>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music intro) (logo background tingles) >> Hi everybody, welcome back to day three of MWC23, my name is Dave Vellante and we're here live at the Theater of Barcelona, Lisa Martin, David Nicholson, John Furrier's in our studio in Palo Alto. Lot of buzz at the show, the Mobile World Daily Today, front page, Netflix chief hits back in fair share row, Greg Peters, the co-CEO of Netflix, talking about how, "Hey, you guys want to tax us, the telcos want to tax us, well, maybe you should help us pay for some of the content. Your margins are higher, you have a monopoly, you know, we're delivering all this value, you're bundling Netflix in, from a lot of ISPs so hold on, you know, pump the brakes on that tax," so that's the big news. Lockheed Martin, FOSS issues, AI guidelines, says, "AI's not going to take over your job anytime soon." Although I would say, your job's going to be AI-powered for the next five years. We're going to talk about data, we've been talking about the disaggregation of the telco stack, part of that stack is a data layer. John Kreisa is here, the CMO of Couchbase, John, you know, we've talked about all week, the disaggregation of the telco stacks, they got, you know, Silicon and operating systems that are, you know, real time OS, highly reliable, you know, compute infrastructure all the way up through a telemetry stack, et cetera. And that's a proprietary block that's really exploding, it's like the big bang, like we saw in the enterprise 20 years ago and we haven't had much discussion about that data layer, sort of that horizontal data layer, that's the market you play in. You know, Couchbase obviously has a lot of telco customers- >> John: That's right. >> We've seen, you know, Snowflake and others launch telco businesses. What are you seeing when you talk to customers at the show? What are they doing with that data layer? >> Yeah, so they're building applications to drive and power unique experiences for their users, but of course, it all starts with where the data is. So they're building mobile applications where they're stretching it out to the edge and you have to move the data to the edge, you have to have that capability to deliver that highly interactive experience to their customers or for their own internal use cases out to that edge, so seeing a lot of that with Couchbase and with our customers in telco. >> So what do the telcos want to do with data? I mean, they've got the telemetry data- >> John: Yeah. >> Now they frequently complain about the over-the-top providers that have used that data, again like Netflix, to identify customer demand for content and they're mopping that up in a big way, you know, certainly Amazon and shopping Google and ads, you know, they're all using that network. But what do the telcos do today and what do they want to do in the future? They're all talking about monetization, how do they monetize that data? >> Yeah, well, by taking that data, there's insight to be had, right? So by usage patterns and what's happening, just as you said, so they can deliver a better experience. It's all about getting that edge, if you will, on their competition and so taking that data, using it in a smart way, gives them that edge to deliver a better service and then grow their business. >> We're seeing a lot of action at the edge and, you know, the edge can be a Home Depot or a Lowe's store, but it also could be the far edge, could be a, you know, an oil drilling, an oil rig, it could be a racetrack, you know, certainly hospitals and certain, you know, situations. So let's think about that edge, where there's maybe not a lot of connectivity, there might be private networks going in, in the future- >> John: That's right. >> Private 5G networks. What's the data flow look like there? Do you guys have any customers doing those types of use cases? >> Yeah, absolutely. >> And what are they doing with the data? >> Yeah, absolutely, we've got customers all across, so telco and transportation, all kinds of service delivery and healthcare, for example, we've got customers who are delivering healthcare out at the edge where they have a remote location, they're able to deliver healthcare, but as you said, there's not always connectivity, so they need to have the applications, need to continue to run and then sync back once they have that connectivity. So it's really having the ability to deliver a service, reliably and then know that that will be synced back to some central server when they have connectivity- >> So the processing might occur where the data- >> Compute at the edge. >> How do you sync back? What is that technology? >> Yeah, so there's, so within, so Couchbase and Couchbase's case, we have an autonomous sync capability that brings it back to the cloud once they get back to whether it's a private network that they want to run over, or if they're doing it over a public, you know, wifi network, once it determines that there's connectivity and, it can be peer-to-peer sync, so different edge apps communicating with each other and then ultimately communicating back to a central server. >> I mean, the other theme here, of course, I call it the software-defined telco, right? But you got to have, you got to run on something, got to have hardware. So you see companies like AWS putting Outposts, out to the edge, Outposts, you know, doesn't really run a lot of database to mind, I mean, it runs RDS, you