from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone here live in San Francisco at Moscone West of cubes exclusive coverage of Red Hat summit 2018 I'm John four with mykos John Troy a founder of tech reckoning advisory and on community services firm our next guest is Jason O'Connell openshift platform owner of mark mcquarrie group welcome to the cubes let's get it right that's right well the retail bank of Macquarie so thank you and financial services thanks for coming on so bossy begging is pretty hot big time early adopter of all things tech yes and you doing a lot of work at kubernetes tell us about what you're doing take a minute to explain your job what your focus is some of the some of the environment DevOps things you're doing it's a basically I'm head of the container platform team at Macquarie Bank so basically my team manages open shifts on AWS we do the architecture on there but we also focus a lot on the value add on top so we don't just give our our customers for my team are the developers and the development teams we don't just give them a blank platform we do a lot of automation a lot of work on top of that basically because we want to make sure that the idea of a platform as a service is that we do as much as possible to make developers lives easy talk about the journey when did you start on this effort Asli Amazon's great cloud we use it as well other clouds are coming on you had Google and Microsoft and others but when did the open shift conversations start happening where were you what year was it how long have you been using it it's gone through some great changes I want to get your experience on that open shifter journey I mean somewhat of an early adopter I mean we started looking at this two years ago so that was openshift 3.1 a lot of the basic features weren't even there and it took us a year to both build it out as well as migrate about 40 applications to production so it was only a year ago that we've been in production so it's evolved like so rapidly during that time so 40 applications migrating right that enough in and of itself in a year is is a pretty heavy lift can you talk a little bit about are you just re platforming the applications obviously probably not rewriting at this point the open shift has been a good home for the applications that you started out with it sounds like I mean one of the reasons to choose open shift was docker and it was about that migration path I mean part of the migration was ensuring that developers could get everything running locally get these legacy systems we did a lot of micro services running locally on docker containers on their laptop then the migration was was easy from there but we deliberately didn't want to do like a lift and shift we wanted to rethink how we delivered software as part of this project okay what's the biggest challenges you had in doing this I mean as you can open ships got some great movement Houston Cooper native good bet and kubernetes is looking like a really awesome way to move workloads around and manage containers and clusters so you know what's what are some of the things we've learned what are some of the complexities that you overcame can you share a little bit about some of the specifics I think I think the newness is is probably the biggest challenge I mean going back to two years ago there was some very basic components that weren't there at the time and we knew were coming and even now there are pieces of work which we just don't tackle and we do a very quick fix because we know it's coming later I mean it's just moving and evolving so quickly you know we're waiting a lot for sto which is coming in the future so we're holding back on investing in certain areas because of that so it's always a constant challenge yeah I still looking good and the service mesh is hot as well how has OpenShift helped you but what's the list if you had to kind of boil it down what's the bin the the impact to you guys where's the where's that coming from I mean before we even selected OpenShift we had we're looking at our objectives from a business perspective not a technology perspective I'm the biggest objective we had was speed to delivery you know how could you get a business idea a product idea into production as fast as possible or even if you look at a minor fix to something something that should be easier develop it takes a data ride why does it take a month to release the production so speed of delivery was one of the key objectives and I can tell you more about how we we delivered that in detail but just going back to the objectives we also looked at developer experience you know sometimes the developers are not spending enough time coding and doing it they want they get bogged down in a lot of other pieces of work that I I'm really delivering business value yeah so again we wanted the platform to handle that for them they could focus more on their work this is the promise of DevOps and the whole idea of DevOps is to automate away the hassles and I mean my partner Dave a lot that calls a rock fetches no one likes to do all that work it's like can someone else just handle it and then when you got now automation that frees it up but this brings up the thing that I would love to get your reaction to because one things we've been covering and talking a lot about in the cube is this isn't happening around us it's not just what we're doing but this new modern way to deploy software you'll get like some of the big things that are happening in with cloud native and you mission is do is to do this awesome dynamic things on the fly that are automated away so it changes the how software is being built how are you guys embracing that what's the thought obviously you've got a team that's got the mindset of dev yeah I'll see embracing this vision and if everything else is probably substandard she'll you look at you know waterfall or any kind of non agile what is the your view of this modern era of writing code and building applications what I mean for people who don't aren't getting it how are you how do you explain it you know I think it's I mean it's an unbelievable time that we're in at the moment I mean the amount of automation that we're doing is huge and part of our openshift is that it's an automated bull platform so I've got a few junior guys in my team they're like two graduates and in turn they do a lot of the automation yeah it's that easy if you look at interestingly in like security and risk teams and governance teams where we're finding look they can improve security risk and all this by automating you know they're the one set and now we've got SEC offs movements and things like that so speed of production is is does not prohibit better security and in fact with Sec ups the amount of automation we do you got a far greater amount of security because we now know everything that's deployed we can continually scanning for vulnerabilities yeah so Jason you talked about it being new we've talked a little bit about culture how much of this has been a training exercise how much is that it's been a cultural shift within your organization as one of the leaders of it how are you approaching I mean we're lucky there within Macquarie Bank there was a large scale culture shift towards agile where the whole bank runs in that gel manner so that's helped us then fill in our technology and automation it complements that way of delivering so we've got some very unique ways where we've done automation and delivery which completely rethinks how we used to deliver before so right example yeah for instance now if you think why were people scared of delivering something into production why was a small change scary change and a big part of it is the blast radius if something went wrong you know connecting through to our API is we've got our own channels mobile apps a website you've got a lot of partners there are the companies connecting through as well and so even if you did a small change if it costs an issue everyone's affected at once so a big piece of what we did to deliver faster is allowed targeted releases you know I could target a release and a change just to you we could target it to a percentage of customers monitor rolled out quickly if there's a problem dial it up if it's looking good good target to any channel it seems like there's a business benefit to that too right that's massive here because you also can promise stability on certain channels if you want you can have faster channels that are moving quickly and in an API driven world we've got external companies connecting through to these api's you want to be able to say that we've given you a stable offering and you can upgrade when you want and then our channels we cannot move more fast so we've got a minister no-brainer I mean really the old way is completely dead because of that because I think what the blast radius you're pointing about blast radius the risk is massive so everyone's kind of on edge all these tests have to go in redundancies as if the planning is ridiculous all for the risk all that energy you're optimizing for a potential non-event or event here with micro services and you an out can go down to the granular level the granularity is really amazing so when you go forward first of all it's a recruiting opportunity to get better engineers wait this is a way we work I'm going forward I want you to comment on your opinion as an industry participant and can clarify this because a lot of people get confused here Automation they think jobs are going away administration is getting automated system admin type roles where junior people can now do more operating things but the operating roles not going away so talk about that that ops side because now the ops are more efficient the right things are audited maybe but talk about that dynamic between the right things being automated and the right things that are gonna roll to operational service messages or whatnot yeah I mean basically it's about getting people to do these higher-order functions so the people who are doing things manually and operating things manually you look at our Ops teams now morphing into like the classic SRE team you know the side reliability engineering teams where they're spending a significant amount of that time automating things you know looking at alerting and monitoring and then Auto healing I mean it's actually more work to automate everything but with a far greater amount of quality and reliability and what we get and the benefits are long it's worth it basically you do the work upfront and you reap the benefits and then variety away it's like writing rolling out software managing workloads talk about multi class here on Amazon multi cloud is a big focus to your hybrid cloud multi-cloud obviously we're seeing that trend how do you look at multi cloud as a practitioner what are some of the things that check our check boxes for you in terms of okay as we start looking to the next level there might be a multiple cloud scenario how do you think about that and how do you put that into perspective that's worth noting even two years ago and we selected openshift it was with the idea that we could go multi cloud you know that for the users for the developers they're not going to know the difference where we run it on so we're not locked into any provider final question for you if you can boil down openshift into kind of like a soundbite for you what does it mean to you guys what's been the benefit what's been it it's been that what's been the role what's the benefit of OpenShift as you pour the cloud journey you know I could say speed I could say automation I mean that's huge but but really open shift and read how to pick the winner which is docker and kubernetes and a colleague of mine is in coop con in Copenhagen last week he's constantly messaging me saying there's new tooling you guys can use this you can use that and it means that rather than us doing the work we're just getting tooling from the community so it's the de facto standards so that's that's probably the biggest benefit all the goodness is just coming right to your front door luckily and I got to do my homework every night playing around with this technology so yeah gates success story and again the great community open-source projects out there you guys can bring that in and productize it for the retail bank congratulations love open-source stories like this tier one citizen and again continues to power the world open source softens the cube do our part bring and use all the data from Red Hat summit 2018 I'm John fryer with John Tory we'll be back with more after this short break

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone here live in San Francisco at Moscone West of cubes exclusive coverage of Red Hat summit 2018 I'm John four with mykos John Shroyer founder of tech reckoning advisory and on community services firm our next guest is Jason O'Connell openshift platform owner of mark McQuarrie group welcome to the Cuse let's get it right that's right well the retail bank of Macquarie so thank you and financial services thanks for coming on so bas lead banking is pretty hot big-time early adopter of all things tech yes and you doing a lot of work at kubernetes tell us about what you're doing take a minute to explain your job what your focus is some of the some of the environment DevOps things you're doing that's the basic I'm head of the container platforms team at Macquarie Bank so basically my team manages open shifts on AWS we do the architecture on there but we also focus a lot on the value add on top so we don't just give our our customers for my team are the developers and the development teams we don't just give them a blank platform we do a lot of automation a lot of work on top of that basically because we want to make sure that the idea of a platform as a service is that we do as much as possible to make developers lives easy tell about the journey when did you start on this effort Asli Amazon's great cloud we use it as well other clouds are coming on you got Google and Microsoft and others but when did the open shift conversations start happening where were you what year was it how long have you been using it it's gone through some great changes I want to get your experience on that opened she have to journey I mean somewhat of an early adopter I mean we started looking at this two years ago so that was openshift 3.1 a lot of the basic features weren't even there but it took us a year to both build it out as well as migrate about 40 applications to production so there's only a year ago that we've been in production so it's evolved like so rapidly during that time so 40 applications migrating right that enough in and of itself in a year is is a pretty heavy lift can you talk a little bit about are you just replied forming the applications obviously probably not rewriting at this point the open shift has been a good home for the applications that you started out with it sounds like I mean one of the reasons to choose openshift was docker and it was about that migration path I mean part of the migration was ensuring that developers could get everything running locally get these legacy systems we did a lot of micro services running locally on docker containers on their laptop then the migration was was easy from there but we deliberately didn't want to do like a lift and shift we wanted to rethink how we delivered software as part of this project okay what's the biggest challenges you had in doing this I mean as you go but she has got some great movements you could burn aces a good bet and kubernetes is looking like a really awesome way to move workloads around and manage containers and clusters so you know what's what are some of the things we've learned what are some of the complexities that you overcame can you share a little bit about some of the specifics I think I think the newness is is probably the biggest challenge I mean going back to two years ago there were some very basic components that weren't there at the time when we knew were coming and even now there are pieces of work which we just don't tackle and we do a very quick fix because we know it's coming later I mean it's just moving and evolving so quickly you know we're waiting a lot for sto which is coming in the future so we're holding back on investing in certain areas because of that so it's always a constant challenge yeah I still looking good and the service mesh is hot as well how has OpenShift helped you but what's the what's the if you had to kind of boil it down what's the been the the impact to you guys where's the where's that coming from I mean before we even selected OpenShift we had we're looking at our objectives from a business perspective not a technology perspective I'm the biggest objective we had with speed to delivery you know how could you get a business idea a product idea into production as fast as possible or even if you look at a minor fix to something something that should be easier develop it takes a data ride why does it take a month to release the production so speed of delivery was one of the key objectives and I can tell you more about how we we delivered that in detail but just going back to the objectives we also looked at developer experience you know sometimes the developers are not spending enough time coding and doing if they want they get bogged down in a lot of other pieces of work dinner I'm really delivering business value yeah so again we wanted the platform to handle that for them they could focus more on their work and this is the promise of DevOps and the whole idea of DevOps is to automate away the hassles and I mean my part to Dave a lot that calls a rock fetches no one likes to do all that work it's like can someone else just handle it and then when you got now automation that frees it up but this brings up the thing I would love to get your reaction to because one things we've been covering and talking a lot about in the cube is this is been happening around us it's not just what we're doing but this new modern way to deploy software you look at like some of the big things that are happening in with cloud native and you mention SEO is to do this awesome dynamic things on the fly that are automated away so it changes the how software is being built how are you guys embracing that what's the thought oh so you've got a team that's got the mindset of DevOps yeah I'll see embracing this vision and if everything else is probably substandard she'll you look at you know waterfall or any kind of non agile what is the your view of this modern era of writing code and building applications what I mean for people who don't aren't getting it how are you how do you explain it you know I think it's I mean it's an unbelievable time that we're in at the moment I mean the amount of automation that we're doing is huge and part of our openshift is that it's an automated bull platform so I've got a few junior guys in my team they're like two graduates and in turn they do a lot of the automation yeah it's that easy now everything's got API so we can connect everything so I do find when we interface with some of the older school teams in different parts of the bank that aren't doing this level of automation they used to manual processes and manual ways of doing things and now we look at everything where everything can be automated that's thing you really truly feel now opened up that you could automate absolutely everything I mean the developer productivity one is key you know state of mind is another I mean the mood is better okay people are in a better mood more productive yeah and I think if you look at interestingly in like security and risk teams and governments teams where we're finding look they can improve security risk and all this by automating you know they're the one set and now we've got SEC offs movements and things like that so speed of production is is does not prohibit better security and in fact with Sec ups the amount of automation we do you got a far greater amount of security because we now know everything that's deployed we can continually scanning for vulnerabilities yeah what so Jason you talked about it being new we've talked a little bit about culture how much of this has been a training exercise how much is that it's a cultural shift within your organization as one of the leaders of it how are you approaching I mean we're lucky there within Macquarie Bank there was a large scale culture shift towards agile where the whole thing runs in that gel manner so that's helped us then feel in our technology and automation it complements that way of delivering so we've got some very unique ways where we've done automation and delivery which completely rethinks how we used to deliver before so example yeah for instance now if you think why were people scared of delivering something into production why was a small change scary change and a big part of it is the blast radius if something went wrong you know connecting through to our API is we've got our own channels we've got mobile apps got a website you've got a lot of partners there are the companies connecting through as well and so even if you did a small change if it costs an issue everyone's affected at once so a big piece of what we did to deliver faster is allowed targeted releases you know I could target a release and a change just to you we could target it to a percentage of customers monitor rolled out quickly if there's a problem dial it up if it's looking good good target to any channel it seems like there's a business benefit to that too oh it's massive here because you also can promise stability on certain channels if you want you can have faster channels that are moving quickly and in an API driven world we've got external companies connecting through to these api's you want to be able to say that we've given you a stable offering and you can upgrade when you want and then our channels we cannot move more fast so we've got mr. no-brainer I mean really the old way is completely dead because of that because you think about the blast radius you're pointing about blast radius the risk is massive so everyone's kind of on edge all these tests have to go in redundancies as if the planning is ridiculous all for the risk well that energy you're optimizing for a potential non-event or event here with micro-services and you and app can go down to the granular level the granularity is really amazing so when you go forward first of all it's a recruiting opportunity to get better engineers wait this is a way we work I'm going forward I want you to comment on your opinion as an industry participant and can clarify this because a lot of you'll get confused here automation they think jobs are going away administration is getting automated system admin type roles where junior people can now do more operating things but the operating roles not going away so talk about that that ops side because now the ops are more efficient the right things are audited me you but talk about that dynamic between the right things being automated and the right things that are gonna roll to operational service meshes or whatnot yeah I mean basically it's about getting people to do these higher-order functions so the people who are doing things manually and operating things manually you look at our Ops teams now morphing into like the classic SRE team you know the side reliability engineering teams where they're spending a significant amount of that time automating things you know looking at alerting and monitoring then Auto healing I mean it's actually more work to automate everything but with a far greater amount of quality and reliability when we go and the benefits are long it's worth it basically you do the work upfront and you reap the benefits and then variety of ways like writing rolling out software managing workloads talk about multi class here on Amazon multi cloud is a big focus to your hybrid cloud multi-cloud obviously we're seeing that trend how do you look at multi cloud as a practitioner what are some of the things that check our check boxes for you in terms of ok as we start looking for the next level there might be a multiple cloud scenario how do you think about that and how do you put that into perspective that's worth noting even two years ago and we selected open shifty it was with the idea that we could go multi-cloud you know that for the users for the developers they're not going to know the difference where we run it on so we're not locked into any provider I mean at the moment we're kind of just exploring Google cloud and we're looking at what it would look like so even we don't know yet some people have spoken about stretching your cluster across to clouds that means one cluster across two seems very difficult to me that a lot of latency issues potentially there's also cloud arbitrage you know can we get certain workloads on a card that's cheaper can we use spot instances can we spin things up and down we're on Google it's cheaper and then it also raises questions around okay do we need Federation and we know Federation has been talked about a lot with kubernetes how do we manage so many clusters and even on AWS now we have three production clusters you had multi clouds how am I gonna manage that what about the services layer of clouds right obviously the Red Hat platform gives you a services layer that could run anywhere but underneath that right AWS has its own services layer Google you know a lot of AI ml you know it could you be able to are you thinking about taking advantage or how are you thinking about those different offerings on different different places I mean this is the challenge I face and what we're exploring is that do some teams have the differentiating services the unique services that they want on Google especially for managing data machine learning we know those services are key for them some teams will have that but yet then can we call them over from AWS even oh do we have to deploy in in Google and have that in one data center can we go across with services so it's really like not just cloud AWS cloud Google but it's actually criss-crossing that's another thing we're exploring Jason thanks for coming on the cube really appreciate your commentary I've seen multiple red hats you guys have won awards you've been here before great job final question for you if you could boil down OpenShift into kind of like a sound byte for you what does it mean to you guys what's been the benefit what's been it it's been that what's been the role what's the benefit of openshift as you explore the cloud journey you know I could say speed I could say automation I mean that's huge but but really OpenShift and read how to pick the winner which is docker and kubernetes and a colleague of mine is in pucon in copenhagen last week he's constantly messaging me saying there's new tooling you guys can use this you can use that and a means that rather than us doing the work we're just getting tooling from the community so it's the de facto standards so that's that's probably the biggest benefit all the goodness is just coming right to your front door likely and I got to do my homework every night playing around with this technology so yeah great success story and again the great community open-source projects out there you guys can bring that in and productize it for the retail bank congratulations love open-source stories like this tier one citizen and again continues to power the world open-source softens the cube doing our part bring and use all the data from Red Hat summit 2018 I'm John fryer with John Tory we'll be back with more after this short break

