you. That's the easy part because snowflake works with Alteryx and Alteryx turns data into breakthroughs with just a click. Your organization can automate analytics with drag and drop building blocks, easily access snowflake data with both sequel and no SQL options, share insights, powered by Alteryx data science and push processing to snowflake for lightning, fast performance, you get answers you can put to work in your teams, get repeatable processes they can share in that's exciting because not only is your data no longer sitting around in silos, it's also mobilized for the next opportunity. Turn your data into a breakthrough Alteryx and snowflake >>Okay. We're back here in the queue, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest Terek do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to see >>Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security, and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer, you know, cloud migration momentum, and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central company's strategy. They always have been. We recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner community and strategy now addresses several kinds of partners, spanning solution providers to global SIS and technology partners, such as snowflake and together, we help our customers realize the business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform, guidance, deployment, support, and other professional services. >>Great. Let's get a little bit more into the relationship between Altrix and S in snowflake, the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing their costs. Um, Altrix proudly achieved. Snowflake's highest elite tier in their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the destroyed solution. We developed two great assets. One is the officer starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows, and videos, helping customers to get going more easily with an altered since snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Altryx and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems much faster. >>Cool. Kara, can you give us your perspective on the partnership? >>Yeah, definitely. Dave, so as Barb mentioned, we've got this standing very successful partnership going back years with hundreds of happy joint customers. And when I look at the beginning, Altrix has helped pioneer the concept of self-service analytics, especially with use cases that we worked on with for, for data prep for BI users like Tableau and as Altryx has evolved to now becoming from data prep to now becoming a full end to end data science platform. It's really opened up a lot more opportunities for our partnership. Altryx has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud, uh, with Alteryx orchestrating the end to end machine learning workflows Alteryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources, but so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful, um, that I can come up with today, the big challenges or trends for us, and Altrix really helps us across all of them. Um, there are three particular ones I'm going to talk about the first one being self-service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, um, you know, the, the technology users, but the business users, right? I think every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with Altrix is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So, um, with self-service analytics, with Ultrix designer they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst, um, report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now, with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. Um, and then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. Um, and with Altryx creating this platform so they can cater to both the everyday business user, the quote unquote, citizen data scientists, and making a code friendly for data scientists to be able to get at their notebooks and all the different tools that they want to use. Um, they fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution caring to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx um, if we look at mobilizing your data, getting access to third-party datasets, to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view, um, within their, their data applications. And so with Altryx alterations, we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with the snowflake data marketplace so that we can enrich these workflows, these great, great workflows that Altrix writing provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities, Dave. So those are three I see, uh, easily that we're going to be able to solve a lot of customer challenges with. >>So thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having imagine infrastructure to even be able to do it, to get applications off the ground. And so we created something to be cloud-native. We created to be a SAS managed service. So now that that Altrix is moving to the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster and they don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, um, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had two pre desktop products, and today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products were committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers, cloud and analytic >>Are. How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, gain efficiencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through discovery questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Dark. How do you see it? You'll go to market strategy. >>Yeah. Dave we've. Um, so we initially started selling, we initially sold snowflake as technology, right? Uh, looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we're starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Altrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so, um, Barb talked about these, these starter kits where it's prescriptive, you've got a demo and, um, a way that customers can get off the ground and running, right? >>Cause we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working in healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map two lines of business with Alteryx. >>Great. Thanks Derek. Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. Uh, we're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the ultra partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra score, providing our partners with earlier access to benefits, um, I could talk about our program for 30 minutes. I know we don't have time. The key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Tarik will give you the last word. What should we be looking for from, >>Yeah, thanks. Thanks, Dave. As BARR mentioned, Altrix has been the forefront of innovating with us. They've been integrating into, uh, making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before that extensibility is really what we're excited about. Um, the ability for Ultrix to plug into this extensibility framework that we call snow park and to be able to extend out, um, ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala, not Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right there probably day sets in, in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right? I think it's exciting to see what we're going to be able to do together with these upcoming innovations. Great >>Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with some closing thoughts in a summary, don't go away. >>1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops make that 2.3. The sector times out the wazoo, whites are much of this velocity's pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into insights, they turn to Altryx Qualtrics analytics, automation, >>Okay, let's summarize and wrap up the session. We can pretty much agree the data is plentiful, but organizations continue to struggle to get maximum value out of their data investments. The ROI has been elusive. There are many reasons for that complexity data, trust silos, lack of talent and the like, but the opportunity to transform data operations and drive tangible value is immense collaboration across various roles. And disciplines is part of the answer as is democratizing data. This means putting data in the hands of those domain experts that are closest to the customer and really understand where the opportunity exists and how to best address them. We heard from Jay Henderson that we have all this data exhaust and cheap storage. It allows us to keep it for a long time. It's true, but as he pointed out that doesn't solve the fundamental problem. Data is spewing out from