(upbeat music) >> Hello everyone, welcome to this CUBE Showcase, accelerating business transformation with VMware Cloud on AWS. It's a solution innovation conversation with two great guests, Fred Wurden, VP of Commercial Services at AWS and Narayan Bharadwaj, who's the VP and General Manager of Cloud Solutions at VMware. Gentlemen, thanks for joining me on the showcase. >> Great to be here. >> Great. Thanks for having us on. It's a great topic. >> We've been covering this VMware cloud on AWS since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. What's this mean? And the press were not really on board with the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for AWS and it continues two years later and I want to just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to re:Invent, which is only a couple weeks away Feels like tomorrow. But as we prepare, a lot going on. Where are we with the evolution of the solution? >> I mean, first thing I want to say is October 2016 was a seminal moment in the history of IT. When Pat Gelsinger and Andy Jassy came together to announce this. And I think John, you were there at the time I was there. It was a great, great moment. We launched the solution in 2017 year after that at VMworld, back when we called it VMworld. I think we have gone from strength to strength. One of the things that has really mattered to us is we've learned from AWS also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we built a service offering now five years old. Pretty remarkable journey. In the first years we tried to get across all the regions, that was a big focus because there was so much demand for it. In the second year, we started going really on enterprise great features. We invented this pretty awesome feature called Stretched Clusters, where you could stretch a vSphere cluster using vSAN and NSX-T across to AZs in the same region. Pretty phenomenal four nines of availability that applications started to get with that particular feature. And we kept moving forward, all kinds of integration with AWS Direct Connect, Transit Gateways with our own advanced networking capabilities. Along the way, Disaster Recovery, we punched out two new services just focused on that. And then more recently we launched our Outposts partnership. We were up on stage at re:Invent, again, with Pat and Andy announcing AWS Outposts and the VMware flavor of that, VMware Cloud and AWS Outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >> That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And this has been the theme for AWS, man, since I can remember from day one, Fred. You guys do the heavy lifting as you always say for the customers. Here, VMware comes on board. Takes advantage of the AWS and just doesn't miss a beat. Continues to move their workloads that everyone's using, vSphere, and these are big workloads on AWS. What's the AWS perspective on this? How do you see it? >> Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the skill set that they're familiar with and the advanced capabilities that they've been using on-prem and then overlay it on top of the AWS infrastructure that's evolving quickly and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the customers. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and responding to what customers want. So pretty excited about just seeing the transformation and the speed that which customers can move to while at VMC. >> That's a great value proposition. We've been talking about that in context to anyone building on top of the cloud. They can have their own supercloud, as we call it, if you take advantage of all the CapEx and investment Amazon's made and AWS has made and continues to make in performance IaaS and PaaS, all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options in the market? What makes it different? What's the combination? You mentioned jointly engineered. What are some of the key differentiators of the service compared to others? >> Yeah. I think one of the key things Fred talked about is this jointly engineered notion. Right from day one we were the early adopters of the AWS Nitro platform. The reinvention of EC2 back five years ago. And so we have been having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software-defined data center, compute storage networking on EC2, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally on AWS EC2 global regions. Now the other thing that's a real differentiator for us, what customers tell us about is this whole notion of a managed service. And this was somewhat new to VMware. But we took away the pain of this undifferentiated heavy lifting where customers had to provision rack stack hardware, configure the software on top, and then upgrade the software and the security patches on top. So we took away all of that pain as customers transitioned to VMware cloud in AWS. In fact, my favorite story from last year when we were all going through the Log4j debacle. Industry was just going through that. Favorite proof point from customers was before they could even race this issue to us, we sent them a notification saying, we already patched all of your systems, no action from you. The customers were super thrilled. I mean, these are large banks. Many other customers around the world were super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >> Narayan, that's a great point. The whole managed service piece brings up the security. You kind of teasing at it, but there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. Fred, we were commenting before we came on camera more bits than ever before and at the physics layer too, as well as the software. So you never know when there's going to be a zero-day vulnerability out there. It happens. We saw one with Fortinet this week. This came out of the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me, we see the value when we talk to customers on theCUBE about this. It was a real easy understanding of what the cloud means to them with VMware now with the AWS. But the question that comes up that we want to get more clarity on is how do you guys handle support together? >> Well, what's interesting about this is that it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like SAP, we'll go end-to-end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where we're improving reliability in as a first order of principle between both companies. So from availability and reliability standpoint, it's top of mind and no matter where the particular item might land, we're going to go help the customer resolve that. It works really well. >> On the VMware side, what's been the feedback there? What are some of the updates? >> Yeah, I think, look, I mean, VMware owns and operates the service, but we work phenomenal backend relationship with AWS. Customers call VMware for the service or any issues. And then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The key management that we jointly do. All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution, do complex things like cloud migration, which is much, much easier with the VMware Cloud in AWS. We're presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >> You had mentioned, I've got list here of some of the innovations. You mentioned the stretch clustering, getting the geos working, advanced network, Disaster Recovery, FedRAMP, public sector certifications, Outposts. All good, you guys are checking the boxes every year. You got a good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in? What's on the list this year? What items will be next year? How do you see the new things, the list of accomplishments? People want to know what's next. They don't want to see stagnant growth here. They want to see more action as cloud continues to scale and modern applications cloud native. You're seeing more and more containers, more and more CI/CD pipelining with modern apps, put more pressure on the system. What's new? What's the new innovations? >> Absolutely. And I think as a five year old service offering, innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explore. First of all, our new platform i4i.metal. It's isolate based. It's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and AWS at this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally and separate that from compute. So two different storage offerings there. One is with AWS FSx with NetApp ONTAP, which brings in our NetApp partnership as well into the equation and really get that NetApp based really excited about this offering as well. And the second storage offering called VMware Cloud Flex Storage. VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware Cloud Flex Compute where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware Cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the vCPU memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that we are launching in the market this year. And then last but not least, top of ransomware. Of course it's a hot topic in the industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware Cloud DR solution. A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Northstar. Our ability to have layer four through layer seven, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers is sort at the heart of our (faintly speaking). >> The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better faster, networking more options there. The Flex Compute is interesting. If you don't mind me getting a quick clarification, could you explain the resource-defined versus hardware-defined? Because this is what we had saw at Explore coming out, that notion of resource-defined versus hardware-defined. What does that mean? >> Yeah, I mean I think we have been super successful in this hardware-defined notion. We we're scaling by the hardware unit that we present as software-defined data centers. And so that's been super successful. But customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally. Lower the cost even more. And so this is the part where resource-defined starts to be very, very interesting as a way to think about, here's my bag of resources exactly based on what the customers request before fiber machines, five containers. It's size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. That's a whole different service offering that adds value and customers are comfortable. They can go from one to the other. They can go back to that host based model if they so choose to. And there's a jump off point across these two different economic models. >> It's cloud flexibility right there. I like the name. Fred, let's get into some of the examples of customers, if you don't mind, let's get into some of the, we have some time. I want to unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on theCUBE is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like feels great. It's just like we're running VMware on AWS and then they start consuming higher level services. That adoption next level happens and because it's in the cloud. So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple use cases? >> Sure. Well, there's a couple. One, it's pretty interesting that like you said, as there's more and more bits, you need better and better hardware and networking. And we're super excited about the i4 and the capabilities there in terms of doubling and or tripling what we're doing around lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanzu or with any other container and or services within AWS. So there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is allowed to then consume and use things, for example, with Textract or any other really cool service that has monthly and quarterly innovations. So there's things that you just could not do before that are coming out and saving customers money and building innovative applications on top of their current app base in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too many here. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >> Narayan, what's your perspective from the VMware side? 'Cause you guys have now a lot of headroom to offer customers with Amazon's higher level services and or whatever's homegrown where it's being rolled out 'cause you now have a lot of hybrid too. So what's your take on what's happening in with customers? >> I mean, it's been phenomenal. The customer adoption of this and banks and many other highly sensitive verticals are running production-grade applications, tier one applications on the service over the last five years. And so I have a couple of really good examples. S&P Global is one of my favorite examples. Large bank, they merge with IHS Markit, big conglomeration now. Both customers were using VMware Cloud and AWS in different ways. And with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated 1000 workloads to VMware Cloud and AWS in just six weeks. Pretty phenomenal if you think about everything that goes into a cloud migration process, people process technology. And the beauty of the technology going from VMware point A to VMware point B. The lowest cost, lowest risk approach to adopting VMware Cloud and AWS. So that's one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe, but constantly entering new markets with a limited number of regions and progressing our roadmap. >> It's great to see. I mean, the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. Congratulations. >> One of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're seeing those benefits. If you're running really inefficiently in your own data center, that is not a great use of power. So the actual calculators and the benefits to these workloads are pretty phenomenal just in being more green, which I like. We just all need to do our part there and this is a big part of it here. >> It's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issue is another one. You see that constraints. I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security. I mean, I remember interviewing Steven Schmidt with that AWS and many years ago, this is like 2013 and at that time people were saying, the cloud's not secure. And he's like, listen, it's more secure in the cloud on-premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot, the stay current on the isolation there is hard. So I think the security and supply chain, Fred, is another one. Do you agree? >> I absolutely agree. It's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and have the resources that are available and run them more efficiently. And then like you said on the security point, security is job one. It is the only P1. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >> And Narayan, your point earlier about the managed service patching and being on top of things is really going to get better. All right, final question. I really want to thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I want to end with a curve ball and put you eyes on the spot. We're talking about a new modern shift. We're seeing another inflection point. We've been documenting it. It's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and innovation in the infrastructure side. So the question is for you guys each to answer is, what's the same and what's different in today's market? So it's like we want more of the same here, but also things have changed radically and better here. What's changed for the better and what's still the same thing hanging around that people are focused on? Can you share your perspective? >> I'll tackle it. Businesses are complex and they're often unique, that's the same. What's changed is how fast you can innovate. The ability to combine managed services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about, that's elastic. You could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a rate that most people can't even comprehend and understand the set of services that are available to them. It's really fascinating to see what a one pizza team of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only going to continue to accelerate that. That's my take, Narayan. >> You got a lot of platform to compete on. With Amazon, you got a lot to build on. Narayan, your side. What's your answer to that question? >> I think we are seeing a lot of innovation with new applications that customers are constantly (faintly speaking). I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly build on the agility that developers desire and build all the security and the pipelines to energize that production quickly and efficiently. I think we are seeing, we are at the very start of that sort of journey. Of course, we have invested in Kubernetes, the means to an end, but we're so much more beyond that's happening in industry and I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >> Well, gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on solving these complexities with distractions, whether it's higher level services with large scale infrastructure. At your fingertips, infrastructure as code, infrastructure to be provisioned, serverless, all the good stuff happen and Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator again, being a cloud operator and developer. So the developer ops is kind of, DevOps is changing too. So all for the better. Thank you for spending the time and we're seeing again that traction with the VMware customer base and AWS getting along great together. So thanks for sharing your perspectives. >> We appreciate it. Thank you so much. >> Thank you John. >> This is theCUBE and AWS VMware showcase accelerating business transformation, VMware Cloud on AWS. Jointly engineered solution bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Furrier, your host. Thanks for watching. (gentle music)

(upbeat music) >> Hello everyone, welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE in theCUBE Studios. We've got a special video here. We love when we have startups that are launching. It's an exclusive video of a hot startup that's launching. Got great reviews so far. You know, word on the street is, they got something different and unique. We're going to' dig into it. Amit Govrin who's the CEO and co-founder of Kubiya, which stands for Cube in Hebrew, and they're headquartered in Bay Area and in Tel Aviv. Amit, congratulations on the startup launch and thanks for coming in and talk to us in theCUBE >> Thank you, John, very nice to be here. >> So, first of all, a little, 'cause we love the Cube, 'cause theCUBE's kind of an open brand. We've never seen the Cube in Hebrew, so is that true? Kubiya is? >> Kubiya literally means cube. You know, clearly there's some additional meanings that we can discuss. Obviously we're also launching a KubCon, so there's a dual meaning to this event. >> KubCon, not to be confused with CubeCon. Which is an event we might have someday and compete. No, I'm only kidding, good stuff. I want to get into the startup because I'm intrigued by your story. One, you know, conversational AI's been around, been a category. We've seen chat bots be all the rage and you know, I kind of don't mind chat bots on some sites. I can interact with some, you know, form based knowledge graph, whatever, knowledge database and get basic stuff self served. So I can see that, but it never really scaled or took off. And now with Cloud Native kind of going to the next level, we're starting to see a lot more open source and a lot more automation, in what I call AI as code or you know, AI as a service, machine learning, developer focused action. I think you guys might have an answer there. So if you don't mind, could you take a minute to explain what you guys are doing, what's different about Kubiya, what's happening? >> Certainly. So thank you for that. Kubiya is what we would consider the first, or one of the first, advanced virtual assitants with a domain specific expertise in DevOps. So, we respect all of the DevOps concepts, GitOps, workflow automation, of those categories you've mentioned, but also the added value of the conversational AI. That's really one of the few elements that we can really bring to the table to extract what we call intent based operations. And we can get into what that means in a little bit. I'll save that maybe for the next question. >> So the market you're going after is kind of, it's, I love to hear starters when they, they don't have a Gartner Magic quadrant, they can fit nicely, it means they're onto something. What is the market you're going after? Because you're seeing a lot of developers driving a lot of the key successes in DevOps. DevOps has evolved to the point where, and DevSecOps, where developers are driving the change. And so having something that's developer focused is key. Are you guys targeting the developers, IT buyers, cloud architects? Who are you looking to serve with this new opportunity? >> So essentially self-service in the world of DevOps, the end user typically would be a developer, but not only, and obviously the operators, those are the folks that we're actually looking to help augment a lot of their efforts, a lot of the toil that they're experiencing in a day to day. So there's subcategories within that. We can talk about the different internal developer tools, or platforms, shared services platforms, service catalogs are tangential categories that this kind of comes on. But on top of that, we're adding the element of conversational AI. Which, as I mentioned, that's really the "got you". >> I think you're starting to see a lot of autonomous stuff going on, autonomous pen testing. There's a company out there doing I've seen autonomous AI. Automation is a big theme of it. And I got to ask, are you guys on the business side purely in the cloud? Are you born in the cloud, is it a cloud service? What's the product choice there? It's a service, right? >> Software is a service. We have the classic, Multi-Tenancy SAAS, but we also have a hybrid SAAS solution, which allows our customers to run workflows using remote runners, essentially hosted at their own location. >> So primary cloud, but you're agnostic on where they could consume, how they want to' consume the product. >> Technology agnostic. >> Okay, so that's cool. So let's get into the problem you're solving. So take me through, this will drive a lot of value here, when you guys did the company, what problems did you hone in on and what are you guys seeing as the core problem that you solve? >> So we, this is a unique, I don't know how unique, but this is a interesting proposition because I come from the business side, so call it the top down. I've been in enterprise sales, I've been in a CRO, VP sales hat. My co-founder comes from the bottom up, right? He ran DevOps teams and SRE teams in his previous company. That's actually what he did. So, we met each other halfway, essentially with me seeing a lot of these problems of self-service not being so self-service after all, platforms hitting walls with adoption. And he actually created his own self-service platform, within his last company, to address his own personal pains. So we essentially kind of met with both perspectives. >> So you're absolutely hardcore on self-service. >> We're enabling self-service. >> And that basically is what everybody wants. I mean, the developers want self-service. I mean, that's kind of like, you know, that's the nirvana. So take us through what you guys are offering, give us an example of use cases and who's buying your product, why, and take us through that whole piece. >> Do you mind if I take a step back and say why we believe self-service has somewhat failed or not gotten off. >> Yeah, absolutely. >> So look, this is essentially how we're looking at it. All the analysts and the industry insiders are talking about self-service platforms as being what's going to' remove the dependency of the operator in the loop the entire time, right? Because the operator, that scarce resource, it's hard to hire, hard to train, hard to retain those folks, Developers are obviously dependent on them for productivity. So the operators in this case could be a DevOps, could be a SecOps, it could be a platform engineer. It comes in different flavors. But the common denominator, somebody needs an access request, provisioning a new environment, you name it, right? They go to somebody, that person is operator. The operator typically has a few things on their plate. It's not just attending and babysitting platforms, but it's also innovating, spinning up, and scaling services. So they see this typically as kind of, we don't really want to be here, we're going to' go and do this because we're on call. We have to take it on a chin, if you may, for this. >> It's their child, they got to' do it. >> Right, but it's KTLOs, right, keep the lights on, this is maintenance of a platform. It's not what they're born and bred to do, which is innovate. That's essentially what we're seeing, we're seeing that a lot of these platforms, once they finally hit the point of maturity, they're rolled out to the team. People come to serve themselves in platform, and low and behold, it's not as self-service as it may seem. >> We've seen that certainly with Kubernetes adoption being, I won't say slow, it's been fast, but it's been good. But I think this is kind of the promise of what SRE was supposed to be. You know, do it once and then babysit in the sense of it's working and automated. Nothing's broken yet. Don't call me unless you need something, I see that. So the question, you're trying to make it easier then, you're trying to free up the talent. >> Talent to operate and have essentially a human, like in the loop, essentially augment that person and give the end users all of the answers they require, as if they're talking to a person. >> I mean it's basically, you're taking the virtual assistant concept, or chat bot, to a level of expertise where there's intelligence, jargon, experience into the workflows that's known. Not just talking to chat bot, get a support number to rebook a hotel room. >> We're converting operational workflows into conversations. >> Give me an example, take me through an example. >> Sure, let's take a simple example. I mean, not everyone provisions EC2's with two days (indistinct). But let's say you want to go and provision new EC2 instances, okay? If you wanted to do it, you could go and talk to the assistant and say, "I want to spin up a new server". If it was a human in the loop, they would ask you the following questions: what type of environment? what are we attributing this to? what type of instance? security groups, machine images, you name it. So, these are the questions that typically somebody needs to be armed with before they can go and provision themselves, serve themselves. Now the problem is users don't always have these questions. So imagine the following scenario. Somebody comes in, they're in Jira ticket queue, they finally, their turn is up and the next question they don't have the answer to. So now they have to go and tap on a friend, or they have to go essentially and get that answer. By the time they get back, they lost their turn in queue. And then that happens again. So, they lose a context, they lose essentially the momentum. And a simple access request, or a simple provision request, can easily become a couple days of ping pong back and forth. This won't happen with the virtual assistant. >> You know, I think, you know, and you mentioned chat bots, but also RPA is out there, you've seen a lot of that growth. One of the hard things, and you brought this up, I want to get your reaction to, is contextualizing the workflow. It might not be apparent, but the answer might be there, it disrupts the entire experience at that point. RPA and chat bots don't have that contextualization. Is that what you guys do differently? Is that the unique flavor here? Is that difference between current chat bots and RPA? >> The way we see it, I alluded to the intent based operations. Let me give a tangible experience. Even not from our own world, this will be easy. It's a bidirectional feedback loop 'cause that's actually what feeds the context and the intent. We all know Waze, right, in the world of navigation. They didn't bring navigation systems to the world. What they did is they took the concept of navigation systems that are typically satellite guided and said it's not just enough to drive down the 280, which typically have no traffic, right, and to come across traffic and say, oh, why didn't my satellite pick that up? So they said, have the end users, the end nodes, feed that direction back, that feedback, right. There has to be a bidirectional feedback loop that the end nodes help educate the system, make the system be better, more customized. And that's essentially what we're allowing the end users. So the maintenance of the system isn't entirely in the hands of the operators, right? 