(upbeat music) >> Hey everyone, Lisa Martin here with you on theCUBE Live from Mobile World Congress '23 in Barcelona. We're having a great day at the show. We hope you are too. I've got two guests here with me next. We're going to be talking about telco's 5G, all that exciting stuff. Please welcome Jason Inskeep, the AVP 5G, and Private 5G Center of Excellence at AT&T Business. And Doug Lieberman is here as well. Senior Director, Global Solutions Co-Creation Services at Dell Technologies. Guys, it's great to have you on the show, live from the show floor, talk to me about what's going on, how are you? >> Hey, thanks for having us on. It's a great show, I'm happy to be back here this year and really looking forward to the conversations that are going on and really continuing these partnerships that Dell has with companies like AT&T to truly drive the realities and the benefits of 5G. >> Absolutely, Doug, talk to me a little bit. You have an interesting title, Director of Global Solutions Co-Creation Services at Dell. Tell me a little bit about your role, what you're responsible for, and then Jason we'll have you do the same. >> Yeah, thanks for bringing that up. So, I have a very interesting role and a very exciting role at Dell because we have a unique organization that I run globally whose job it is, is to work with telcos to co-create services for enterprise and jointly go to market with those. So that basically take the combined power of AT&T and Dell and bring that to enterprise customers and other telcos so that enterprises can realize the value of, and truly leverage and harness the capabilities of 5G for private mobility and Mac and IOT and connected devices. >> Jason, let's bring you into the conversation now. You have an interesting title as well. You're with the 5G Center of Excellence at AT&T. Talk a little bit about your role and that COE. >> Yeah, thanks for having me again as well. The role with my team at AT&T is we're on the cutting edge. We're sitting in between our customers and our product houses that are working with folks at Dell, really helping putting our products together in the space of 5G. A lot of open opportunities here, a lot of things changing really fast. So my teams are off as well as putting this stuff in customers production sites it's also taking and capturing that information, working with my internal partners, both on the technology side, on the product side, and partners like Dell who are coming in helping us enabling those products and services that we can take and scale out through the different opportunities that we're seeing in this space. >> Let's double click on that partner angle, Jason, will stay with you. The 5G revolution, it's here, we are all excited about it. There's so much potential that will come from that. Let's talk about the AT&T/Dell partnership. How are you guys working together to deliver 5G globally? Jason, we'll start with you and then Doug will go to you. >> Yeah, at the core of it, when we started looking at 5G and seeing the changes that were happening, one of the biggest changes is it became software defined. So, the way we could deploy the hardware with the software becomes a whole new conversation. And what we saw coming out of that is it's not going to be a single winner and loser to really execute the way it's necessary for the experiences of tomorrow. It has to be an ecosystem that comes together. Dell creates a great opportunity for us from the hardware perspective to move those services around, to scale those services ultimately to all kinds of site types up to cities right down to small offices. And those different form factors that they bring with the software and the network pieces that we're adding on top of it help to streamline the flows and processes and really gets to that next generation that we see happening, which is this converged architecture. This meeting of network and application, creating a whole new skillset along with products. So we're at the very top we've got Dell/AT&T, at a partner level, it gets at a granular level too. The users and the developers underneath are starting to change as well, so very interesting dichotomy happening right now. >> Right, Doug, what's through Dell's lens? Tell us a little bit about the partnership and how you're working together to deliver 5G and really unlock its potential globally. >> Yeah, thank you, I'd love to bonus off of what Jason was saying, for Dell, what we look at is through the lens of an enterprise. An enterprise needs to execute their business function, their outcome, their mission that they need to operate. And so therefore they have workloads that they need to run. And 5G is an enabler for that technology, and there's lots of other enablers but the key piece is how can they get their business work done better, faster, cheaper, more efficiently, more securely? And the combination of AT&T and Dell truly is a combination that brings in a partnership that brings together a full breadth of those capabilities, with understanding what those enterprise workloads are and how they work and how an enterprise would leverage these capabilities. And then bonus on top of that and merge together with that the capabilities of AT&T. And when you look at 5G, there's a lot of people that talk about 5G being the enterprise G. And a lot of that is because of things that Jason mentioned. As we move to a disaggregated stack where you have software-defined aspects of it, and the ability in the underlying definition of what 5G in the specifications to allow much more customization. It means that enterprises now cannot just take connectivity as it is and use it however it comes but actually work with a telco and work with Dell to customize that connectivity in a way that better meets their requirements. Whether that be with slicing or private mobility or roaming between private and the public network and things like profiles and being able to have different views of how different users and devices connect to that network are all key in truly harnessing the power of that connectivity to have always on, always connected, always integrated systems from the edge, the core, to the cloud. >> Always on, always connected. That's what we all expect these days. Wherever we are in the world, whatever we're trying to do. But to be able to take advantage of all that 5G offers for all of us, telcos have to create infrastructures that can support it, let's double click guys on the infrastructure that Dell and AT&T have put in place to enable this. Jason, I want to get your perspective first and then Doug will go to you. >> Yeah, I mean, it's foundational, the things that we're trying to do and build out here and there's a lot of complexity in it now that we didn't have before because of the flexibility in it. It's one of those things like the good news in software is you can do whatever you want. The bad news in software is you can do whatever you want. Once you have that foundation there though in terms of infrastructure, which for us is really air to glass. Fiber through the spectrum on top. But underneath of that, we have the servers, we have that infrastructure where those fibers come together where that air meets the radios and so forth. And we've got to have that great foundation. So working with Dell and getting those spaces built together preps the area as needed so that there's additional place now for compute and scale at that new converged meet-me point. And that's going to be the opportunity that we're trying to think about really to get that foundation in a way that maximizes capacity and maximizes control for the customers and enterprises in particular. And more importantly, maximizes the time horizon. Because if you're putting in a foundation like this, you're not looking at two to three years. You're trying to skate beyond, skate where the puck is going, look at five, 10 years out, set that foundation. And that's what we're trying to look at with Dell. What can our network do already? Where can we push it? In return, they're going to build their solutions to help maximize that potential. >> From an infrastructure perspective, Doug, I want to understand really where Dell is really shining there but also what are some of the differentiators that Dell brings to this foundational infrastructure that to your point, is built for scale? >> Yeah, so it really all comes down to as we start to see this transition that's been happening for years, but it's accelerating because of always-connected devices and everything connected and the great proliferation of data at the edge. As we move assets from the data center and out to the edge we introduce new challenges that have to be overcome. You have things like security, automation, infrastructure cost, maintenance, day-one operations, day-two operations, all of these things are new complexities which enterprises want to enable their workloads, enable the outcomes that they want to generate. But they need to make sure that they're not taking a step backwards when it comes to things like regulations. In Europe, you've got GDPR, and in the US you've got different security regulations. No one wants to be the next front page headline about their company being attacked and having a ransomware attack. And so as we spread out these assets, what Dell is here to do is to work with AT&T and enable enterprises to effectively build their virtual enterprise around the world where those assets, whether they're at the edge or the core or in the cloud, are all managed with the same profiles and the same security features and the same automation that they have in a core data center. So my ability to deploy an edge cloud so that I can leverage AT&T's network and have end-user devices do things like gaming or connect to video services or get directed retail advertising to you are not basically introducing new vectors for security vulnerabilities into that network. And so Dell has worked really hard and is a leader in the industry in providing automation and lower cost of ownership and security for those solutions. So it's not just about putting a server out there but it's about putting an infrastructure and a cloud that is connected by AT&T's backbone and to a central core of automation management and orchestration capabilities so that I can leverage those assets securely and efficiently. >> That security element that you bring up, Doug, is so incredibly critical. We talk about it at every event, we talk about it every day. We've seen such dramatic changes in the threat landscape in the last couple of years with covid and things like that. So that security element isn't trivial, it's essential for every type of enterprise regardless of where they are. I want to talk a little bit now about best practices. And Doug, go back to you, looking at what AT&T is achieving, the 5G COE, what you're doing with Dell. From your lens and your experiences, what are some of the best practices for telcos deploying secured network and connectivity at the edge? >> Yeah, well, I think the first one is that automation and that orchestration, right? The answer is that you cannot have snowflakes at every single ag point. You need to make sure that those infrastructures are consistent and compliant with the integrations and with the policies that have been set across the network. The second thing is that you want to make sure that the connectivity is monitored and metered and managed so that we know whether, for example that endpoint is there and it's not there, if it goes offline. And ensuring the end-user experience is consistent throughout. And so what we are seeing is that it's really important that we provide an implementation where the enterprise can get a consistent and a predictable outcome for what they're trying to accomplish. What they don't want to do, what enterprises hate and is really bad for them is when they provide an inconsistent or inappropriate results to their users, to their customer base. So if your website goes offline or you're a gaming platform, if people can't get to your game you're going to lose customers, you're going to lose business you're going to have people lose faith in your network. And so our partnership with AT&T and with other telcos is about ensuring that we have all those aspects covered, day zero, day one, and day two, as well as the security aspects. And that back haul is an essential piece of that because as we get more and more devices and more and more edge devices set up, there's more sprawl. And so the complexity goes up substantially, but what really wins is when you can take that complexity and use it to your advantage and be able to manage and deploy those systems as though they were all within your virtual enterprise. >> Using complexity to your advantage. That's an interesting one, Doug, that you're bringing up. Jason, I want to know, what does that mean for you and how is AT&T leveraging complexity to its advantage for its customers all over the globe? >> You know, first thing is if you're thinking about, we're a network company we're not just a 5G company, so we're wireline, we're wireless, we're global in terms of the amount of fiber we have in the ground, the amount of in the US, domestic sailor deployments, our investments in FirstNet, is our first responder network here in the US. So we have a big portfolio inclusive of IOT. That is a global brand as well. That, if you look at it through the outside lens, that's super complex, all over the planet. So when we're talking to our customers now in this new world, which is very much, "Hey, you can do these things on your own." We go back and the bigger, obviously have the products, and the network and the tech but now that customers can take advantage of it and take things that Dell have rolled out, they need that new new age expertise. You also got the Dell expertise of building these platforms from maybe a software level, from an orchestration level, those kind of things. And at the edge that's creating a new type of person and a new type of workflow, a new type of way to respond and work. So that combination of those two is going to be that new skillset. It's in small pockets now, it's growing in how that looks because it's a little combination of both the app developer and the network developer, that's coming together. Our footprint and in terms of what we provide in there is not just 5G, it's 5G, it's fiber, it's all of those pieces together. And that's what's going to super enable that experience that Doug talked about when you're thinking about gaming or transportation, it's not just the network performance, it's the roundtrip, so we're really trying to focus on that and educate our customers in that way with the expertise that we bring over years and years of building these things. >> And if I could just jump in there. I'd like to just emphasize something Jason just said. When we look at workloads at the edge, very rarely are those workloads uniquely just an edge workload, there are components. The example I like to use is video surveillance. If you are a big box store and you have video surveillance inside your store, there is a set of workloads and outcomes you need for immediate response at that edge. You want to know if there's a safety hazard, if there is a theft or those things. Those things need to be processed real time in the store before the thief leaves the store. But then there's a set of connectivity as well where you want to process that data up in the cloud to get long-term analytics and data off of that information. What's my average store density on a Thursday afternoon in November when it's 20 degrees out. Because that would drive how many employees I have, how much inventory I carry, et cetera. And that combination is a factor that drives all the different aspects of AT&T's network. We need the connectivity in the store for the practicability and the spectrum for the cameras that talk to a central server. We need the high-speed backup and throughput in order to provide cyber recovery as well as point-of-sales services so that they can do credit card transactions flawlessly, which is using a lot of wireline services for AT&T. And together with their cloud and their other capabilities, an enterprise needs all those different aspects to work, both the edge, the core and the cloud coming together to form an outcome from one piece of input. So that one piece of input, that video stream is used in multiple different ways and because of that, that network that AT&T brings can support the end-to-end outcome and use cases for that implementation, as an example. >> That end-to-end roundtrip that you guys talked about is essential for every type of enterprise. A lot of great work that Dell and AT&T are doing together to really enable enterprises to really capitalize on all that the new technology that 5G has the potential to deliver. So I got to wrap things up, Jason, with you. From a business-customer perspective, what's next for AT&T? What can those business customers expect? >> Just continued to scaling because you're looking at a space that's evolving rapidly. It's evolving rapidly, there's a lot of opportunity. You look at the private wireless space in particular, it's nascent, but growing rapidly with the customers having their ability to do this on their own. So for us, and really where we're starting to think now is we're seeing the things move from POC, starting to move to production, customers are starting to think about what's next. For us, we're trying to skate ahead of that knowing how we built our own networks, knowing how we engaged in our own partnerships like with Dell and trying to bring that expertise back to the customer, because it isn't cookie cutter anymore. There's a lot of flexibility and each input creates a different output. So it's up to us to at least help them balance that. Define what I like to affectionately call, "Find their Goldilocks." What is that just right for them? >> Great point, Jason, it is no longer a cookie cutter. Cookie cutter isn't going to cut it. Jason, Doug, thank you so much for joining me on theCUBE today from Mobile World Congress in Barcelona. We appreciate thank you all of your insights. Sounds like some great work that AT&T and Dell are doing together. Enterprises have a lot to look forward to. Thank you again for your time. >> Thank you very much, >> Thank you. >> Looking forward to seeing you at the show. >> I'm Lisa Martin from theCUBE at Mobile World Congress '23 in Barcelona. Thanks for watching. (upbeat music)

(bright upbeat music) >> Well, hi everybody, John Wallace here and welcome to theCUBE, the leader in high-tech coverage. Glad to have you aboard here as we continue our coverage here at re:Invent 2022. We're out at The Venetian in Las Vegas. A lot of energy down on that exhibit floor, I promise you. We're a little bit away from the maddening crowd, but we're here with the Executive Summit sponsored by Accenture. I've got two guests I want to introduce you to. Jason Beyer who is the vice president of Data and Analytics at Bridgestone Americas. Jason, good to see you, sir. >> Hello, John. >> And Josh von Schaumburg, who is the managing director and North America lead for AWS Security at Accenture. Josh, good to see you. >> Thanks for having us. >> Yeah, first off, just quick take on the show. I know you've only been here about a day or so, but just your thoughts about what you're seeing on the floor in terms of energy, enthusiasm and, I think, turnout, right? I'm really impressed by it. We've got a lot of people down there. >> Yeah, I've been certainly impressed, John, with the turnout. But just as you say, the energy of the crowd, the excitement for the new things coming, it seems like it's a really pivotal moment for many organizations, including my own, and really excited to see what's coming over the next couple days. >> Let's jump into Bridgestone then. I kind of kidded you before we started the interview saying, all right, tires and golf balls, that's what I relate to, but you have a full array of consumer products and solution you're offering and your responsibility is managing the data and the analytics and making sure those business lines are as efficient as possible. >> Absolutely, John. So in my role, I have the privilege of being in an enterprise position. So I get to see the vast array of Bridgestone, which it is a large, highly vertically integrated company all the way from raw material sourcing of natural rubber to retail services in the automotive industry. We're at scale across those areas. The exciting thing about the company right now is we're going through this business transformation of becoming, you know, building on that heritage and that great legacy of having high quality high performance, highly focused on safety products to becoming a product and solutions company, and particular a sustainable solutions company. So what that means is we're bringing not only those great products to market, tires, golf balls, hoses, all kinds of rubber, air springs products to market, but thinking about how do we service those after they're in the market, how do we bring solutions to help fleets, vehicle owners, vehicle operators operate those in a sustainable way, in a cost effective way? So those solutions, of course, bring all new sets of data and analytics that come with it, and technology and moving to the cloud to be cloud native. So this new phase for the organization that we refer to as Bridgestone 3.0, and that business strategy is driving our cloud strategy, our technology strategy, and our data strategy and AWS and Accenture are important partners in that. >> Yeah, so we hear a lot about that these days about this transformation, this journey that people are on now. And Josh, when Bridgestone or other clients come to you and they talk about their migrations and what's their footprint going to look like and how do they get there, in the case of Bridgestone when they came to you and said, "All right, this is where we want to go with this. We're going to embark on a significant upgrade of our systems here," how do you lead 'em? How do you get 'em there? >> Yeah, I think there are a couple key cloud transformation value drivers that we've emphasized and that I've seen at Bridgestone in my time there. I mean, number one, just the rapid increase in the pace of innovation that we've seen over the last couple years. And a lot of that is also led by the scalability of all of the cloud native AWS services that we're leveraging, and in particular with the CDP platform. It really started off as a single-use case and really a single-tenant data lake. And then through the strategic vision of Jason and the leadership team, we've been able to expand that to 10 plus tenants and use cases. And a big reason behind that is the scalability of all these AWS services, right? So as we add more and more tenants, all the infrastructure just scales without any manual provisioning any tuning that we need to do. And that allows us to go really from idea, to POC, to production in really a matter of months when traditionally it might take years. >> So- >> If I can build upon that. >> Please do, yeah. >> The CDP, or central data platform, is part of a broader reference architecture that reflects that business strategy. So we looked at it and said, we could have taken a couple of different approaches to recognize the business challenges we're facing. We needed to modernize our core, our ERP, our manufacturing solutions move to smart factory and green factories, our PLM solutions. But at the same time, we're moving quickly. We have a startup mindset in our mobility solutions businesses where we're going to market on our customer and commerce solutions, and we needed to move at a different pace. And so to decouple those, we, in partnership with Accenture and AWS, built out a reference architecture that has a decoupling layer that's built around a data fabric, a data connected layer, integrated data services as well. A key part of that architecture is our central data platform built on AWS. This is a comprehensive data lake architecture using all the modern techniques within AWS to bring data together, to coalesce data, as well as recognize the multiple different modes of consumption, whether that's classic reporting, business intelligence, analytics, machine learning data science, as well as API consumption. And so we're building that out. A year ago it was a concept on a PowerPoint and just show and kind of reflect the innovation and speed. As Josh mentioned, we're up to 10 tenants, we're growing exponentially. There's high demand from the organization to leverage data at scale because of the business transformation that I mentioned and that modernization of the core ecosystem. >> That's crazy fast, right? And all of a sudden, whoa! >> Faster than I expected. >> Almost snap overnight. And you raise an interesting point too. I think when you talk about how there was a segment of your business that you wanted to get in the startup mode, whereas I don't think Bridgestone, I don't think about startup, right? I think in a much more, I wouldn't say traditional, but you've got big systems, right? And so how did you kind of inject your teams with that kind of mindset, right? That, hey, you're going to have to hit the pedal here, right? And I want you to experiment. I want you to innovate. And that might be a little bit against the grain from what they were used to. >> So just over two years ago, we built and started the organization that I have the privilege of leading, our data and analytics organization. And it's a COE. It's a