our operational systems, but much of it lacks business context for the data teams chartered with analyzing that data. >>So we heard about the trend toward low code development and federating data access. The reason this is important is because the business lines have the context and the more responsibility they take for data, the more quickly and effectively organizations are going to be able to put data to work. We also talked about the harmonization between centralized teams and enabling decentralized data flows. I mean, after all data by its very nature is distributed. And importantly, as we heard from Adam Wilson and Suresh Vittol to support this model, you have to have strong governance and service the needs of it and engineering teams. And that's where the trifecta acquisition fits into the equation. Finally, we heard about a key partnership between Altrix and snowflake and how the migration to cloud data warehouses is evolving into a global data cloud. This enables data sharing across teams and ecosystems and vertical markets at massive scale all while maintaining the governance required to protect the organizations and individuals alike. >>This is a new and emerging business model that is very exciting and points the way to the next generation of data innovation in the coming decade. We're decentralized domain teams get more facile access to data. Self-service take more responsibility for quality value and data innovation. While at the same time, the governance security and privacy edicts of an organization are centralized in programmatically enforced throughout an enterprise and an external ecosystem. This is Dave Volante. All these videos are available on demand@theqm.net altrix.com. Thanks for watching accelerating automated analytics in the cloud made possible by Altryx. And thanks for watching the queue, your leader in enterprise tech coverage. We'll see you next time.

(bright upbeat music) >> Welcome to The Cube. We're here for the AWS Executive Summit part of Reinvent 2021. I'm John Farrow, your host of the Cube. We've got a great segment focus here, Art of the Possible is the segment. Jas Bains, Chief Executive at Hafod and Jamie Smith, director of research and innovation and Laetitia Cailleteau who's the global lead of conversational AI at Accenture. Thanks for joining me today for this Art of the Possible segment. >> Thank you. >> So tell us a little bit about Hafod and what you guys are doing to the community 'cause this is a really compelling story of how technology in home care is kind of changing the game and putting a stake in the ground. >> Yeah, so Hafod is one of the largest not for profits in Wales. We employ about 1400 colleagues. We have three strands a service, which practices on key demographics. So people who are vulnerable and socioeconomically disadvantaged. Our three core strands of service are affordable housing, we provide several thousand homes to people in housing need across Wales. We also are an extensive provider of social provision, both residential and in the community. And then we have a third tier, which is a hybrid in between. So that supports people who are not quite ready for independent living but neither are they ready for residential care. So that's a supportive provision. I suppose what one of the things that marks Hafod out and why we're here in this conversation is that we're uniquely placed as one of the organizations that actually has a research and innovation capacity. And it's the work of the research and innovation capacity led by Jamie that brought about this collaboration with Accenture which is great in great meaning and benefits. So thousands of our customers and hopefully universal application as it develops. >> You know this is a really an interesting discussion because multiple levels, one, the pandemic accelerated this needs so, I want to get comments on that. But two, if you look at the future of work and work and home life, you seeing the convergence of where people live. And I think this idea of having this independent home and the ecosystem around it, there's a societal impact as well. So what brought this opportunity together? How did this come together with Accenture and AWS? >> We're going for Jamie and Laetitia. >> Yeah, I can start. Well, we were trying to apply for the LC Aging Grand Challenge in the U.K., so the United Kingdom recognized the need for change around independent living and run a grand challenge. And then we got together as part of this grand challenge. You know, we had some technology, we had trialed with AGK before and Hanover Housing Association. Hafod was really keen to actually start trying some of that technology with some of the resident. And we also worked with Swansea University, was doing a lot of work around social isolation and loneliness. And we came together to kind of pitch for the grand challenge. And we went quite far actually, unfortunately we didn't win but we have built such a great collaboration that we couldn't really let it be, you know, not going any further. And we decided to continue to invest in this idea. And now we here, probably 18 months on with a number of people, Hafod using the technology and a number of feedbacks and returns coming back and us having a grand ambitions to actually go much broader and scale this solution. >> Jas and Jamie, I'd love to get your reaction and commentary on this trend of tech for good because I mean, I'm sure you didn't wake up, oh, just want to do some tech for good. You guys have an environment, you have an opportunity, you have challenges you're going to turn into opportunities. But if you look at the global landscape right now, things that are jumping out at us are looking at the impact of social media on people. You got the pandemic with isolation, this is a first order problem in this new world of how do we get technology to change how people feel and make them better in their lives. >> Yeah, I think for us, the first has to be a problem to solve. There's got to be a question to be answered. And for us, that was in this instance, how do we mitigate loneliness and how do we take services that rely on person to person contact and not particularly scalable and replicate those through technology somehow. And even if we can do 10% of the job of that in-person service then for us, it's worth it because that is scalable. And there are lots of small interventions we can make using technology which is really efficient way for us to support people in the community when we just can't be everywhere at once. >> So, John, just to add, I think that we have about 1500 people living in households that are living alone and isolated. And I think the issue for us was more than just about technology because a lot of these people don't have access to basic technology features that most of us would take for granted. So far this is a two-prong journey. One is about increasing the accessibility to tech and familiarizing people so that they're comfortable with these devices technology and two importantly, make sure that we have the right means to help people reduce their loneliness and isolation. So the opportunity to try out something over the last 12 months, something that's bespoke, that's customized that will undoubtedly be tweaked as we go forward has been an absolutely marvelous opportunity. And for us, the collaboration with Accenture has been absolutely key. I think what we've seen during COVID is cross-fertilization. We've seen multi-disciplinary teams, we've got engineers, architects, manufacturers, and clinicians, and scientists, all trying to develop new solutions around COVID. And I think this probably just exemplary bias, especially as a post COVID where industry and in our case for example public sector and academia working together. >> Yeah, that's a great example and props to everyone there. And congratulations on this really, really important initiative. Let's talk about the home care solution. What does it do? How does it work? Take us through what's happening? >> Okay, so Home Care is actually a platform which is obviously running on AWS technology and this particular platform is the service offered accessible via voice through the Alexa device. We use the Echo Show to be able to use voice but also visuals to kind of make the technology more accessible for end user. On the platform itself, we have a series of services available out there. We connecting in the background a number of services from the community. So in the particular case of Hafod, we had something around shopping during the pandemic where we had people wanting to have access to their food bank. Or we also had during the pandemic, there was some need for