'Cause that's the part that they dread. And the maintenance of the system is democratized across all the users that they can teach the system, give input to the system, hone in the system in order to make it more of the DNA of the organization. >> You and I were talking before you came on this camera interview, you said playfully that the Siri for DevOps, which kind of implies, hey infrastructure, do something for me. You know, we all know Siri, so we get that. So that kind of illustrates kind of where the direction is. Explain why you say that, what does that mean? Is that like a NorthStar vision that you guys are approaching? You want to' have a state where everything's automated in it's conversational deployments, that kind of thing. And take us through why that Siri for DevOps is. >> I think it helps anchor people to what a virtual assistant is. Because when you hear virtual assistant, that can mean any one of various connotations. So the Siri is actually a conversational assistant, but it's not necessarily a virtual assistant. So what we're saying is we're anchoring people to that thought and saying, we're actually allowing it to be operational, turning complex operations into simple conversations. >> I mean basically they take the automate with voice Google search or a query, what's the score of the game? And, it also, and talking to the guy who invented Siri, I actually interviewed on theCUBE, it's a learning system. It actually learns as it gets more usage, it learns. How do you guys see that evolving in DevOps? There's a lot of jargon in DevOps, a lot of configurations, a lot of different use cases, a lot of new technologies. What's the secret sauce behind what you guys do? Is it the conversational AI, is it the machine learning, is it the data, is it the model? Take us through the secret sauce. >> In fact, it's all the above. And I don't think we're bringing any one element to the table that hasn't been explored before, hasn't been done. It's a recipe, right? You give two people the same ingredients, they can have complete different results in terms of what they come out with. We, because of our domain expertise in DevOps, because of our familiarity with developer workflows with operators, we know how to give a very well suited recipe. Five course meal, hopefully with Michelin stars as part of that. So a few things, maybe a few of the secret sauce element, conversational AI, the ability to essentially go and extract the intent of the user, so that if we're missing context, the system is smart enough to go and to get that feedback and to essentially feed itself into that model. >> Someone might say, hey, you know, conversational AI, that was yesterday's trend, it never happened. It was kind of weak, chat bots were lame. What's different now and with you guys, and the market, that makes a redo or a second shot at this, a second bite at the apple, as they say. What do you guys see? 'Cause you know, I would argue that it's, you know, it's still early, real early. >> Certainly. >> How do you guys view that? How would you handle that objection? >> It's a fair question. I wasn't around the first time around to tell you what didn't work. I'm not afraid to share that the feedback that we're getting is phenomenal. People understand that we're actually customizing the workflows, the intent based operations to really help hone in on the dark spots. We call it last mile, you know, bottlenecks. And that's really where we're helping. We're helping in a way tribalize internal knowledge that typically hasn't been documented because it's painful enough to where people care about it but not painful enough to where you're going to' go and sit down an entire day and document it. And that's essentially what the virtual assistant can do. It can go and get into those crevices and help document, and operationalize all of those toils. And into workflows. >> Yeah, I mean some will call it grunt work, or low level work. And I think the automation is interesting. I think we're seeing this in a lot of these high scale situations where the talented hard to hire person is hired to do, say, things that were hard to do, but now harder things are coming around the corner. So, you know, serverless is great and all this is good, but it doesn't make the complexity go away. As these inflection points continue to drive more scale, the complexity kind of grows, but at the same time so is the ability to abstract away the complexity. So you're starting to see the smart, hired guns move to higher, bigger problems. And the automation seems to take the low level kind of like capabilities or the toil, or the grunt work, or the low level tasks that, you know, you don't want a high salaried person doing. Or I mean it's not so much that they don't want to' do it, they'll take one for the team, as you said, or take it on the chin, but there's other things to work on. >> I want to add one more thing, 'cause this goes into essentially what you just said. Think about it's not the virtual system, what it gives you is not just the intent and that's one element of it, is the ability to carry your operations with you to the place where you're not breaking your workflows, you're actually comfortable operating. So the virtual assistant lives inside of a command line interface, it lives inside of chat like Slack, and Teams, and Mattermost, and so forth. It also lives within a low-code editor. So we're not forcing anyone to use uncomfortable language or operations if they're not comfortable with. It's almost like Siri, it travels in your mobile phone, it's on your laptop, it's with you everywhere. >> It makes total sense. And the reason why I like this, and I want to' get your reaction on this because we've done a lot of interviews with DevOps, we've met at every CubeCon since it started, and Kubernetes kind of highlights the value of the containers at the orchestration level. But what's really going on is the DevOps developers, and the CICD pipeline, with infrastructure's code, they're basically have a infrastructure configuration at their disposal all the time. And all the ops challenges have been around that, the repetitive mundane tasks that most people do. There's like six or seven main use cases in DevOps. So the guardrails just need to be set. So it sounds like you guys are going down the road of saying, hey here's the use cases you can bounce around these use cases all day long. And just keep doing your jobs cause they're bolting on infrastructure to every application. >> There's one more element to this that we haven't really touched on. It's not just workflows and use cases, but it's also knowledge, right? Tribal knowledge, like you asked me for an example. You can type or talk to the assistant and ask, "How much am I spending on AWS, on US East 1, on so and so customer environment last week?", and it will know how to give you that information. >> Can I ask, should I buy a reserve instances or not? Can I ask that question? 'Cause there's always good trade offs between buying the reserve instances. I mean that's kind of the thing that. >> This is where our ecosystem actually comes in handy because we're not necessarily going to' go down every single domain and try to be the experts in here. We can tap into the partnerships, API, we have full extensibility in API and the software development kit that goes into. >> It's interesting, opinionated and declarative are buzzwords in developer language. So you started to get into this editorial thing. So I can bring up an example. Hey cube, implement the best service mesh. What answer does it give you? 'Cause there's different choices. >> Well this is actually where the operator, there's clearly guard rails. Like you can go and say, I want to' spin up a machine, and it will give you all of the machines on AWS. Doesn't mean you have to get the X one, that's good for a SAP environment. You could go and have guardrails in place where only the ones that are relevant to your team, ones that have resources and budgetary, you know, guidelines can be. So, the operator still has all the control. >> It was kind of tongue in cheek around the editorialized, but actually the answer seems to be as you're saying, whatever the customer decided their service mesh is. So I think this is where it gets into as an assistant to architecting and operating, that seems to be the real value. >> Now code snippets is a different story because that goes on to the web, that goes onto stock overflow, and that's actually one of the things. So inside the CLI, you could actually go and ask for code snippets and we could actually go and populate that, it's a smart CLI. So that's actually one of the things that are an added value of that. >> I was saying to a friend and we were talking about open source and how when I grew up, there was no open source. If you're a developer now, I mean there's so much code, it's not so much coding anymore as it is connecting and integrating. >> Certainly. >> And writing glue layers, if you will. I mean there's still code, but it's not, you don't have to build it from scratch. There's so much code out there. This low-code notion of a smart system is interesting 'cause it's very matrix like. It can build its own code. >> Yes, but I'm also a little wary with low-code and no code. I think part of the problem is we're so constantly focused on categories and categorizing ourselves, and different categories take on a life of their own. So low-code no code is not necessarily, even though we have the low-code editor, we're not necessarily considering ourselves low-code. >> Serverless, no code, low-code. I was so thrown on a term the other day, architecture-less. As a joke, no we don't need architecture. >> There's a use case around that by the way, yeah, we do. Show me my AWS architecture and it will build the architect diagram for you. >> Again, serverless architect, this is all part of infrastructure's code. At the end of the day, the developer has infrastructure with code. Again, how they deploy it is the neuron. That's what we've been striving for. >> But infrastructure is code. You can destroy, you know, terraform, you can go and create one. It's not necessarily going to' operate it for you. That's kind of where this comes in on top of that. So it's really complimentary to infrastructure. >> So final question, before we get into the origination story, data and security are two hot areas we're seeing fill the IT gap, that has moved into the developer role. IT is essentially provisioned by developers now, but the OP side shifted to large scale SRE like environments, security and data are critical. What's your opinion on those two things? >> I agree. Do you want me to give you the normal data as gravity? >> So you agree that IT is now, is kind of moved into the developer realm, but the new IT is data ops and security ops basically. >> A hundred percent, and the lines are so blurred. Like who's what in today's world. I mean, I can tell you, I have customers who call themselves five different roles in the same day. So it's, you know, at the end of the day I call 'em operators 'cause I don't want to offend anybody because that's just the way it is. >> Architectural-less, we're going to' come back to that. Well, I know we're going to' see you at CubeCon. >> Yes. >> We should catch up there and talk more. I'm looking forward to seeing how you guys get the feedback from the marketplace. It should be interesting to hear, the curious question I have for you is, what was the origination story? Why did you guys come together, was it a shared problem? Was it a big market opportunity? Was it an itch you guys were scratching? Did you feel like you needed to come together and start this company? What was the real vision behind the origination? Take a take a minute to explain the story. >> No, absolutely. So I've been living in Palo Alto for the last couple years. Previous, also a founder. So, you know, from my perspective, I always saw myself getting back in the game. Spent a few years in AWS essentially managing partnerships for tier one DevOps partners, you know, all of the known players. Some in public, some of them not. And really the itch was there, right. I saw what everyone's doing. I started seeing consistency in the pains that I was hearing back, in terms of what hasn't been solved. So I already had an opinion where I wanted to go. And when I was visiting actually Israel with the family, I was introduced by a mutual friend to Shaked, Shaked Askayo, my co-founder and CTO. Amazing guy, unbelievable technologists, probably one the most, you know, impressive folks I've had a chance to work with. And he actually solved a very similar problem, you know, in his own way in a previous company, BlueVine, a FinTech company where he was head of SRE, having to, essentially, oversee 200 developers in a very small team. The ratio was incongruent to what the SRE guideline would tell. >> That's more than 10 x rate developer. >> Oh, absolutely. Sure enough. And just imagine it's four different time zones. He finishes day shift and you already had the US team coming, asking for a question. He said, this is kind of a, >> Got to' clone himself, basically. >> Well, yes. He essentially said to me, I had no day, I had no life, but I had Corona, I had COVID, which meant I could work from home. And I essentially programed myself in the form of a bot. Essentially, when people came to him, he said, "Don't talk to me, talk to the bot". Now that was a different generation. >> Just a trivial example, but the idea was to automate the same queries all the time. There's an answer for that, go here. And that's the benefit of it. >> Yes, so he was able to see how easy it was to solve, I mean, how effective it was solving 70% of the toil in his organization. Scaling his team, froze the headcount and the developer team kept on going. So that meant that he was doing some right. >> When you have a problem, and you need to solve it, the creativity comes out of the woodwork, you know, invention is the mother of necessity. So final question for you, what's next? Got the launch, what are you guys hope to do over the next six months to a year, hiring? Put a plug in for the company. What are you guys looking to do? Take a minute to share the future vision and get a plug in. >> A hundred percent. So, Kubiya, as you can imagine, announcing ourselves at CubeCon, so in a couple weeks. Opening the gates towards the public beta and NGA in the next couple months. Essentially working with dozens of customers, Aston Martin, and business earn in. We have quite a few, our website's full of quotes. You can go ahead. But effectively we're looking to go and to bring the next operator, generation of operators, who value their time, who value the, essentially, the value of tribal knowledge that travels between organizations that could be essentially shared. >> How many customers do you guys have in your pre-launch? >> It's above a dozen. Without saying, because we're actually looking to onboard 10 more next week. So that's just an understatement. It changes from day to day. >> What's the number one thing people are saying about you? >> You got that right. I know it's, I'm trying to be a little bit more, you know. >> It's okay, you can be cocky, startups are good. But I mean they're obviously, they're using the product and you're getting good feedback. Saving time, are they saying this is a dream product? Got it right, what are some of the things? >> I think anybody who doesn't feel the pain won't know, but the folks who are in the trenches, or feeling the pain, or experiencing this toil, who know what this means, they said, "You're doing this different, you're doing this right. You architected it right. You know exactly what the developer workflows," you know, where all the areas, you know, where all the skeletons are hidden within that. And you're attending to that. So we're happy about that. >> Everybody wants to clone themselves, again, the tribal knowledge. I think this is a great example of where we see the world going. Make things autonomous, operationally automated for the use cases you know are lock solid. Why wouldn't you just deploy? >> Exactly, and we have a very generous free tier. People can, you know, there's a plugin, you can sign up for free until the end of the year. We have a generous free tier. Yeah, free forever tier, as well. So we're looking for people to try us out and to give us feedback. >> I think the self-service, I think the point is, we've talked about it on the Cube at our events, everyone says the same thing. Every developer wants self-service, period. Full stop, done. >> What they don't say is they need somebody to help them babysit to make sure they're doing it right. >> The old dashboard, green, yellow, red. >> I know it's an analogy that's not related, but have you been to Whole Foods? Have you gone through their self-service line? That's the beauty of it, right? Having someone in a loop helping you out throughout the time. You don't get confused, if something's not working, someone's helping you out, that's what people want. They want a human in the loop, or a human like in the loop. We're giving that next best thing. >> It's really the ratio, it's scale. It's a scaling. It's force multiplier, for sure. Amit, thanks for coming on, congratulations. >> Thank you so much. >> See you at KubeCon. Thanks for coming in, sharing the story. >> KubiyaCon. >> CubeCon. Cube in Hebrew, Kubiya. Founder, co-founder and CEO here, sharing the story in the launch. Conversational AI for DevOps, the theory of DevOps, really kind of changing the game, bringing efficiency, solving a lot of the pain points of large scale infrastructure. This is theCUBE, CUBE conversation, I'm John Furrier, thanks for watching. (upbeat electronic music)

(upbeat music) >> Welcome back everyone to theCUBE's coverage of VMware Explore '22, formerly VMworld. This is our 12th year covering it. I'm John Furrier with Dave Vellente. Two sets, three days of wall-to-wall coverage. We're starting to get the execs rolling in from VMware. Sumit Dhawan, president of VMware's here. Great to see you. Great keynote, day one. >> Great to be here, John. Great to see you, Dave. Day one, super exciting. We're pumped. >> And you had no problem with the keynotes. We're back in person. Smooth as silk up there. >> We were talking about it. We had to like dust off a cobweb to make some of these inputs. >> It's not like riding a bike. >> No, it's not. We had about 40% of our agencies that we had to change out because they're no longer in business. So, I have to give kudos to the team who pulled it together. They did a fabulous job. >> You do a great check, great presentation. I know you had a lot to crack in there. Raghu set the table. I know this is for him, this was a big moment to lay out the narrative, address the Broadcom thing right out of the gate, wave from Hock Tan in the audience, and then got into the top big news. Still a lot of meat on the bone. You get up there, you got to talk about the use cases, vSphere 8, big release, a lot of stuff. Take us through the keynote. What was the important highlights for you to share, the folks watching that didn't see the keynote or wanted to get your perspective? >> Well, first of all, did any of you notice that Raghu was running on the stage? He did not do that in rehearsal. (John chuckles) I was a little bit worried, but he really did it. >> I said, I betcha that was real. (everyone chuckles) >> Anyways, the jokes aside, he did fabulous. Lays out the strategy. My thinking, as you said, was to first of all speak with their customers and explain how every enterprise is facing with this concept of cloud chaos that Raghu laid out and CVS Health story sort of exemplifies the situation that every customer is facing. They go in, they start with cloud first, which is needed, I think that's the absolutely right approach. Very quickly build out a model of getting a cloud ops team and a platform engineering team which oftentimes be a parallel work stream to a private cloud infrastructure. Great start. But as Roshan, the CIO at CVS Health laid out, there's an inflection point. And that's when you have to converge these because the use cases are where stakeholders, this is the lines of businesses, app developers, finance teams, and security teams, they don't need this stove piped information coming at 'em. And the converge model is how he opted to organize his team. So we called it a multi-cloud team, just like a workspace team. And listen, our commitment and innovations are to solve the problems of those teams so that the stakeholders get what they need. That's the rest of the keynote. >> Yeah, first of all, great point. I want to call out that inflection point comment because we've been reporting coming into VMworld with super cloud and other things across open source and down into the weeds and into the hood. The chaos is real. So, good call. I love how you guys brought that up there. But all industry inflection points, if you go back in history of the tech industry, at every single major inflection point, there was chaos, complexity, or an enemy proprietary. However you want to look at it, there was a situation where you needed to kind of reign in the chaos as Andy Grove would say. So we're at that inflection point, I think that's consistent. And also the ecosystem floor yesterday, the expo floor here in San Francisco with your partners, it was vibrant. They're all on this wave. There is a wave and an inflection point. So, okay. I buy that. So, if you buy the inflection point, what has to happen next? Because this is where we're at. People are feeling it. Some say, I don't have a problem but they're cut chaos such is the problem. So, where do you see that? How does VMware's team organizing in the industry and for customers specifically to solve the chaos, to reign it in and cross over? >> Yeah, you're a 100% right. Every inflection point is associated with some kind of a chaos that had to be reigned in. So we are focused on two major things right now which we have made progress in. And maybe third, we are still work in-progress. Number one is technology. Today's technology announcements are directly to address how that streamlining of chaos can be done through a cloud smart approach that we laid out. Our Aria, a brand new solution for management, significant enhancements to Tanzu, all of these for public cloud based workloads that also extend to private cloud. And then our cloud infrastructure with newer capabilities with AWS, Azure, as well as with new innovations on vSphere 8 and vSAN 8. And then last but not the least, our continuous automation to enable anywhere workspace. All these are simple innovation that have to address because without those innovations, the problem is that the chaos oftentimes is created because lack of technology and as a result structure has to be put in place because tooling and technology is not there. So, number one goal we see is providing that. Second is we have to be independent, provide support for every possible cloud but not without being a partner of theirs. That's not an easy thing to do but we have the DNA as a company, we have done that with data centers in the past, even though being part of Dell we did that in the data center in the past, we have done that in mobility. And so we have taken the challenge of doing that with the cloud. So we are continually building newer innovation and stronger and stronger partnerships with cloud provider which is the basis of our commercial relationships with Microsoft Azure too, where we have brought Azure VMware solution into VMware cloud universal. Again, that strengthens the value of us being neutral because it's very important to have a Switzerland party that can provide these multi-cloud solutions that doesn't have an agenda of a specific cloud, yet an ecosystem, or at least an influence with the ecosystem that can bring going forward. >> Okay, so technology, I get that. Open, not going to be too competitive, but more open. So the question I got to ask you is what is the disruptive enabler to make that happen? 