center of expertise in the organization. We partner with specialized teams in product development, marketing, other places to enable data and analytics everywhere. We wanted to be pervasive, it's a team sport. But we really embraced at that moment what we refer to as a dual speed mindset. Speed one, we've got to move at the speed of the business. And that's variable. Based on the different business units and lines of lines of business and functional areas, the core modernization efforts, those are multi-year transformation programs that have multiple phases to them, and we're embedded there building the fundamentals of data governance and data management and reporting operational things. But at the same time, we needed to recognize that speed of those startup businesses where we're taking solutions and service offerings to market, doing quick minimum viable product, put it in a market, try it, learn from it adapt. Sometimes shut it down and take those learnings into the next area as well as joint ventures. We've been much more aggressive in terms of the partnerships in the marketplace, the joint ventures, the minority investments, et cetera, really to give us that edge in how we corner the market on the fleet and mobility solutions of the future. So having that dual speed approach of operating at the speed of the business, we also needed to balance that with speed two, which is building those long term capabilities and fundamentals. And that's where we've been building out those practical examples of having data governance and data management across these areas, building robust governance of how we're thinking about data science and the evolution of data science and that maturity towards machine learning. And so having that dual speed approach, it's a difficult balancing act, but it's served us well, really partnering with our key business stakeholders of where we can engage, what services they need, and where do we need to make smart choices between those two different speeds. >> Yeah, you just hit on something I want to ask Josh about, about how you said sometimes you have to shut things down, right? It's one thing to embark on I guess a new opportunity or explore, right? New avenues. And then to tell your client, "Well, might be some bumps along the way." >> Yeah. >> A lot of times people in Jason's position don't want to hear that. (laughs) It's like, I don't want to hear about bumps. >> Yeah. >> We want this to be, again, working with clients in that respect and understanding that there's going to be a learning curve and that some things might not function the way you want them to, we might have to take a right instead of a left. >> Yeah, and I think the value of AWS is you really can fail fast and try to innovate and try different use cases out. You don't have any enormous upfront capital expenditure to start building all these servers in your data center for all of your use cases. You can spin something up easily based in idea and then fail fast and move on to the next idea. And I also wanted to emphasize I think how critical top-down executive buy-in is for any cloud transformation. And you could hear it, the excitement in Jason's voice. And anytime we've seen a failed cloud transformation, the common theme is typically lack of executive buy-in and leadership and vision. And I think from day one, Bridgestone has had that buy-in from Jason throughout the whole executive team, and I think that's really evident in the success of the CDP platform. >> Absolutely. >> And what's been your experience in that regard then? Because I think that's a great point Josh raised that you might be really excited in your position, but you've got to convince the C-suite. >> Yeah. >> And there are a lot of variables there that have to be considered, that are kind of out of your sandbox, right? So for somebody else to make decisions based on a holistic approach, right? >> I could tell you, John, talking with with peers of mine, I recognize that I've probably had a little bit of privilege in that regard because the leadership at Bridgestone has recognized to move to this product and solutions organization and have sustainable solutions for the future we needed to move to the cloud. We needed to shift that technology forward. We needed to have a more data-driven approach to things. And so the selling of that was not a huge uphill a battle to be honest. It was almost more of a pull from the top, from our global group CEO, from our CEOs in our different regions, including in Bridgestone Americas. They've been pushing that forward, they've been driving it. And as Josh mentioned, that's been a really huge key to our success, is that executive alignment to move at this new pace, at this new frame of innovation, because that's what the market is demanding in the changing landscape of mobility and the movement of vehicles and things on the road. >> So how do you two work together going forward, Ben? Because you're in a great position now. You've had this tremendous acceleration in the past year, right? Talking about this tenfold increase and what the platform's enabled you to do, but as you know, you can't stand still. Right? (laughs) >> Yeah. There's so much excitement, so many use cases in the backlog now, and it's really been a snowball effect. I think one of the use cases I'm most excited about is starting to apply ML, you know, machine learning to the data sets. And I think there's an amazing IoT predictive maintenance use case there for all of the the censored data collected across all of the tires that are sold. There's an immense amount of data and ultimately we can use that data to predict failures and make our roads safer and help save lives >> Right. >> It's hard to not take a long time to explain all the things because there is a lot ahead of us. The demand curve for capabilities and the enabling things that AWS is going to support is just tremendous. As Josh mentioned, the, the AI ML use cases ahead of us, incredibly exciting. The way we're building and co-innovating things around how we make data more accessible in our data marketplace and more advanced data governance and data quality techniques. The use of, you know, creating data hubs and moving our API landscape into this environment as well is going to be incredibly empowering in terms of accessibility of data across our enterprise globally, as well as both for our internal stakeholders and our external stakeholders. So, I'll stop there because there's a lot of things in there. >> We could be here a long time. >> Yes, we could. >> But it is an exciting time and I appreciate that you're both sharing your perspectives on this because you've got a winning formula going and look forward to what's happening. And we'll see you next year right back here on the Executive Summit. >> Absolutely. >> To measure the success in 2023. How about that? >> Sounds good, thank you, Jim. >> Is that a deal? >> Awesome. >> Sounds good. >> Excellent, good deal. You've been watching AWS here at Coverage of Reinvent '22. We are the Executive Summit sponsored by Accenture and you are watching theCUBE, the leader in high tech coverage. (gentle music)

>>Hey everyone, and welcome back to Las Vegas. Viva Las Vegas, baby. This is the Cube live at AWS Reinvent 2022 with tens of thousands of people. Lisa Martin here with Dave Valante. Dave, we've had some great conversations. This is day one of four days of wall to wall coverage on the cube. We've been talking data. Every company is a data company. Data protection, data resiliency, absolutely table stakes for organizations to, >>And I think ecosystem is the other big theme. And that really came to life last year. You know, we came out of the pandemic and it was like, wow, we are entering a new era. People no longer was the ecosystem worried about it, AWS competing with them. They were more worried about innovating and building on top of AWS and building their own value. And that's really, I think, the theme of the 2020s within the ecosystem. >>And we're gonna be talking about building on top of aws. Two guests join us, two alumni join us. Stephen Manley is here, the CTO of Druva. Welcome back. Jason crat as well is here. CIO and CTO of Summit Carbon Solutions. Guys, great to have you back on the program. >>Thank you. >>Let's start with you giving the audience an understanding of the company. What do you guys do? What do you deliver value for customers? All that good >>Stuff. Yeah, no, for sure. So Summit Carbon is the world's largest carbon capture and sequestration company capturing close to 15 million tons of carbon every year. So it doesn't go into the atmosphere. >>Wow, fantastic. Steven, the, the risk landscape today is crazy, right? There's, there's been massive changes. We've talked about this many times. What are some of the things, you know, ransomware is a, is, I know as you say, this is a, it's not a, if it's gonna happen, it's when it's how frequent, it's what's gonna be the damage. What are some of the challenges and concerns that you're hearing from customers out there today? >>Yeah, you know, it really comes down to three things. And, and everybody is, is terrified of ransomware and justifiably so. So, so the first thing that comes up is, how do I keep up? Because I have so much data in so many places, and the threats are evolving so quickly. I don't have enough money, I don't have enough people, I don't have enough skilled resources to be able to keep up. The second thing, and this ties in with what Dave said, is, is ecosystem. You know, it used to be that your, your backup was siloed, right? They'd sit in the basement and, and you wouldn't see, see them. But now they're saying, I've gotta work with my security team. So rather than hoping the security team stays away from me, how do I integrate with them? How do I tie together? And then the third one, which is on everybody's mind, is when that attack happens, and like you said, it's win and, and the bell rings and they come to me and they say, all right, it's time for you to recover. It's time for, for all this investment we've put in. Am I gonna be ready? Am I going to be able to execute? Because a ransom or recovery is so different than any other recovery they've ever done. So it's those three things that really are top of mind for >>How, so what is the, what are the key differences, if you could summarize? I mean, I >>Know it's so, so the first one is you can't trust the environment you're restoring into. Even with a disaster, it would finish and you'd say, okay, I'm gonna get my data center set up again and I'm gonna get things working. You know, when I try to recover, I don't know if everything's clean yet. I'm trying to recover while I'm still going through incident response. So that's one big difference. A second big difference is I'm not sure if the thing I'm recovering is good, I've gotta scan it. I've gotta make sure what's inside it is, is, is alright. And then the third thing is what we're seeing is the targets are usually not necessarily the crown jewels because those tend to be more protected. And so they're running into this, I need to recover a massive amount of what we might call tier two, tier three apps that I wasn't ready for because I've always been prepared for that tier one disaster. And so, so those three things they go, it's stuff I'm not prepared or covering. It's a flow. I'm not used to having to check things and I'm not sure where I'm gonna recover too when the, when the time comes. >>Yeah, just go ahead. Yeah, that's right. I mean, I think for me, the biggest concern is the blind spots of where did I actually back it up or not. You know, what did I get it? Cuz you, we always protect our e r p, we always protect these sort of classes of tiers of systems, but then it's like, oh, that user's email box didn't get it. Oh, that, you know, that one drive didn't get it. You know, or, or, or whatever it is. You know, the infrastructure behind it all. I forgot to back that up. That to me the blind spots are the scariest part of a ransomware attack. >>And, and if you think about it, some of the most high profile attacks, you know, on the, on the colonial pipeline, they didn't go after the core assets. They went after billing. That's right. But billing brought everything down so they're smart enough to say, right, I'm not gonna take the, the castle head on. Is there is they're that. Exactly. >>And so how do you, I get, I mean you can air gap and do things like that in terms of protecting the, the, the data, the corrupt data. How do you protect the corrupt environment? Like that's, that's a really challenging issue. Is >>It? I don't know. I mean, I'll, I'll you can go second here. I think that what's interesting to me about is that's what cloud's for. You can build as many environments as you want. You only pay for what you use, right? And so you have an opportunity to just reconstruct it. That's why things, everything is code matters. That's why having a cloud partner like Druva matters. So you can just go restore wherever you need to in a totally clean environment. >>So the answer is you gotta do it in the cloud. Yeah. What if it's on prem? >>So if it's on prem, what we see people do is, and, and, and this is where testing and, and where cloud can still be an asset, is you can look and say a lot of those assets I'm running in the data center, I could still recover in the cloud. And so you can go through DR testing and you can start to define what's in your on-prem so that you could make it, you know, so you can make it cloud recoverable. Now, a lot of the people that do that then say, well actually why am I even running this on prem anymore in the first place? I should just move this to the cloud now. But, but, but there are people in that interim step. But, but, but it's really important because you, you're gonna need a clean environment to play in. And it's so hard to have a clean environment set up in a data center cuz it basically means I'm not touching this, I'm just paying for something to sit idle. Whereas cloud, I can spin that up, right? Get a, a cloud foundation suite and, and just again, infrastructures code, spin things up, test it, spin it down. It doesn't cost me money on a daily basis. >>Jason, talk a little bit about how you are using Druva. Why Druva and give us a kind of a landscape of your IT environment with Druva. >>Yeah. You know, so when we first started, you know, we did have a competitor solution and, and, and it was only backing up, you know, we were a startup. It was only backing up our email. And so as you pointed out, the ecosystem really matters because we grew out of email pretty quick as a startup. And we had to have real use cases to protect and the legacy product just wouldn't support us. And so our whole direction, or my direction to my team is back it up wherever it is, you know, go get it. And so we needed somebody in the field, literally in the middle of Nebraska or Iowa to have their laptop backed up. We needed our infrastructure, our data center backed up and we needed our, our SaaS solutions backed up. We needed it all. And so we needed a partner like Druva to help us go get it wherever it's at. >>Talk about the value in, with Druva being cloud native. >>Yeah. To us it's a big deal, right? There's all sorts of products you could go by to go just do endpoint laptop protection or just do SAS backups. For us, the value is in learning one tool and mastering it and then taking it to wherever the data is. To me, we see a lot of value for that because we can have one team focus on one product, get good at it, and drive the value. >>That consolidation theme is big right now, you know, the economic headwinds and so forth. What was the catalyst for you? Was it, is that something you started, you know, years ago? Just it's good practice to do that? What's, >>Well, no, I mean luckily I'm in a very good position as a startup to do define it, you know, but I've been in those legacy organizations where we've got a lot of tech debt and then how do you consolidate your portfolio so that you can gain more value, right? Cause you only get one budget a year, right? And so I'm lucky in, in the learnings I've had in other enterprises to deal with this head on right now as we grow, don't add tech debt, put it in right. Today. >>Talk to us a little bit about the SaaS applications that you're backing up. You know, we, we talk a lot with customers, the shared, the shared responsibility model that a lot of customers aren't aware of. Where are you using that competing solution to protect SaaS applications before driven and talk about Yeah. The, the value in that going, the data protection is our responsibility and not the SA vendor. >>No, absolutely. I mean, and it is funny to go to, you know, it's like Office 365 applications and go to our, our CFO and a leadership and be like, no, we really gotta back it up to a third party. And they're like, but why? >>It's >>In the cloud, right? And so there's a lot of instruction I have to provide to my peers and, and, and my users to help them understand why these things matter. And, and, and it works out really well because we can show value really quick when anything happens. And now we get, I mean, even in SharePoint, people will come to us to restore things when they're fully empowered to do it. But my team's faster. And so we can just get it done for them. And so it's an extra from me, it's an extra SLA or never service level I can provide to my internal customers that, that gives them more faith and trust in my organization. >>How, how are the SEC op teams and the data protection teams, the backup teams, how are they coming together? Is is, is data protection backup just morphing into security? Is it more of an adjacency? What's that dynamic like? >>So I'd say right now, and, and I'll be curious to hear Jason's organization, but certainly what we see broadly is, you know, the, the teams are starting to work together, but I wouldn't say they're merging, right? Because, you know, you think of it in a couple of ways. The first is you've got a production environment and that needs to be secured. And then you've got a protection environment. And that protection environment also has to be secured. So the first conversation for a lot of backup teams is, alright, I need to actually work with the security team to make sure that, that my, my my backup environment, it's air gapped, it's encrypted, it's secured. Then I think the, the then I think you start to see people come together, especially as they go through, say, tabletop exercises for ransomware recovery, where it's, alright, where, where can the backup team add value here? >>Because certainly recovery, that's the basics. But as there log information you can provide, are there detection pieces that you can offer? So, so I think, you know, you start to see a partnership, but, but the reality is, you know, the, the two are still separate, right? Because, you know, my job as a a protection resiliency company is I wanna make sure that when you need your data, it's gonna be there for you. And I certainly want to, to to follow best secure practices and I wanna offer value to the security team, but there's a whole lot of the security ecosystem that I want to plug into. I'm not trying to replace them again. I want to be part of that broader ecosystem. >>So how, how do you guys approach it? Yeah, >>That's interesting. Yeah. So in my organization, we, we are one team and, and not to be too cheesy or you know, whatever, but as Amazon would say, security is job one. And so we treat it as if this is it. And so we never push something into production until we are ready. And ready to us means it's got a security package on it, it's backed up, the users have tested it, we are ready to go. It's not that we're ready just be to provide the service or the thing. It's that we are actually ready to productionize this. And so it's ready for production data and that slows us down in some cases. But that's where DevOps and this idea of just merging everything together into a central, how do we get this done together, has worked out really well for us. So, >>So it's really the DevOps team's responsibility. It's not a separate data protection function. >>Nope. Nope. We have specialists of course, right? Yeah, yeah. Because you need the extra level, the CISSPs and those people Yeah, yeah. To really know what they're doing, but they're just part of the team. Yeah. >>Talk about some of the business outcomes that you're achieving with Druva so far. >>Yeah. The business outcomes for me are, you know, I meet my SLAs that's promising. I can communicate that I feel more secure in the cloud and, and all of my workloads because I can restore it. And, and that to me helps everybody in my organization sleep well, sleep better. We are, we transport a lot of the carbon in a pipeline like Colonial. And so to us, we are, we are potential victims of, of a pipe, a non pipeline group, right? Attacking us, but it's carbon, you know, we're trying to get it outta atmosphere. And so by protecting it, no matter where it is, as long as we've got internet access, we can back it up. That provides tons of value to my team because we have hundreds of people in the field working for us every day who collect data and generate it. >>What would you say to a customer who's maybe on the fence looking at different technologies, why dva? >>You know, I think, you know, do the research in my mind, it'll win if you just do the research, right? I mean, there might be vendors that'll buy you nice dinners or whatever, and those are, those are nice things, but the, the reality is you have to protect your data no matter where it is. If it's in a SaaS application, if it's in a cloud provider, if it's infrastructure, wherever it is, you need it. And if you just go look at the facts, there it is, right? And so I, I'd say be objective. Look at the facts, it'll prove itself. >>Look at the data. There you go. Steven Druva recently announced a data resiliency guarantee with a big whopping financial sum. Talk to us a little bit about that, the value in it for your customers and for prospects, >>Right? So, so basically there's, there's really two parts to this guarantee. The first is, you know, across five different SLAs, and I'll talk about those, you know, if we violate those, the customers can get a payout of up to 10 million, right? So again, putting, putting our money where our mouth is in a pretty large amount. But, but for me, the exciting part, and this is, this is where Jason went, is it's about the SLAs, right? You know, one of Drew's goals is to say, look, we do the job for you, we do the service for you so you can offer that service to your company. And so the SLAs aren't just about ransomware, some of them certainly are, you know, that, that you're going to be able to recover your data in the event of a ransomware attack, that your data won't get exfiltrated as part of a ransomware attack. >>But also things like backup success rates, because as much as recovery matters a lot more than backup, you do need a backup if you're gonna be able to get that recovery done. There's also an SLA to say that, you know, if 10 years down the road you need to recover your data, it's still recoverable, right? So, so that kind of durability piece. And then of course the availability of the service because what's the point of a service if it's not there for you when you need it? And so, so having that breadth of coverage, I think really reflects who Druva is, which is we're doing this job for you, right? We want to make this this service available so you can focus on offering other value inside your business. And >>The insurance underwriters, if they threw holy water on >>That, they, they, they were okay with it. The legal people blessed it, you know, it, you know, the CEO signed off on it, the board of directors. So, you know, it, and it, it's all there in print, it's all there on the web. If you wanna look, you know, make sure, one of the things we wanted to be very clear on is that this isn't just a marketing gimmick that we're, we're putting, that we're putting substance behind it because a lot of these were already in our contracts anyway, because as a SAS vendor, you're signing up for service level agreements anyway. >>Yeah. But most of the service level agreements and SaaS vendors are crap. They're like, you know, hey, you know, if something bad happens, you know, we'll, we'll give you a credit, >>Right? >>For, you know, for when you were down. I mean, it's not, you never get into business impact. I mean, even aws, sorry, I mean, it's true. We're a customer. I read define print, I know what I'm signing up for. But, so that's, >>We read it a lot and we will not, we don't really care about the credits at all. We care about is it their force? Is it a partner? We trust, we fight that every day in our SLAs with our vendors >>In the end, right? I mean this, we are the last line of defense. We are the thing that keeps the business up and running. So if your business, you know, can't get to his data and can't operate, me coming to you and saying, Dave, I've got some credits for you after you, you know, after you declare bankruptcy, it'll be great. Yeah, that's not a win. >>It's no value, >>Not helpful. The goal's gotta be, your business is up and running cuz that's when we're both successful. So, so, so, you know, we view this as we're in it together, right? We wanna make sure your business succeeds. Again, it's not about slight of hand, it's not about, you know, just, just putting fine print in the contract. It's about standing up and delivering. Because if you can't do that, why are we here? Right? The number one thing we hear from our customers is Dr. Just works. And that's the thing I think I'm most proud of is Druva just works. >>So, speaking of Juva, just working, if there's a billboard in Santa Clara near the new offices about Druva, what's, what's the bumper sticker? What's the tagline? >>I, I, I think, I think that's it. I think Druva just works. Keeps your data safe. Simple as that. Safe and secure. Druva works to keep your data safe and secure. >>Saved me. >>Yeah. >>Truva just works. Guys, thanks so much for joining. David, me on the program. Great to have you back on the cube. Thank you. Talking about how you're working together, what Druva is doing to really putting, its its best foot forward. We appreciate your insights and your time. Thank >>You. Thanks guys. It's great to see you guys. Likewise >>The show for our guests and Dave Ante. I'm Lisa Martin, you're watching the Cube, the leader in enterprise and emerging tech coverage.