having access to financial coaching and things like that. So we actually brought all of the service on the platform and the skills and this skill was really learning how to interact with the end user. And it was all customized for them to be able to access those things in a very easy way. It did work almost too well because some of our end users have been a kind of you know, have not been digital literate before and it was working so well, they were like, "But why can't it do pretty much anything on the planet? "Why can't it do this or that?" So the expectations were really, really high but we did manage to bring comfort to Hafod residents in a number of their daily kind of a need, some of the things during COVID 'cause people couldn't meet face to face. There was some challenge around understanding what events are running. So the coaches would publish events, you know, through the skills and people would be able to subscribe and go to the event and meet together virtually instead of physically. The number of things that really kind of brought a voice enabled experience for those end users. >> You know, you mentioned the people like the solution just before we, I'm going to get the Jamie in a second, but I want to just bring up something that you brought up. This is a digital divide evolution because digital divide, as Josh was saying, is that none about technology,, first, you have to access, you need access, right? First, then you have to bring broadband and internet access. And then you have to get the technology in the home. But then here it seems to be a whole nother level of digital divide bridging to the new heights. >> Yeah, completely, completely. And I think that's where COVID has really accelerated the digital divide before the solution was put in place for Hafod in the sense that people couldn't move and if they were not digitally literate, it was very hard to have access to services. And now we brought this solution in the comfort of their own home and they have the access to the services that they wouldn't have had otherwise on their own. So it's definitely helping, yeah. >> It's just another example of people refactoring their lives or businesses with technology. Jamie, what's your take on the innovation here and the technical aspects of the home care solutions? >> I think the fact that it's so easy to use, it's personalized, it's a digital companion for the home. It overcomes that digital divide that we talked about, which is really important. If you've got a voice you can use home care and you can interact with it in this really simple way. And what I love about it is the fact that it was based on what our customers told us they were finding difficult during this time, during the early lockdowns of the pandemic. There was 1500 so people Jas talked about who were living alone and at risk of loneliness. Now we spoke to a good number of those through a series of welfare calls and we found out exactly what it is they found challenging. >> What were some of the things that they were finding challenging? >> So tracking how they feel on a day-to-day basis. What's my mood like, what's my wellbeing like, and knowing how that changes over time. Just keeping the fridge in the pantry stocked up. What can I cook with these basic ingredients that I've got in my home? You could be signposted to basic resources to help you with that. Staying connected to the people who are really important to you but the bit that shines out for me is the interface with our services, with our neighborhood coaching service, where we can just give these little nudges, these little interventions just to mitigate and take the edge of that loneliness for people. We can see the potential of that coming up to the pandemic, where you can really encourage people to interact with one another, to be physically active and do all of those things that sort of mitigate against loneliness. >> Let me ask you a question 'cause I think a very important point. The timing of the signaling of data is super important. Could you comment on the relevance of having access to data? If you're getting something connected, when you're connected like this, I can only imagine the benefits. It's all about timing, right? Knowing that someone might be thinking some way or whether it's a tactical, in any scenario, timing of data, the right place at the right time, as they say. What's your take on that 'cause it sounds like what you're saying is that you can see things early when people are in the moment. >> Yeah, exactly. So if there's a trend beginning to emerge, for example, around some of these wellbeing, which has been on a low trajectory for a number of days, that can raise a red flag in our system and it alerts one of our neighborhood coaches just to reach out to that person and say, "Well, John, what's going on? "You haven't been out for a walk for a few days. "We know you like to walk, what's happening?" And these early warning signs are really important when we think of the long-term effects of loneliness and how getting upstream of those, preventing it reaching a point where it moves from being a problem into being a crisis. And the earlier we can detect that the more chance we've got of these negative long-term outcomes being mitigated. >> You know, one of the things we see in the cloud business is kind of separate track but it kind of relates to the real world here that you're doing, is automation and AI and machine learning bringing in a lot of value if applied properly. So how are you guys seeing, I can almost imagine that patterns are coming in, right? Do you see patterns in the data? How does AI and analytics technology improve this process especially with the wellbeing and emotional wellbeing of the elderly? >> I think one of the things we've learned through the pilot study we've done is there's not one size fits all. You know, all those people are very different individuals. They have very different habits. You know, there's some people not sleeping over the night. There's some people wanting to be out early, wanting to be social. Some people you have to put in much more. So it's definitely not one size fits all. And automation and digitalization of those kinds of services is really challenging because if they're not personalized, it doesn't really catch the interest or the need of the individuals. So for me as an IT professional being in the industry for like a 20 plus years, I think this is the time where personalization has really a true meaning. Personalization at scale for those people that are not digitally literate. But also in more vulnerable settings 'cause there's just so many different angles that can make them vulnerable. Maybe it's the body, maybe it's the economy position, their social condition, there's so many variation of all of that. So I think this is one of the use case that has to be powered by technology to complement the human side of it. If we really want to start scaling the services we provide to people in general, meaning obviously, in all the Western country now we all growing old, it's no secret. So in 20 years time the majority of everybody will be old and we obviously need people to take care of us. And at the moment we don't have that population to take care of us coming up. So really to crack on those kinds of challenges, we really need to have technology powering and just helping the human side to make it more efficient, connected than human. >> It's interesting. I just did a story where you have these bots that look at the facial recognition via cameras and can detect either in hospitals and or in care patients, how they feel. So you see where this is going. Jas I got to ask you how all this changes, the home care model and how Hafod works. Your workforce, the career's culture, the consortium you guys are bringing to the table, partners, you know this is an ecosystem now, it's a system. >> Yes John, I think that probably, it's also worth talking a little bit about the pressures on state governments around public health issues which are coming to the fore. And clearly we need to develop alternative ways that we engage with mass audiences and technology is going to be absolutely key. One of the challenges I still think that we've not resolved in the U.K. level, this is probably a global issue, is about data protection. When we're talking to cross governmental agencies, it's about sharing data and establishing protocols and we've enjoyed a few challenging conversations with colleagues around data protection. So I think those need to be set out in the context of the journey of this particular project. I think that what's interesting around COVID is that, hasn't materially changed