'Cause you got customers, partners and team of VMware, what's the disruptive enabler that's going to get you to that level? >> Over the hump. I mean, listen, our value is this community. All this community has one of two paths to go. Either, they become stove piped into just the public-private cloud infrastructure or they step up as this convergence that's happening around them to say, "You know what? I have the solution to tame this multi-cloud complexity, to reign the chaos," as you mentioned because tooling and technologies are available. And I know they work with the ecosystem. And our objective is to bring this community to that point. And to me, that is the best path to overcome it. >> You are the connective tissue. I was able to sit into the analyst meeting today. You were sort of the proxy for CVS Health where you talked about the private that's where you started, the public cloud ops team, bringing that together. The platform is the glue. That is the connective tissue. That's where Tanzu comes in. That's where Aria comes in. And that is the disruptive technology which it's hard to build that. >> From a technology perspective, it's an enabler of something that has never been done before in that level of comprehensiveness, from a more of a infrastructure side thinking perspective. Yes, infrastructure teams have enabled self-service portals. Yes, infrastructure teams have given APIs to developers, but what we are enabling through Tanzu is completely next level where you have a lot richer experience for developers so that they never ever have to think about the infrastructure at all. Because even when you enable infrastructure as API, that's still an API of the infrastructure. We go straight to the application tier where they're just thinking about authorized set of microservices. Containers can be orchestrated and built automatically, shifting security left where we're truly checking them or enabling them to check the security vulnerabilities as they're developing the application, not going into the production when they have to touch the infrastructure. To me, that's an enabler of a special power that this new multi-cloud team can have across cloud which they haven't had in the past. >> Yeah, it's funny, John, I'd say very challenging technically. The challenge in 2010 was the software mainframe, remember the marketing people killed that term. >> Yeah, exactly. >> But you think about that. We're going to make virtualization and the overhead associated with that irrelevant. We're going to be able to run any workload and VMware achieved that. Now you're saying we run anything anywhere, any Kubernete, any container. >> That's the reality. That's the chaos. >> And the cloud and that's a new, real problem. Real challenging problem that requires serious engineering. >> Well, I mean it's aspirational, right? Let's get the reality, right? So true spanning cloud, not yet there. You guys, I think your vision is definitely right on in the sense that we'd like the chaos and multicloud's a reality. The question is AWS, Azure, Google Cloud, other clouds, they're not going to sit still. No one's going to let VMware just come up and take everything. You got to enable so the market- >> True, true. I don't think this is the case of us versus them because there is so much that they have to express in terms of the value of every cloud. And this happened in the case of, by the way, whether you go into infrastructure or even workspace solutions, as long as the richest of the experience and richest of the controls are provided, for their cloud to the developers that makes the adoption of their cloud simpler. It's a win-win for every party. >> That's the key. I think the simplest. So, I want to ask you, this comes up a lot and I love that you brought that up, simple and self-service has proven developers who are driving the change, cloud DevOps developers. They're driving the change. They're in charge more than ever. They want self-service, easier to deploy. I want a test, if I don't like it, I want to throw it away. But if I like something, I want to stick with it. So it's got to be self-service. Now that's antithetical to the old enterprise model of solve complexity with more complexity. >> Yeah, yeah. >> So the question for you is as the president of VMware, do you feel good that you guys are looking out over the landscape where you're riding into the valley of the future with the demand being automation, completely invisible, abstraction layer, new use case scenarios for IT and whatever IT becomes. Take us through your mindset there, because I think that's what I'm hearing here at this year, VMware Explorer is that you guys have recognized the shift in demographics on the developer side, but ops isn't going away either. They're connecting. >> They're connected. Yeah, so our vision is, if you think about the role of developers, they have a huge influence. And most importantly they're the ones who are driving innovation, just the amount of application development, the number of developers that have emerged, yet remains the scarcest resource for the enterprise are critical. So developers often time have taken control over decision on infrastructure and ops. Why? Because infrastructure and ops haven't shown up. Not because they like it. In fact, they hate it. (John chuckles) Developers like being developers. They like writing code. They don't really want to get into the day to day operations. In fact, here's what we see with almost all our customers. They start taking control of the ops until they go into production. And at that point in time, they start requesting one by one functions of ops, move to ops because they don't like it. So with our approach and this sort of, as we are driving into the beautiful valley of multi-cloud like you laid out, in our approach with the cross cloud services, what we are saying is that why don't we enable this new team which is a reformatted version of the traditional ops, it has the platform engineering in it, the key skill that enables the developer in it, through a platform that becomes an interface to the developers. It creates that secure workflows that developers need. So that developers think and do what they really love. And the infrastructure is seamless and invisible. It's bound to happen, John. Think about it this way. >> Infrastructure is code. >> Infrastructure has code, and even next year, it's invisible because they're just dealing with the services that they need. >> So it's self-service infrastructure. And then you've got to have that capability to simplified, I'll even say automated or computational governance and security. So Chris Wolf is coming on Thursday. >> Yeah. >> Unfortunately I won't be here. And he's going to talk about all the future projects. 'Cause you're not done yet. The project narrows, it's kind of one of these boring, but important. >> Yeah, there's a lot of stuff in the oven coming out. >> There's really critical projects coming down the pipeline that support this multi-cloud vision, is it's early days. >> Well, this is the thing that we were talking about. I want to get your thoughts on. And we were commenting on the keynote review, Hock Tan bought VMware. He's a lot more there than he thought. I mean, I got to imagine him sitting in the front row going there's some stuff coming out of the oven. I didn't even, might not have known. >> He'd be like, "Hmm, this extra value." (everyone chuckles) >> He's got to be pretty stoked, don't you think? >> He is, he is. >> There's a lot of headroom on the margin. >> I mean, independent to that, I think the strategy that he sees is something that's compelling to customers which is what, in my assessment, speaking with him, he bought VMware because it's strategic to customers and the strategic value of VMware becomes even higher as we take our multi-cloud portfolio. So it's all great. >> Well, plus the ecosystem is now re-energize. It's always been energized, but energized cuz it's sort of had to be, cuz it's such a strong- >> And there was the Dell history there too. >> But, yeah it was always EMC, and then Dell, and now it's like, wow, the ecosystem's- >> Really it's released almost. I like this new team, we've been calling this new ops kind of vibe going refactored ops, as you said, that's where the action's happening because the developers want to go faster. >> They want to go faster. >> They want to go fast cuz the velocity's paying off of them. They don't want to have to wait. They don't want security reviews. They want policy. They want some guardrails. Show me the track. >> That's it. >> And let me drive this car. >> That's it because I mean think about it, if you were a developer, listen, I've been a developer. I never really wanted to see how to operate the code in production because it took time away for developing. I like developing and I like to spend my time building the applications and that's the goal of Aria and Tanzu. >> And then I got to mention the props of seeing project Monterey actually come out to fruition is huge because that's the future of computing architecture. >> I mean at this stage, if a customer from here on is modernizing their infrastructure and they're not investing in a holistic new infrastructure from a hardware and software perspective, they're missing out an opportunity on leveraging the numbers that we were showing, 20% increase in calls. Why would you not just make that investment on both the hardware and the software layer now to get the benefits for the next five-six years. >> You would and if I don't have to make any changes and I get 20% automatically. And the other thing, I don't know if people really appreciate the new curve that the Silicon industry is on. It blows away the history of Moore's law which was whatever, 35-40% a year, we're talking about 100% a year price performance or performance improvements. >> I think when you have an inflection point as we said earlier, there's going to be some things that you know is going to happen, but I think there's going to be a lot that's going to surprise people. New brands will emerge, new startups, new talent, new functionality, new use cases. So, we're going to watch that carefully. And for the folks watching that know that theCUBE's been 12 years with covering VMware VMworld, now VMware Explore, we've kind of met everybody over the years, but I want to point out a little nuance, Raghu thing in the keynote. During the end, before the collective responsibility sustainment commitment he had, he made a comment, "As proud as we are," which is a word he used, there's a lot of pride here at VMware. Raghu kind of weaved that in there, I noticed that, I want to call that out there because Raghu's proud. He's a proud product guy. He said, "I'm a product guy." He's delivering keynote. >> Almost 20 years. >> As proud as we are, there's a lot of pride at VMware, Sumit, talk about that dynamic because you mentioned customers, your customer is not a lot of churn. They've been there for a long time. They're embedded in every single company out there, pretty much VMware is in every enterprise, if not all, I mean 99%, whatever percentage it is, it's huge penetration. >> We are proud of three things. It comes down to number one, we are proud of our innovations. You can see it, you can see the tone from Raghu or myself, or other executives changes with excitement when we're talking about our technologies, we're just proud. We're just proud of it. We are a technology and product centric company. The second thing that sort of gets us excited and be proud of is exactly what you mentioned, which is the customers. The customers like us. It's a pleasure when I bring Roshan on stage and he talks about how he's expecting certain relationship and what he's viewing VMware in this new world of multi-cloud, that makes us proud. And then third, we're proud of our talent. I mean, I was jokingly talking to just the events team alone. Of course our engineers do amazing job, our sellers do amazing job, our support teams do amazing job, but we brought this team and we said, "We are going to get you to run an event after three years from not they doing one, we're going to change the name on you, we're going to change the attendees you're going to invite, we're going to change the fact that it's going to be new speakers who have never been on the stage and done that kind of presentation. >> You're also going to serve a virtual audience. >> And we're going to have a virtual audience. And you know what? They embraced it and they surprised us and it looks beautiful. So I'm proud of the talent. >> The VMware team always steps up. You never slight it, you've got great talent over there. The big thing I want to highlight as we end this day, the segment, and I'll get your thoughts and reactions, Sumit, is again, you guys were early on hybrid. We have theCUBE tape to go back into the video data lake and find the word hybrid mentioned 2013, 2014, 2015. Even when nobody was talking about hybrid. >> Yeah, yeah. >> Multicloud, Raghu, I talked to Raghu in 2016 when he did the Pat Gelsinger, I mean Raghu, Pat and Andy Jassy. >> Yeah. >> When that cloud thing got cleared up, he cleared that up. He mentioned multicloud, even then 2016, so this is not new. >> Yeah. >> You had the vision, there's a lot of stuff in the oven. You guys make announcements directionally, and then start chipping away at it. Now you got Broadcom buys VMware, what's in the oven? How much goodness is coming out that's like just hitting the fruits are starting to bear on the tree. There's a lot of good stuff and just put that, contextualize and scale that for us. What's in the oven? >> First of all, I think the vision, you have to be early to be first and we believe in it. Okay, so that's number one. Now having said that what's in the oven, you would see us actually do more controls across cloud. We are not done on networking side. Okay, we announced something as project Northstar with networking portfolio, that's not generally available. That's in the oven. We are going to come up with more capability on supporting any Kubernetes on any cloud. We did some previews of supporting, for example, EKS. You're going to see more of those cluster controls across any Kubernetes. We have more work happening on our telco partners for enablement of O-RAN as well as our edge solutions, along with the ecosystem. So more to come on those fronts. But they're all aligned with enabling customers multi-cloud through these five cross cloud services. They're all really, some of them where we have put a big sort of a version one of solution out there such as Aria continuation, some of them where even the version one's not out and you're going to see that very soon. >> All right. Sumit, what's next for you as the president? You're proud of your team, we got that. Great oven description of what's coming out for the next meal. What's next for you guys, the team? >> I think for us, two things, first of all, this is our momentum season as we call it. So for the first time, after three years, we are now being in, I think we've expanded, explored to five cities. So getting this orchestrated properly, we are expecting nearly 50,000 customers to be engaging in person and maybe a same number virtually. So a significant touchpoint, cuz we have been missing. Our customers have departed their strategy formulation and we have departed our strategy formulation. Getting them connected together is our number one priority. And number two, we are focused on getting better and better at making customers successful. There is work needed for us. We learn, then we code it and then we repeat it. And to me, those are the two key things here in the next six months. >> Sumit, thank you for coming on theCUBE. Thanks for your valuable time, sharing what's going on. Appreciate it. >> Always great to have chatting. >> Here with the president, the CEO's coming up next in theCUBE. Of course, we're John and Dave. More coverage after the short breaks, stay with us. (upbeat music)

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

>>Yeah. Hello and welcome to the Cubes Presentation of Women in Tech Global Event Celebrating International Women's Day I'm John for a host of the Cube. We had a great guest in Cuba. Alumni Veranda re vice president. Commercial sales for Europe, Middle East and Africa. EMEA at AWS Amazon Web service to great to see you. Thank you for coming in all the way across the pond and the US to Palo Alto from London. >>Thank you, John. Great to see you again. I'm super excited to be part of this particularly special event. >>Well, this is a celebration of International Women's Day. It's gonna continue throughout the rest of the year, and every day is International Women's Day. But you're actually international. Your women in Tech had a great career. We talk that reinvent. Let's step back and walk through your career. Highlights to date. What have been some of the key things in your career history that you can share? >>Uh, thanks, John. It's always nice to reflect on this, you know? Look, I the way I would classify my career. First of all, it's very it's been very international. I was born and raised in India I went to study in the US It was always a dream to go do that. I did my masters in Boston University. I then worked in the U S. For a good 17 years across A number of tech, uh, tech companies in particular, started my career at McKinsey in the very early days and then moved on to work for E M. C. You'll you'll probably remember them, John. Very well, of course, There now, Del um And then I moved over to Europe. So I've spent the last 18 years here in Europe. Um, and that's been across a couple of different things. I I always classify. Half my career has been strategy, transformation, consulting, and the other half of my career is doing the real job of actually running operations. And I've been, you know, 12 15 years in the tech and telecom sector had the excitement of running Schneider Electric's business in the UK Denniston and Private Equity went back to McKinsey Boomerang, and then a W s called me, and how could I possibly refuse that? So it's been really exciting, I think the one big take away when I reflect on my career is. I've always had this Northstar about leading a business someday, and then I've sort of through my career master set of skills to be able to do that. And I think that's probably what you see. Very eclectic, very mobile, very international and cross industry. Uh, in particular. >>I love the strategy and operations comment because they're both fun, but they're different ones. Very execution, tactical operating. The business strategy is kind of figuring out the future of the 20 mile stare. You know, playing that chess match, so to speak, all great skills and impressive. But I have to ask you, what got you in the tech sector? Why technology? >>Well, so you know, in some ways I kind of fell into it, John, right? Because when I was growing up, my father was always in the tech space, so he had a business and fax machines and he was a reseller of cannon. If you remember Cannon, um, and microfilm equipment and I grew up around him, and he was a real entrepreneur. I mean, always super visionary about new things that were coming out. And so as I followed him around, I said, I kind of wanna be him. And it's a little bit about that sort of role model right early in your career. And then when I moved to the U. S. To study again, it wasn't like I thought I was gonna go to attack. I mean, I wasn't an engineer, you know. I grew up in India with economics degree. That's when women went into We didn't necessarily go into science. But when I joined McKinsey in the early days, I ended up working with, you know, the big companies of the days. You know, the IBMs, the E M. C. Is the Microsoft the oracles, etcetera. So I just then began to love, love the innovation, always being on the sort of bleeding edge. Um, and I guess it was a little bit just fascinating for me not being an engineer to learn how technology had all these applications in terms of how businesses advanced. So I guess, Yeah, that's kind of why I still think it around with it. It's interesting >>how you mentioned how you at that time you pipeline into economics, which is math. Of course. Uh, math is needed for economics, but also the big picture and This is one of the conversation we're having, Uh, this year, the breaking down the barriers for women in tech. Now there's more jobs you don't You don't need to have one pathway into into science or, you know, we're talking stem versus steam arts are super important, being creative. So the barriers to get in are being removed. I mean, if you think about the surface area for technology. So I got to ask you, what barriers do you think Stop girls and young women the most in considering a career in Tech? >>I've got to start with role models, John. Right? Because I think a number of us grew up, by the way, being the only not having the allies in the business, right? All of us, all the all the managers and hiring people are males rather than females. And the fact of the matter is, we didn't have this sort of he for she movement. And I think that's the biggest barrier is not having enough role models and positive role models in the business. I can tell you that research shows that actually, when you have female role models, you tend to hire more and actually what employees say is they feel more supportive when they have actually female managers. So I think there are lots of goodness, but we just need to accelerate how many role models we have. I think the other things I will say to you as well is, if you look at just the curriculum and the ability to get women into stem, right, I mean, we need to have colleges, universities, schools also encouraging women into stem. And you've probably heard about our programme. You know, it's something we do to encourage girls into stem. I think it's really important that teachers and others are actually encouraging girls to do math, for example, right? It's not just about science. Math is great. Logic is great, by the way. Philosophy is great. I just love what you said. I think increasingly, the EQ and EQ parts have to come together, and I think that's what women excel at. Um, so I think that's another very, very big carrier, and then the only other thing I will say is we're gonna watch the language we use, like when I think about job descriptions, they tend to be very male oriented languages we look at CVS now, if you haven't been a female in tech for a long time, your CV isn't going to show a lot of tech, is it? So for recruiters out there, look for competencies. Look for capabilities. You mentioned strategy and arts earlier. We have this leadership principles, As you know, John, really well, think big and dive deep, right? That strategy and operations. And so I think we we need to recruit for that. And we need to recruit for culture. And we need to recruit for people with ambition, an aspiration and not always Just look at 20 years of experience because you're not gonna find it. So I think those are some of the big barriers. Um, that I that I at least think, is stopping women from getting into town. But the biggest one is not enough women at the top hiring women. >>I think people want to see themselves, or at least an aspirational version of what they could be. And I think that's only gonna get better. Lots changed. A lot has happened over the years, but now, with technology in everyone's life, covid pulled forward a lot of realities. You know, the current situation in Europe where you're you are now has pulled forward a lot of realities around community, cyber, digital, our lives. And I think this opens up new positions, clearly cybersecurity. And I'm sure the job boards in every company is hiring people that didn't exist years ago, but also this new problems to solve. So the younger generation coming up, um, is gonna work on these problems, and they need to have role models. So what's your reaction to that? You know, new problems are opportunities their new so usually solved by probably the next generation. Uh, they need mentors. All this kind of works together. What's your reaction? >>Yeah, and, you know, let me pick up on something we're doing that I think is really important. I think you have to address age on the pipeline problem, you know, because they're just is a pipeline problem, you know, at the end of the day, And by that, what I mean is, we need to have more and more people with the and I'm not gonna use the word engineering or science. I'm going to use the word digital skills, right? And I think what we've we've committed to doing, John, you know, I'm very proud of this is we said we're gonna train 29 people 29 million people around this world on digital skills for free by 2025. Right, That's gonna help us get that pipeline going. The other thing we do is something called Restart where we actually do 12 weeks of training for the under, employed and under served right and underrepresented communities. And that means in 12 weeks we can get someone. And you know, this case I talk to you about this before I love it. Fast food operator to cloud, right? I mean, that's that's what I call changing the game on pipeline. But But here's the other stand. Even if the pipeline is good and we often see that the pipeline can be as much as 50% at the very early career women, by the time you get into the C suite, you're not a 50 anymore. You're less than 20%. So the other big thing John there, and this comes back to the types of roles you have an opportunities you