>> Hello everyone and welcome back to theCUBE, where we're live from Dallas, Texas here at Super computing 2022. I am joined by my cohost David Nicholson. Thank you so much for being here with me and putting up with my trashy jokes all day. >> David: Thanks for having me. >> Yeah. Yes, we are going to be talking about AI this morning and I'm very excited that our guest has has set the stage for us here quite well. Please welcome Andrea Booker. Andrea, thank you so much for being here with us. >> Absolutely. Really excited to be here. >> Savannah: How's your show going so far? >> It's been really cool. I think being able to actually see people in person but also be able to see the latest technologies and and have the live dialogue that connects us in a different way than we have been able to virtually. >> Savannah: Oh yeah. No, it's all, it's all about that human connection and that it is driving towards our first question. So as we were just chit chatting. You said you are excited about making AI real and humanizing that. >> Andrea: Absolutely. >> What does that mean to you? >> So I think when it comes down to artificial intelligence it means so many different things to different people. >> Savannah: Absolutely. >> I was talking to my father the other day for context, he's in his late seventies, right. And I'm like, oh, artificial intelligence, this or that, and he is like, machines taking over the world. Right. >> Savannah: Very much the dark side. >> A little bit Terminator. And I'm like, well, not so much. So that was a fun discussion. And then you flip it to the other side and I'm talking to my 11 year old daughter and she's like, Alexa make sure you know my song preferences. Right. And that's the other very real way in which it's kind of impacting our lives. >> Savannah: Yeah. >> Right. There's so many different use cases that I don't think everyone understands how that resonates. Right. It's the simple things from, you know, recommend Jason Engines when you're on Amazon and it suggests just a little bit more. >> Oh yeah. >> I'm a little bit to you that one, right. To stuff that's more impactful in regards to getting faster diagnoses from your doctors. Right. Such peace of mind being able to actually hear that answer faster know how to go tackle something. >> Savannah: Great point, yeah. >> You know, and, and you know, what's even more interesting is from a business perspective, you know the projections are over the next five years about 90% of customers are going to use AI applications in in some fashion, right. >> Savannah: Wow. >> And the reason why that's interesting is because if you look at it today, only about 15% of of them are doing so. Right. So we're early. So when we're talking growth and the opportunity, it's, it's amazing. >> Yeah. I can, I can imagine. So when you're talking to customers, what are are they excited? Are they nervous? Are you educating them on how to apply Dell technology to advance their AI? Where are they off at because we're so early? >> Yeah well, I think they're figuring it out what it means to them, right? >> Yeah. Because there's so many different customer applications of it, right? You have those in which, you know, are on on the highest end in which that our new XE products are targeting that when they think of it. You know, I I, I like to break it down in this fashion in which artificial intelligence can actually save human lives, right? And this is those extreme workloads that I'm talking about. We actually can develop a Covid vaccine faster, right. Pandemic tracking, you know with global warming that's going on. And we have these extreme weather events with hurricanes and tsunamis and all these things to be able to get advanced notice to people to evacuate, to move. I mean, that's a pretty profound thing. And it is, you know so it could be used in that way to save lives, right? >> Absolutely. >> Which is it's the natural outgrowth of the speeds and feeds discussions that we might have internally. It's, it's like, oh, oh, speed doubled. Okay. Didn't it double last year? Yeah. Doubled last year too. So it's four x now. What does that mean to your point? >> Andrea: Yeah, yeah. >> Savannah: Yeah. >> Being able to deliver faster insight insights that are meaningful within a timeframe when otherwise they wouldn't be meaningful. >> Andrea: Yeah. >> If I tell you, within a two month window whether it's going to rain this weekend, that doesn't help you. In hindsight, we did the calculation and we figured out it's going to be 40 degrees at night last Thursday >> Knowing it was going to completely freeze here in Dallas to our definition in Texas but we prepare better to back to bring clothes. >> We were talking to NASA about that yesterday too. I mean, I think it's, it's must be fascinating for you to see your technology deployed in so many of these different use cases as well. >> Andrea: Absolutely, absolutely. >> It's got to be a part of one of the more >> Andrea: Not all of them are extreme, right? >> Savannah: Yeah. >> There's also examples of, you know natural language processing and what it does for us you know, the fact that it can break down communication barriers because we're global, right? We're all in a global environment. So if you think about conference calls in which we can actually clearly understand each other and what the intent is, and the messaging brings us closer in different ways as well. Which, which is huge, right? You don't want things lost in translation, right? So it, it helps on so many fronts. >> You're familiar with the touring test idea of, of, you know whether or not, you know, the test is if you can't discern within a certain number of questions that you're interacting with an AI versus a real human, then it passes the touring test. I think there should be a natural language processing test where basically I say, fine >> Andrea: You see if people was mad or not. >> You tell me, you tell me. >> I love this idea, David. >> You know? >> Yeah. This is great. >> Okay. AI lady, >> You tell me what I meant. >> Yeah, am I actually okay? >> How far from, that's silly example but how far do you think we are from that? I mean, what, what do you seeing out there in terms of things where you're kind of like, whoa, they did this with technology I'm responsible for, that was impressive. Or have you heard of things that are on the horizon that, you know, again, you, you know they're the big, they're the big issues. >> Yeah. >> But any, anything kind of interesting and little >> I think we're seeing it perfected and tweaked, right? >> Yeah. >> You know, I think going back to my daughter it goes from her screaming at Alexa 'cause she did hear her right the first time to now, oh she understands and modifies, right? Because we're constantly tweaking that technology to have a better experience with it. And it's a continuum, right? The voice to text capabilities, right. You know, I I'd say early on it got most of those words, right Right now it's, it's getting pretty dialed in. Right. >> Savannah: That's a great example. >> So, you know, little things, little things. >> Yeah. I think I, I love the, the this thought of your daughter as the example of training AI. What, what sort of, you get to look into the future quite a bit, I'm sure with your role. >> Andrea: Absolutely. >> Where, what is she going to be controlling next? >> The world. >> The world. >> No, I mean if you think about it just from a generational front, you know technology when I was her age versus what she's experiencing, she lives and breathes it. I mean, that's the generational change. So as these are coming out, you have new folks growing with it that it's so natural that they are so open to adopting it in their common everyday behaviors. Right? >> Savannah: Yeah. >> But they'd they never, over time they learn, oh well how it got there is 'cause of everything we're doing now, right. >> Savannah: Yeah. >> You know, one, one fun example, you know as my dad was like machines are taking over the world is not, not quite right. Even if when you look at manufacturing, there's a difference in using AI to go build a digital simulation of a factory to be able to optimize it and design it right before you're laying the foundation that saves cost, time and money. That's not taking people's jobs in that extreme event. >> Right. >> It's really optimizing for faster outcomes and, and and helping our customers get there which is better for everyone. >> Savannah: Yeah and safer too. I mean, using the factory example, >> Totally safer. >> You're able to model out what a workplace injury might be or what could happen. Or even the ergonomics of how people are using. >> Andrea: Yeah, should it be higher so they don't have to bend over? Right. >> Exactly. >> There's so many fantastic positive ways. >> Yeah so, so for your dad, you know, I mean it's going to help us, it's going to make, it's going to take away when I. Well I'm curious what you think, David when I think about AI, I think it's going to take out a lot of the boring things in life that, that we don't like >> Andrea: Absolutely. Doing. The monotony and the repetitive and let us optimize our creative selves maybe. >> However, some of the boring things are people's jobs. So, so it is, it it it will, it will it will push a transition in our economy in the global economy, in my opinion. That would be painful for some, for some period of time. But overall beneficial, >> Savannah: Yes. But definitely as you know, definitely there will be there will be people who will be disrupted and, you know. >> Savannah: Tech's always kind of done that. >> We No, but we need, I, I think we need to make sure that the digital divide doesn't get so wide that you know that, that people might not be negative, negatively affected. And, but, but I know that like organizations like Dell I believe what you actually see is, >> Andrea: Yeah. >> No, it's, it's elevating people. It's actually taking away >> Andrea: Easier. >> Yeah. It's, it's, it's allowing people to spend their focus on things that are higher level, more interesting tasks. >> Absolutely. >> David: So a net, A net good. But definitely some people disrupted. >> Yes. >> I feel, I feel disrupted. >> I was going to say, are, are we speaking for a friend or for ourselves here today on stage? >> I'm tired of software updates. So maybe if you could, if you could just standardize. So AI and ML. >> Andrea: Yeah. >> People talk about machine learning and, and, and and artificial intelligence. How would you differentiate the two? >> Savannah: Good question. >> It it, it's, it's just the different applications and the different workloads of it, right? Because you actually have artificial intelligence you have machine learning in which the learn it's learning from itself. And then you have like the deep learning in which it's diving deeper in in its execution and, and modeling. And it really depends on the workload applications as long as well as how large the data set is that's feeding into it for those applications. Right. And that really leads into the, we have to make sure we have the versatility in our offerings to be able to meet every dimension of that. Right. You know our XE products that we announced are really targeted for that, those extreme AI HPC workloads. Right. Versus we also have our entire portfolio products that we make sure we have GPU diversity throughout for the other applications that may be more edge centric or telco centric, right? Because AI isn't just these extreme situations it's also at the edge. It's in the cloud, it's in the data center, right? So we want to make sure we have, you know versatility in our offerings and we're really meeting customers where they're at in regards to the implementation and and the AI workloads that they have. >> Savannah: Let's dig in a little bit there. So what should customers expect with the next generation acceleration trends that Dell's addressing in your team? You had three exciting product announcements here >> Andrea: We did, we did. >> Which is very exciting. So you can talk about that a little bit and give us a little peek. >> Sure. So, you know, for, for the most extreme applications we have the XE portfolio that we built upon, right? We already had the XC 85 45 and we've expanded that out in a couple ways. The first of which is our very first XC 96 88 way offering in which we have Nvidia's H 100 as well as 8 100. 'Cause we want choice, right? A choice between performance, power, what really are your needs? >> Savannah: Is that the first time you've combined? >> Andrea: It's the first time we've had an eight way offering. >> Yeah. >> Andrea: But we did so mindful that the technology is emerging so much from a thermal perspective as well as a price and and other influencers that we wanted that choice baked into our next generation of product as we entered the space. >> Savannah: Yeah, yeah. >> The other two products we have were both in the four way SXM and OAM implementation and we really focus on diversifying and not only from vendor partnerships, right. The XC 96 40 is based off Intel Status Center max. We have the XE 86 40 that is going to be in or Nvidia's NB length, their latest H 100. But the key differentiator is we have air cold and we have liquid cold, right? So depending on where you are from that data center journey, I mean, I think one of the common themes you've heard is thermals are going up, performance is going up, TBPs are going up power, right? >> Savannah: Yeah. >> So how do we kind of meet in the middle to be able to accommodate for that? >> Savannah: I think it's incredible how many different types of customers you're able to accommodate. I mean, it's really impressive. I feel lucky we've gotten to see these products you're describing. They're here on the show floor. There's millions of dollars of hardware literally sitting in your booth. >> Andrea: Oh yes. >> Which is casual only >> Pies for you. Yeah. >> Yeah. We were, we were chatting over there yesterday and, and oh, which, which, you know which one of these is more expensive? And the response was, they're both expensive. It was like, okay perfect >> But assume the big one is more. >> David: You mentioned, you mentioned thermals. One of the things I've been fascinated by walking around is all of the different liquid cooling solutions. >> Andrea: Yeah. >> And it's almost hysterical. You look, you look inside, it looks like something from it's like, what is, what is this a radiator system for a 19th century building? >> Savannah: Super industrial? >> Because it looks like Yeah, yeah, exactly. Exactly, exactly. It's exactly the way to describe it. But just the idea that you're pumping all of this liquid over this, over this very, very valuable circuitry. A lot of the pitches have to do with, you know this is how we prevent disasters from happening based on the cooling methods. >> Savannah: Quite literally >> How, I mean, you look at the power requirements of a single rack in a data center, and it's staggering. We've talked about this a lot. >> Savannah: Yeah. >> People who aren't kind of EV you know electric vehicle nerds don't appreciate just how much power 90 kilowatts of power is for an individual rack and how much heat that can generate. >> Andrea: Absolutely. >> So Dell's, Dell's view on this is air cooled water cooled figure it out fit for for function. >> Andrea: Optionality, optionality, right? Because our customers are a complete diverse set, right? You have those in which they're in a data center 10 to 15 kilowatt racks, right? You're not going to plum a liquid cool power hungry or air power hungry thing in there, right? You might get one of these systems in, in that kind of rack you know, architecture, but then you have the middle ground the 50 to 60 is a little bit of choice. And then the super extreme, that's where liquid cooling makes sense to really get optimized and have the best density and, and the most servers in that solution. So that's why it really depends, and that's why we're taking that approach of diversity, of not only vendors and, and choice but also implementation and ways to be able to address that. >> So I think, again, again, I'm, you know electric vehicle nerd. >> Yeah. >> It's hysterical when you, when you mention a 15 kilowatt rack at kind of flippantly, people don't realize that's way more power than the average house is consuming. >> Andrea: Yeah, yeah >> So it's like your entire house is likely more like five kilowatts on a given day, you know, air conditioning. >> Andrea: Maybe you have still have solar panel. >> In Austin, I'm sorry >> California, Austin >> But, but, but yeah, it's, it's staggering amounts of power staggering amounts of heat. There are very real problems that you guys are are solving for to drive all of these top line value >> Andrea: Yeah. >> Propositions. It's super interesting. >> Savannah: It is super interesting. All right, Andrea, last question. >> Yes. Yes. >> Dell has been lucky to have you for the last decade. What is the most exciting part about you for the next decade of your Dell career given the exciting stuff that you get to work on. >> I think, you know, really working on what's coming our way and working with my team on that is is just amazing. You know, I can't say it enough from a Dell perspective I have the best team. I work with the most, the smartest people which creates such a fun environment, right? So then when we're looking at all this optionality and and the different technologies and, and, and you know partners we work with, you know, it's that coming together and figuring out what's that best solution and then bringing our customers along that journey. That kind of makes it fun dynamic that over the next 10 years, I think you're going to see fantastic things. >> David: So I, before, before we close, I have to say that's awesome because this event is also a recruiting event where some of these really really smarts students that are surrounding us. There were some sirens going off. They're having competitions back here. >> Savannah: Yeah, yeah, yeah. >> So, so when they hear that. >> Andrea: Where you want to be. >> David: That's exactly right. That's exactly right. >> Savannah: Well played. >> David: That's exactly right. >> Savannah: Well played. >> Have fun. Come on over. >> Well, you've certainly proven that to us. Andrea, thank you so much for being with us This was such a treat. David Nicholson, thank you for being here with me and thank you for tuning in to theCUBE a lot from Dallas, Texas. We are all things HPC and super computing this week. My name's Savannah Peterson and we'll see you soon. >> Andrea: Awesome.