the nature in which we do things, probably not in our focus and our work remains the same. But what we're seeing is very clear evidence of the ways, I mean, who would have thought that 12 months ago, the majority of our workforce would be working from home? So rapid mobilization to ensure that people can use, set IT home effectively. And then how does that relationship impact with people in the communities we're serving? Some of whom have got access to technology, others who haven't. So that's been, I think the biggest change, and that is a fundamental change in the design and delivery of future services that organizations like us will be providing. So I would say that overall, some things remain the same by and large but technology is having an absolutely profound change in the way that our engagement with customers will go forward. >> Well, you guys are in the front end of some massive innovation here with this, are they possible and that, you're really delivering impact. And I think this is an example of that. And you brought up the data challenges, this is something that you guys call privacy by design. This is a cutting edge issue here because there are benefits around managing privacy properly. And I think here, your solution clearly has value, right? And no one can debate that, but as these little blockers get in the way, what's your reaction to that? 'Cause this certainly is something that has to be solved. I mean, it's a problem. >> Yeah, so we designed a solution, I think we had, when we design, I co-designed with your end-users actually. We had up to 14 lawyers working with us at one point in time looking at different kinds of angles. So definitely really tackle the solution with privacy by design in mind and with end users but obviously you can't co-design with thousands of people, you have to co-design with a representative subset of a cohort. And some of the challenge we find is obviously, the media have done a lot of scaremongering around technology, AI and all of that kind of things, especially for people that are not necessarily digitally literate, people that are just not in it. And when we go and deploy the solution, people are a little bit worried. When we make them, we obviously explain to them what's going to happen if they're happy, if they want to consent and all that kind of things. But the people are scared, they're just jumping on a technology on top of it we're asking them some questions around consent. So I think it's just that the solution is super secured and we've gone over millions of hoops within Accenture but also with Hafod itself. You know, it's more that like the type of user we deploying the solution to are just not in that world and then they are little bit worried about sharing. Not only they're worried about sharing with us but you know, in home care, there there's an option as well to share some of that data with your family. And there we also see people are kind of okay to share with us but they don't want to share with their family 'cause they don't want to have too much information kind of going potentially worrying or bothering some of their family member. So there is definitely a huge education kind of angle to embracing the technology. Not only when you create the solution but when you actually deploy it with users. >> It's a fabulous project, I am so excited by this story. It's a great story, has all the elements; technology, innovation, cidal impact, data privacy, social interactions, whether it's with family members and others, internal, external. In teams themselves. You guys doing some amazing work, thank you for sharing. It's a great project, we'll keep track of it. My final question for you guys is what comes next for the home care after the trial? What are Hafod's plans and hopes for the future? >> Maybe if I just give an overview and then invite Jamie and Laetitia. So for us, without conversations, you don't create possibilities and this really is a reflection of the culture that we try to engender. So my ask of my team is to remain curious, is to continue to explore opportunities because it's home care up to today, it could be something else tomorrow. We also recognize that we live in a world of collaboration. We need more cross industrial partnerships. We love to explore more things that Accenture, Amazon, others as well. So that's principally what I will be doing is ensuring that the culture invites us and then I hand over to the clever people like Jamie and Laetitia to get on with the technology. I think for me we've already learned an awful lot about home care and there's clearly a lot more we can learn. We'd love to build on this initial small-scale trial and see how home care could work at a bigger scale. So how would it work with thousands of users? How do we scale it up from a cohort of 50 to a cohort of 5,000? How does it work when we bring different kinds of organizations into that mix? So what if, for example, we could integrate it into health care? So a variety of services can have a holistic view of an individual and interact with one another, to put that person on the right pathway and maybe keep them out of the health and care system for longer, actually reducing the costs to the system in the long run and improving that person's outcomes. That kind of evidence speaks to decision-makers and political partners and I think that's the kind of evidence we need to build. >> Yeah, financial impact is there, it's brutal. It's a great financial impact for the system. Efficiency, better care, everything. >> Yeah and we are 100% on board for whatever comes next. >> Laetitia-- >> What about you Laetitia? >> Great program you got there. A amazing story, thank you for sharing. Congratulations on this awesome project. So much to unpack here. I think this is the future. I mean, I think this is a case study of represents all the moving parts that need to be worked on, so congratulations. >> Thank you. >> Thank you. >> We are the Art of the Possible here inside the Cube, part of AWS Reinvent Executive Summit, I'm John Furrier, your host, thanks for watching. (bright upbeat music)

(bright upbeat music) >> Welcome to The Cube. We're here for the AWS Executive Summit part of Reinvent 2021. I'm John Farrow, your host of the Cube. We've got a great segment focus here, Art of the Possible is the segment. Jas Bains, Chief Executive at Hafod and Jamie Smith, director of research and innovation and Laetitia Cailleteau who's the global lead of conversational AI at Accenture. Thanks for joining me today for this Art of the Possible segment. >> Thank you. >> So tell us a little bit about Hafod and what you guys are doing to the community 'cause this is a really compelling story of how technology in home care is kind of changing the game and putting a stake in the ground. >> Yeah, so Hafod is one of the largest not for profits in Wales. We employ about 1400 colleagues. We have three strands a service, which practices on key demographics. So people who are vulnerable and socioeconomically disadvantaged. Our three core strands of service are affordable housing, we provide several thousand homes to people in housing need across Wales. We also are an extensive provider of social provision, both residential and in the community. And then we have a third tier, which is a hybrid in between. So that supports people who are not quite ready for independent living but neither are they ready for residential care. So that's a supportive provision. I suppose what one of the things that marks Hafod out and why we're here in this conversation is that we're uniquely placed as one of the organizations that actually has a research and innovation capacity. And it's the work of the research and innovation capacity led by Jamie that brought about this collaboration with Accenture which is great in great meaning and benefits. So thousands of our customers and hopefully universal application as it develops. >> You know this is a really an interesting discussion because multiple levels, one, the pandemic accelerated this needs so, I want to get comments on that. But two, if you look at the future of work and work and home life, you seeing the convergence of where people live. And I think this idea of having this independent home and the ecosystem around it, there's a societal impact as well. So what brought this opportunity together? How did this come together with Accenture and AWS? >> We're going for Jamie and Laetitia. >> Yeah, I can start. Well, we were trying to apply for the LC Aging Grand Challenge in the U.K., so the United Kingdom recognized the need for change around independent living and run a grand challenge. And then we got together as part of