create. We've got to pull women through the pipeline. We've really got to encourage that there are sponsors and not just mentors. I think women are sorry to say this over mentored and under sponsored. We need more people say I'm gonna open the door for you and create the opportunity I had that advantage. I hit people through my career. By the way, they were all men, right? Who actually stood out there and bang on the door and said, Okay, Tunisia is gonna go do this. And my first break I remember was having done strategy all my life when the CEO come into the room and you said, You're gonna better locks and you're gonna go run the P and L in Benelux and I almost fainted because I thought, Oh, my God, I've never run a PNR before But it's that type of risk taking that's going to be critical. And I think we've got to train our leaders and our managers to have those conversations be the sponsors, get that unconscious bias training. We all have it. Every single one of us has it. I think those are the combinations of things that are going to actually help open the door and make a see that Actually, it's not just about coding. It's actually about sales. It's about marketing. It's about product management. It's about strategy. It's about sales operations. It's about really, really thinking differently about your customers, right? And that's the thing that I think is attractive about technology. And you know what? Maybe that leads you to eventually become a coder. Or maybe not. Maybe you enter from coding, but those are all the range is available to you in technology, which is not good at advertising, >>that there's more applications than ever before. But I love your comment about over mentoring and under sponsored. Can you quickly just define the difference between those two support elements sponsoring versus, uh, mentoring sponsoring >>So mentors And by the way they can range from my son is my mentor, you know, is a great reverse mentor. By the way, I really encourage you to have the reverse mentoring going. So many mentors are people from all walks of your life, right? And you should have, you know, half a dozen of those. At least I think right who are going to be able to help you deal with situations, help coach you give you feedback respond to concerns You're having find ways for you to navigate all the stuff you need, by the way. Right? And feedback the gift we need that sponsors. It's not about the feedback. Necessarily. It's people who literally will create opportunities for you. Mentors don't necessarily do that. Sponsors will say you You know what? We got the phone. Call John and say, John, I've got the perfect person for you. You need to go speak to her. That's the big difference. John and a couple of sponsors. It's not about many, >>and that's where the change happens. I love that comment. Good call. I'm glad I could double down on that. Now that you have the environment, pipeline and working, you have the people themselves in the environment getting better sponsors and mentors, hopefully working more and more together. But once they're in the environment, they still got to be part of it. So as girls and young women and to the working sector for tech, what advice would you give them? Because now they're in the game there in the arena. So what advice would you give them? Because the environments they are now >>yeah, yeah. I mean, Gosh, John, it's you know, you've lived your career in this space. It's an exciting place to be right. Um, it's a growth opportunity. And I think that's a really important point because the more you enter sectors where there's a lot of growth and I would say hyper right growth, that's just gonna open the doors to so many more things. If you're in a place where it's all about cost cutting and restructuring, do you know what? It's super hard to really compete and have fun, right? And as we say, make history. So it's an exciting place. Today's world transformation equals digital transformation, right? So tech is the place to be, because tech is about transformation, Right? So coming in here, the one advice I would give you is Just do it because believe me, there's so much you can do, like take the risk, find someone is going to give you that entree point and get in the door right? And look, you know what's the worst that could happen? The worst that could happen is you don't like it. Fine. There's lots of other things than to go to. So my advice is, you know, don't take the mm. The really bad tips I've received in my career, right? Don't let people tell you you can't do it. You're not good enough. You don't have the experience, right? It's a male's world. You're a woman. It's all about you and not about EQ. Because that's just rubbish, Frankly, right. The top tip I was ever given was actually to take the risk and go for it. And that was my father. And then all these other sponsors I've had around the way. So that's that's the one thing I would say. The other thing I will say to you is the reason I advise it and the reason you should go for it. It's purposeful. Technology is changing our lives, you know, And we will all live to be no longer. 87 I think 100 right? And so you have the opportunity to change the course of the world by coming to technology. The vaccine deployment John was a great example, right? Without cloud, we couldn't have launch these vaccines as fast as we did. Right? Um, so I think there's a tonne of purpose. You've got to get in and then you've got to find. As I said, those sponsors, you've got to find those mentors. You've got to not worry about vertical opportunities and getting promoted. You gotta worry about horizontal opportunities, right? And doing the things that I needed to get the skills that you require, right? I also say one thing. Um, don't Don't let people tell you not to speak up, not to express your opinion. Do all of the above be authentic, Be authentic style. You will see more role models. Many, many more role models are gonna come out in tech that are going to be female role models. And actually, the men are really stepping up to the role models. And so we will be better together. And here's the big thing. We need you. We can do this without women. There's no possible way that we will be able to deliver on the absolute incredible transformation we have ahead of us without you. >>Inclusion, Diversity equity. These are force multipliers for companies. If applied properly, it's competitive advantage. And so breaking the bias. The theme this year is super super important. It sounds like common sense, but the reality is you break the bias It's not just women as men, as all of us. What can we do? Better to bring that force multiplier capabilities and competitive advantage of inclusion, diversity, equity to business. >>So the first thing I would say and my doctor used to always tell me this if it hurts, don't do it right. I would say to you just do it. Get diverse teams in place because if you have diverse teams, you have diversity of thought. You don't have to worry as much about bias because, you know, you've got the people around the table who actually represent the world. We also do something really cool. We have something called biassed busters. And so in meetings we have bias borders. People are going to, like, raise their hand and say, I'm not sure that that was really meant the way it was supposed to be, So I think that's just a nice little mechanism that we have here, Um, in a W s that helps. The other thing I would say to you is being your authentic self. You can't be a man and mentioned be women, and you're not gonna replicate somebody else because you're never gonna succeed if you do that, you know? So I would say be your authentic self all of the time, You know, we know. We know that women are sometimes labelled as aggressive when they're really not. Don't worry about it. It's not personal. I think the main thing you have to do is and I advise women all the time Is calibrate the feedback you're getting okay? Don't catastrophizing it right. Calibrate it. Taken in, you don't have to react to every feedback in the world, right? And make sure that you're also conscious of your own biases, right? So I think those are my Those are my two cents John for what they were for breaking device. I love the thing. >>Be yourself, You know, Don't take it too personal. Have some fun. That's life. That's a life lesson. Um, Final question, while I got you here, you're a great inspiration, and you're a great role model. You're running a very big business for Amazon web services. Europe, Middle East and Africa is a huge territory. It's its own thing. It's It's like you're bigger than some companies out there. Your role in your organisation. What's the hot area out there you were talking before camera. That's emerging areas that you're focused on. People are watching this young women, young ladies around the world. We're gonna look at this and say, What wave should I jump on? What's the hot things happening in in Europe? Middle Eastern Africa? >>I think the three things I would mention and I'm sure there's I'm sure, John, as we've spoken to my peers across the other gos, right, there are some similarities. The very, very hot thing right now is sustainability. Um, and you know, people are really building sustainability into their strategy. It's no longer sort of just an E S G goal in itself. It's actually very much part of changing the way they do business. So I think that's the hard part. And that's why again, I think it's a phenomenal place to be. I think the other big thing that we're absolutely talking about a lot is, and you know, this is getting even more complicated right now is just around security and cyber security and where that's going and how can we be really thinking about how we address some of these concerns that are coming out and I think there's There's something. There's a lot to be said about the way we build our infrastructure in terms of that context. So I think that's the second one. I think the third one is. People are really looking at technology to change the way businesses operate. So how does HR operate? How do you improve your employee value proposition? How do you do marketing in the next generation? How do you do finance in the next generation? So across the business is no longer the place of I t. It really is about changing the way we are as businesses and all of us becoming tech companies at the core. So the big thing there, John, is data data at the heart of everything we do data not because it's there in front of you, but data because you can actually make decisions on the back of it. So those are the things, Um, I seem to come across a lot more than anything else. >>It's always great to talk to you, your senior leader at AWS, um, inspirational to many. And thank you for taking the time to speak with us here on this great event. Women in text. Global Celebration of International Women's Day. Thank you so much for your time. >>Thank you, John. Always great to talk to you. >>We will definitely be keeping in touch More storeys to be had and we're gonna bring it to you. This is the cubes continuing presentation of women in tech. A global event celebrating International Women's Day. I'm John for your host. Thanks for watching. Yeah.

(tranquil music) >> Alation was an early pioneer in solving some of the most challenging problems in so-called big data. Founded early last decade, the company's metadata management and data catalog have always been considered leading examples of modern tooling by customers and analysts alike. Governance is one area that customers identified as a requirement to extend their use of Alation's platform. And it became an opportunity for the company to expand its scope and total available market. Alation is doing just that today, announcing new data governance capabilities, and partner integrations that align with the market's direction of supporting federated governance. In other words, a centralized view of policy to accommodate distributed data in this world of an ever expanding data cloud, which we talk about all the time in theCUBE. And with me to discuss these trends and this announcement is Satyen Sangani, who's the CEO and co-founder of Alation. Satyen, welcome back to the CUBE. Good to see you. >> Thank you Dave, It's great to be back. >> Okay, so you heard my open, please tell us about the patterns that you were seeing in the market and what you were hearing from customers that led you in this direction and then we'll get into the announcement. >> Yeah, so I think there are really two patterns, right? I mean, when we started building this notion of a data catalog, as you said a decade ago, there was this idea that metadata management broadly classified was something that belonged in IT, lived in IT and was essentially managed by IT, right? I always liken it to kind of an inventory management system within a warehouse relative to Amazon.com, which has obviously broadly published for the business. And so, with the idea of bringing all of this data directly to the business and allowing people arbitrarily, depending on their role to use the data. You know, you saw one trend, which was just this massive, shift in how much data was available at any given time. I think the other thing that happened was that at the same time, data governance went through a real transitionary phase where there was a lot of demand often spurred by regulations. Whether that's GDPR, CCPA or more recently than that, certainly the Basel accord. And if you think about all of those regulations, people had to get something in a place. Now what we ended up finding out was when we were selling in to add accounts, people would say, well guess what? I've got this data governance thing going on, but nobody's really using it. I built this business glossary, it's been three years. Nothing's been really very effective. And we were never able to get the value and we need to get value because there are so many more people now accessing and using and leveraging the data. And so with that, we started really considering whether or not we needed to build a formal capability in the market. And that's what we're today that we're doing. >> I liked the way you framed that. And if you think back, we were there as you were in the early big day-to-days. And all the talk was about volume, variety and velocity. And those are sort of IT concepts. How do you deal with all these technical challenges? And then the fourth V which you just mentioned was value. And that's where the line of business really comes in. So let's get into the news. What are you announcing today? >> So we're announcing a new application on top of Alation's Catalog platform, which is an Alations data governance application. That application will be released with our 2021.3 release on September 14th. And what's exciting about that is that we are going to now allow customers to discreetly and elegantly and quickly consume a new application to get data governance regimes off the ground and initiatives off the ground, much more quickly than they've ever been able to do. This app is really all about time to value. It's about allowing customers to be able to consume what they need when they need it in order to be able to get successful governance initiatives going. And so that's what we're trying to deliver. >> So maybe you could talk a little bit about how you think about data governance and specifically your data governance approach. And maybe what's different about Alation's solution. >> Yeah, I think there's a couple of things that are different. I think the first thing that's most critically different is that we move beyond this notion of sort of policy declaration into the world of policy application and policy enforcement, right? I think a lot of data governance regimes basically stand up and say, look you know, it's all about people and then process and then technology. And what we need to do is declare who all the governors are and who all the stewards are. And then we're going to get all our policies in the same place and then the business will follow them. And the reality is people don't change their workflows to go off and arbitrarily follow some data governance policy that they don't know exists, or they don't want to actually have to follow up. And so really what you've got to do is make sure that the policy and the knowledge exists as in where the data exists. And that's why it's so critical to build governance into the catalog. And so what we're doing here is we're basically saying, look, you could declare policies with a new policy center inside of Alation. Those policies will get automatically created in some cases by integrating with technologies like Snowflake. But beyond that, what we're also doing is we're saying, look, we're going to move into the world of taking those policies and applying them to the data on an automated basis using ML and AI and basically saying that now it doesn't have to be some massive boil the ocean three-year regime to get very little value in a very limited business loss rate. Rather all of your data sets, all of your terms can be put into a single place on an automated basis. That's constantly being used by people and constantly being updated by the new systems that are coming online. And that's what's exciting about it. >> So I just want to follow up on that. So if I'm hearing you correctly, it's the humans are in the loop, but it's not the only source of policy, right? The machines are assisting. And in some cases managing end-to-end that policy. Is that right? >> You've got it. I think the the biggest challenge with data governance today is that it basically relies a little bit like the Golden Gate Bridge. You know, you start painting it and by the time you're done painting it, you've got to go back and start painting it again, because it relies upon people. And there's just too much change in the weather and there's too much traffic and there's just too much going on in the world of data. And frankly in today's world, that's not even an apt analogy because often what happens is midway through. You've got to restart painting from the very beginning because everything's changed. And so there's so much change in the IT landscape that the traditional way of doing data governance just doesn't work. >> Got it, so in winning through the press release, three things kind of stood out. I wonder if we could unpack them, there were multi-cloud, governance and security. And then of course the AI or what I like to call machine intelligence in there. And what you call the people centric approach. So I wonder if we could dig in into these and help us understand how they fit together. So thinking about multi-cloud governance, how do you think about that? Why is that so challenging and how are you solving that problem? >> Yeah, well every cloud technology provider has its own set of capabilities and platforms. And often those slight differences are causing differences in how those technologies are adopted. And so some teams optimize for certain capabilities and certain infrastructure over others. And that's true even within businesses. And of course, IT teams are also trying to diversify their IT portfolios. And that's another reason to go multi-cloud. So being able to have a governance capability that spans, certainly all of the good grade called megascalers, but also these new, huge emerging platforms like Snowflake of course and others. Those are really critical capabilities that are important for our customers to be able to get a handle on top of. And so this idea of being cloud agnostic and being able to sort of have a single control plane for all of your policies, for all of your data sets, that's a critical must have in a governance regime today. So that's point number one. >> Okay and then the machine learning piece, the AI, you're obviously injecting that into the application, but maybe tell us what that means both maybe technically and from a business stand point. >> Yeah, so this idea of a data policy, right? Can be sometimes by operational teams, but basically it's a set of rules around how one should and should not be able to use data, right? And so those are great rules. It could be that people who are in one country shouldn't be able to access the data of another country, very simple role, right? But how do you actually enforce that? Like you can declare it, but if there is a end point on a server that allows you to access the data, the policy is effectively moot. And so what you got to go do is make sure that at the point of leverage or at the point of usage, people know what the policy happens to be. And that's where AI come in. You can say let's document all the data sets that happened to be domiciled in Korea or in China. And therefore make sure that those are arbitrarily segregated so that when people want to use that as datasets, they know that the policy exists and they know that it's been applied to that particular dataset. That's somewhere where AI and ML can be super valuable rather than a human being trying to document thousands of databases or tens of thousands of data sets, which is really kind of a (mumbles) exercise. And so, that application of automation is really critical and being able to do governance at the scale that most enterprises have to do it. >> You got it 'cause humans just can't do that at scale. Now what do you mean by people-centric approach? Can you explain that? >> Yeah, often what I find with governance is that there's this notion of kind of there's this heavy notion of how one should deal with the data, right? So often what I find is that there are certain folks who think, oh well, we're going to declare the rules and people are just going to follow them. And if you've ever been well, a parent or in some cases seeing government operate, you realize that that actually isn't how things work. And involve them in how things are run. And if you do that, right? You're going to get a lot more success in how you apply rules and procedures because people will understand that and people know why they exist. And so what we do within this governance regime is we basically say, look, we want to make sure that the people who are using the data, leveraging the data are also the people who are stewarding the data. There shouldn't be a separate role of data steward that is arbitrarily defined off, just because you've been assigned to a job that you never wanted to do. Rather it should be a part of your day job. And it should be something that you do because you really want to do it. And it's a part of your workflow. And so this idea of being people centric is all about how do you engage the analyst, the product managers, the sales operation managers, to document those sales data sets and those product data sets. So that in fact, those people can be the ones who are answering the questions, not somebody off to the side who knows nothing about the data. >> Yeah, I think you've talked in previous CUBE interviews about context and that really fits to this discussion. So these capabilities are part of an application, which is what? it's a module onto your existing platform. And it's sort of it's a single platform, right? I mean, we're not bespoke products. Maybe you can talk about that. >> Yeah, that's exactly right. I mean, it's funny because we've evolved and built a relation with a lot of capability. I mean, interestingly we're launching this data governance application but I would say 60% of our almost 300 customers would say they do a form or a significant part of data governance, leveraging relations. So it's not like we're new to this market. We've been selling in this market for years. What's different though, is that we've talked a lot about the catalog as a platform over the last year. And we think that that's a really important concept because what is a platform? It's a capability that has multiple applications built on top of it, definitionally. And it's also a capability where third party developers can leverage APIs and SDKs to build applications. And thirdly, it has all of the requisite capabilities and content. So that those application developers, whether it's first party from Alation or third party can really build those applications efficiently, elegantly and economically well. And the catalog is a natural platform because it contains all of the knowledge of the datasets. And it has all of the people who might be leveraging data in some fundamental way. And so this idea of building this data governance module allows a very specialized audience of people in governance to be able to leverage the full capabilities of the platform, to be able to do their work faster, easier, much more simply and easily than they ever could have. And that's why we're so excited about this launch, because we think it's one example of many applications, whether it's ourselves building it or third parties that could be done so much more elegantly than it previously could have been. Because we have so much knowledge of the data and so much knowledge of how the company operates. >> Irrespective of the underlying cloud platform is what I heard before. >> irrespective of the underlying cloud platform, because the data as you know, lives everywhere. It's going to live in AWS, it's going to live in Snowflake. It's going to live on-premise inside of an Oracle database. That's not going to be changed. It's going to live in Teradata. It's going to live all over the place. And as a consequence of that, we've got to be able to connect to everything and we've got to be able to know everything. >> Okay, so that leads me to another big part of the announcement, which is the partnership and integration with Snowflake. Talk about how that came about. I mean, why snowflake? How should customers think about the future of data management. In the context of this relationship, obviously Snowflake talks about the data cloud. I want to understand that better and where you fit. >> Yeah, so interestingly, this partnership like most great partnerships was born in the field. We at the late part of last year had observed with Snowflake that we were in scores of their biggest accounts. And we found that