>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging 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)

(light upbeat music) (mouse clicks) >> Hey, everyone. Welcome back to the program. Lisa Martin here. I've got two guests joining me. Please welcome back to The Cube, Paula Hansen, the chief revenue officer and president at Alteryx. And Jacqui Van der Leij - Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the program. >> Thank you, Lisa. >> Thank you, Lisa. >> It's great to be here. >> Yeah, Paula. We're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation. With analytics as they talked about at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform but ultimately, we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >> Excellent. Sounds like a very strategic program. We're going to unpack that. Jacqui let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How, Jacqui, did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is just when we started out was, is that, you know, our, especially in finance they became spreadsheet professionals, instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no, we're not independent. You couldn't move forward. You would've been dependent on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. And finally, we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks because you always have, not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's our people that need to actually really embrace it and making that accessible for them, I would say is definitely not per se, a roadblock but basically some, a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula will start with you, and then Jacqui will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven? Paula? >> Yes. Well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting, all of our key performance metrics for business planning across our audit function to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter so it's really remained across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases. And so one of the other things that we've seen many companies do is to gamify that process to build a game that brings users into the experience for training and to work with each other, to problem solve, and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of you know, getting people excited about it but it's also understanding that this is a journey. And everybody is the different place in their journey. You have folks that's already really advanced who has done this every day, and then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the initial destination. I say initially, because I believe the journey is never really complete. What we have done is that we decided to invest in a... We build a proof of concepts and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom. And we told people, "Listen, we're going to teach you this tool, super easy. And let's just see what you can do." We ended up having 70 entries. We had only three weeks. So, and these are people that has... They do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon. From the 70 entries with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was people had a proof of concept, they knew that it worked, and they overcame that initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula will start with you. >> Absolutely. And Jacqui says it so well, which is that it really is a journey that organizations are on. And we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay, and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED, we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED just made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kicked that momentum from the hackathon. Like we don't lose that excitement, right? So we just launched a program called eBay Masterminds. And what it basically is, it's an inclusive innovation initiative, where we firmly believe that innovation is for upscaling for all analytics role. So it doesn't matter your background, doesn't matter which function you are in, come and participate in this, where we really focus on innovation, introducing new technologies and upscaling our people. We are... Apart from that, we also said... Well, we should just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter Alteryx. And we're working with actually, we're working with SparkED and they're helping us develop that program. And we really hope that, let us say, by the end of the year have a pilot and then also next, was hoping to roll it out in multiple locations, in multiple countries, and really, really focus on that whole concept of analytics role. >> Analytics role, sounds like Alteryx and eBay have a great synergistic relationship there, that is jointly aimed at, especially, kind of, going down the stuff and getting people when they're younger interested and understanding how they can be empowered with data across any industry. Paula let's go back to you. You were recently on The Cube's Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world? How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last, I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. (Paula clears throat) So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud, is to empower all of those people in every job function regardless of their skillset. As Jacqui pointed out from people that would, you know are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud and it operates in a multi-cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skills gap as you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues. And what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we started about getting excited about things when it comes to analytics, I can go on all day but I'll keep it short and sweet for you. I do think we are on the topic full of data scientists. And I really feel that that is your next step, for us anyways, it's just that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx would just release the AI/ML solution, allowing, you know, folks to not have a data scientist program but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses quite a few. And right now, through our mastermind program we're actually running a four-months program for all skill levels. Teaching them AI/ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services, we have even some of our engineers, are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all was able to develop a solution where, you know, there is a checkout feedback, checkout functionality on the eBay site, where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in. And now instead of us or somebody going to the bay to try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. And it's a beautiful tool, and I'm very impressed when you saw the demo and they've been developing that further. >> That sounds fantastic. And I think just the one word that keeps coming to mind and we've said this a number of times in the program today is, empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you >> Thank you, Lisa. >> Thank you so much. (light upbeat music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four E's that's, everyone, everything, everywhere and easy analytics. Those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics. Not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com, and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring The Cube. For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (light upbeat music)

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

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

>>Hey everyone. Welcome back to the program. Lisa Martin here, I've got two guests joining me, please. Welcome back to the cube. Paula Hansen, the chief revenue officer and president at Al alters and Jackie Vander lake grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an alter Ricks is helping eBay innovate with analytics. Ladies. Welcome. It's great to have you both on the program. >>Thank you, Lisa. It's great to be here. >>Yeah, Paula, we're gonna start with you in this program. We've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation with analytics. As they talked about at the forefront of software investments, how's alters helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course, with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills, assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics, maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic program. We're gonna unpack that Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jackie did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >>So I think the main thing for us is just when we started out was is that, you know, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes, >>Starting with people is really critical. Jackie, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and, and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that, you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And we, there was no, we're not independent. You couldn't move forward. You would've opinion on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. >>And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy? And that is not so daunting on somebody who's brand new to the field. And I would, I would call those out as your, as your major roadblocks, because you always have not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's, it's our people that need to actually really embrace it and, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically some, a block you wanna be able to move. >>It's really all about putting people. First question for both of you and Paula will start with you. And then Jackie will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven Paula. >>Yes. Well, we leverage our platform across all of our business functions here at Altrix and just like Jackie explained it, eBay finances is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a, a key sponsor for using our own technology. We use Altrix for forecasting, all of our key performance metrics for business planning across our audit function, to help with compliance and regulatory requirements tax, and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? >>And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>Yeah, I think it means to what Paula has said in terms of, you know, you know, getting people excited about it, but it's also understanding that this is a journey and everybody's the different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you put, get everybody in their different phases to get to the, the initial destination. I say initially, because I believe the journey is never really complete. What we have done is, is that we decided to invest in an Ebola group of concept. And we got our CFO to sponsor a hackathon. We opened it up to everybody in finance, in the middle of the pandemic. So everybody was on zoom and we had, and we told people, listen, we're gonna teach you this tool super easy. >>And let's just see what you can do. We ended up having 70 entries. We had only three weeks. So, and these are people that has N that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 inches with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was, people had a proof of concept. They, they knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up. Now >>That's fantastic. And the, the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome. Sometimes the, the cultural barriers is key. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you are empowering the next generation of data workers, Paula will start with you? >>Absolutely. And, and Jackie says it so well, which is that it really is a journey that organizations are on. And, and we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Altrix to help address this skillset gap on a global level is through a program that we call sparked, which is essentially a, no-cost a no cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to, to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked. We started last may, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're gonna continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people within necessary analytics skills to solve all the problems that data can help solve. >>So spark has made a really big impact in such a short time period. And it's gonna be fun to watch the progress of that. Jackie, let's go over to you now talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we basically wanted to make sure that we keep that momentum from the hackathon that we don't lose that excitement, right? So we just launched a program called Ebo masterminds. And what it basically is, it's an inclusive innovation initiative where we firmly believe that innovation is all up scaling for all analytics for. So it doesn't matter. Your background doesn't matter which function you are in, come and participate in, in this where we really focus on innovation, introducing new technologies and upskilling our people. We are apart from that, we also say, well, we should just keep it to inside eBay. We, we have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter alter. And we're working with actually, we're working with spark and they're helping us develop that program. And we really hope that as a say, by the end of the year, have a pilot and then also make you, so we roll it out in multiple locations in multiple countries and really, really focus on, on that whole concept of analytics, role >>Analytics for all sounds like ultra and eBay have a great synergistic relationship there that is jointly aimed at, especially kind of going down the staff and getting people when they're younger, interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the Cube's super cloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating. What is by default a multi-cloud world? How does the alters analytics cloud platform enable CIOs to democratize analytics across their organization? >>Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs with business leaders is that they're integrating data analysis and the skill of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Altrics analytics cloud is to empower all of those people in every job function, regardless of their skillset. As Jackie pointed out from people that would, you know, are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Altrics analytics cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and drive real business outcomes. As a result of unlocking the potential of data, >>As well as really re lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the, the beauty of what Altrics is enabling. And, and eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where alters fits in on as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >>When we start about getting excited about things, when it comes to analytics, I can go on all day, but I I'll keep it short and sweet for you. I do think we are on the topic full of, of, of data scientists. And I really feel that that is your next step for us anyways, is that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's, it's something completely different. And it's something that, that is in everybody to a certain extent. So again, partner with three X would just released the AI ML solution, allowing, you know, folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with alters and we, we purchased a license, this quite a few. And right now through our mastermind program, we're actually running a four months program for all skill levels, teaching, teaching them AI ML and machine learning and how they can build their own models. >>We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I wanna give you a quick example of, of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where, you know, there is a checkout feedback checkout functionality on the eBay site where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. >>And it's a beautiful tool and very impressed. You saw the demo and they developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with, with varying degrees of skill level, going down to the high school level, really exciting, we'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I wanna thank you so much for joining me on the program today and talking about how alters and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>As you heard over the course of our program organizations, where more people are using analytics who have the deeper capabilities in each of the four E's, that's, everyone, everything everywhere and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We wanna thank you so much for watching the program today. Remember you can find all of the content on the cue.net. You can find all of the news from today on Silicon angle.com and of course, alter.com. We also wanna thank alt alters for making this program possible and for sponsored in the queue for all of my guests. I'm Lisa Martin. We wanna thank you for watching and bye for now.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, 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 winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>>Hey, everyone, welcome back to the programme. Lisa Martin here. I've got two guests joining me. Please welcome back to the Q. Paula Hanson, the chief Revenue officer and president at all tricks. And Jackie Vanderlei Grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an all tricks is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the programme. >>Thank you, Lisa. Not great to be >>here. >>Yeah, Paula, we're gonna start with you in this programme. We've heard from Jason Klein. We've heard from Allan Jacobsen. They talked about the need to democratise analytics across any organisation to really drive innovation with analytics as they talked about at the forefront of software investments. House all tricks, helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. Absolutely is about our customers success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform. But ultimately we help our customers to create a culture of data literacy and analytics from the top of the organisation starting with the C suite and we partner with our customers to build their road maps for scaling that culture of analytics through things like enablement programmes, skills assessments, hackathons, uh, setting up centres of excellence to help their organisation scale and drive governance of this, uh, analytics capability across the Enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practises so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic programme. We're gonna unpack that, Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the I. D. C report that showed that 93% of organisations are not utilising the analytic skills of their employees. But then there's eBay. How Jackie did eBay become one of the 7% of organisations who's really maturing and how are you using analytics across the organisation at bay? >>So I think the main thing for us is when we started out was is that you know our especially in finance. They became spreadsheet professionals instead of the things that we really want our influence to add value to. And we realised we have to address that. And we also knew we couldn't wait for all our data to be centralised until we actually start using the data or start automating and be more effective. Um, so ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >>Starting with people is really critical jacket continuing with you. What was in the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think you know, Eva is a very data driven company. We have a lot of data. I think we are 27 years around this year. So we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them, um, to move forward. The other thing is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no we're not independent. You couldn't move forward. You're dependent on somebody else's roadmap to get to data to get the information you want it. So really finding something that everybody could access analytics or access data. And finally we have to realise, is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would I would call those out as your as your major roadblocks, because you always have always. But most of the times you have support from the top. In our case we have. But in the end of the day, it's it's our people that need to actually really embrace it and making that accessible for them. I would say it's not to say a road block a block you want to be able to do. >>It's really all about putting people first question for both of you and Paula will start with you and then Jackie will go to you. I think the message in this programme that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organisations are empowering people, those in the organisation that may not have technical expertise to be able to leverage data so that they can actually be data driven colour. >>Yes, well, we leverage our platform across all of our business functions here at all tricks. And just like Jackie explained that eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data, uh, flowing through our enterprise, and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Ruben has been a key sponsor for using our own technology. We use all tricks for forecasting all of our key performance metrics for business planning across our audit function, uh, to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to How do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other to problem solve and, along the way, maybe earn badges, depending on the capabilities and trainings that they take and just have a little healthy competition, Uh, as an employee based around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable that they feel supportive, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>I think it means to what Paula has said in terms of, you know, getting people excited about it. But it's also understanding that this is a journey and everybody is the different place in their journey. You have folks that's already really advanced. Who's done this every day. And then you have really some folks that this is brand new and, um, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the the initial destination. And I say initial because I believe the journey is never really complete. Um, what we have done is that we decided to invest in a group of concept when we got our CFO to sponsor a hackathon. Um, we open it up to everybody in finance, um, in the middle of the pandemic. So everybody was on Zoom, um, and we had and we told people, Listen, we're gonna teach you this tool. It's super easy, and let's just see what you can do. We ended up having 70 injuries. We had only three weeks. So these are people that that do not have a background. They are not engineers and not data scientists and we ended up with 25,000 our savings at the end of the hackathon. Um, from the 70 countries with people that I've never, ever done anything like this before. And there you have the results. And they just went from there because people had a proof of concept. They knew that it worked and they overcame the initial barrier of change. Um, and that's what we are seeing things really, really picking up now >>that's fantastic. And the business outcome that you mentioned that the business impact is massive, helping folks get that confidence to be able to overcome. Sometimes the cultural barriers is key there. I think another thing that this programme has really highlighted is there is a clear demand for data literacy in the job market, regardless of organisation. Can each of you share more about how your empowering the next generation of data workers Paula will start with you? >>Absolutely. And Jackie says it so well, which is that it really is a journey that organisations are on and we, as people in society, are on in terms of up skilling our capabilities. Uh, so one of the things that we're doing here at all tricks to help address the skill set gap on a global level is through a programme that we call Sparked, which is essentially a no cost analyst education programme that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this programme is really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises when we close gap and empower more people with the necessary analytic skills to solve all the problems that data can help solve. >>So >>I just made a really big impact in such a short time period is gonna be fun to watch the progress of that. Jackie, let's go over to you now Talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we definitely wanted to make sure that we kept implemented from the hackathon that we don't lose that excitement life. So we just launched a programme for evil masterminds and what it basically is. It's an inclusive innovation initiative where we firmly believe that innovation is all upscaling for all analytics role. So it doesn't matter. Your background doesn't matter which function you are in. Come and participate in this where we really focus on innovation, introducing these technologies and upscaling of people. Um, we are apart from that. We also said, Well, we should just keep it to inside the way we have to share this innovation with the community. So we are actually working on developing an analytics high school programme which we hope to pilot by the end of this year. We will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, But also, um, how to use all tricks and we're working with Actually, we're working with spark and they're helping us develop that programme. And we really hope that it is said by the end of the year, have a pilot and then also makes you must have been rolled out in multiple locations in multiple countries and really, really, uh, focused on that whole concept of analytic school >>analytics. Girl sounds like ultra and everybody have a great synergistic relationship there that is jointly aimed at especially kind of going down the stock and getting people when they're younger, interested and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the cubes Super Cloud event just a couple of weeks ago and you talked about the challenges the companies are facing as they are navigating what is by default, a multi cloud world. How does the all tricks analytics cloud platform enable CEO s to democratise analytics across their organisation? >>Yes, business leaders and CEO s across all industries are realising that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organisations. Last I checked, there was two million data scientists in the world. So that's, uh, woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CEO s with business leaders is that they are integrating data analysis and the skill set of data analysis into virtually every job function. Uh, and that is what we think of when we think of analytics for all. And so our mission with all tricks analytics cloud is to empower all of those people in every job function, regardless of their skill set, as Jackie pointed out, from people that would are just getting started all the way to the most sophisticated of technical users. Um, every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organisations. So that's our goal with all tricks, analytics cloud and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyse and report out so that we can break down data silos across the Enterprise and Dr Real Business Outcomes. As a result, of unlocking the potential of data >>as well as really listening that skills gap. As you were saying, There's only two million data scientists. You don't need to be a data scientist. That's the beauty of what all tricks is enabling. And eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where all tricks fits in as that analytics maturity journey continues. And what are some of the things that you're most excited about as analytics truly gets democratised across eBay >>when we start about getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. Um, I do think we're on the topic full of data scientists, and I really feel that that is your next step for us, anyway. Is that how do we get folks to not see data scientist as this big thing like a rocket scientist it's something completely different and it's something that is in everybody in a certain extent. So, um, game partnering with all tricks to just release uh, ai ml um, solution allowing. You know, folks do not have a data scientist programme but actually build models and be able to solve problems that way. So we have engaged with all turrets and we purchase the licence is quite a few. And right now, through our masterminds programme, we're actually running a four months programme. Um, for all skill levels, um, teaching them ai ml and machine learning and how they can build their own models. Um, we are really excited about that. We have over 50 participants without the background from all over the organisation. We have members from our customer services. We have even some of our engineers are actually participating in the programme will just kick it off. And I really believe that that is our next step. Um, I want to give you a quick example of the beauty of this is where we actually, um, just allow people to go out and think about ideas and come up with things and one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution. Where, um, you know there is a checkout feedback checkout functionality on the eBay side, There's sellers or buyers can pervade them at information. And she built a model to be able to determine what relates to tax specific what is the type of problem and even predict how that problem can be solved before we as human, even stepped in. And now, instead of us or somebody going to debate and try to figure out what's going on there, we can focus on fixing their versus, um, actually just reading through things and not adding any value and its a beautiful tool. And I'm very impressed when we saw the demo and they've been developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind. And we've said this a number of times in the programme. Today's empowerment, what you're actually really doing to truly empower people across the organisation with with varying degrees of skill level, going down to the high school level really exciting. We'll have so stay tuned to see what some of the great things are that come from this continued partnership? Ladies, I wanna thank you so much for joining me on the programme today and talking about how all tricks and eBay are really partnering together to democratise analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>Thank you so much.