this grand challenge. You know, we had some technology, we had trialed with AGK before and Hanover Housing Association. Hafod was really keen to actually start trying some of that technology with some of the resident. And we also worked with Swansea University, was doing a lot of work around social isolation and loneliness. And we came together to kind of pitch for the grand challenge. And we went quite far actually, unfortunately we didn't win but we have built such a great collaboration that we couldn't really let it be, you know, not going any further. And we decided to continue to invest in this idea. And now we here, probably 18 months on with a number of people, Hafod using the technology and a number of feedbacks and returns coming back and us having a grand ambitions to actually go much broader and scale this solution. >> Jas and Jamie, I'd love to get your reaction and commentary on this trend of tech for good because I mean, I'm sure you didn't wake up, oh, just want to do some tech for good. You guys have an environment, you have an opportunity, you have challenges you're going to turn into opportunities. But if you look at the global landscape right now, things that are jumping out at us are looking at the impact of social media on people. You got the pandemic with isolation, this is a first order problem in this new world of how do we get technology to change how people feel and make them better in their lives. >> Yeah, I think for us, the first has to be a problem to solve. There's got to be a question to be answered. And for us, that was in this instance, how do we mitigate loneliness and how do we take services that rely on person to person contact and not particularly scalable and replicate those through technology somehow. And even if we can do 10% of the job of that in-person service then for us, it's worth it because that is scalable. And there are lots of small interventions we can make using technology which is really efficient way for us to support people in the community when we just can't be everywhere at once. >> So, John, just to add, I think that we have about 1500 people living in households that are living alone and isolated. And I think the issue for us was more than just about technology because a lot of these people don't have access to basic technology features that most of us would take for granted. So far this is a two-prong journey. One is about increasing the accessibility to tech and familiarizing people so that they're comfortable with these devices technology and two importantly, make sure that we have the right means to help people reduce their loneliness and isolation. So the opportunity to try out something over the last 12 months, something that's bespoke, that's customized that will undoubtedly be tweaked as we go forward has been an absolutely marvelous opportunity. And for us, the collaboration with Accenture has been absolutely key. I think what we've seen during COVID is cross-fertilization. We've seen multi-disciplinary teams, we've got engineers, architects, manufacturers, and clinicians, and scientists, all trying to develop new solutions around COVID. And I think this probably just exemplary bias, especially as a post COVID where industry and in our case for example public sector and academia working together. >> Yeah, that's a great example and props to everyone there. And congratulations on this really, really important initiative. Let's talk about the home care solution. What does it do? How does it work? Take us through what's happening? >> Okay, so Home Care is actually a platform which is obviously running on AWS technology and this particular platform is the service offered accessible via voice through the Alexa device. We use the Echo Show to be able to use voice but also visuals to kind of make the technology more accessible for end user. On the platform itself, we have a series of services available out there. We connecting in the background a number of services from the community. So in the particular case of Hafod, we had something around shopping during the pandemic where we had people wanting to have access to their food bank. Or we also had during the pandemic, there was some need for having access to financial coaching and things like that. So we actually brought all of the service on the platform and the skills and this skill was really learning how to interact with the end user. And it was all customized for them to be able to access those things in a very easy way. It did work almost too well because some of our end users have been a kind of you know, have not been digital literate before and it was working so well, they were like, "But why can't it do pretty much anything on the planet? "Why can't it do this or that?" So the expectations were really, really high but we did manage to bring comfort to Hafod residents in a number of their daily kind of a need, some of the things during COVID 'cause people couldn't meet face to face. There was some challenge around understanding what events are running. So the coaches would publish events, you know, through the skills and people would be able to subscribe and go to the event and meet together virtually instead of physically. The number of things that really kind of brought a voice enabled experience for those end users. >> You know, you mentioned the people like the solution just before we, I'm going to get the Jamie in a second, but I want to just bring up something that you brought up. This is a digital divide evolution because digital divide, as Josh was saying, is that none about technology,, first, you have to access, you need access, right? First, then you have to bring broadband and internet access. And then you have to get the technology in the home. But then here it seems to be a whole nother level of digital divide bridging to the new heights. >> Yeah, completely, completely. And I think that's where COVID has really accelerated the digital divide before the solution was put in place for Hafod in the sense that people couldn't move and if they were not digitally literate, it was very hard to have access to services. And now we brought this solution in the comfort of their own home and they have the access to the services that they wouldn't have had otherwise on their own. So it's definitely helping, yeah. >> It's just another example of people refactoring their lives or businesses with technology. Jamie, what's your take on the innovation here and the technical aspects of the home care solutions? >> I think the fact that it's so easy to use, it's personalized, it's a digital companion for the home. It overcomes that digital divide that we talked about, which is really important. If you've got a voice you can use home care and you can interact with it in this really simple way. And what I love about it is the fact that it was based on what our customers told us they were finding difficult during this time, during the early lockdowns of the pandemic. There was 1500 so people Jas talked about who were living alone and at risk of loneliness. Now we spoke to a good number of those through a series of welfare calls and we found out exactly what it is they found challenging. >> What were some of the things that they were finding challenging? >> So tracking how they feel on a day-to-day basis. What's my mood like, what's my wellbeing like, and knowing how that changes over time. Just keeping the fridge in the pantry stocked up. What can I cook with these basic ingredients that I've got in my home? You could be signposted to basic resources to help you with that. Staying connected to the people who are really important to you but the bit that shines out for me is the interface with our services, with our neighborhood coaching service, where we can just give these little nudges, these little interventions just to mitigate and take the edge of that loneliness for people. We can see the potential of that coming up to the pandemic, where you can really encourage people to interact with one another, to be physically active and do all of those things that sort of mitigate against loneliness. >> Let me ask you a question 'cause I think a very important point. The timing of the signaling of data is super important. Could you comment on the relevance of having access to data? If you're getting something connected, when you're connected like this, I can only imagine the benefits. It's all about timing, right? Knowing that someone might be thinking some way or whether it's a tactical, in any scenario, timing of data, the right place at the right time, as they say. What's your take on that 'cause it sounds like what you're saying is that you can see things early when