when you found a really, really large Snowflake engagement, often you were going to be complementing that with a reasonable engagement with Alation. And so seeing that pattern as we were going out and raising our funding route at the beginning of this year, we basically found that Snowflake obviously with their Snowflake Ventures Investment arm realized how strategic having a great answer in the governance market happened to be. Now there are other use cases that we do with Snowflake. We can certainly get into those. But what we realized was that if you had a huge scale, Snowflake engagement, governance was a rate limiter to customers' ability to grow faster. And therefore also Snowflake's ability to grow faster within that account. And so we worked with them to not only develop a partnership but much more critically a roadmap that was really robust. And so we're now starting to deliver on that roadmap and are super excited to share a lot of those capabilities in this release. And so that means that we're automatically ingesting policies and controls from Snowflake into Alation, giving full transparency into both setting and also modifying and understanding those policies for anybody. And so that gives you another control plane through which to be able to manage all of the data inside of your enterprise, irrespective of how many instances of Snowflake you have and irrespective of how many controls you have available to you. >> And again, on which cloud runs on. So I want to follow up with that really interesting because Snowflake's promise of the data cloud, is it essentially abstracts the underlying complexity of the cloud. And I'm trying to understand, okay, how much of this is vision, how much is is real? And it's fine to have a Northstar, but sometimes you get lost in the marketing. And then the other part of the promise, and of course, big value proposition is data sharing. I mean, I think they've nailed that use case, but the challenge when you start sharing data is federated governance. And as well, I think you mentioned Oracle, Teradata that stuff's not all in the cloud, a lot of that stuff on-prem and you guys can deal with that as well. So help us sort of to those circles, if you can. Where do you fit into that equation? >> I think, so look, Snowflake is a magical technology and in the sense that if you look at the data, I mean, it reveals a very, very clear story of the ability to adopt Snowflake very quickly. So any data team with an organization can get up and running with the Snowflake instance with extraordinary speed and capability. Now that means that you could have scores, hundreds of instances of Snowflake within a single institution. And to the extent that you want to be able to govern that data to your point, you've got to have a single control plane through which you can manage all of those various instances. Whether they're combined or merged or completely federated and distinct from each other. Now, the other problem that comes up on governance is also discoverability. If you have all these instances, how do you know what the right hand is doing if the left hand is working independently of it? You need some way to be able to coordinate that effort. And so that idea of discoverability and governance is really the value proposition that Alation brings to the table. And the idea there is that people can then can get up and running much more quickly because, hey, what if I want to spin up a Snowflake instance, but there's somebody else, two teams over those already solved the problem or has the data that I need? Well, then maybe I don't even need to do that anymore. Or maybe I can build on top of that work to be able to get to even better outcome even faster. And so that's the sort of kind of one plus one equals three equation that we're trying to build with them. >> So that makes sense and that leads me to one of my favorite topics with the notion is this burgeoning movement around the concept of a data mesh in it. In other words, the notion that increasingly organizations are going to push to decentralize their data architectures and at the same time support a centralized policy. What do you think about this trend? How do you see Alation fitting in? >> Yeah, maybe in a different CUBE conversation. We can talk a little bit about my sort of stylized history of data, but I've got this basic theory that like everybody started out what sort of this idea of a single source of truth. That was a great term back in the 90s where people were like, look, we just need to build a single source of truth and we can take all of our data and physically land it up in a single place. And when we do that, it's going to all be clean, available and perfect. And we'll get back to the garden of Eden, right? And I think that idea has always been sort of this elusive thing that nobody's ever been able to really accomplish, right? Because in any data environment, what you're going to find is that if people use data, they create more data, right? And so in that world, you know, like that notion of centralization is always going to be fighting this idea of data sprawl. And so this concept of data mesh I think is, you know, there's formal technical definitions. But I'll stick with maybe a very informal one, which is the one that you offered. Which is just sort of this decentralized mode of architecture. You can't have decentralization if nobody knows how to access those different data points, 'cause otherwise they'll just have copies and sprawl and rework. And so you need a catalog and you need centralized policies so that people know what's available to them. And people have some way of being able to get conformed data. Like if you've got data spread out all over the place, how do you know which is the right master? How do you know what's the right customer record? How do you know what's your right chart of accounts? You've got to have services that exist in order to be able to find that stuff and to be able to leverage them consistently. And so, to me the data mesh is really a continuation of this idea, which the catalog really enabled. Which is if you can build a single source of reference, not a single source of truth, but a single place where people can find and discover the data, then you can govern a single plane and you can build consistent architectural rules so that different services can exist in a decentralized way without having to sort of bear all the costs of centralization. And I think that's a super exciting trend 'cause it gives power back to people who want to use the data more quickly and efficiently. >> And I think as we were talking about before, it's not about just the IT technical aspects, hey, it works. It's about putting power in the hands of the lines of business. And a big part of the data mesh conversation is around building data products and putting context or putting data in the hands of the people who have the context. And so it seems to me that Alation, okay, so you could have a catalog that is of the line of businesses catalog, but then there's an Uber catalog that sort of rolls up. So you've got full visibility. It seems that you've fit perfectly into that data mesh. And whether it's a data hub, a data warehouse, data lake, I mean, you don't care. I mean, that's just another node that you can help manage. >> That's exactly right. I mean, it's funny because we all look at these market scapes where people see these vendor landscapes of 500 or 800 different data and AI and ML and data architecture vendors. And often I get asked, well, why doesn't somebody come along and like consolidate all this stuff? And the reality is that tools are a reflection of how people think. And when people have different problems and different sets of experiences, they're going to want to use the best tool in order to be able to solve their problem. And so the nice thing about having a mesh architecture is you can use whatever tool you want. You just have to expose your data in a consistent way. And if you have a catalog, you can be able to have different teams using different infrastructure, different tools, different fundamental methods of building the software. But as long as they're exposing it in a consistent way, it doesn't matter. You don't necessarily need to care how it's built. You just need to know that you've got good data available to you. And that's exactly what a catalog does. >> Well, at least your catalog. I think the data mesh, it should be tools that are agnostic. And I think there are certain tools that are, I think you guys started with that principle. Not every data catalog is going to enable that, but I think that is the trend Satyen. And I think you guys have always fit into that. It's just that I think you were ahead of the time. Hey, we'll give you the last word. Give us the closing thoughts and bring us home. >> Well, I mean that's exactly right. Like, not all the catalogs are created equal and certainly not all governance is created equal. And I think most people say these words and think that are simple to get into. And then it's a death by a thousand cuts. I was literally on the phone with a chief data officer yesterday of a major distributor. And they basically said, look, like we've got sprawl everywhere. We've got data everywhere. We've got it in every type of system. And so having that sophistication turned into something that's actually easy to use is a super hard problem. And it's the one that we're focused on every single day that we wake up and every single night when we go to sleep. And so, that's kind of what we do. And we're here to make governance easy, to make data discovery easy. Those are the things that we hold our hats on. And we're super excited to put this release out 'cause we think it's going to make customers so much more capable of building on top of the problems that they've already solved. And that's what we're here to do. >> Good stuff, Satyen. Thanks so much, congratulations on the announcement and great to see you again. >> You too, Dave. Great talking. >> All right, thanks for watching this CUBE conversation. This is Dave Vellante, we'll see you next time. (tranquil music)

>>Okay, >>listen, we're gearing up for the start of the snowflake Data Cloud Summit, and we wanna go back to the early roots of Snowflake. We've got some of the founding engineers here. Abdul Monir, Ashish Motive, Allah and Alison Lee There three individuals that were at snowflake in the early years and participated in many of the technical decisions that led to the platform and is making snowflake famous today. Folks, great to see you. Thanks so much for taking some time out of your busy schedules. Hey, it's gotta be really gratifying. Thio, See this platform that you've built, you know, taking off and changing businesses. So I'm sure it was always smooth sailing. Right? There were. There were no debates. Wherever. >>I've never seen an engineer get into the bed. >>Alright, So seriously so take us back to the early days. You guys, you know, choose whoever wants to start. But what was it like early on? We're talking 2013 here, right? >>When I think back to the early days of Snowflake, I just think of all of us sitting in one room at the time. You know, we just had an office that was one room with, you know, 12 or 13 engineers sitting there clacking away on our keyboards, uh, working really hard, turning out code, uh, punctuated by you know, somebody asking a question about Hey, what should we do about this, or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we're doing. >>So so Abdul it was just kind of heads down headphones on, just coating or e think there was >>a lot of talking and followed by a lot of typing. Andi, I think there were periods of time where where you know, anyone could just walk in into the office and probably out of the office and all the here is probably people, uh, typing away at their keyboards. And one of my member vivid, most vivid memories is actually I used to sit right across from Alison, and there's these huge to two huge monitor monitors between us and I would just here typing away in our keyboard, and sometimes I was thinking and and and, uh and all that type and got me nervous because it seemed like Alison knew exactly what what, what she needed to do, and I was just still thinking about it. >>So she she was just like bliss for for you as a developer engineer was it was a stressful time. What was the mood? So when you don't have >>a whole lot of customers, there's a lot of bliss. But at the same time, there was a lot of pressure on us to make sure that we build the product. There was a time line ahead of us. We knew we had to build this in a certain time frame. Um, so one thing I'll add to what Alison and Abdulle said is we did a lot of white boarding as well. There are a lot of discussions, and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune, and and there we have it. >>Yes, so I mean, it is a really exciting time doing any start up. But when you know when you have to make decisions and development, invariably you come to a fork in the road. So I'm curious as to what some of those forks might have been. How you guys decided You know which fork to take. Was there a Yoda in the room that served as the Jedi master? I mean, how are those decisions made? Maybe you could talk about that a little bit. >>Yeah, that's an interesting question. And I think one of a Zai think back. One of the memories that that sticks out in my mind is is this, uh, epic meeting and one of our conference rooms called Northstar. Many of our conference rooms are named after ski resorts because the founders, they're really into skiing. And that's why that's where the snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was It was the sign up flow and and there were a few different options on the table and and and one of the options that that people were gravitating Teoh, one of the founders, didn't like it and and on, and they said a few times that there's this makes no sense. There's no other system in the world that does it this way, and and I think one of the other founders said, uh, that's exactly why we should do it this way. And or at least seriously, consider this option. So I think there was always this, um, this this, uh, this tendency and and and this impulse that that we needed to think big and think differently and and not see the world the way it is but the way we wanted it to be and then work our way backwards and try to make it happen. >>Alison, Any fork in the road moments that you remember. >>Well, I'm just thinking back to a really early meeting with sheesh! And and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our our column metadata. Andi, I think it's funny that you that you mentioned Yoda because we often make jokes about one of our founders. Teary Bond refer to him as Yoda because he hasn't its tendency to say very concise things that kind of make you scratch your head and say, Wow, why didn't I think of that? Or you know, what exactly does that mean? I never thought about it that way. So I think when I think of the Yoda in the room, it was definitely Terry, >>uh, excuse you. Anything you can add to this, this conversation >>I'll agree with Alison on the you're a comment for short. Another big fork in the road, I recall, was when we changed. What are meta store where we store our own internal metadata? We used >>to use >>a tool called my sequel and we changed it. Thio another database called Foundation TV. I think that was a big game changer for us. And, you know, it was a tough decision. It took us a long time. For the longest time, we even had our own little branch. It was called Foundation DB, and everybody was developing on that branch. It's a little embarrassing, but, you know, those are the kind of decisions that have altered altered the shape of snowflake. >>Yeah. I mean, these air, really, you know, down in the weeds, hardcore stuff that a lot of people that might not be exposed to What would you say was the least obvious technical decision that you had to make it the time. And I wanna ask you about the most obvious to. But what was the what was the one that was so out of the box? I mean, you kind of maybe mentioned it a little bit before, but what if we could double click on that? >>Well, I think one of the core decisions in our architectures the separation of compute and storage on Do you know that is really court architecture. And there's so many features that we have today, um, for instance, data sharing zero copy cloning that that we couldn't have without that architecture. Er, um and I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work on being able Thio have that architecture and still get great performance. >>Anything? Yeah, anything that was, like, clearly obvious, that is, Maybe that maybe that was the least and the most that that separation from computing story because it allowed you toe actually take advantage of cloud native. But But was there an obvious one that, you know, it's sort of dogma that you, you know, philosophically lived behind. You know, to this day, >>I think one really obvious thing, um is the sort of no tuning, no knobs, ease of use story behind snowflake. Andi and I say it's really obvious because everybody wants their system to be easy to use. But then I would say there are tons of decisions behind that, that it's not always obvious three implications of of such a choice, right, and really sticking to that. And I think that that's really like a core principle behind Snowflake that that led to a lot of non obvious decisions as a result of sticking to that principle. So, yeah, I >>think to add to that now, now you've gotten us thinking I think another really interesting one was was really, um, should we start from scratch or or should we use something that already exists and and build on top of that? And I think that was one of these, um, almost philosophical kind of stances that we took that that a lot of the systems that were out there were the way they were because because they weren't built for the for the platforms that they were running on, and the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were gonna build it from scratch, and we weren't gonna borrow a single line of code from many other database out there. And this was something that really shocked a lot of people and and many times that this was pretty crazy and it waas. But this is how you build great products. >>That's awesome. All right. She should give you the last word. We got, like, just like 30 seconds left to bring us home >>Your till date. Actually, one of those said shocks people when you talk to them and they say, Wow, you're not You're not really using any other database and you build this entirely yourself. The number of people who actually can build a database from scratch are fairly limited. The group is fairly small, and so it was really a humongous task. And as you mentioned, you know, it really changed the direction off how we design the database. What we what does the database really mean? Tow us right the way Snowflake has built a database. It's really a number of organs that come together and form the body and That's also a concept that's novel to the database industry. >>Guys, congratulations. You must be so proud. And, uh, there's gonna be awesome watching the next next decade, so thank you so much for sharing your stories. >>Thanks, dude. >>Thank you.

>> Okay listen, we're gearing up for the start of the Snowflake Data Cloud Summit. And we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Munir, Ashish Motivala and Allison Lee. They're three individuals that were at Snowflake, in the early years and participated in many of the technical decisions. That led to the platform and is making Snowflake famous today. Folks great to see you. Thanks so much for taking some time out of your busy schedules. >> Thank you for having us- >> Same. >> It's got to be really gratifying to see this platform that you've built, taking off and changing businesses. So I'm sure it was always smooth sailing, right? There were no debates, where there ever? >> I've never seen an engineer get into a debate. >> Yeah alright, so seriously. So take us back to the early days, you guys choose whoever wants to start, but what was it like, early on we're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake. I just think of all of us sitting in one room at the time, we just had an office that was one room with 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code punctuated by somebody asking a question about hey, what should we do about this? Or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we were doing. >> So, Abdul was it just kind of heads down, headphones on just coding or? >> I think there was a lot of talking and followed by a lot of typing. And I think there were periods of time where anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away their keyboards. And one of my most vivid memory is actually I used to sit right across from Allison and there was these two huge monitors between us. And I would just hear her typing away at her keyboard. And sometimes I was thinking and all that typing got me nervous because it seemed like Allison knew exactly what she needed to do. And I was just still thinking about it. >> So Ashish was this like bliss for you as a developer or an engineer? Or was it a stressful time? What was the mood? >> Then when you don't have a whole lot of customers, there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us. We knew we had to build this in a certain timeframe. So one thing I'll add to what Allison and Abdul said is, we did a lot of whiteboarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune and there we have it. >> Yeah, it is a really exciting time. We can do it any start-up. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided which fork to take. Was there a Yoda in the room that served as the Jedi Master? How are those decisions made? Maybe you could talk about that a little bit. >> That's an interesting question. And as I think back one of the memories that sticks out in my mind is this epic meeting in one of our conference rooms called Northstar and many of our conference rooms are named after ski resorts because the founders are really into skiing. And that's where the Snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was the sign up flow and there were a few different options on the table. And one of the options that people were gravitating to, one of the founders didn't like it. And they said a few times that this makes no sense. There's no other system in the world that does it this way. And I think one of the other founders said, that's exactly why we should do it this way or at least seriously consider this option. So, I think there was always this tendency and this impulse that we needed to think big and think differently and not see the world the way it is, but the way we wanted it to be and then work our way backwards and try to make it happen. >> Allison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our column metadata. And I think it's funny that you that you mentioned Yoda, because we often make jokes about one of our founders Thierry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, wow, why didn't I think of that? Or what exactly does that mean? I never thought about it that way. So, when I think of the Yoda in the room, it was definitely Thierry, >> Ashish is there anything you can add to this conversation? >> I'll agree with Allison on the Yoda comment for sure. Another big fork in the road I recall was when we changed one of our meadow store, where we store and are willing to try and metadata. We used to use a tool called my SQL and we changed it to another database called foundation DV. I think that was a big game changer for us. And it was a tough decision. It took us a long time, for the longest time we even had our own little branch it was called foundation DV and everybody was developing on that branch, it's a little embarrassing but those are the kinds of decisions that have altered the shape of Snowflake. >> Yeah, these are really down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? You kind of maybe mentioned it a little bit before, but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage that is really core to our architecture. And there's so many features that we have today, for instance data sharing, zero-copy cloning, that we couldn't have without that architecture. And I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly- >> Yeah, anything that was like clearly obvious, maybe that was the least and the most that separation from compute and store, 'cause it allowed you to actually take advantage of cloud native, but was there an obvious one that is it sort of dogma that you philosophically live behind to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious the implications of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake that led to a lot of non-obvious decisions as a result of sticking to that principle. >> To wrap to that now you've gotten us thinking, I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that. And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were because they weren't built for the platforms that they were running on. And the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were going to build it from scratch and we weren't going to borrow a single line of code from any other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy. And it was, but this is how you build great products. >> That's awesome, all right, Ashish give your last word, we got like just 30 seconds left take, bring us home. >> Till date actually one of those that shocks people when you talk to them and they say, wow, you're not really using any other database? And you build this entirely yourself? The number of people who actually can build a database from scratch are fairly limited. The group is fairly small. And so it was really a humongous task. And as you've mentioned, it really changed the direction of how we designed the database. What does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks Dave. >> Thank you- >> Thank you.