>>Welcome back everyone to the cubes coverage of VM wear Explorer, 2022 formerly VM world. The Cube's 12th year covering the annual conference. I'm Jennifer Daveon. We got Jason Bloomberg here. Who's a Silicon angle contributor guest author, president of inte analyst firm. Great to see you, Jason. Thanks for coming on the queue. >>Yeah, it's great to be here. Thanks a lot. >>And thanks for contributing to Silicon angle. We really appreciate your articles and, and so does the audience, so thanks for that. >>Very good. We're happy >>To help. All right. So I gotta ask you, okay. We've been here on the desk. We haven't had a chance to really scour the landscape here at Moscone. What's going, what's your take on what's going on with VMware Explorer, not world. Yeah. Gotta see the name change. You got the overhang of the, the cloud Broadcom, which from us, it seems like it's energized people like, like shocked to the system something's gonna happen. What's your take. >>Yeah, something's definitely going to happen. Well, I've been struggling with VMware's messaging, you know, how they're messaging to the market. They seem to be downplaying cloud native computing in favor of multi-cloud, which is really quite different from the Tansu centric messaging from a year or two ago. So Tansu is still obviously part of the story, but it's really, they're relegating the cloud native story to an architectural pattern, which it is, but I believe it's much more than that. It's really more of a paradigm shift in how organizations implement it. Broadly speaking, where virtualization is part of the cloud native story, but VMware is making cloud native part of the virtualization story. Do so >>Do you think that's the, the mischaracterization of cloud native or a bad strategy or both? >>Well, I think they're missing an opportunity, right? I think they're missing an opportunity to be a cloud native leader. They're well positioned to do that with Tansu and where the technology was going and the technology is still there. Right? It's not that that >>They're just downplaying it. >>They're just downplaying it. Right. So >>As, as they were security too, they didn't really pump up security at >>All. Yeah. And you know, vSphere is still gonna be based on Kubernetes. So it's, they're going to be cloud native in terms of Kubernetes support across their product line. Anyway. So, but they're, they're really focusing on multi-cloud and betting the farm on multi-cloud and that ties to the change of the name of the conference. Although it's hard to see really how they're connecting the dots. Right. >>It's a bridge you can't cross, you can't see that bridge crossing what you're saying. Yeah. I mean, I thought that was a clever way of saying, oh, we're exploring new frontiers, which is kinda like, we don't really know what it is >>Yet. Yeah. Yeah. I think the, the term Explorer was probably concocted by a committee where, you know, they eliminated all the more interesting names and that was the one that was left. But, you know, Raghu explained that that Explorer is supposed to expand the audience for the conference beyond the VMware customer to this broader multi-cloud audience. But it's hard to say whether you >>Think it worked. Was there people that you recognize here or identified as a new audience? >>I don't think so. Not, not at this show, but over time, they're hoping to have this broader audience now where it's a multi-cloud audience where it's more than just VMware. It's more than just individual clouds, you know, we'll see if that works. >>You heard the cl the cloud chaos. Right. Do you, do you think they're, multi-cloud cross cloud services is a solution looking for a problem or is the problem real? Is there a market there? >>Oh, oh, the cloud chaos. That's a real problem. Right? Multi-cloud is, is a reality. Many organizations are leveraging different clouds for different reasons. And as a result, you have management security, other issues, which lead to this chaos challenge. So the, the problem is real aria. If they can get it up and running and, you know, straightened out, it's gonna be a great solution, but there are other products on the market that are more mature and more well integrated than aria. So they're going to, you know, have to compete, but VMware is very good at that. So, you know, I don't, I don't count the outing. Who >>Do you see as the competition lay out the horses on the track from your perspective? >>Well, you know, there's, there's a lot of different companies. I, I don't wanna mention any particular ones cuz, cuz I don't want to, you know, favor certain ones over others cuz then I get into trouble. But there's a, a lot of companies that >>Okay, I will. So you got a red hat with, you got obvious ones, Cisco, Cisco, I guess is Ashi Corp plays a role? Well, >>Cisco's been talking about this, >>Anybody we missed. >>Well, there's a number of smaller players, including some of the exhibitors at the, at the show that are putting together this, you know, I guess cloud native control plane that covers more than just a single cloud or cover on premises of virtualization as well as multiple clouds. And that's sort of the big challenge, right? This control plane. How do we come up with a way of managing all of this, heterogeneous it in a unified way that meets the business need and allows the technology organization, both it and the application development folks to move quickly and to do what they need to do to meet business needs. Right? So difficult for large organizations to get out of their own way and achieve that, you know, level of speed and scalability that, that, that technology promises. But they're organizationally challenged to, >>To accomplish. I think I've always looked at multi-cloud as a reality. I do see that as a situational analysis on the landscape. Yeah, I got Azure because I got Microsoft in my enterprise and they converted everything to the cloud. And so I didn't really change that. I got Amazon cause that's from almost my action is, and I gotta use Google cloud for some AI stuff. Right. All good. Right. I mean that's not really spanning anything. There's no ring. It's not really, it's like point solutions within the ecosystem, but it's interesting to see how people are globbing onto multi-cloud because to me it feels like a broken strategy trying to get straightened out. Right. Like, you know, multi-cloud groping from multi-cloud it feels that way. And, and that makes a lot of sense cuz if you're not on the right side of this historic shift right now, you're gonna be dead. >>So which side of the street do you wanna be on? I think it's becoming clear. I think the good news is this year. It's like, if you're on this side of the street, you're gonna be, be alive. Yeah. And this side of the street, not so much. So, you know, that's cloud native obviously hybrid steady state mul how multi-cloud shakes out. I don't think the market's ready personally in terms of true multi-cloud I think it's, it's an opportunity to have the conversation. That's why we're having the super cloud narrative. Cause it's a lit more attention getting, but it focuses on, it has to do something specific. Right? It can't be vaporware. The market won't tolerate vaporware and the new cloud architecture, at least that's my opinion. What's your reaction? Yeah. >>Well the, well you're quite right that a lot of the multiple cloud scenarios involve, you know, picking and choosing the various capabilities each of the cloud provider pro offers. Right? So you want TensorFlow, you have a little bit of Google and you want Amazon for something, but then Amazon's too expensive for something else. So you go with a Azure for that or you have Microsoft 365 as well as Amazon. Right? So you're, that's sort of a multi-cloud right there. But I think the more strategic question is organizations who are combining clouds for more architectural reasons. So for example, you know, back backup or failover or data sovereignty issues, right, where you, you can go into a single cloud and say, well, I want, you know, different data and different regions, but they may a, a particular cloud might not have all the answers for you. So you may say, okay, well I want, I may one of the big clouds or there's specialty cloud providers that focus on data sovereignty solutions for particular markets. And, and that might be part of the mix, right? Isn't necessarily all the big clouds. >>I think that's an interesting observation. Cause when you look at, you know, hybrid, right. When you really dig into a lot of the hybrid was Dr. Right? Yeah. Well, we got, we're gonna use the cloud for backup. And that, and that, what you're saying is multi-cloud could be sort of a similar dynamic, >>The low-head fruit, >>Which is fine, which is not that interesting. >>It's the low hanging fruit though. It's the easy, it's that risk free? I won't say risk free, but it's the easiest way not to get killed, >>But there's a translate into just sort of more interesting and lucrative and monetizable opportunities. You know, it's kind of a big leap to go from Dr. To actually building new applications that cross clouds and delivering new monetization value on top of data and you know, this nerve. >>Yeah. Whether that would be the best way to build such applications, the jury's still out. Why would you actually want to do well? >>I was gonna ask you, is there an advantage? We talked to Mariana, Tess, who's, you know, she's CTO of into it now of course, into it's a, you know, different kind of application, but she's like, yeah, we kinda looked hard at that multiple cloud thing. We found it too complex. And so we just picked one cloud, you know, in, for kind of the same thing. So, you know, is there an advantage now, the one advantage John, you pointed this out is if I run on Microsoft, I'll make more money. If I run on Amazon and you know, they'll, they'll help me sell. So, so that's a business justification, but is there a technical reason to do it? You know, global presence, there >>Could be technical reason not to do it either too. So >>There's more because of complexity. >>You mean? Well, and or technical debt on some services might not be there at this point. I mean the puzzle pieces gotta be there, assume that all clouds have have the pieces. Right. Then it's a matter of composability. I think E AJ who came on AJ Patel who runs modern applications development would agree with your assessment of cloud native being probably the driving front car on this messaging, because that's the issue like once you have the, everything there, then you're composing, it's the orchestra model, Dave. It's like, okay, we got everything here. How do I stitch it together? Not so much coding, writing code, cuz you got everything in building blocks and patterns and, and recipes. >>Yeah. And that's really what VMware has in mind when they talk about multi-cloud right? From VMware's perspective, you can put their virtual machine technology in any cloud. So if you, if you do that and you put it in multiple clouds, then you have, you know, this common, familiar environment, right. It's VMware everywhere. Doesn't really matter which cloud it's in because you get all the goodness that VMware has and you have the expertise on staff. And so now you have, you know, the workload portability across clouds, which can give you added benefits. But one of the straw men of this argument is that price arbitrage, right. I'm gonna, you know, put workloads in Amazon if it's cheaper. But if then if Amazon, you know, Azure has a different pricing structure for something I'm doing, then maybe I'll, I'll move a workload over there to get better pricing. That's difficult to implement in practice. Right. That's so that's that while people like to talk about that, yeah. I'm gonna optimize my cost by moving workloads across clouds, the practicalities at this point, make it difficult. Yeah. But with, if you have VMware, any your clouds, it may be more straightforward, but you still might not do it in order to save money on a particular cloud bill. >>It still, people don't want data. They really, really don't want to move >>Data. This audience does not want do it. I mean, if you look at the evolution, this customer base, even their, their affinity towards cloud native that's years in the making just to good put it perspective. Yeah. So I like how VMware's reality is on crawl, walk, run their clients, no matter what they want 'em to do, you can't make 'em run. And when they're still in diapers right. Or instill in the crib. Right. So you gotta get the customers in a mode of saying, I can see how VMware could operate that. I know and know how to run in an environment because the people who come through this show, they're like teams, it's like an offsite meeting, meets a conference and it's institutionalized for 15 plus years of main enterprise workload management. So I like, that's just not going away. So okay. Given that, how do you connect to the next thing? >>Well, I think the, the missing piece of the puzzle is, is the edge, right? Because it's not just about connecting one hyperscaler to another hyperscaler or even to on-premises or a private cloud, it's also the edge, the edge computing and the edge computing data center requirements. Right. Because you have, you could have an edge data center in a, a phone tower or a point of presence, a telco point of presence, which are those nondescript buildings, every town has. Right? Yeah, yeah. Yeah. And you know, we have that >>Little colo that no one knows about, >>Right, exactly. That, you know, used to be your DSL end point. And now it's just a mini data center for the cloud, or it could be the, you know, the factory computer room or computer room in a retailer. You know, every retailer has that computer room in the modern retails target home Depot. They will have thousands of these little mini cloud data centers they're handling their, their point of sale systems, their, you know, local wifi and all these other local systems. That's, that's where the interesting part of this cloud story is going because that is inherently heterogeneous inherently mixed in terms of the hardware requirements, the software requirements and how you're going to build applications to support that, including AI based applications, which are sort of the, one of the areas of major innovation today is how are we going to do AI on the edge and why would we do it? And there's huge, huge opportunity to >>Well, real time referencing at the edge. Exactly. Absolutely. With all the data. My, my question is, is, is, is the cloud gonna be part of that? Or is the edge gonna actually bring new architectures and new economics that completely disrupt the, the economics that we've known in the cloud and in the data center? >>Well, this for hardware matters. If form factor matters, you can put a data center, the size of four, you know, four U boxes and then you're done >>Nice. I, >>I think it's a semantic question. It's something for the marketers to come up with the right jargon for is yeah. Is the edge part of the cloud, is the cloud part of the edge? Are we gonna come up with a new term, super cloud HyperCloud? >>Yeah. >>Wonder woman cloud, who knows? Yeah. But what, what >>Covers everything, but what might not be semantic is the, I, I come back to the Silicon that inside the, you know, apple max, the M one M two M two ultras, the, what Tesla's doing with NPUs, what you're seeing, you know, in, in, in arm based innovations could completely change the economics of computing, the security model. >>As we say, with the AJ >>Power consumption, >>Cloud's the hardware middleware. And then you got the application is the business everything's completely technology. The business is the app. I >>Mean we're 15 years into the cloud. You know, it's like every 15 years something gets blown up. >>We have two minutes left Jason. So I want to get into what you're working on for when your firm, you had a great, great traction, great practice over there. But before that, what's the, what's your scorecard on the event? How would you, what, what would be your constructive analysis? Positive, good, bad, ugly for VMwares team around this event. What'd they get right? What'd they need to work on >>Well as a smaller event, right? So about one third, the size of previous worlds. I mean, it's, it's, it's been a reasonably well run event for a smaller event. I, you know, in terms of the logistics and everything everything's handled well, I think their market messaging, they need to sort of revisit, but in terms of the ecosystem, you know, I think the ecosystem is, is, is, is doing well. You know, met with a number of the exhibitors over the last few days. And I think there's a lot of, a lot of positive things going on there. >>They see a wave coming and that's cloud native in your mind. >>Well, some of them are talking about cloud native. Some of them aren't, it's a variety of different >>Potentially you're talking where they are in this dag are on the hardware. Okay, cool. What's going on with your research? Tell us what you're focused on right now. What are you digging into? What's going on? Well, >>Cloud native, obviously a big part of what we do, but cybersecurity as well, mainframe modernization, believe it or not. It's a hot topic. DevOps continues to be a hot topic. So a variety of different things. And I'll be writing an article for Silicon angle on this conference. So highlights from the show. Great. Focusing on not just the VMware story, but some of the hot spots among the exhibitors. >>And what's your take on the whole crypto defi world. That's emerging. >>It's all a scam hundred >>Percent. All right. We're now back to enterprise. >>Wait a minute. Hold on. >>We're out of time. >>Gotta go. >>We'll make that a virtual, there are >>A lot of scams. >>I'll admit that you gotta, it's a lot of cool stuff. You gotta get through the underbelly that grows the old bolt. >>You hear kit earlier. He's like, yeah. Well, forget about crypto. Let's talk blockchain, but I'm like, no, let's talk crypto. >>Yeah. All good stuff, Jason. Thanks for coming on the cube. Thanks for spending time. I know you've been busy in meetings and thanks for coming back. Yeah. Happy to help. All right. We're wrapping up day two. I'm Jeff David ante cube coverage. Two sets three days live coverage, 12th year covering VMware's user conference called explore now was formerly VM world onto the next level. That's what it's all about. Just the cube signing off for day two. Thanks for watching.