people are in the moment. >> Yeah, exactly. So if there's a trend beginning to emerge, for example, around some of these wellbeing, which has been on a low trajectory for a number of days, that can raise a red flag in our system and it alerts one of our neighborhood coaches just to reach out to that person and say, "Well, John, what's going on? "You haven't been out for a walk for a few days. "We know you like to walk, what's happening?" And these early warning signs are really important when we think of the long-term effects of loneliness and how getting upstream of those, preventing it reaching a point where it moves from being a problem into being a crisis. And the earlier we can detect that the more chance we've got of these negative long-term outcomes being mitigated. >> You know, one of the things we see in the cloud business is kind of separate track but it kind of relates to the real world here that you're doing, is automation and AI and machine learning bringing in a lot of value if applied properly. So how are you guys seeing, I can almost imagine that patterns are coming in, right? Do you see patterns in the data? How does AI and analytics technology improve this process especially with the wellbeing and emotional wellbeing of the elderly? >> I think one of the things we've learned through the pilot study we've done is there's not one size fits all. You know, all those people are very different individuals. They have very different habits. You know, there's some people not sleeping over the night. There's some people wanting to be out early, wanting to be social. Some people you have to put in much more. So it's definitely not one size fits all. And automation and digitalization of those kinds of services is really challenging because if they're not personalized, it doesn't really catch the interest or the need of the individuals. So for me as an IT professional being in the industry for like a 20 plus years, I think this is the time where personalization has really a true meaning. Personalization at scale for those people that are not digitally literate. But also in more vulnerable settings 'cause there's just so many different angles that can make them vulnerable. Maybe it's the body, maybe it's the economy position, their social condition, there's so many variation of all of that. So I think this is one of the use case that has to be powered by technology to complement the human side of it. If we really want to start scaling the services we provide to people in general, meaning obviously, in all the Western country now we all growing old, it's no secret. So in 20 years time the majority of everybody will be old and we obviously need people to take care of us. And at the moment we don't have that population to take care of us coming up. So really to crack on those kinds of challenges, we really need to have technology powering and just helping the human side to make it more efficient, connected than human. >> It's interesting. I just did a story where you have these bots that look at the facial recognition via cameras and can detect either in hospitals and or in care patients, how they feel. So you see where this is going. Jas I got to ask you how all this changes, the home care model and how Hafod works. Your workforce, the career's culture, the consortium you guys are bringing to the table, partners, you know this is an ecosystem now, it's a system. >> Yes John, I think that probably, it's also worth talking a little bit about the pressures on state governments around public health issues which are coming to the fore. And clearly we need to develop alternative ways that we engage with mass audiences and technology is going to be absolutely key. One of the challenges I still think that we've not resolved in the U.K. level, this is probably a global issue, is about data protection. When we're talking to cross governmental agencies, it's about sharing data and establishing protocols and we've enjoyed a few challenging conversations with colleagues around data protection. So I think those need to be set out in the context of the journey of this particular project. I think that what's interesting around COVID is that, hasn't materially changed the nature in which we do things, probably not in our focus and our work remains the same. But what we're seeing is very clear evidence of the ways, I mean, who would have thought that 12 months ago, the majority of our workforce would be working from home? So rapid mobilization to ensure that people can use, set IT home effectively. And then how does that relationship impact with people in the communities we're serving? Some of whom have got access to technology, others who haven't. So that's been, I think the biggest change, and that is a fundamental change in the design and delivery of future services that organizations like us will be providing. So I would say that overall, some things remain the same by and large but technology is having an absolutely profound change in the way that our engagement with customers will go forward. >> Well, you guys are in the front end of some massive innovation here with this, are they possible and that, you're really delivering impact. And I think this is an example of that. And you brought up the data challenges, this is something that you guys call privacy by design. This is a cutting edge issue here because there are benefits around managing privacy properly. And I think here, your solution clearly has value, right? And no one can debate that, but as these little blockers get in the way, what's your reaction to that? 'Cause this certainly is something that has to be solved. I mean, it's a problem. >> Yeah, so we designed a solution, I think we had, when we design, I co-designed with your end-users actually. We had up to 14 lawyers working with us at one point in time looking at different kinds of angles. So definitely really tackle the solution with privacy by design in mind and with end users but obviously you can't co-design with thousands of people, you have to co-design with a representative subset of a cohort. And some of the challenge we find is obviously, the media have done a lot of scaremongering around technology, AI and all of that kind of things, especially for people that are not necessarily digitally literate, people that are just not in it. And when we go and deploy the solution, people are a little bit worried. When we make them, we obviously explain to them what's going to happen if they're happy, if they want to consent and all that kind of things. But the people are scared, they're just jumping on a technology on top of it we're asking them some questions around consent. So I think it's just that the solution is super secured and we've gone over millions of hoops within Accenture but also with Hafod itself. You know, it's more that like the type of user we deploying the solution to are just not in that world and then they are little bit worried about sharing. Not only they're worried about sharing with us but you know, in home care, there there's an option as well to share some of that data with your family. And there we also see people are kind of okay to share with us but they don't want to share with their family 'cause they don't want to have too much information kind of going potentially worrying or bothering some of their family member. So there is definitely a huge education kind of angle to embracing the technology. Not only when you create the solution but when you actually deploy it with users. >> It's a fabulous project, I am so excited by this story. It's a great story, has all the elements; technology, innovation, cidal impact, data privacy, social interactions, whether it's with family members and others, internal, external. In teams themselves. You guys doing some amazing work, thank you for sharing. It's a great project, we'll keep track of it. My final question for you guys is what comes next for the home care after the trial? What are Hafod's plans and hopes for the future? >> Maybe if I just give an overview and then invite Jamie and Laetitia. So for us, without conversations, you don't create possibilities and this really is a reflection of the culture that we try to engender. So my ask of my team is to remain curious, is to continue to explore opportunities because it's home care up to today, it could be something else tomorrow. We also recognize that we live in a world of collaboration. We need more cross industrial partnerships. We love to explore more things that Accenture, Amazon, others as well. So that's principally what I will be doing is ensuring that the culture invites us and then I hand over to the clever people like Jamie and Laetitia