>>from around the globe If the cube with digital coverage of M I t. Chief data officer and Information quality symposium brought to you by Silicon Angle Media >>Hello, everyone. This is Day Volonte and welcome back to our continuing coverage of the M I t. Chief Data Officer CDO I Q event Interpol Bhandari is here. He's a leading voice in the CDO community and a longtime Cubillan Interpol. Great to see you. Thanks for coming on for this. Especially >>program. My pleasure. >>So when you you and I first met, you laid out what I thought was, you know, one of the most cogent frameworks to understand what a CDO is job was where the priority should be. And one of those was really understanding how, how, how data contributes to the monetization of station aligning with lines of business, a number of other things. And that was several years ago. A lot of change since then. You know, we've been doing this conference since probably twenty thirteen and back then, you know, Hadoop was coming on strong. A lot of CEOs didn't want to go near the technology that's beginning to change. CDOs and cto Zehr becoming much more aligned at the hip. The reporting organizations have changed. But I love your perspective on what you've observed as changing in the CDO roll over the last half decade or so. >>Well, did you know that I became chief data officer in two thousand six? December two thousand and six And I have done this job four times four major overnight have created of the organization from scratch each time. Now, in December of two thousand six, when I became chief data officer, there were only four. Chief Data Officer, uh, boom and I was the first in health care, and there were three, three others, you know, one of the Internet one and credit guns one and banking. And I think I'm the only one actually left standing still doing this job. That's a good thing or a bad thing. But like, you know, it certainly has allowed me to love the craft and then also scripted down to the level that, you know, I actually do think of it purely as a craft. That is. I know, going into a mutual what I'm gonna do. They were on the central second. No, the interesting things that have unfolded. Obviously, the professions taken off There are literally thousands off chief data officers now, and there are plenty off changes. I think the main change, but the job is it's, I think, a little less daunting in terms off convincing the senior leadership that it's need it because I think the awareness at the CEO level is much, much, much better than what it waas in two thousand six. Across the world. Now, having said that, I think it is still only awareness and don't think that there's really a deep understanding of those levels. And so there's a lot off infusion, which is why you will. You kind of think this is my period. But you saw all these professions take off with C titles, right? Chief Data officer, chief analytics officer, chief digital officer and chief technology officer. See, I off course is being there for a long time. And but I think these newer see positions. They're all very, very related, and they all kind of went to the same need which had to do with enterprise transformation, digital transformation, that enterprises chief digital officer, that's another and and people were all trying to essentially feel the elephants and they could only see part of it at the senior levels, and they came up with which have a role you know, seemed most meaningful to them. But really, all of us are trying to do the same job, which is to accelerate digital transformation in the enterprise. Your comment about you kind of see that the seat eels and sea deals now, uh, partnering up much more than in the past, and I think that's in available the major driving force full. That is, in my view, anyway. It's is artificial intelligence as people try to infuse artificial intelligence. Well, then it's very technical field. Still, it's not something that you know you can just hand over to somebody who has the business jobs, but not the deep technical chops to pull that off. And so, in the case off chief data officers that do have the technical jobs, you'll see them also pretty much heading up the I effort in total and you know, as I do for the IBM case, will be building the Data and AI Enablement internal platform for for IBM. But I think in other cases you you've got Chief date officers who are coming in from a different angle. You know, they built Marghera but the CTO now, because they have to. Otherwise you cannot get a I infused into the organization. >>So there were a lot of other priorities, obviously certainly digital transformation. We've been talking about it for years, but still in many organisations, there was a sense of, well, not on my watch, maybe a sense of complacency or maybe just other priorities. Cove. It obviously has changed that now one hundred percent of the companies that we talked to are really putting this digital transformation on the front burner. So how has that changed the role of CDO? Has it just been interpolate an acceleration of that reality, or has it also somewhat altered the swim lanes? >>I think I think it's It's It's Bolt actually, so I have a way of looking at this in my mind, the CDO role. But if you look at it from a business perspective, they're looking for three things. The CEO is looking for three things from the CDO. One is you know this person is going to help with the revenue off the company by enabling the production of new products, new products of resulting in new revenue and so forth. That's kind of one aspect of the monetization. Another aspect is the CEO is going to help with the efficiency within the organization by making data a lot more accessible, as well as enabling insights that reduce into and cycle time for major processes. And so that's another way that they have monitor. And the last one is a risk reduction that they're going to reduce the risk, you know, as regulations. And as you have cybersecurity exposure on incidents that you know just keep keep accelerating as well. You're gonna have to also step in and help with that. So every CDO, the way their senior leadership looks at them is some mix off three. And in some cases, one has given more importance than the other, and so far, but that's how they are essentially looking at it now. I think what digital transformation has done is it's managed to accelerate, accelerate all three off these outcomes because you need to attend to all three as you move forward. But I think that the individual balance that's struck for individuals reveals really depends on their ah, their company, their situation, who their peers are, who is actually leading the transformation and so >>forth, you know, in the value pie. A lot of the early activity around CDO sort of emanated from the quality portions of the organization. It was sort of a compliance waited roll, not necessarily when you started your own journey here. Obviously been focused on monetization how data contributes to that. But But you saw that generally, organizations, even if they didn't have a CDO, they had this sort of back office alliance thing that has totally changed the the in the value equation. It's really much more about insights, as you mentioned. So one of the big changes we've seen in the organization is that data pipeline you mentioned and and cycle time. And I'd like to dig into that a little bit because you and I have talked about this. This is one of the ways that a chief data officer and the related organizations can add the most value reduction in that cycle time. That's really where the business value comes from. So I wonder if we could talk about that a little bit and how that the constituents in the stakeholders in that in that life cycle across that data pipeline have changed. >>That's a very good question. Very insightful questions. So if you look at ah, company like idea, you know, my role in totally within IBM is to enable Ibn itself to become an AI enterprise. So infuse a on into all our major business processes. You know, things like our supply chain lead to cash well, process, you know, our finance processes like accounts receivable and procurement that soulful every major process that you can think off is using Watson mouth. So that's the That's the That's the vision that's essentially what we've implemented. And that's how we are using that now as a showcase for clients and customers. One of the things that be realized is the data and Ai enablement spots off business. You know, the work that I do also has processes. Now that's the pipeline you refer to. You know, we're setting up the data pipeline. We're setting up the machine learning pipeline, deep learning blank like we're always setting up these pipelines, And so now you have the opportunity to actually turn the so called EI ladder on its head because the Islander has to do with a first You collected data, then you curated. You make sure that it's high quality, etcetera, etcetera, fit for EI. And then eventually you get to applying, you know, ai and then infusing it into business processes. And so far, But once you recognize that the very first the earliest creases of work with the data those themselves are essentially processes. You can infuse AI into those processes, and that's what's made the cycle time reduction. And although things that I'm talking about possible because it just makes it much, much easier for somebody to then implement ai within a lot enterprise, I mean, AI requires specialized knowledge. There are pieces of a I like deep learning, but there are, you know, typically a company's gonna have, like a handful of people who even understand what that is, how to apply it. You know how models drift when they need to be refreshed, etcetera, etcetera, and so that's difficult. You can't possibly expect every business process, every business area to have that expertise, and so you've then got to rely on some core group which is going to enable them to do so. But that group can't do it manually because I get otherwise. That doesn't scale again. So then you come down to these pipelines and you've got to actually infuse AI into these data and ai enablement processes so that it becomes much, much easier to scale across another. >>Some of the CEOs, maybe they don't have the reporting structure that you do, or or maybe it's more of a far flung organization. Not that IBM is not far flung, but they may not have the ability to sort of inject AI. Maybe they can advocate for it. Do you see that as a challenge for some CEOs? And how do they so to get through that, what's what's the way in which they should be working with their constituents across the organization to successfully infuse ai? >>Yeah, that's it's. In fact, you get a very good point. I mean, when I joined IBM, one of the first observations I made and I in fact made it to a senior leadership, is that I didn't think that from a business standpoint, people really understood what a I met. So when we talked about a cognitive enterprise on the I enterprise a zaydi em. You know, our clients don't really understand what that meant, which is why it became really important to enable IBM itself to be any I enterprise. You know that. That's my data strategy. Your you kind of alluded to the fact that I have this approach. There are these five steps, while the very first step is to come up with the data strategy that enables a business strategy that the company's on. And in my case, it was, Hey, I'm going to enable the company because it wants to become a cloud and cognitive company. I'm going to enable that. And so we essentially are data strategy became one off making IBM. It's something I enterprise, but the reason for doing that the reason why that was so important was because then we could use it as a showcase for clients and customers. And so But I'm talking with our clients and customers. That's my role. I'm really the only role I'm playing is what I call an experiential selling there. I'm saying, Forget about you know, the fact that we're selling this particular product or that particular product that you got GPU servers. We've got you know what's an open scale or whatever? It doesn't really matter. Why don't you come and see what we've done internally at scale? And then we'll also lay out for you all the different pain points that we have to work through using our products so that you can kind of make the same case when you when you when you apply it internally and same common with regard to the benefit, you know the cycle, time reduction, some of the cycle time reductions that we've seen in my process is itself, you know, like this. Think about metadata business metadata generating that is so difficult. And it's again, something that's critical if you want to scale your data because you know you can't really have a good catalogue of data if you don't have good business, meditate. Eso. Anybody looking at what's in your catalog won't understand what it is. They won't be able to use it etcetera. And so we've essentially automated business metadata generation using AI and the cycle time reduction that was like ninety five percent, you know, haven't actually argue. It's more than that, because in the past, most people would not. For many many data sets, the pragmatic approach would be. Don't even bother with the business matter data. Then it becomes just put somewhere in the are, you know, data architecture somewhere in your data leg or whatever, you have data warehouse, and then it becomes the data swamp because nobody understands it now with regard to our experience applying AI, infusing it across all our major business processes are average cycle time reduction is seventy percent, so just a tremendous amount of gains are there. But to your point, unless you're able to point to some application at scale within the enterprise, you know that's meaningful for the enterprise, Which is kind of what the what the role I play in terms of bringing it forward to our clients and customers. It's harder to argue. I'll make a case or investment into A I would then be enterprise without actually being able to point to those types of use cases that have been scaled where you can demonstrate the value. So that's extremely important part of the equation. To make sure that that happens on a regular basis with our clients and customers, I will say that you know your point is vomited a lot off. Our clients and customers come back and say, Tell me when they're having a conversation. I was having a conversation just last week with major major financial service of all nations, and I got the same point saying, If you're coming out of regulation, how do I convince my leadership about the value of a I and you know, I basically responded. He asked me about the scale use cases You can show that. But perhaps the biggest point that you can make as a CDO after the senior readership is can we afford to be left up? That is the I think the biggest, you know, point that the leadership has to appreciate. Can you afford to be left up? >>I want to come back to this notion of seventy percent on average, the cycle time reduction. That's astounding. And I want to make sure people understand the potential impacts. And, I would say suspected many CEOs, if not most understand sort of system thinking. It's obviously something that you're big on but often times within organisations. You might see them trying to optimize one little portion of the data lifecycle and you know having. Okay, hey, celebrate that success. But unless you can take that systems view and reduce that overall cycle time, that's really where the business value is. And I guess my we're real question around. This is Every organization has some kind of Northstar, many about profit, and you can increase revenue are cut costs, and you can do that with data. It might be saving lives, but ultimately to drive this data culture, you've got to get people thinking about getting insights that help you with that North Star, that mission of the company, but then taking a systems view and that's seventy percent cycle time reduction is just the enormous business value that that drives, I think, sometimes gets lost on people. And these air telephone numbers in the business case aren't >>yes, No, absolutely. It's, you know, there's just a tremendous amount of potential on, and it's it's not an easy, easy thing to do by any means. So we've been always very transparent about the Dave. As you know, we put forward this this blueprint right, the cognitive enterprise blueprint, how you get to it, and I kind of have these four major pillars for the blueprint. There's obviously does this data and you're getting the data ready for the consummation that you want to do but also things like training data sets. How do you kind of run hundreds of thousands of experiments on a regular basis, which kind of review to the other pillar, which is techology? But then the last two pillars are business process, change and the culture organizational culture, you know, managing organizational considerations, that culture. If you don't keep all four in lockstep, the transformation is usually not successful at an end to end level, then it becomes much more what you pointed out, which is you have kind of point solutions and the role, you know, the CEO role doesn't make the kind of strategic impact that otherwise it could do so and this also comes back to some of the only appointee of you to do. If you think about how do you keep those four pillars and lock sync? It means you've gotta have the data leader. You also gotta have the technology, and in some cases they might be the same people. Hey, just for the moment, sake of argument, let's say they're all different people and many, many times. They are so the data leader of the technology of you and the operations leaders because the other ones own the business processes as well as the organizational years. You know, they've got it all worked together to make it an effective conservation. And so the organization structure that you talked about that in some cases my peers may not have that. You know, that's that. That is true. If the if the senior leadership is not thinking overall digital transformation, it's going to be difficult for them to them go out that >>you've also seen that culturally, historically, when it comes to data and analytics, a lot of times that the lines of business you know their their first response is to attack the quality of the data because the data may not support their agenda. So there's this idea of a data culture on, and I want to ask you how self serve fits into that. I mean, to the degree that the business feels as though they actually have some kind of ownership in the data, and it's largely, you know, their responsibility as opposed to a lot of the finger pointing that has historically gone on. Whether it's been decision support or enterprise data, warehousing or even, you know, Data Lakes. They've sort of failed toe live up to that. That promise, particularly from a cultural standpoint, it and so I wonder, How have you guys done in that regard? How did you get there? Many Any other observations you could make in that regard? >>Yeah. So, you know, I think culture is probably the hardest nut to crack all of those four pillars that I back up and you've got You've got to address that, Uh, not, you know, not just stop down, but also bottom up as well. As you know, period. Appear I'll give you some some examples based on our experience, that idea. So the way my organization is set up is there is a obviously a technology on the other. People who are doing all the data engineering were kind of laying out the foundational technical elements or the transformation. You know, the the AI enabled one be planning networks, and so so that are those people. And then there is another senior leader who reports directly to me, and his organization is all around adoptions. He's responsible for essentially taking what's available in the technology and then working with the business areas to move forward and make this make and infuse. A. I do the processes that the business and he is looking. It's done in a bottom upwards, deliberately set up, designed it to be bottom up. So what I mean by that is the team on my side is fully empowered to move forward. Why did they find a like minded team on the other side and go ahead and do it? They don't have to come back for funding they don't have, You know, they just go ahead and do it. They're basically empowered to do that. And that particular set up enabled enabled us in a couple of years to have one hundred thousand internal users on our Central data and AI enabled platform. And when I mean hundred thousand users, I mean users who were using it on a monthly basis. We company, you know, So if you haven't used it in a month, we won't come. So there it's over one hundred thousand, even very rapidly to that. That's kind of the enterprise wide storm. That's kind of the bottom up direction. The top down direction Waas the strategic element that I talked with you about what I said, Hey, be our data strategy is going to be to create, make IBM itself into any I enterprise and then use that as a showcase for plants and customers That kind of and be reiterated back. And I worked the senior leadership on that view all the time talking to customers, the central and our senior leaders. And so that's kind of the air cover to do this, you know, that mix gives you, gives you that possibility. I think from a peer to peer standpoint, but you get to these lot scale and to end processes, and that there, a couple of ways I worked that one way is we've kind of looked at our enterprise data and said, Okay, therefore, major pillars off data that we want to go after data, tomato plants, data about our offerings, data about financial data, that s and then our work full student and then within that there are obviously some pillars, like some sales data that comes in and, you know, been workforce. You could have contractors. Was his employees a center But I think for the moment, about these four major pillars off data. And so let me map that to end to end large business processes within the company. You know, the really large ones, like Enterprise Performance Management, into a or lead to cash generation into and risk insides across our full supply chain and to and things like that. And we've kind of tied these four major data pillars to those major into and processes Well, well, yes, that there's a mechanism they're obviously in terms off facilitating, and to some extent one might argue, even forcing some interaction between teams that are the way they talk. But it also brings me and my peers much closer together when you set it up that way. And that means, you know, people from the HR side people from the operation side, the data side technology side, all coming together to really move things forward. So all three tracks being hit very, very hard to move the culture fall. >>Am I also correct that you have, uh, chief data officers that reporting to you whether it's a matrix or direct within the division's? Is that right? >>Yeah, so? So I mean, you know, for in terms off our structure, as you know, way our global company, we're also far flung company. We have many different products in business units and so forth. And so, uh, one of the things that I realized early on waas we are going to need data officers, each of those business units and the business units. There's obviously the enterprise objective. And, you know, you could think of the enterprise objectives in terms of some examples based on what I said in the past, which is so enterprise objective would be We've gotta have a data foundation by essentially making data along these four pillars. I talked about clients offerings, etcetera, you know, very accessible self service. You have mentioned south, so thank you. This is where the South seven speaks. Comes it right. So you can you can get at that data quickly and appropriately, right? You want to make sure that the access control, all that stuff is designed out and you're able to change your policies and you'd swap manual. But, you know, those things got implemented very rapidly and quickly. And so you've got you've got that piece off off the off the puzzle due to go after. And then I think the other aspect off off. This is, though, when you recognize that every business unit also has its own objectives and they are looking at some of those things somewhat differently. So I'll give you an example. We've got data any our product units. Now, those CEOs right there, concern is going to be a lot more around the products themselves And how were monetizing those box and so they're not per se concerned with, You know, how you reduce the enter and cycle time off IBM in total supply chain so that this is my point. So they but they're gonna have substantial considerations and objectives that they want to accomplish. And so I recognize that early on, and we came up with this notion off a data officer council and I helped staff the council s. So this is why that's the Matrix to reporting that we talked about. But I selected some of the key Blair's that we have in those units, and I also made sure they were funded by the unit. So they report into the units because their paycheck is actually determined. Pilot unit and which makes them than aligned with the objectives off the unit, but also obviously part of my central approach so that I can disseminate it out to the organization. It comes in very, very handy when you are trying to do things across the company as well. So when we you know GDP our way, we have to get the company ready for Judy PR, I would say that this mechanism became a key key aspect of what enabled us to move forward and do it rapidly. Trouble them >>be because you had the structure that perhaps the lines of business weren't. Maybe is concerned about GDP are, but you had to be concerned with it overall. And this allowed you to sort of hiding their importance, >>right? Because think of in the case of Jeannie PR, they have to be a company wide policy and implementation, right? And if he did not have that structure already in place, it would have made it that much harder. Do you get that uniformity and consistency across the company, right, You know, So you will have to in the weapon that structure, but we already have it because way said Hey, this is around for data. We're gonna have these types of considerations that they are. And so we have this thing regular. You know, this man network that meat meets regularly every month, actually, and you know, when things like GDP are much more frequently than that, >>right? So that makes sense. We're out of time. But I wonder if we could just close if you could address the M I t CDO audience that probably this is the largest audience, Believe or not, now that it's that's virtual definitely expanded the audience, but it's still a very elite group. And the reason why I was so pleased that you agreed to do this is because you've got one of the more complex organizations out there and you've succeeded. And, ah, a lot of the hard, hard work. So what? What message would you leave the M I t CDO audience Interpol? >>So I would say that you know, it's it's this particular professional. Receiving a profession is, uh, if I have to pick one trait of let me pick two traits, I think what is your A change agent? So you have to be really comfortable with change things are going to change, the organization is going to look to you to make those changes. And so that's what aspect off your job, you know, may or may not be part of me immediately. But the those particular set of skills and characteristics and something that you know, one has to, uh one has to develop or time, And I think the other thing I would say is it's a continuous looming jaw. So you continue sexism and things keep changing around you and changing rapidly. And, you know, if you just even think just in terms off the subject areas, I mean this Syria today you've got to understand technology. Obviously, you've gotta understand data you've got to understand in a I and data science. You've got to understand cybersecurity. You've gotta understand the regulatory framework, and you've got to keep all that in mind, and you've got to distill it down to certain trends. That's that's happening, right? I mean, so this is an example of that is that there's a trend towards more regulation around privacy and also in terms off individual ownership of data, which is very different from what's before the that's kind of weather. Bucket's going and so you've got to be on top off all those things. And so the you know, the characteristic of being a continual learner, I think is a is a key aspect off this job. One other thing I would add. And this is All Star Coleman nineteen, you know, prik over nineteen in terms of those four pillars that we talked about, you know, which had to do with the data technology, business process and organization and culture. From a CDO perspective, the data and technology will obviously from consent, I would say most covert nineteen most the civil unrest. And so far, you know, the other two aspects are going to be critical as we move forward. And so the people aspect of the job has never bean, you know, more important down it's today, right? That's something that I find myself regularly doing the stalking at all levels of the organization, one on a one, which is something that we never really did before. But now we find time to do it so obviously is doable. I don't think it's just it's a change that's here to stay, and it ships >>well to your to your point about change if you were in your comfort zone before twenty twenty two things years certainly taking you out of it into Parliament. All right, thanks so much for coming back in. The Cuban addressing the M I t CDO audience really appreciate it. >>Thank you for having me. That my pleasant >>You're very welcome. And thank you for watching everybody. This is Dave a lot. They will be right back after this short >>break. You're watching the queue.