(upbeat music) >> Welcome back to San Francisco, "theCUBE" is live, our day two coverage of VMware Explore 2022 continues. Lisa Martin with Dave Nicholson. Dave and I are pleased to welcome Jason Collier, principal member of technical staff at AMD to the program. Jason, it's great to have you. >> Thank you, it's great to be here. >> So what's going on at AMD? I hear you have some juicy stuff to talk about. >> Oh, we've got a ton of juicy stuff to talk about. Clearly the Project Monterey announcement was big for us, so we've got that to talk about. Another thing that I really wanted to talk about was a tool that we created and we call it, it's the VMware Architecture Migration Tool, call it VAMT for short. It's a tool that we created and we worked together with VMware and some of their professional services crew to actually develop this tool. And it is also an open source based tool. And really the primary purpose is to easily enable you to move from one CPU architecture to another CPU architecture, and do that in a cold migration fashion. >> So we're probably not talking about CPUs from Tandy, Radio Shack systems, likely this would be what we might refer to as other X86 systems. >> Other X86 systems is a good way to refer to it. >> So it's interesting timing for the development and the release of a tool like this, because in this sort of X86 universe, there are players who have been delayed in terms of delivering their next gen stuff. My understanding is AMD has been public with the idea that they're on track for by the end of the year, Genoa, next gen architecture. So can you imagine a situation where someone has an existing set of infrastructure and they're like, hey, you know what I want to get on board, the AMD train, is this something they can use from the VMware environment? >> Absolutely, and when you think about- >> Tell us exactly what that would look like, walk us through 100 servers, VMware, 1000 VMs, just to make the math easy. What do you do? How does it work? >> So one, there's several things that the tool can do, we actually went through, the design process was quite extensive on this. And we went through all of the planning phases that you need to go through to do these VM migrations. Now this has to be a cold migration, it's not a live migration. You can't do that between the CPU architectures. But what we do is you create a list of all of the virtual machines that you want to migrate. So we take this CSV file, we import this CSV file, and we ask for things like, okay, what's the name? Where do you want to migrate it to? So from one cluster to another, what do you want to migrate it to? What are the networks that you want to move it to? And then the storage platform. So we can move storage, it could either be shared storage, or we could move say from VSAN to VSAN, however you want to set it up. So it will do those storage migrations as well. And then what happens is it's actually going to go through, it's going to shut down the VM, it's going to take a snapshot, it is going to then basically move the compute and/or storage resources over. And once it does that, it's going to power 'em back up. And it's going to check, we've got some validation tools, where it's going to make sure VM Tools comes back up where everything is copacetic, it didn't blue screen or anything like that. And once it comes back up, then everything's good, it moves onto the next one. Now a couple of things that we've got feature wise, we built into it. You can parallelize these tasks. So you can say, how many of these machines do you want to do at any given time? So it could be, say 10 machines, 50 machines, 100 machines at a time, that you want to go through and do this move. Now, if it did blue screen, it will actually roll it back to that snapshot on the origin cluster. So that there is some protection on that. A couple other things that are actually in there are things like audit tracking. So we do full audit logging on this stuff, we take a snapshot, there's basically kind of an audit trail of what happens. There's also full logging, SYS logging, and then also we'll do email reporting. So you can say, run this and then shoot me a report when this is over. Now, one other cool thing is you can also actually define a change window. So I don't want to do this in the middle of the afternoon on a Tuesday. So I want to do this later at night, over the weekend, you can actually just queue this up, set it, schedule it, it'll run. You can also define how long you want that change window to be. And what it'll do, it'll do as many as it can, then it'll effectively stop, finish up, clean up the tasks and then send you a report on what all was successfully moved. >> Okay, I'm going to go down the rabbit hole a little bit on this, 'cause I think it's important. And if I say something incorrect, you correct me. >> No problem. >> In terms of my technical understanding. >> I got you. >> So you've got a VM, essentially a virtual machine typically will consist of an entire operating system within that virtual machine. So there's a construct that containerizes, if you will, the operating system, what is the difference, where is the difference in the instruction set? Where does it lie? Is it in the OS' interaction with the CPU or is it between the construct that is the sort of wrapper around the VM that is the difference? >> It's really primarily the OS, right? And we've not really had too many issues doing this and most of the time, what is going to happen, that OS is going to boot up, it's going to recognize the architecture that it's on, it's going to see the underlying architecture, and boot up. All the major operating systems that we test worked fine. I mean, typically they're going to work on all the X86 platforms. But there might be instruction sets that are kind of enabled in one architecture that may not be in another architecture. >> And you're looking for that during this process. >> Well usually the OS itself is going to kind of detect that. So if it pops up, the one thing that is kind of a caution that you need to look for. If you've got an application that's explicitly using an instruction set that's on one CPU vendor and not the other CPU vendor. That's the one thing where you're probably going to see some application differences. That said, it'll probably be compatible, but you may not get that instruction set advantage in it. >> But this tool remediates against that. >> Yeah, and what we do, we're actually using VM Tools itself to go through and validate a lot of those components. So we'll look and make sure VM Tools is enabled in the first place, on the source system. And then when it gets to the destination system, we also look at VM Tools to see what is and what is not enabled. >> Okay, I'm going to put you on the spot here. What's the zinger, where doesn't it work? You already said cold, we understand, you can schedule for cold migrations, that's not a zinger. What's the zinger, where doesn't it work? >> It doesn't work like, live migrations just don't work. >> No live, okay, okay, no live. What about something else? What's the oh, you've got that version, you've got that version of X86 architecture, it-won't work, anything? >> A majority of those cases work, where it would fail, where it's going to kick back and say, hey, VM Tools is not installed. So where you would see this is if you're running a virtual appliance from some vendor, like insert vendor here that say, got a firewall, or got something like that, and they don't have VM Tools enabled. It's going to fail it out of the gate, and say, hey, VM Tools is not on this, you might want to manually do it. >> But you can figure out how to fix that? >> You can figure out how to do that. You can also, and there's a flag in there, so in kind of the options that you give it, you say, ignore VM Tools, don't care, move it anyway. So if you've got less, some VMs that are in there, but they're not a priority VM, then it's going to migrate just fine. >> Got It. >> Can you elaborate a little bit on the joint development work that AMD and VMware are doing together and the value in it for customers? >> Yeah, so it's one of those things we worked with VMware to basically produce this open source tool. So we did a lot of the core component and design and we actually engaged VMware Professional Services. And a big shout out to Austin Browder. He helped us a ton in this project specifically. And we basically worked, we created this, kind of co-designed, what it was going to look like. And then jointly worked together on the coding, of pulling this thing together. And then after that, and this is actually posted up on VMware's public repos now in GitHub. So you can go to GitHub, you can go to the VMware samples code, and you can download this thing that we've created. And it's really built to help ease migrations from one architecture to another. So if you're looking for a big data center move and you got a bunch of VMs to move. I mean, even if it's same architecture to same architecture, it's definitely going to ease the pain of going through and doing a migration of, it's one thing when you're doing 10 machines, but when you're doing 10,000 virtual machines, that's a different story. It gets to be quite operationally inefficient. >> I lose track after three. >> Yeah. >> So I'm good for three, not four. >> I was going to ask you what your target market segment is here. Expand on that a little bit and talk to me about who you're working with and those organizations. >> So really this is targeted toward organizations that have large deployments in enterprise, but also I think this is a big play with channel partners as well. So folks out there in the channel that are doing these migrations and they do a lot of these, when you're thinking about the small and mid-size organizations, it's a great fit for that. Especially if they're kind of doing that upgrade, the lift and shift upgrade, from here's where you've been five to seven years on an architecture and you want to move to a new architecture. This is really going to help. And this is not a point and click GUI kind of thing. It's command line driven, it's using PowerShell, we're using PowerCLI to do the majority of this work. And for channel partners, this is an excellent opportunity to put the value and the value add and VAR, And there's a lot of opportunity for, I think, channel partners to really go and take this. And once again, being open source. We expect this to be extensible, we want the community to contribute and put back into this to basically help grow it and make it a more useful tool for doing these cold migrations between CPU architectures. >> Have you seen any in the last couple of years of dynamics, obviously across the world, any industries in particular that are really leading edge for what you guys are doing? >> Yeah, that's really, really interesting. I mean, we've seen it, it's honestly been a very horizontal problem, pretty much across all vertical markets. I mean, we've seen it in financial services, we've seen it in, honestly, pretty much across the board. Manufacturing, financial services, healthcare, we have seen kind of a strong interest in that. And then also we we've actually taken this and presented this to some of our channel partners as well. And there's been a lot of interest in it. I think we presented it to about 30 different channel partners, a couple of weeks back about this. And I got contact from 30 different channel partners that said they're interested in basically helping us work on it. >> Tagging on to Lisa's question, do you have visibility into the AMD thought process around the timing of your next gen release versus others that are competitors in the marketplace? How you might leverage that in terms of programs where partners are going out and saying, hey, perfect time, you need a refresh, perfect time to look at AMD, if you haven't looked at them recently. Do you have any insight into that in what's going on? I know you're focused on this area. But what are your thoughts on, well, what's the buzz? What's the buzz inside AMD on that? >> Well, when you look overall, if you look at the Gartner Hype Cycle, when VMware was being broadly adopted, when VMware was being broadly adopted, I'm going to be blunt, and I'm going to be honest right here, AMD didn't have a horse in the race. And the majority of those VMware deployments we see are not running on AMD. Now that said, there's an extreme interest in the fact that we've got these very cored in systems that are now coming up on, now you're at that five to seven year refresh window of pulling in new hardware. And we have extremely attractive hardware when it comes to running virtualized workloads. The test cluster that I'm running at home, I've got that five to seven year old gear, and I've got some of the, even just the Milan systems that we've got. And I've got three nodes of another architecture going onto AMD. And when I got these three nodes completely maxed to the number of VMs that I can run on 'em, I'm at a quarter of the capacity of what I'm putting on the new stuff. So what you get is, I mean, we worked the numbers, and it's definitely, it's like a 30% decrease in the amount of resources that you need. >> That's a compelling number. >> It's a compelling number. >> 5%, 10%, nobody's going to do anything for that. You talk 30%. >> 30%. It's meaningful, it's meaningful. Now you you're out of Austin, right? >> Yes. >> So first thing I thought of when you talk about running clusters in your home is the cost of electricity, but you're okay. >> I'm okay. >> You don't live here, you don't live here, you don't need to worry about that. >> I'm okay. >> Do you have a favorite customer example that you think really articulates the value of AMD when you're in customer conversations and they go, why AMD and you hit back with this? >> Yeah. Actually it's funny because I had a conversation like that last night, kind of random person I met later on in the evening. We were going through this discussion and they were facing exactly this problem. They had that five to seven year infrastructure. It's funny, because the guy was a gamer too, and he's like, man, I've always been a big AMD fan, I love the CPUs all the way since back in basically the Opterons and Athlons right. He's like, I've always loved the AMD systems, loved the graphics cards. And now with what we're doing with Ryzen and all that stuff. He's always been a big AMD fan. He's like, and I'm going through doing my infrastructure refresh. And I told him, I'm just like, well, hey, talk to your VAR and have 'em plug some AMD SKUs in there from the Dells, HPs and Lenovos. And then we've got this tool to basically help make that migration easier on you. And so once we had that discussion and it was great, then he swung by the booth today and I was able to just go over, hey, this is the tool, this is how you use it, here's all the info. Call me if you need any help. >> Yeah, when we were talking earlier, we learned that you were at Scale. So what are you liking about AMD? How does that relate? >> The funny thing is this is actually the first time in my career that I've actually had a job where I didn't work for myself. I've been doing venture backed startups the last 25 years and we've raised couple hundred million dollars worth of investment over the years. And so one, I figured, here I am going to AMD, a larger corporation. I'm just like, am I going to be able to make it a year? And I have been here longer than a year and I absolutely love it. The culture at AMD is amazing. We still have that really, I mean, almost it's like that underdog mentality within the organization. And the team that I'm working with is a phenomenal team. And it's actually, our EVP and our Corp VP, were actually my executive sponsors, we were at a prior company. They were one of my executive sponsors when I was at Scale. And so my now VP boss calls me up and says, hey, I'm putting a band together, are you interested? And I was kind of enjoying a semi-retirement lifestyle. And then I'm just like, man, because it's you, yes, I am interested. And the group that we're in, the work that we're doing, the way that we're really focusing on forward looking things that are affecting the data center, what's going to be the data center like three to five years from now. It's exciting, and I am having a blast, I'm having the time of my life. I absolutely love it. >> Well, that relationship and the trust that you will have with each other, that bleeds into the customer conversations, the partner conversations, the employee conversations, it's all inextricably linked. >> Yes it is. >> And we want to know, you said three to five years out, like what? Like what? Just general futurist stuff, where do you think this is going. >> Well, it's interesting. >> So moon collides with the earth in 2025, we already know that. >> So we dialed this back to the Pensando acquisition. When you look at the Pensando acquisition and you look at basically where data centers are today, but then you look at where basically the big hyperscalers are. You look at an AWS, you look at their architecture, you specifically wrap Nitro around that, that's a very different architecture than what's being run in the data center. And when you look at what Pensando does, that's a lot of starting to bring what these real clouds out there, what these big hyperscalers are running into the grasps of the data center. And so I think you're going to see a fundamental shift. The next 10 years are going to be exciting because the way you look at a data center now, when you think of what CPUs do, what shared storage, how the networking is all set up, it ain't going to look the same. >> Okay, so the competing vision with that, to play devil's advocate, would be DPUs are kind of expensive. Why don't we just use NICs, give 'em some more bandwidth, and use the cheapest stuff. That's the competing vision. >> That could be. >> Or the alternative vision, and I imagine everything else we've experienced in our careers, they will run in parallel paths, fit for function. >> Well, parallel paths always exist, right? Otherwise, 'cause you know how many times you've heard mainframe's dead, tape's dead, spinning disk is dead. None of 'em dead, right? The reality is you get to a point within an industry where it basically goes from instead of a growth curve like that, it goes to a growth curve of like that, it's pretty flat. So from a revenue growth perspective, I don't think you're going to see the revenue growth there. I think you're going to see the revenue growth in DPUs. And when you actually take, they may be expensive now, but you look at what Monterey's doing and you look at the way that those DPUs are getting integrated in at the OEM level. It's going to be a part of it. You're going to order your VxRail and VSAN style boxes, they're going to come with them. It's going to be an integrated component. Because when you start to offload things off the CPU, you've driven your overall utilization up. When you don't have to process NSX on basically the X86, you've just freed up cores and a considerable amount of them. And you've also moved that to where there's a more intelligent place for that pack to be processed right, out here on this edge. 'Cause you know what, that might not need to go into the host bus at all. So you have just alleviated any transfers over a PCI bus, over the PCI lanes, into DRAM, all of these components, when you're like, but all to come with, oh, that bit needs to be on this other machine. So now it's coming in and it's making that decision there. And then you take and integrate that into things like the Aruba Smart Switch, that's running the Pensando technology. So now you got top of rack that is already making those intelligent routing decisions on where packets really need to go. >> Jason, thank you so much for joining us. I know you guys could keep talking. >> No, I was going to say, you're going to have to come back. You're going to have to come back. >> We've just started to peel the layers of the onion, but we really appreciate you coming by the show, talking about what AMD and VMware are doing, what you're enabling customers to achieve. Sounds like there's a lot of tailwind behind you. That's awesome. >> Yeah. >> Great stuff, thank you. >> It's a great time to be at AMD, I can tell you that. >> Oh, that's good to hear, we like it. Well, thank you again for joining us, we appreciate it. For our guest and Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE Live" from San Francisco, VMware Explore 2022. We'll be back with our next guest in just a minute. (upbeat music)

(upbeat music) >> Hey everyone. Welcome back to San Francisco, VMware Explorer 2022, Lisa Martin and Dave Nicholson here. We've been having some great conversations today. Lots of news coming out about VMware and its partner ecosystem. We're going to have another conversation about that next. Please welcome two guests to the program, Chance Bingen, technical marketing engineer at NetApp and Jason Massae, staff technical marketing architect, storage and vVols at VMware. Guys, welcome to the program. >> Thanks. >> Glad to be here. >> It's nice to be back in person. >> It is. It's very nice. Oh my gosh. >> And we're hearing there about 7,000 to 10,000 people here, when I was in the Keynote, this morning it was definitely standing room only. >> Yeah, yeah. You've definitely seen the numbers ticked up at the last minute. It was good to see that. It's good, I think a lot of people have really wanted to get back, get that one on one that face to face. There's nothing like being able to, you know, talk to, the experts, talk to the vendors, you know, see your comrades. I mean, that's the thing. I mean, we've seen people that I haven't seen for years, even on my own team, so really good to be back into it. >> It is and it was lots of news coming out this morning during the Keynote. My goodness. But Jason, talk to me, the NetApp and VMware folks had been in tight partnership for a long time. Talk to me about, get both of your perspective from a technical perspective about the depth of the partnership. >> Yeah, so actually NetApp was one of the original design partners for vVols. And with that, now with some of the stuff we're doing with more current stuff with virtual volumes is, NetApp is back and we've got some pretty neat stuff that we've been working on with vVols. And NetApp's got some pretty neat stuff that they've been working on to enable the customers with more features, more functionality with the virtual volume functionality. >> Yeah, absolutely. >> Give us a quick primer on what is a vVol? What is a virtual volume? How does it fit into the, into this stack of stuff that we do in IT? >> Yeah. So the easiest way to kind of think of what a vVol is or a virtual volume is you can think of it kind of like an RDM, those row device map, which is kind of a four letter word. We don't really like those, but the idea is that object, that virtual volume is native on the array and presented directly to the VM. But now what we do is we're presenting all of the storage array features up to vSphere and we're managing those storage features via policy based management. But instead of applying storage capabilities at a data store level, we're now applying them at a VM or an application level. So you can have one data store and multiple VMs, and every VM can have a different storage capability managed by a policy that the VI admin gets to manage now. So he doesn't have to go to the storage admin to say, I need a new line, or I need a new volume. He can just go in and create a policy or change a policy. And now that storage capability is applied to the VM or the application. >> Yeah. One thing I'd like to add to that is you can mentioned the word capabilities. >> So we look at the actual data protocols, whether they're file based or block based, you know, I-scuzzy, fiber channel, whatever the case might be. Those protocols have defined sets of capabilities and attributes and things they can expose. What vVols along with the VASA protocol brings to the table is the ability to expose things that are just impossible to expose via the data protocols themselves. So that the, actual nature of the array, what kind of array is it? What's it capable of doing? What is the nature of, you know, encryption? You know, is this going to be a secure, encrypted data store? Is it going to be something else? It just allows you to do so much more with the advanced capabilities that modern storage arrays have than you could ever do if you were just using the data protocols by themselves. >> Right? Yeah. Kind of under that same context. If you think about before with traditional storage, the vSphere or the array really doesn't understand what's going on underlying storage, but with vVols the array and vSphere completely understand at a disc level even, how that VM should be treated. So that helps the storage admin. Storage admin can now go in and see a specific disc of a VM and see the performance on the array. They can go in the array and see, oh, this disc on this VM has got performance issues or needs to be encrypted, or here's the size of that disc. And you couldn't easily see that with your traditional storage. So there's really a lot of benefits and it frees up a lot of time for the storage administrator and enables the VI admin to be able to do a lot of the storage management. >> So there have been, there been a lot of movements over the last decade in the realm of software defined storage. Where essentially all of the things that you are talking about are completely abstracted from the underlying hardware. In this case, you're leveraging the horsepower, if you will and the intelligence of a storage array that has a lot of horsepower and intelligence, and you're accessing those features. You mentioned encryption, whether if you're doing a snapshot or something like that, what's interesting here is it kind of maps to what we're looking at now, which is the trend in the direction of things like DPUs. >> If you go back in history