to get on with the technology. I think for me we've already learned an awful lot about home care and there's clearly a lot more we can learn. We'd love to build on this initial small-scale trial and see how home care could work at a bigger scale. So how would it work with thousands of users? How do we scale it up from a cohort of 50 to a cohort of 5,000? How does it work when we bring different kinds of organizations into that mix? So what if, for example, we could integrate it into health care? So a variety of services can have a holistic view of an individual and interact with one another, to put that person on the right pathway and maybe keep them out of the health and care system for longer, actually reducing the costs to the system in the long run and improving that person's outcomes. That kind of evidence speaks to decision-makers and political partners and I think that's the kind of evidence we need to build. >> Yeah, financial impact is there, it's brutal. It's a great financial impact for the system. Efficiency, better care, everything. >> Yeah and we are 100% on board for whatever comes next. >> Laetitia-- >> What about you Laetitia? >> Great program you got there. A amazing story, thank you for sharing. Congratulations on this awesome project. So much to unpack here. I think this is the future. I mean, I think this is a case study of represents all the moving parts that need to be worked on, so congratulations. >> Thank you. >> Thank you. >> We are the Art of the Possible here inside the Cube, part of AWS Reinvent Executive Summit, I'm John Furrier, your host, thanks for watching. (bright upbeat music)

>>Hi, welcome to the cubes coverage of splunk.com 21. I need some Martin Brian Berg joins me next director at Accenture leading the EMEA Splunk partnership. Brian, welcome to the program. Talk to me a little bit about the Splunk Accenture partnership. This goes back about five years, I believe. >>Yeah, let me provide a bit of, uh, of a history. Uh, we have been starting with Splunk very intensively more than five years ago. Uh, we have been working very closely together to create something like an incubator approach to really serve the markets as, as best as possible. It was really successful. So exponential growth far beyond the markets, uh, for the last five years. So I'm really proud to be part of that journey. And, uh, the partnership is kind of anchored around three core components. The first component is what we typically call matching up our deep Accentia industry expertise with cloud spend Splunk technology. So it really gives a unique differentiator in the market combining that unique industry understanding and the Splunk technology, which is really capable to have an end to end platform for our clients. I'll give you an example a couple of years ago with, and starting to work in Germany was Dr. >>Bank cargo, which is one of the leading European, uh, freights or companies that, where we really put the Splunk that Phonto to the stretch and are using even IOT data like vegan shots, sensors, or locomotive data to create very fancy, you know, the use cases. So that, that's just an example how the deep industry expertise of Accentia and the blank technology expertise can work together. So the second part, maybe just to mention that is that Accenture in the partnership is developing industrialized solutions and that is, uh, needing to Accentia IP, which very rapidly can serve our customers in creating value and to transforming our clients on their journey. A great example is our supply chain of ring. We have developed a supply chain control tower, which has these days, obviously with the pandemic situation and the supply chain issues, uh, impacting our economic, uh, return. Uh, recovery is a very specific and very strong case. You can really use Splunk as a real time supply chain tour, and that's kind of the industrialized vertical solutions, which we also, uh, did in our partnership at last. Let me comment on that one, the kind of service pillar is really around cloud. So we are focusing heavily on the cloud business. As we see Splunk also an enabler of the cloud journey for our clients >>And both Splunk and Accenture on their own, uh, digital transformation Splunk going to some subscription only back in 2019, Accenture beginning, it's a cloud transformation, 2015. Talk to me about the cloud first initiative. You launched this about a year ago. So during a very challenging time, talk to me about the objectives of the cloud first initiative, how you're working together with Splunk and what some of the value is in it for the customers. >>So Accenture really sings clouds. You see it that we did a very aggressive transformation. The shift we even changed our organization, organizational structure, how we serve our customers within our cloud service to approach. So we combine our expertise from our strategy and consulting experts with implementation and delivery expertise, to have the full end, to end perspective on what we need to transform and transition our clients into the cloud journey. Um, and we are heavily investing into the cloud markets. Uh, we are doing research, uh, in the market to understand also the client needs and the market developments. For example, we recently launched a European, uh, study called cloud continuum where we interviewed more than 4,000 executives around the globe on what are the key priorities along their cloud journey? What is it really that makes it unique and differentiated? Uh, and we see what are the driving factors in the cloud market in Europe, it's a bit special as compared to the us, uh, the key priority driver of our clients moving into the cloud is cost competitive toughness. So they are really moving into the cloud to save costs. The cost play only the second, uh, kind of the answer was like 38% of respondents has been elaborating around increasing customer value. And here you see already the difference between Europe and us, uh, it's, it's much, much lagging behind in terms of understanding the data in your cloud to create new business opportunities and new business value for your customers, which, uh, which is typically, uh, an opportunity, but also challenge >>One of the challenges that organizations often face regardless of where they are in the world is looking at cloud from a price point perspective rather than a transformational journey perspective. But it sounds like you've actually seen the opposite with this survey that you mentioned. >>Yeah. I mean, that's, that's a fair point. So as set, uh, in, in Europe, we are having many clients and customers focusing on the cost competitiveness, but that typically just one key challenge. Uh, another challenge, especially in Europe is around complexity of our data regulation of trust and compliance. So that very often leads to, again, silos in the cloud architecture. So typically something you would want to overcome with the cloud journey and again, in a kind of siloed infrastructure. So we are having, we have seen that more than 60% of our customers have stirred parts of that data and on-premise data stores. They have kind of hybrid cloud environments. We have more than 48% of our customers in kind of a cloud environment. So you will see that the cloud journey again is a very complex task complex journey, and you are ending up very often in a new silos and he explained comes into play because blank can enable you to have the end to end perspective across your full stack, including a multi and hybrid cloud environment. And that's why the reason why we are looking for a strong interlock of our Splunk business into our cloud first approach to really bring that value into our cloud journey of our customers. >>So the, the complexity is, has been increasing. You mentioned a very high percentage of customers in that hybrid multi-cloud environment. How do you Accenture in Splunk, how does this cloud first initiative help address the complexities that cloud that a multi-cloud environment brings and unlock the opportunities in all of this data? >>Yeah, I mean, there's different ways to see that in my perspective, the cloud transformation, the cloud journey always requires a smart data cloud strategy as a core tool. I call it the core to win because without the cloud data strategy, you are losing really the benefit of the cloud journey in terms of the full value potential of your data. Um, I do see like an evolutionary path of the cloud transformation. First of all, is bringing and transitioning our clients into the cloud. And Splunk would be at the first milestone, the end to end perspective of having the cloud transplant, the cloud ops of ability and club monitoring capability. So