[Music] hi and welcome to another cube conversation this time from the MCS Hilux immersion day at the Santa Clara Marriott beautiful Northern California we're going to be spending the entire day having a series of discussions about what it means to do a better job of both digital services management and operations management and how those technologies are coming together to dramatically alter how business operates how customers get value and ultimately how profits are generated we're going to start this conversation with a CDO a chief digital officer from Genpact sanjay sri tvasta welcome to the cube thank you very much so to start tell us a little bit about Jim pacts interesting company comprised we are indeed Genpact is a large global professional services provider for digital transformation services we serve many of the fortune 500 companies around the world and we help them think through their business processes in the business models and digitally transform that to take advantage of so all the new capabilities that are coming through so digital service outcomes is a very important feature of that because I presume that when you have those conversations with customers you're talking about the outcomes that they're trying to achieve yeah and not just the services that you're gonna provide it's fine so tell us a little bit about what is a digital service outcome and why is it so important yeah well I think the reality is that what technology is doing it it's disintermediating the ecosystem so many of the industries our clients operate in and they have to go back and reimagine their value proposition of the core of what they do with the use of new innovative technologies and it's that intersection of new capabilities of new innovative business models that really use emerging technologies but intersect them with their business models with their business processes and the requirements of their clients and help them rethink reimagine and deliver the new value proposition that's really what it's all about so digital service outcome would then be the things that the business must do and must do well but ideally with a different experience or with a different degree of flexibility and agility or with and cost profile I got that right correct so when we think about that what are some of the key elements of a digital service success we like to think about three critical success factors in driving any digital transformation the first one is the notion of experience and what I mean by that is not user interface for a piece of software but the journey of a customer an employee a provider a partner in engaging with you in your business model and we think about journey mapping that scientifically we think about design thinking on the back of that and we think about reimagining what the new experience looks like one of the largest things we learned in the industry is digital transformation on the back of costs take out a productivity or efficiency is is is insufficient to drive and optimize the value that digital can bring and using experience as the compass is sort of the Northstar in that journey is a meaningful differentiator and drive our business benefits so that's number one in the second area that's become increasingly apparent is the intersection of domain with digital and the thinking there is that to materialize the benefit of digital in an enterprise you have to intersect it with the specifics of that business how users interact what clients seek how does business actually happen you know we talk about it artificial intelligence a lot we do a lot of work in AI is an example and there's key thing about machine learning is goal orientation and what is goal orientation it's about understanding the specifics of your environments you can actually orient the goal of the machine learning algorithm to deliver higher high accuracy results and it's something that can often easily get overlooked so indexing on the two halves of the whole the yin and the yang the the the piece around digital and the innovative technologies and being able to leverage and take advantage of them but equally be founded and domain understand the environment and use that knowledge to drive the right materialization of the and that's the second critical success factor I think to get it right I think that third one is the notion of how do you build a framework for innovation you know it's not the sort of thing where large fortune company 100 500 fortune 500 companies can necessarily experiment and you know it's a little bit for go happy-go-lucky strategy it doesn't really work you have to innovate at scale you have to do it in a fundamental fashion you have to do it as a critical success factor and so one of the biggest things we focus on is how do you innovate at the edge innovation must be at the edge this is where the rubber meets the road but governance has to be at the core let me build on that for a second because you said innovations at the edge so basically that means where the brand promise is being enacted for the customer and that could be at an industrial automation setting or it could be in recommendation if any any number of things but it's where the value proposition is realized for the customer correct okay that's exactly right and that's where innovation must happen so as a large corporation you must be you know it's important to set up a framework that allows you to do innovation at the edge otherwise it's not meaningful innovation if you will it's just a lot of busy work and yet as you do that and if you change your business model is you bring new components to the equation how do you drive governance and it's increasingly becoming more important you think about we're gonna be in a AI first world increasingly more and more that's the reality the world we're going in and in that AI first world you know III work here in Palo Alto I walk into my office a couple of hundred people in any given day if tomorrow morning I walked in and hundred people didn't show up for work I would know right away because I can see them now fast forward to an environment where we have digital workers we have automation BOTS we have conversationally I chat box and in that world understanding which of my AI components are on which ones are off which ones showed up for work today which ones fell sick and really being able to understand that governance and that's just the productivity piece of it then you think about data and security AI changes complete dimensions on that and you think about bias and explained ability to become increasingly important and notion of a digital ethics board and thinking about ethics more pervasively so I think that companies and clients we serve that do really well in digital transformation are those that keen on those three things the notion of experience is the true compass for how you try transformation the ability to intermix domain and digital in a meaningfully intersecting fashion and to be thoughtful proactive and get governance right up front in the journey to come so let me again building out a little bit because people are increasingly recognizing that we're not going to centralized with cloud we're going to greater distribute we're going to distribute data more we're going to distribute function more but you just added another dimension that some some of us have been thinking about for a long time and that's this notion of distributing authorities yeah so that an individual at the edge can make the decision based on the data and the resources that are available with the appropriate set of authorities and that has to be handled at a central in a in a overall coherent governed way so that leaves the next question and just before you go that I mean I think the best example of that is we do that most corporations do that really well in the financial scheme of things business is that the edge make decisions on a day-to-day basis on pricing and and relationships and so on and so forth and yet there's a central audit committee that looks through the financials and make sure it meets the right requirements and has the right framework and much in the same way we're gonna start seeing digital ethics committees that become part of these large corporations as they think about digitizing the business governance at the end of the day is how do you how you orchestrate multiple divergent claims against a common set of assets and and being able to do that it's absolutely essential and it leads to this notion of we've got to cite these ideas of digital business digital services and operations management how are we going to weave them together utilizing some of these new technologies new fabrics that are now possible to both achieve the outcomes we're talking about at scale in its speed yeah well the the technology capabilities are improving really well in that area and so the good news is there's a set of tools that are now available that give you the ingredients the the components of the recipe that's required to make dinner well you know the the work that needs to happen is actually how to orchestrate their that to figure out which components you to come in and how do you pull together a vertical stack that has the right components to meet your needs today and more importantly to address the needs of the future because this is changing like no other time in history you want options with everything you do now you want to make sure that you have a stream of options for the future and that's especially important here that's right that's exactly right and and the the the quick framework we've established there is sort of the three-legged stool of how do you integrate quickly how do you modular eyes your investments and how do you govern them into one integrated whole and those become really important I'll give you examples you know much of the work we do will work with the consumer bank for instance and they'll want to do a robotic process automation engagement will run on for nine months they'll get 1,800 robots up and running and the next question becomes well now we have all this data that we didn't really have because now we have an RPA running how do I learn some machine learning insights from there and so we then work with them to actually drive some insights and get these questions answered and then the engagement changes to well now that we have this pattern recognition that we understand more questions will be asked how do I respond to those questions a automatically and before they get asked this notion of next best action and so you think about that journey of a traditional client you know the requirements change from robotics to machine learning to conversationally AI to something else and keeping that string of investments that that innovative sort of streak true and yet being able to manage govern and protect the investments that's the key role and especially if we do want to look at innovation at the edge because we want to see some commonalities otherwise we freaked people out along the way don't exactly right so I'm J Street of AUSA thank you very much for being on the cube thank you for having me and once again I'm Peter Burroughs and we'll be back with our next guest shortly from BMC Hilux immersion day here at the Santa Clara Marriott thanks very much for listening

>> (Announcer) Live, from Las Vegas it's the Cube. Covering VM World 2018. Brought to you by VM Ware and it's ecosystem partners. >> Welcome back to the Cube's continuing coverage of VM World 2018, I'm Lisa Marin, with Dave Vellante >> Hey, Lisa. >> Dave, day three, we have had tremendous guests the last couple of days. And we're- a lot of alumni, a lot of new guests, another alumni joining us, Calline Sanchez, vice president of IMB Enterprise System Storage. Welcome back, Calline, it's great to have you here. >> No, thank you very much for letting me be here. >> And I want to congratulate Calline, because she was just named for the Tucson Hispanic Chamber of Commerce, 2018 Businesswoman of the Year. Just a few weeks ago. Amazing. >> Lovin' Tucson, by the way. >> Thank you. >> U of A. >> Yes. >> Bear Down. >> I appreciate the Wildcats reference, so, >> Haha. >> No doubt. And so, this Saturday, oh, I'm sorry. This Saturday, the first game, so- >> My daughter is a freshman at U of A, Hi, Pilar, I love you, baby. Good luck. You're going to crush it, I know you are. >> Haha. >> Dad of the year going on here. So, just before we get into all the storage stuff- >> Yeah. >> They're doing a, they're honoring you, just in about a month and a half or so, with this- >> Yeah. Yes, and I'm very excited about that. Just like you were saying with the community aspect, it's a high-touch award, and I was very thankful for it, because they gave me specific examples of, what I've done in Southern Arizona, in Tucson in particular, that they'll name. For instance, Excite for Girls, and things like that. >> That's awesome. >> Girls in STEM, right? >> Congratulations, that's fantastic. >> We need more inspiration, so, it's great that we, >> Ah, thank you. >> Now count you as one of our distinguished alumni. So, let's talk about what going on at IMB. Here we are at VM World 2018, we're hearing Dave, numbers of upwards of 21,000 people that have been here the last few days. 100,000 more engaging with, expecting to engage with the live streaming and the on demand experiences. What's going on with IBM, you know, from a revenue perspective, a growth perspective? What is exciting you about where you are today? >> So, I will talk in particular about storage. I'm really, really proud about this, being that we work in partnership with, like, Ed Walsh, and then also Eric Herzog. They've inspired me to get closer to building solutions with our end users. So we meet and work with our clients to build up cloud deployment solutions, in partnership with VM Ware, and we enable things like, okay, so there's tape, and then there's cloud-to-tier, so there's fundamental solutions out there in the marketplace that we as developers want to go and play with. It's almost like a great big sandbox. So to speak. >> So, I've got to ask you, because, I mean, everybody in storage says, well, Tape, tape is dead. And every time I see you we talk about tape. We talk about FLAPE. We talk about innovations that are coming to tape. You're a technologist. Right, you just said, as a developer we love to- dot-dot-dot. So, what is it about things like tape, things like mainframe, DS8000, these technologies that have, tried, true, running businesses, what is about those that excite you as a developer? >> Everything old is new again, >> Yeah, right. >> If we just go back to the basics of like, table stakes, right? Security is table stakes, right? Delivering on-time quality releases with optimizers like, tier-to-cloud, things like that. That's fundamental for us. Now, as it relates to tape, so, everything old is new again, like I mentioned a moment ago. Tape was the first device to fully encrypt. So every drive, if it fell off the truck, it was fully encrypted. So, tape is actually training the rest of our portfolio in similar skills, on how we do the end-to-end encryption elements. So, right now with DS8000, we're working in partnership with system Z, to deliver pervasive encryption. >> I got to ask you, so as a development executive, I see you at a lot of these shows. You like coming here? A lot of times, development execs want to, sort of, stay in the lab. But you're out and about, talking to customers. What are you learning? What is that about you that draws you to these shows? >> I was afraid that WE as a lab team would not be relevant unless we have conversations with end users, partners. You know, to really substantiate what's possible from being innovative. So, I would say, number one is relevance, and I felt like, I wanted to more social, because, I'm definitely in some cases, an introvert, though I'm looking above my shoes. That's I'm wearing- >> That's the definition, of an introvert and an extrovert in the tech world. You know that the difference is, right? >> I don't. >> An introvert looks at his or her own shoes, an extrovert looks at your shoes. >> Well, there you go. I've been looking at some shoes- >> Alright, so you're, you're extrovert oriented out here, what are you learning at VM World? what are the customers saying? What are they asking you for? What are you going to take back to the lab? >> A single pane of glass associated with what we intend with like, v-stream, or some of the aspects of automation, with regards to cloud deployment, to make it, like, completely- connected. If that, so to speak. And what I think is really great about all of that is I hate to put it this way, it's very iTunes like. Where it's like, sticky, and it's easy to use, or and, by the way, it's not so expensive, at least to start up. So, a lot of the discussions we've been having are with the various vendors on the expo floor, that they want to build solutions. IBM solutions associate with the cloud, and then the AWS guys, we meet with them. And they're like, well, how are, how can we ensure that we live in an interconnected data-centric world? And so that's what I think is very exciting is that, it's this idea of coopetition. Let's all be well connected, and do it well. >> Let's talk about the customer collaboration, as you mentioned, everything old is new again, we see that, in every aspect of life. Tape, mainframe, but you talked about we need to be relevant, but also need to developing solutions that you end user customers need to solve their business problems. How are you collaborating with customers to stay relevant, and to ensure that their businesses are able to take advantage of the super powers that Pat Gelsinger talked about on Monday, AI, machine learning, emerging technologies, what's that collaboration like? >> I would say the biggest collaborations that I've been participating recently is with cloud servers providers. And they appreciate the economics of physical media, or tape. And so, they think to themselves or they know the data, it's like, okay, less than a half-cent per gig, that's a big deal, right? So, and then we have discussions about total cost of ownership, aspects like that. So the partnership is also, how do we serve the data? And really having discussions about the data. And then, if evaluating the various work streams where, we would want to serve appropriately based on whatever specific cloud infrastructure. And then, also, taking a step back, we have to be interconnected. There's no question. So, I would say the number one set of skills our end users are working with right now happen to be the cloud service providers. >> What are some of the big business benefits that they're achieving, we think, new business models, new revenue streams, market expansion. What are some of the things that you're proud of that IBM storage solutions are helping your customers to deliver? >> Going to tape, it's the economics, yes. It's the security based on encryption, yes. And then also, the other aspect of, is, we're serving big data. I mean, it's like we're having discussions about they're going to grow to, zettabytes by 2020, things like that. I never thought in my life, especially as an engineering student, or in computer science, I would ever be talking about this big of data. And now we're here. And so, we're learning how to enable in partnership with clients, what would be the right, or appropriate solution. >> So, I'm searching our video library, because somebody said this week something that was really interesting to me and I wanted to get your perspective from a development mind, someone who's technical. We're hearing a lot about migrating to the cloud. And how easy that is. And then, I think it was Pat Gelsinger said, there's three laws. There's the law of physics, the laws of a company, and the law of the land. And, those are immutable, generally. But I want to ask you about the laws of physics. So, in terms of just moving data into the cloud, we talk about petabyte, exabytes, there's so much data. How feasible is it for a customer to move data, and just stuff it all into the cloud, and what are you doing to either help them do that, or bring the cloud experience to their data? >> Depending on the client interests of on-prem, off-prem, or hybrid, right? We work to evaluate APIs in collaborations, so we enable a streamline, so it's not only just understanding the components of the cloud deployment, but it's also partnering with all elements of the entire ecosystem's stack. So, it depends but we really start with the client's end use case. What do you want? What kind of security do you want? Are you okay with off-prem, public clouds? Or, maybe it's specific data, how do we go about managing the data so we secure it, like, we bucket-ize it. So those are some of the discussions we've been having on the floor, here, at VM world, but also, within our labs, and also with the clients directly. >> You know what I love about that answer? I'll translate it. It's not a biz- it's not a technical problem, Dave, it's a business problem, >> Yes. >> Is really what you're tell me. >> And that's a fundament- you asked the question before. That's fundamentally why I am here. >> Right. >> I don't believe we can live in this world anymore, where it's like, we build it, and then they come. >> Field of Dreams does not exist anymore. >> Yeah. And so, now we've got to have conversations with our end users, to develop, what we've going to put on the roadmap. And so I always felt like, okay, well, when I'd see the roadmap in the lab, I'm like, okay, well, who wants this? Who asked for this, right? And those ended up becoming some of my fundamental questions. So then, I started to come here, or conferences like this, because I could have those conversations with the end users and partners. >> That's interesting, who wants this? Who needs this? What problems does it solve? Why us, why now? Those are the kinds of things you're asking. >> Let's talk about why us? IBM has been around for a very long time. What do you think, again, in this got to be relevant, we need it to be really defined by customer needs and uses. Everything old is new again. What, in your opinion, makes, why should a customer go, in my VM environment, IBM. >> I'm going to start with why I even personally want to remain with IBM. It's a great big candy store. >> Haha. >> And what I have to remind myself is, just don't eat too much, right? And, by the way, I still eat way too much. But what's great about it is, it's a sandbox, so, I can talk to you software engineers one day, who are telling me about certain APIs they're building in Python. Then, oh, by the way, I meet with a mechanical set of engineers, cuz they want to enable robot arms. Oh, and by the way, should we have a discussion on microcode and firmware for the entire stack. So I take a step back, and I'm thinking, Wow- the only set of conversation I really prior was not having, is about services. And to me, services is like the wrapping paper, for a present that you're about to receive. And really understanding the overall, end-to-end stack infrastructure. So, I believe from an IBM perspective, it's the ecosystem. It's a great big candy store. Just don't eat too much. >> Haha. So, how do you spend your time? Do you spend your time thinking, collaborating with team on, architecture, on, vision, on, northstar, writing code. How do you spend your time day-to-day? >> Can I say, all of the above? And, the vast majority, right now, really just making sure we're relevant in the marketplace, so that we re-fresh the right amount of cycles. So, right now, what we're going to be doing in 2019, we're going to be talking about it right now. Architecting what the future looks like. And that's part of the reason why I'm here at VM World 2018, is I'm wanting to verify my roadmap. Am I taking the right approach with the extended team? Cuz it is team, and I work with them. These engineers and scientists are so right, and have great ideas. Let's just make sure they're great ideas that will keep us relevant and keep us paid. >> So, have you gotten that validation, in the last few days at VM World? >> Give me one more day. >> Haha. Well, Calline, thanks so much for stopping by and sharing. Not only what IBM is doing to continue to innovate and stay relevant, but also what's exciting to you- >> Yeah. >> About working for IBM, and again, Congrats on getting the award. >> Yes, and thank you very much for highlighting that, cuz it's, I'm very excited as just an individual, it's like, it was unexpected. >> Well, you're representing women in tech, women in STEM, it's awesome, congratulations. >> Thank you very much. >> We're really happy. >> And, by the way, I'll definitely reach out to your daughter at some point. >> Oh, great. >> Say, hey, let's go to a tailgate. >> Love it. >> I won't corrupt. >> Haha. Fantastic, Calline, thank you so much for your time. I'm Lisa Martin with Dave Vellante. We want to thank you for watching the Cube, we are in day three of our continue coverage from VM World 2018. Stick around, we'll be right back with our next guest.