long enough, we had the, you know, the TOE, NIC, TCP offload, you know, the idea of, hey, you know what, what if we had a smart device with its own brain power and we leveraged it. Well, you guys have been doing that from a vVols all perspective with NetApp filers, for lack of better term. For how long now, when did, when were they originally? >> 6.0 it was so it's been what? 11, 12 years. Something like that. >> It's been a while. So yeah, but it's been a decade or so. >> Mm-hmm >> So what's on the frontier. What's the latest there in terms of, in terms of cool stuff that's coming out. >> So actually today, in one of the things that we worked with NetApp that was part of the design partnership was, you know, the NVMe over Fabric protocol has become very popular to extend that functionality of all flash to the, an external array. And now we announce today, in including with that NVMe over Fabrics, you can now do vVols with NVMe over Fabrics. And again, that was something that we worked with NetApp to be a design partner for them. >> That's right. We're very excited about it. We've always been, you know, NVMe been something we've been very proud of for a while. Delivering the first end to end NVMe stack from inside the host, through the fabric, to the array, with the arrays front ports, all the way to the disc on the backend. So we're very excited about that. >> So target market joint NetApp, VMware customers, I presume. >> Really it's, the key here that I like to make sure customers understand is to see that vVols are on the leading edge of VMware's storage design. Some tend to think that maybe vVols wasn't the primary focus, but actually now it is the primary focus. Now I always like to give the caveat that VMFS and NFS are not going away. Those are still very much stuff that we work on. It's just that most of the engineering focus is on virtual volumes or vVols. >> Yeah. Similarly, when you talk about and you're sort of alluding to vSAN when we start talking about VMFS and things like that. >> Yeah. >> Architecturally, we've been talking to folks about the recent announcements with capabilities within AWS. You know, NetApp in AWS for VMware environments. Breaking out of the stranglehold that the, oh, you want more storage, you must buy more CPU and memory, building block process entails. The reality is no matter what you do with vSAN, you're going to have certain constraints that go away when now you have the option to leverage storage from the NetApp filers. >> Yeah, absolutely. >> So how does, how do vVols play in the cloud strategy moving forward? >> Well, so one of the things that we do with, vVols currently is mostly On-prem. But when you have the storage architecture, that vVols gives you as far as individual objects, it makes it much easier to migrate up into the cloud because you're not trying to migrate individual VMs that are on another type of system, whatever it might be, those objects are already their own entity. Right, so cloud, Tanzu, those type of things, those vVol objects are already their own entity. So it makes it very easy to migrate them on and off prem. >> So Chance talk to us a little bit about this from NetApp's perspective. You're in customer conversations, who are you talking to? Is this primarily an engineering conversation? Has this gone up the stack in terms of customers are finding themselves in this default multi-cloud environment? >> Yeah, so interestingly, when I talk to customers these days they are almost all either on a journey to a hybrid multi-cloud or they're in some kind of phase of transforming themselves into their own hyperscaler, right? They're be adopting a cloud service provider model and vVols is a perfect fit for that kind of model, because you have the ability to offer different tiers of service, different qualities of service with VM granular controls or VMDK granular controls, even. And even if you look at First Class Disc, right? Which is something that came out largely to support Tanzu, I think which fantastic use case for vVols as well there, but that gives you the ability to offer something like Amazon EBS, right? You can offer Amazon EBS in a native VMware stack using First Class Discs and vVols. And you're able to apply things like quality of service with that granular control that allows you to guarantee that customer the disc that they bought and paid for. They're going to get the IOPS that they're paying for because you're applying those QoS policies directly to that object on the array. And instead of having to worry about is the array going to be able to handle it? Are you going to have one VM that consumes all your IO, you know? You don't have to worry about that with vVols because you've got that integration with the array's native quality controls. >> And Chance what's in this for me as a customer? I'm hearing productivity, I'm hearing cost savings, control efficiency. Talk to me about the benefits in it for the folks that you're talking to. >> Yeah, absolutely. A lot of times it comes down to, you know I mentioned like the cloud service provider model, right? When you're looking to build a robust service catalog and you're able, you want to be able to meet all these like, we mentioned Tanzu, right? Containers as a service, you're able to provide the persistent volumes for your Kubernetes containers that are again, these native objects on the array and you have these fine grain controls, but it's handled at massive scale because it's all handled by storage policies, Kubernetes storage classes, which are natively mapped to VM storage policies through Tanzu. So it just, it gives you the ability to offer all of these services in a, again a rich and robust contents catalog. >> So what are you doing? So you mentioned a couple of things in terms of using array based quality of service. So give me an example of how you're avoiding issues of contention and over subscription in an environment where I'm an administrator and I've got this virtual volume that's servicing this VM or this app on this VM. What kind of visibility do I have down into the actual resources because look at the end of that chain there's a physical resource. And that physical resource represents, what? IOPS and bandwidth and latency and throughput and all of this bundle of things. So how do you avoid colliding with others who are trying to carve vVols out of this world? >> You mean like a noisy neighbor type of thing? >> Yeah. Yeah. >> So that's actually one of the big benefits that you get with vVols is that because those vial objects are native on the array, they're not sharing a loan or a volume. They're not sharing a resource. The only resource they're actually sharing is the array itself. So you don't get that typical noisy neighbor where this one's using all the resources of that volume because really you're looking out at the all encompassing array. And so a storage administrator and the VI admin have a lot more insight. The VI admin can now go to the storage admin if there's say a debugging issue, they want to find a problem. The storage admin now can see those individual objects and say, oh, well this VM, it's not really this, it's not all the discs. It's just disc number two or disc number three or they can actually see at a single disc level on the array, the performance, the latency, you know, the QS, all that stuff. >> Oh, absolutely. >> And that really is what, it frees up at the storage admin's time because the debugging is so much more simple. And it also allows the storage admin a lot more insight. Right? They know those, what's the problem. If you were typically looking at a loaner volume, they don't really know what's going on inside that and neither does the array. But with vVols, the array knows what each disc and how it's supposed to be treated based on the policies that the customer defines. So if one VM is supposed to have a certain QS and another VM isn't. The array knows that that VM, if it goes above it, it's going to be like, nope, you can't have those resources. You weren't granted those resources, but this one was. So you have much more control. And again, it's at an application or a VM level. >> And it's still, it's fairly dynamically configurable. I spoke to a customer just the other day. They are a cloud service provider. And what they do is their customers are able to go in and change their quality of service. So they go into that service portal and they say, okay, I'm paying for gold and I want platinum and they'll go in. They know that they've got a certain time where they need more IO capacity. So they'll go in, they'll pay the fee, increase that capability. And then when they don't need it anymore, they'll downgrade again. >> Okay, so that assumes some ability at the array level to do some sort of resource sharing and balancing to be able to go out and get, say more IO. Because again, fundamentally, if you have a virtual volume, that's drawing its resources from five storage devices, whether those are SSD based or NVMe or spinning disc that represents a finite it amount of resource. The assumption is if you're saying that the array is the pool that you need to worry about, that assumes the array has the ability to go beyond here, based on a policy. >> So that's how it works. It does... >> Well, essentially. I mean, you can't outrun physics. So if the array can't go faster, but the idea is that you understand the performance profile of your array and then you create your service tiers appropriately. >> Okay. >> Yeah. And one of the big benefits is like Chance was saying, if you want to change a profile that used to be a Storage vMotion to a different data store. Now it's just a policy change. The storage admin doesn't have to do anything. The VI admin just changes the policy. And then the array understands, oh, I now need to treat that different. And that's exactly what Chance was talking about in that cloud provider situation, where today I'm using a 100,000 IOPS. I need to use 200,000 tomorrow for special, whatever it is, but I only need to use it for tomorrow. So they don't have to move anything. They just change the policy for that time. And then they change it back. They don't have to do anything on the array itself. They don't have to change anything physically on the VM. It's just a policy change. And that's really where you get that dynamic control of the storage capability. >> So as business dynamics are changing and I'm thinking of like black Friday or Prime day, being able to dial things up and dial it down, they have the ability to do that with a policy. >> Yes. >> Exactly. >> So huge time savings there. >> Oh, it's huge. Yeah. >> Yeah. >> And it simplifies because now, I don't have to have multiple data stores. You can have one data store, all your VMs in there. You can limit test and dev and you can maximize business critical applications. Again, all via policy. So you've simplified your infrastructure. You've gone to more of a programmatic approach of managing your storage capabilities. But you're now managing at the VM level. >> So we mentioned that the cloud chaos (indistinct) that was mentioned this morning during the Keynote and we're saying a lot of customers are still in this cloud chaos phase. They want to get to Cloud Smart. How is this going to be one of those tools that helps customers pull the levers, dial the knobs, to be able to get to eventually, Cloud Smart. >> I could go on for this for hours. (Lisa Laughs) (Chance chuckles) This is really what simplifies storage. Because typically when you use traditional storage, you're going to have to figure out that this data store has this capability or another example, as you mentioned was Tanzu. If you're managing persistent volumes and you're not using something like vVols, if you want to get a certain storage capability, you have to either tag it or you have to create that data store with that capability. All of that goes away when you use vVols. So now that chaos of multiple data stores, multiple lines or multiple volumes, all that stuff goes away. So now you're simplifying your infrastructure, you have a programmatic approach to managing your storage and you can use it for all of your different types of workloads. So cloud, Kubernetes, persistent volumes, all that type of stuff. And again, all being managed via a simple and again, programmatic approach. So you could automate this. You know today, like you said, black Friday. Okay, Black, Friday's coming up. I want to change the policy. You could automate that. So you don't even have to go in and physically make the change of the policy now. You just say on Fridays, change it to this policy on Sunday night, change it back. >> Yep. >> Again, that's not something you can do with traditional storage. >> Okay. >> And I think from a simplification standpoint as well, you know, I was telling you about that other customer a couple days ago, they were running into the inability to grow beyond the bounds of VMFS file systems for very, very large VMs. And so what I talked to them about was look, if you go to vVols, you're not bound by file systems anymore. You have the capacity of the array and you can have VM discs up to 62 terabytes, you know, as many as you want. And it doesn't matter what they fit in because we can fit them all. So it's, to be able to, and that's some of our largest customers, the reason they go with vVols is to be able to grow beyond the bounds of traditional storage, anything like path limits, you know. That's something you have to contend with. >> Path limits, line limits, all that stuff. Typically just disappears with vVols. >> All those limits go away. Guys- >> They go away. >> Amazing. Congratulations on the work that you guys have done. Thank you so much for joining us on theCUBE talking about the value in it for customers and obviously the technical depths of the NetApp, VMware relationship. Guys, we appreciate your time. >> Yeah, thanks for having us on. >> Our pleasure. For my guests and Dave Nicholson. I'm Lisa Martin. You're watching theCUBE live from VMware Explorer 2022, Dave and I will be right back with our next guest. So stick around. (upbeat music)

(upbeat music) >> Okay, welcome back everyone to the Cube's live coverage in Monaco. I'm John Furrier, host of theCube. Monaco Crypto Summit is the event and there's a big conversation later at the yacht club with Prince Albert and everyone else will be there, and it'll be quite the scene. And Rachel Wolfson is here. She's with Cointelegraph. They're the media partner of the event, the official media partner of the Monaco Crypto Summit. She's also MCing the event on stage, presented by DigitalBits. Rachel, thanks for coming on. >> Thanks for having me, John. >> So I know you're busy, thanks for taking the time cause' you got to go jump back in and moderate, and keep things on track. This isn't an inaugural event. So DigitalBits has exploded on the scene. I just saw a thing on YouTube news around this soccer player in Rome, has DigitalBits logo on their jersey. They're a big to do cause everyone's popular and they got a couple teams. So real world, kind of, assets coming together, what's going on in the event that you're MCing? What's the focus? What's the agenda? What's some of the conversations like? >> Yeah, definitely. Well, it's a great event. It's my first time here in Monaco and I'm loving it. And I think that Monaco is really becoming the next crypto hotspot. Definitely in terms of Metaverse and Web3 innovation, I think that we're going to start seeing a lot of that here. That's what we're seeing today at the Summit. So a lot of the presentations that we're seeing are really focused on Web3 and NFT platforms, so for instance, obviously what DigitalBits is doing. We watched a video before the break on Ecosystem and the Metaverse that people can join and be a part of, in terms of real estate, but we're seeing a lot of innovation here today with that. I moderated a great panel with Britney Kaiser, Lauren Bissell, Taross, I'm blanking on his last name, but it was about blockchain and how governments are implementing blockchain. So that was also really interesting to hear about what the Ukrainian government is doing with blockchain. So there's kind of a mix, but I'd say that the overall theme is Web3 and NFTs. >> Yeah. Britney was mentioning some of that, how they're going to preserve buildings and artifacts, so that in case they're looted or destroyed, they can preserve them. >> Right. I think it's called the Heritage Fund. And I just think it's such an interesting use case in terms of how governments are using blockchain because the best use for blockchain in my opinion, is recording data, and having that data be permanent. And so when we can have artifacts in Ukraine recorded on the blockchain, you know by being scanned, it's really revolutionary. And I think that a lot of governments around the world are going to see that use case and say, "Oh wow, blockchain is a great technology for things like that." >> So DigitalBits had a press conference this morning and they talked about their exchange and some other things. Did you attend that press conference or did you get briefed on that? >> I did not attend the press conference. I was prepping for my MC role. >> So they got this exchange thing and then there's real interest from Prince Albert's foundations to bring this into Monaco. So Monaco's got this vibe, big time. >> Rachel: Right. There's a vibe (John chuckles) >> What does it all mean, when you're putting in your reporting? What do you see happening? >> So, I mean, I honestly haven't covered Monaco actually ever in my reporting. And John, you know I've been reporting since 2017, but the vibe that I'm getting just from this summit today is that Web3 and NFTs are going to be huge here. I'm speaking, I haven't... You know, there's a panel coming up about crypto regulations, and so we're going to talk a little bit about laws being passed here in Monaco in terms of Metaverse and digital identity. So I think that there are a few laws around that here that they're looking at, the government here is looking at to kind of add clarity for those topics. >> I had a couple guests on earlier. We were talking about the old days, a couple years ago. You mentioned 2017, so much has changed. >> Yes. >> You know, we had a up and down. 2018 was a good year, and then it kind of dived back and changed a little bit. Then NFTs brought it back up again, been a great hype cycle, but also movement. What's your take on the real progress that's been made? If you zoom out and look at the landscape, what's happened? >> Right. I mean, well, a lot has happened. When I first entered the space, I initially came in, I was interested in enterprise, blockchain and private networks being utilized by enterprises to record data. And then we saw public blockchains come in, like Ethereum and enterprises using them. And then we saw a mix. And now I feel like we're just seeing public blockchains and there's really... (John chuckles) But there's still our private blockchains. But today, I mean, we've gone from that in 2017 to right now, I think, you know, we're recently seeing a lot of these centralized exchanges kind of collapsing. What we've seen with Celsius, for instance, and people moving their crypto to hardware wallets. I think that the space is really undergoing a lot of transformation. It's really revolutionary, actually, to see the hardware wallet market is growing rapidly, and I think that that's going to continue to grow. I think centralized exchanges are still going to exist in custody crypto for enterprises and institutions, and you know, in individuals as well. But we are seeing a shift from centralized exchanges to hardware wallets. NFTs, although the space is, you know, not as big as it was a year ago, it's still quite relevant. But I think with the way the market is looking today, we're only seeing the top projects kind of lead the way now, versus all of the noise that we were seeing previously. So yeah, I think it's- >> So corrections, basically? >> Right. Exactly. Corrections. And I think it's necessary, right. It's very necessary. >> Yeah. It's interesting. You know, you mentioned the big players you got Bitcoin, Ethereum driving a lot. I remember interviewing the crypto kiddies when they first came out, it was kind of a first gen Ethereum, and then it just exploded from there. And I remember saying to myself, if the NFTs and the decentralized applications can have that scale, but then it felt like, okay, there was a lot of jocking for under the covers, under the hood, so to speak. And now you've got massive presence from all the VCs, and Jason Ho has like another crypto fund. I mean, >> Right. you can't go a day without another big crypto fund from you know, traditional venture capitalists. Meanwhile, you got investors who have made billions on crypto, they're investing. So you kind of got a diversity of investor base going on and different instruments. So the investor community's changing and evolving too. >> Right. >> How do you see that evolving? >> Well, it's a really good point you mentioned. So Cointelegraph research recently released a report showing that Web3 is the most sought after investment sector this year. So it was DeFi before, and Web3 is now leading the way over DeFi. And so we're seeing a lot of these venture capitalist funds as you mentioned, create funds allocated just to Web3 growth. And that's exactly what we're seeing, the vibe I'm getting from the Monaco Crypto Summit here today, this is all about Web3. It's all about NFT, it is all about the Metaverse. You know, this is really revolutionary. So I think we're definitely going to see that trend kind of, you know, conquer all of these other sectors that we're seeing in blockchain right now. >> Has Web3 become the coin term for Metaverse and NFTs? Or is that being globalized as all shifted, decentralized? What's the read on it? It seems to be like, kind of all inclusive but it tends to be more like NFT's the new thing and the young Gen Zs >> Yeah want something different than the Millennials and the Xs and the Boomers, who screwed everything up for everybody. >> Yeah. (John chuckles) No, I mean, it's a great question. So when I think of Web3, I categorize NFTs and the Metaverse in there. Obviously it's just, you know the new form of the internet. It's the way the internet is- >> Never fight fashion, as I always say, right? >> Right. Yeah. Right. (John chuckles) It's just decentralization. The fact that we can live in these virtual worlds and own our own assets through NFT, it's all decentralized. And in my opinion, that all falls under the category of Web3. >> Well, you're doing a great job MCing. Great to have you on theCube. >> Rachel: Thanks. I'd like to ask you a personal question if you don't mind. COVID's impacted us all with no events. When did you get back onto the events circuit? What's on your calendar? What have you been up to? >> Yeah, so gosh, with COVID, I think when COVID, you know, when it was actually really happening, (John chuckles) and it still is happening. But when it was, you know, >> John: Like, when it was >> impacting- shut down mode. >> Right. When we were shut down, there were virtual events. And then, I think it was late last year or early this year when the events started happening again. So most recently I was at NFT NYC. Before that, I was at Consensus, which was huge. >> Was that the one in Austin or Miami? >> In Austin. >> That's right, Austin. >> Right. Were you there? >> No, I missed it. >> Okay. It was a very high level, great event. >> Huge numbers, I heard. >> Yes. Massive turnout. (John chuckles) Tons of speakers. It was really informative. >> It feels like a festival. actually. >> It was. It was just like South by Southwest, except for crypto and blockchain. (John chuckles) And then coming up, gosh, there are a lot of events. I'll be at an event in Miami, it's an NFT event that's in a few months. I know that there's a summit happening, I think in Turkey that I may be at as well. >> You're on the road. You're traveling. You're doing a lot of hopping around. >> Yes I am. And there's a lot of events happening in Europe. I'm US-based, but I'm hoping to spend more time in Europe just so I can go to those events. But there's a lot happening. >> Yeah. Cool. What's the most important story people should be paying attention to in your mind? >> Wow. That's... (Rachel chuckles) That's a big question. It's a good question. I think most, you know, the transition that we're seeing now, so in terms of prices, I think people need to focus less on the price of Bitcoin and Ethereum and more on innovation that's happening. So for instance, Web3 innovation, what we're seeing here today, you know, innovation, isn't about prices, but it's more about like actually now is the time to build. >> Yeah. because the prices are a bit down. >> Yeah. I mean, as, you know, Lewis Hamilton's F1 driver had a quote, you know, "It takes a team. No matter who's in the driver's seat, it's a team." So community, Wayne Gretzky skates where the puck is going to be I think is much more what I'm hearing now, seeing what you're saying is that don't try to count the price trade of Bitcoin. This is an evolution. >> Right. >> And the dots are connecting. >> Exactly. And like I said, now is the time to build. What we're seeing with the project Britney mentioned, putting the heritage, you know, on the blockchain from Ukraine, like, that's a great use case for what we're seeing now. I want to see more of those real world use cases. >> Right. Well, Rachel, thanks for coming on theCube. I really appreciate it. Great to see you. >> Thanks, John. >> And thanks for coming out of your schedule. I know you're busy. >> Thanks. Now you get some lunchtime now and get some break. >> Yeah. Get back on stage. Thanks for coming on. >> Rachel: Thank you. >> All right. We're here at the Monaco Crypto Summit. Rachel's MCing the event as part of the official media partner, Cointelegraph. Rachel Wolfson here on theCube. I'm John Furrier. More coverage coming after this short break. >> Thank you. (upbeat music)