it's combining the end-to-end picture and mighty cloud hybrid cloud environment in a single pane of glass, which is really unique from a technology perspective. But in the second step, it could even go further and talking about machine learning technologies about AI and bringing that to the next level on that evolutionary path. >>That's what we typically call AI ops. And that again makes a difference in terms of automation, in terms of efficiencies, in terms of prediction capabilities, which is a huge advantage and value potential for our clients. And the third step is coming back a bit to your point in terms of leaving the data value, uh, in the cloud. So if you are getting more and more advanced, you have so much data in your cloud that you could even use it for new business models for new customer service use cases. Uh, and that's kind of the kind of evolutionary past what I call the data to everything cloud, which is very similar to where Splunk is positioning and using all that data and to end for really bringing value and additional value, add to your customers. There's a >>Tremendous amount of value in that data. If it can be analyzed the value unlocked and analyzed and acted on in real time so that organizations can make business decisions on products and services. And obviously from a competitive differentiation perspective, there's a tremendous amount, a tremendous amount of value. And unlocking that data. What are you seeing in the last, in the last year, since there's been so much acceleration where the customers are coming to you saying Accenture Splunk, help us figure out how to migrate to the cloud. We've got to go quickly, we've got these competitive pressures, we've got a very dynamic world market. What's that pathway like? >>Yeah, it's a very interesting time. So typically you see this cloud transformation journeys as a journey of several years. And in the pandemic situation, you have seen that a couple of months for some of our clients, because it's really important to survive in this very disruptive economic situations. So obviously you start first with, uh, getting the basics done with kind of getting the migration done, getting the migration to the cloud and uplifting our client's technology to the next. So the new kind of cloud paradigm, but, uh, assets that kind of next evolutionary path would be increased. Automation would be increased usage of all the cloud data for additional value add and additional business models. Our client use cases. So that's kind of the starting discussion always is how to bring it to the cloud and how to create that flexibility. That also that grows flexibility in terms of being more resilient, being more agile as a customer, but a Splunk can do much, much more. And that's the story we want to, and we want to explain to the market that the basic steps are the right ones and Splunk is getting you there, especially in multi hybrid thought environments. But the very next step is really untapping. The value. >>A lot of organizations have been challenged culturally in the last year and a half with suddenly this distribution of the workforce. And now here we are still in a distributed environment, maybe getting towards a hybrid model, but cultural change is challenging for organizations in any industry where is cultural change as a part of the pathway that Accenture and Splunk help customers to create >>Absolutely spot on sex dealer for the question. And going back to the research research I was talking earlier on, we have also seen that 46% of our clients are really challenged by the complexity of the transition it's complexity of their business, of their business processes, but also the complexity of the operational change. And that really is a major pitfall and th and the major challenge for us. It's not only a technological challenge, but also it's a change and kind of transition management where we also have specified specialized ones items for an hour at, you know, practice our terms and, and change our practice, which are supporting our clients along that transition journey from a cultural perspective, because I mean, you can change your, your it infrastructure. You can create a new architecture in the cloud, but it's really about getting the business into the next level of understanding these complex data situations and processes and leveraging the value of the cloud. So that's a huge business change as well. >>It is a huge business change, which is challenging for a lot of folks again, given the distributed nature with which in which we are still working. Talk to me about an example of a, of a successful customer that, uh, Accenture and Splunk have worked with in the last year. Who's really embraced the cloud first initiative and is transforming their organizations to not only survive these challenging times, but to thrive as well. >>Yeah, one of my favorite examples is a leading hotel chain. Obviously the hotel industry has been heavily impacted by COVID. Uh, so, uh, there was a need to change to a need to get more resilient, more agile and more flexible. You think the cloud transformation story also, again, as a cost transformation play, but also changing the way the business is working. So we started with a typical cloud transformation journey. Uh, we evolved it towards what we, what we call the AI ops scenario in terms of really using machine learning technologies and AI, to get more prediction, more automation, more efficiencies. So we could even reduce, uh, the operational cost by more than 5%, which is a huge baseline and leading a global companies, uh, which frees up a lot of money, which you can then reinvest for kind of new, smarter business use cases in addressing your clients and understanding your clients and ultimately generating new value for your clients. So that's a very nice example of how you could start with an it transformation journey, changing into the cloud architecture, using AI ops, to freeing up resources for new addresses for kind of new addressable cut customer use cases and business benefits. >>What's the go to market like working customers go to learn more and get started. Are they starting with Accenture? And they starting with Splunk? Can I do both? >>We have a very collaborative partnership with Splunk. We have a strong partnership team as we speak. We have more like more than 4,000 people working on Splunk projects globally. So it's a very strong capability. Um, you can reach out to Accentia and, uh, you can reach out to Splunk. It's kind of a collaborator strategic go-to-market approach nursing. That's also a bit the advantage of the Splunk Accenture partnership that we are very closely, very collaboratively going to the market. Yes, exemptions bringing IP and assets, empty industrialized delivery methodology. We are able to really scale up globally across the market and Splunk is bringing their technology and the expertise. I think it's a winning combination >>And winning complication and not collaboration is certainly critical to enable that. Brian last question would be, as we approach the end of calendar year 2021, what are some of the things on the horizon for the cloud first initiative that you're excited about as we enter 2022, >>I think it's really getting traction. Now. We have seen a lot of our clients going into the cloud, but asset, from my perspective, it's just the start of the journey. So once you get that kind of, uh, interesting milestone start, you can create the automation efficiencies. You can create the data value and use the data very for new CRM scenarios, new years use cases. And that's where it really gets interesting and fun and innovative in getting all these data across your company and understanding and being creative, how you can use that to benefit your customer and to bring that customer experience to the next level. And that's what I'm looking really forward to coming from the it transformation, the cloud transformation journey to the customer experience and to improving the customer perspective. >>Improving the customer perspective is key. As, as the customer experience, we're all customers in our daily lives and our personal lives and our business lives. And we have this expectation that any organization we're dealing with is going to be able to give us a stellar experience. Brian, thank you for joining me on the cube today, sharing the latest and greatest and the Splunk Accenture partnership, the value that you're delivering for customers and some of the things that you're excited about as we go forward. We appreciate your time. >>Thanks for >>Having me. My pleasure for Brian Berg. I'm Lisa Martin. You're watching the cubes coverage of splunk.com 21.