hello everyone welcome to the cube conversations here in our studio in Palo Alto California I'm John Faria co-host of the cube co-founder Sylvania media special guest today inside the cube in Palo Alto Steve Lucas the new CEO of Marketo formerly of sa P industry veteran a lot of experience in the enterprise space now the chief executive officer at Marquette Oh welcome to this cube conversation great to see you yeah great to see you again so Marketo has been on our radar spent on everyone's radar it's been one of the hottest marketing companies that have come out of this generation of SAS what I call SATs cloud offerings and certainly as burn burn in the field in terms of reputation in terms of quality high customer scale a lot of other companies have been bought out you see Oracle doing a lot of stuff you got Salesforce the SAS business is booming oh yeah and you have a rocket ship that you're now the CEO now for two months first question what's it like here now compare a CPA yeah Marketo what's it what's happening well it's I mean s if he's a fantastic company and loved it it's the the the kind of metaphor I've used is it you know with sa P it's it's a bigger it's a bigger vehicle you're driving a bus and you can carry a lot of people with you takes a little bit longer to make a u-turn Marketo is a Formula One car I mean this thing is just in and out of traffic and it's it's unbelievably nimble so it's it's been a big kind of shift culturally but absolutely love it for the folks that are watching you might not know but Steve was in the HANA analytics president of that division with ASAP which was a real interesting transformation because Hana and and and s ap was a traditional big enterprise software company yeah but had to move very quickly Hana was basically built before Hadoop was even conceived and it was built before the big cloud explosion but kind of well built for the cloud so you have to kind of move quickly oh yeah from scratch into the cloud oh yeah with sa Pease resources yeah so compare construct contrast butBut your expense from sa p what is Marquette O's prospects I mean what's going on there I mean I'll see you got a formula speedboat but the big aircraft carriers are thrown pretty big wake they are how are you gonna maneuver yeah yeah well it's it's a fascinating environment right now because you know going from us if he I'd say that my experience they're kind of highly tuned me or prepared me for what I'm doing in Marketo si P had to move nimbly at the time really nimbly you're entering a market where you've got oracle microsoft at a database level they're the incumbents they own massive share how does si penetrate that but we were successful at the time at sa p and i loved that experience coming into Marketo really i mean it's a couple things one is you got to out-innovate the competition this is not rest on your laurels and wait for the release a year and a half from now that doesn't happen so this is about moving quickly but the second thing it's about I believe is it's all about putting the customer at the center of your strategy they have to drive everything I've talked to more marketers more CMOS in the last two months than I have in my last 20 years putting them the center is all about that Marketo their heritage was marketing solutions built by marketers for market what are the people saying you made with a lot of those CMOS more in the past since the past two months what are they saying what's on their agenda what do they care about what's important to them brand revenue and impact they want to know how do I Drive my brand how do I drive revenue and how do I show that impact to my CEO the board whomever it may be but the thing that scares marketers right now the most is what is digital transformation changing relative you know the big trend in macro trend globally how is it changing buyer expectation how is it changing the customer brand relationship that's top of mind Peter Paris who heads up by research for wiki bond and he used to do the b2b practice at Forrester around digital and stay Volante now we're talking yesterday that digital now is everything right so if you look at digital it's not just oh marketing need some tools to send emails out or oh I need to get a website up call IT up and provision or landing page this is now a fabric of pure infrastructure yet the infrastructure was built in the web days and you can go back to your business object days and go back again even back in the 90s that infrastructure now is so hard and as instrumentation there's no agility so that I feel that and we here in our in our teams and our customers that I want agility but I also want to control what the infrastructure might look like but then I don't want to touch it again I wanted to work for me do you see that same dynamic and how does that play out because I mean it's kind of the nuance point but the end of the day shadow marketing is going on shadow IT oh it's happening and it's on this unequivocally I mean so the the it literally the what's crushing the marketer right now is every time we get a new touch point a a watch so we go from just a watch that tells me the time to an Apple watch right every time there's a new touch point there's a new point solution for it and it's crushing the marketer so if it's social there's point solutions if it's mobile there's point solutions if it's a watch there's point solutions I blew my mind I literally saw it start up this is we can do you know monitoring and engagement of people on a watch it's just it's overwhelming the marketer and so their landscape of applications is looking like 30 40 different apps and their big win single sign-on that's the big win for the marketer internally it's just crushing them so what they're looking for your point is the Mahr tech or marketing technology graph and map is so big each one of their own underlying stack database software is that kind of what you're getting at absolutely absolutely you pick a marketing cloud it really doesn't matter you could say Oracle's marketing cloud sales force marketing cloud Adobe's marketing cloud it's just convoluted the the graph or chart of what's out there so point solutions just put together cobble together that's exactly right and so we're the benefit are that this is the the problem with that is what well the problem with that is that you first of all you lose any context relative to who you are there's no way that I can across 30 or 40 systems keep a consistent definition of job for you it's just impossible to do and our notion is we're looking at and what we're driving is a single engagement platform where the definition of you who you are no matter what touch point how we listen to you how we learn from you and how we engage with you it's all the same it's all integrated so let's get back to this point because I think an engagement platform and then the applications are interesting so I mentioned the CMOS earlier there's more development going on in marketing with like programmers developing apps because creig's of course okay so they're using the cloud and the marketing cloud is not like a one-off it has to be part of the core infrastructure so one of the things that wiki bonds gonna be releasing a new research coming up but I saw David floor yesterday who's a head of the research project that they're gonna show market share numbers of Amazon Google all the top cloud guys yeah interesting dynamic past is squeezing now platform-as-a-service is being squeezed down and SAS is increasing and then I as infrastructure stores is kind of shortening which means this automation in there so that the middle layer is gone but yet there's more sass how does that relate to the marketing cloud because the marketing cloud would be considered middleware or is it just the SAS app and does that speak to an explosion of SAS applications well I mean you're gonna see an explosion of SAS applications regardless I mean we reached that point of critical mass a while ago that's there's no going back at this point but if you look at kind of I think you're absolutely right there's compression at the IaaS layer in the past layer etc because these these these larger kind of SAS applications they are really ruling today and if you look at how that applies to marketing we actually think about three technology tiers within marketing there's the listen learn and engage tier the listen it's here is how do I listen on these digital channels the myriad that are out there and then the learned here is core to our platform the engagement platform it's all about an automation engine an AI engine and an analytics engine it's learning and then engaged here is how do I go back to those self same channels I was listening to and engage you the way that you want to be touched and so that's really the stack that comprises the Marketo engagement platform what's interesting the dynamic for us is we're actually seeing our own native applications that we're building on our engagement platform and then we have over 600 partners that are building applications are not building applications on our engagements they're writing software on top of the market absolutely so they're extending it so if social listening which I know is a big thing for Silicon anger that's like the I mean you guys are masters at it that if that's your thing then we have a not only do we have social listening capability but there's an app for that there's dozens so we could potentially plug into that oh absolutely so that's your vision so the vision let's go back to the so more apps a platform that enables more satisfaction yeah and and you mentioned people building on it that's an integration challenge and that's something that people they want to do more of they want to integrate other things with platforms which could be a challenge but it brings up the point data where does the data sit because now the data is the crown jewel yes and also a very important aspect to get real-time information so if you have information on me you won't have access to that data fast that's right and so there's an architectural challenge there there is your thoughts and reaction to the role of data well I first of all marketers still want to own their data and I think we need to be you know the reality is is that if you look a lot at a lot of these marketing clouds that are out there they're the vendor perspective is going to be will if I own your data I own you and our perspective is well you know that your data can sit within our platform but we can actually drive that data into you know on-premise warehouse etc etc so we're our goal is not to own your data ergo we own you that's not our goal I think the big thing like in the content you're saying is you want to use their data to give them value absolutely and so for us it's a matter of you know we can we can do to protect their data - exactly and so for me it's all about you know it's securing the data its but it's also the data is so complex now for the marketer so you've got social data highly unstructured you know you're listening for key words they still have to interpret that information you've got highly structured data demographic for example so it's how do you bring all that together you can bring that together in the Marketo engagement platform and then you can turn that into something meaningful it's always funny always to love to interview the new CEOs because we got the fresh perspective but I can't ask the tough questions cuz you lived in there for two months you get it say I won't even that two months I really can't answer that so I'll get the more generic on that what to try to get this at some of the hidden questions that I like to expose for the audience and really the main one is what attracted Univ Marketo I mean you left a pretty senior very senior position NSA p-president and Marketo is like the ship that's out there it's a motorboat but some are saying that the ways might be big enough and so you know be like okay but their public company so everything's out in the open what attracted you to market what God did say you know what I want to ride this speedboat well the trigger point for me was you know especially it s if he get exposed to kind of the big macro trends big macro trend everybody knows it is digital transformation as if he's talking that Microsoft Accenture picked the big company they're talking digital transfers and it is real the reality is you either are a digital native company were born digital uber or you're going digital ie you know you're a hospitality company trying to compete with air B&B and you gotta go digital so it's yeah I wrote an article I want on go digital or die right that's that's the that's the notion and when I looked at that I said so how does that lens apply to marketing well the reality is is that the marketer in the digital economy is only going to win if they can engage with not two or three people but Millions in an authentic and personalized manner at scale so that it's kind of juxtaposed how do you do that how do you engage with millions of people but at scale but deliver personalized an authentic experience and I looked at Marketo and I saw this platform and I just said oh my gosh there they are there's like this this convergence of those two things that are going to happen and I just think that the whole kind of marketing automation space which is known as really I I want to transform that into the engagement space we're talking about things like this engagement economy trend I absolutely believe we are fully in this notion of the engagement economy I think Marketo is right there so I gotta ask you a question is this is interesting you mentioned getting personalized information one of the things that's apparent we talked about on my Silicon Valley Friday show if you go to soundcloud.com /john for every year that people watching can get the copies of those but the thing was the recent election highlighted an issue around trust right v news younger natives digital natives younger kids they actually don't know what fake news is and what real news is a lot of people are moving off cable TV into digital which opens up the snapchats of the world different channels omni-channel like things and so this brings up this notion of communities because what people are turning to in this time of no trusting the mainstream media right news or Trump or what they were saying it's causing a lot of theater but it highlights an issue which is what's real what's not its content content is also has a relationship with users content is marketing content is trust is now a huge deal how do marketers now deal with the fact that content marketing coming from a company it could be fake news but there's a real or not and how do they get the context jewel connections is it the communities and we see that election people kind of going back to their tribe and saying oh anti Trump or Trump or whatever so tribal communities are a big part of data it is what's your thoughts on this trust factor and data and the content yeah yeah well so I think I mean a couple things first of all you know the I I think you or I as a consumer you know where anybody really we don't respond well to stare I'll moderately creepy advertisements that show up that you you know you know okay you're tracking my cookie you know in my browser and that that is just that's a non-starter I think that that in and of itself is is not interesting now we respond well to there's I said that that kind of personalized and I use that word authentic content so if there's content it's not just hey I know that you visited you know three websites about cars so I'm just going to pump you with ads full of cars but if we deliver thoughtful content it could be a comparison of vehicles that you've been looking at and take a look so there's more thoughtful content that you can deliver that that I think can come through a Mar tech platform like what we have our engagement platform no I will tell you that that trust to me it's it's not just the the authentic nature it's also a consistent engagement you can't show up show me an ad one time and I'm just gonna buy from you it doesn't work that way anymore so it's about having a relationship digital at scale but you know it's it's delivering that human touch I wrote a blog on this one where I said how do you deliver the human touch its Kate for blog addresses it it's on Marquitos website actually yeah right on our website so we talked about that as well and as companies are moving away from you or I managing the social engagement to the AI engines the machines engaging with us I think that we run the risk the marketer runs the risk of reinforcing the stare aisle you know kind of engagement and that's not what we want we want warm human touch that breeds trust sowhat's marcado's technology I mean people look at Marketo and people in marketing general yeah they're just hiring agencies to do all this work this isn't real maar tech marketing technology going on I like some of the technology for the folks watching because yeah I think it's pretty interesting most people don't understand that's a lot of machine learning a lot of technology involved in databases from security to trust also enabling real-time yeah share some insight into what's going on there so so this so there's a notion of engagement platform which we believe is is just fundamentally different than your run-of-the-mill marketing cloud so the engagement platform for Marketo is all about that listen learn and engage kind of methodology that we think about and the listening notion as I said literally as we can listen to anything your custom data social channels smoke signals if we had to we can read and consume almost anything and if we can't do it one of our partners can with like a DMP for example they learn the core of our engagement engine and this is pretty neat so we have three engines in our engagement engine we have the automation engine which is all about I hear you say something on Facebook I can engage with you then there's the analytics engine so I can help you understand what are people talking about on Facebook what are you talking on a LinkedIn and then there's the AI engine now this is where I think the the merger of the marketer and the machine is going to start coming together in a big big way so our AI engine allows you to not just say well if people say Silicon angle on Twitter then send them this but you can actually have it adapt and customize learn and reason learn and reason so X writes out and do some it's right it's predictive Oh not only just predictive actually have it I think it's borderline kind of clairvoyant but understand well I'm not just gonna immediately react to something that you put on Twitter I'm gonna go and I'm gonna check the rest of your digital persona there's a digital assistant basically not a sales rep it's more of an assistant it is it is and and so the future of marketing is simple I can build a marketing or an engagement campaign and I can click a button that says make it adaptive and then that's when the machine in the marketer come together and so on top of that engine we have our marketing applications our native apps like marketing automation we have an account based marketing which is a pretty big deal especially in the enterprise account based marketing is all about going from the single buyer to the consensus buying that you know behavior that's see in the enterprise and then we have other technologies like mobile marketing so we can track when you open an app if you close it if you click on it so it's not just one thing we have a range of marketing apps that sit on the platform right so I want to get the final question I get your thoughts on just the future of the business obviously a year you're there two months you got to get to know the team you've got to get to know the players any changes on the horizon that he let's shop so you got a big launch coming up with it well Ryan codename Orion which is there a new engagement platform that you guys pre-announce and get the announcement coming up there got a book you going on but if for Marketo what's the guiding Northstar for you what do you what do you say to customers and kind of the vision and and what changes you look that might be coming down the pike yeah so I think so the vision really there's two elements to that one is that our core focus like at its core is we're going to help the CMO build the lasting relationship derive revenue for the company and the way that we're going to do that is deliver the engagement platform which we are now rolling out I mean we've been working on a ryan for a long time way before I showed up and Orion takes the ability for a marketer to go from millions of interesting touch points per year social mobile did you know digital touch points to quadrillions of touch points we are ready for that digital transformation what we call the engagement economy era I'm writing a book on there the whole notion of engagement economy we're entering this new era where if you're not able to engage with people and and also things because things will be out there too at scale you won't win you just won't we want to get your thoughts on one final point I know we're kind of running up on time in this segment but if you look at the cloud go back to 2008 2007 timeframe when it really emerged and Amazon is already you know had a couple years under their belts with what they were doing you saw the DevOps movement developed merging development and operators be the real catalyst those early adopters you know those you know Navy SEALs the Green Berets you know eating nails and spit and glass out so so that was Facebook that was the big web scalars Yahoo essentially invented Hadoop which became big data you saw all these companies that were new natives build their own stuff not buy off-the-shelf equipment and they became the the canary in the coal mines for everybody else now everyone wants to be like AWS and even Microsoft's changes to be more like AWS and competing directly with them Google is changing so there was early guys on Facebook what they're doing drones and virtual reality you know what these stuff they're doing with open open compute those are now leaders so they're the predictors of the future in my opinion so I look at it so the question I want to ask you is how does Marketo rank up because companies that don't have huge early adopters of the scale side of it platforms that can't scale probably won't have any Headroom so do you have an example where your business has guys pushing the tech scaling it up that are gonna be that canary in the coal mine you guys have that mix of business can you give some examples yeah first of all we have fantastic customers that are using us today kind of scale Oh at scale absolutely whether it's a GE for example GE is literally attributing billions in revenue to the the Marketo engine and the campaigns and efforts that they're driving through that but ge is a perfect example Microsoft another great when there's lots of great examples of customers of ours that are doing what I would I would call hyper scale in engagement within marketing data and they're with marketing data etc so they're using your tools at large large scale yeah and I'd say it's the scale that that today you get these hyper scale example points but tomorrow everybody's gonna have to do it it's just what's neat for us you see the same thing I was mentioned that those hyper scales are gonna be the you know the pioneers that are gonna let the settlers come in and and behind them do you see that more typically and the neat part for us is is because as a marketing automation technology or an engagement platform we're fully integrated with Facebook Linkedin etc so they actually pull us forward we get that I think we get that we've got the telescope to see the canary in the coalmine a little bit further down the road assuming it's a well-lit coal mine but we get to see that a little bit further down the road so I it's an advantage for us strategically I got to ask you the question because in the database world the systems of record the services of engagement and then systems of AI IBM calls it cognitive yes how do you guys play in that new era is that just all marketing for them well I mean everybody has their cognitive exist yeah and you have something it's so they're every two degrees so everyone has tech and we certainly have what what I characterize as adaptive and intuitive that's my version of AI you know I think saying artificially intelligent it's kind of like I've met a bunch of teenagers that I consider to be artificially intelligent but the reality is is that everybody to a degree has this brochure layer tech that they run around waving it really comes down to what's practical what's usable and for us that's we're focused on is what is adaptive and intuitive technology that's going to merge the marketer in the machine final question final final question is what's the top three priorities for you if we look back on your performance next year this time what are the top three things you want to accomplish as the new CEO of Marketo well number one champion engagement economy that whole we're there and I think people just need to understand what it is to is help the market or win I mean the reality is if you boil it down you ask the question what does the marketer what they want to win they just want to win help their company win and so we want to help the marketer win and then three is really engage our marketing nation we've got a community of an online community talking about communities over a hundred thousand marketers that are working inside of that community it's just absolutely huge and so I want to engage the community if we can do that and be just customer centric and oriented our technology the AI all of those things part of our engagement platform it's gonna help us win to stick congratulations on being the co-chief executive Marketo great to see you Steve Lucas here inside the cube and Paul all those new Studios here in Pella 4,500 square feet you see a lot more content live programming as well as featured interviews with top CEOs of Silicon Valley and top technology companies I'm John Fourier thanks for watching