know, maybe they're going to eventually work with companies like... I mean, you're a partner of AWS- >> John: We are. >> Right? So do you see that kind of cloud infrastructure that's moving to the edge? Do you see that as an opportunity for companies like Couchbase? >> Yeah, we do. We see customers wanting to push more and more of that compute out to the edge and so partnering with AWS gives us that opportunity and we are certified on Outpost and- >> Oh, you are? >> We are, yeah. >> Okay. >> Absolutely. >> When did that, go down? >> That was last year, but probably early last year- >> So I can run Couchbase at the edge, on Outpost? >> Yeah, that's right. >> I mean, you know, Outpost adoption has been slow, we've reported on that, but are you seeing any traction there? Are you seeing any nibbles? >> Starting to see some interest, yeah, absolutely. And again, it has to be for the right use case, but again, for service delivery, things like healthcare and in transportation, you know, they're starting to see where they want to have that compute, be very close to where the actions happen. >> And you can run on, in the data center, right? >> That's right. >> You can run in the cloud, you know, you see HPE with GreenLake, you see Dell with Apex, that's essentially their Outposts. >> Yeah. >> They're saying, "Hey, we're going to take our whole infrastructure and make it as a service." >> Yeah, yeah. >> Right? And so you can participate in those environments- >> We do. >> And then so you've got now, you know, we call it supercloud, you've got the on-prem, you've got the, you can run in the public cloud, you can run at the edge and you want that consistent experience- >> That's right. >> You know, from a data layer- >> That's right. >> So is that really the strategy for a data company is taking or should be taking, that horizontal layer across all those use cases? >> You do need to think holistically about it, because you need to be able to deliver as a, you know, as a provider, wherever the customer wants to be able to consume that application. So you do have to think about any of the public clouds or private networks and all the way to the edge. >> What's different John, about the telco business versus the traditional enterprise? >> Well, I mean, there's scale, I mean, one thing they're dealing with, particularly for end user-facing apps, you're dealing at a very very high scale and the expectation that you're going to deliver a very interactive experience. So I'd say one thing in particular that we are focusing on, is making sure we deliver that highly interactive experience but it's the scale of the number of users and customers that they have, and the expectation that your application's always going to work. >> Speaking of applications, I mean, it seems like that's where the innovation is going to come from. We saw yesterday, GSMA announced, I think eight APIs telco APIs, you know, we were talking on theCUBE, one of the analysts was like, "Eight, that's nothing," you know, "What do these guys know about developers?" But you know, as Daniel Royston said, "Eight's better than zero." >> Right? >> So okay, so we're starting there, but the point being, it's all about the apps, that's where the innovation's going to come from- >> That's right. >> So what are you seeing there, in terms of building on top of the data app? >> Right, well you have to provide, I mean, have to provide the APIs and the access because it is really, the rubber meets the road, with the developers and giving them the ability to create those really rich applications where they want and create the experiences and innovate and change the way that they're giving those experiences. >> Yeah, so what's your relationship with developers at Couchbase? >> John: Yeah. >> I mean, talk about that a little bit- >> Yeah, yeah, so we have a great relationship with developers, something we've been investing more and more in, in terms of things like developer relations teams and community, Couchbase started in open source, continue to be based on open source projects and of course, those are very developer centric. So we provide all the consistent APIs for developers to create those applications, whether it's something on Couchbase Lite, which is our kind of edge-based database, or how they can sync that data back and we actually automate a lot of that syncing which is a very difficult developer task which lends them to one of the developer- >> What I'm trying to figure out is, what's the telco developer look like? Is that a developer that comes from the enterprise and somebody comes from the blockchain world, or AI or, you know, there really doesn't seem to be a lot of developer talk here, but there's a huge opportunity. >> Yeah, yeah. >> And, you know, I feel like, the telcos kind of remind me of, you know, a traditional legacy company trying to get into the developer world, you know, even Oracle, okay, they bought Sun, they got Java, so I guess they have developers, but you know, IBM for years tried with Bluemix, they had to end up buying Red Hat, really, and that gave them the developer community. >> Yep. >> EMC used to have a thing called EMC Code, which was a, you know, good effort, but eh. And then, you know, VMware always trying to do that, but, so as you move up the stack obviously, you have greater developer affinity. Where do you think the telco developer's going to come from? How's that going to evolve? >> Yeah, it's interesting, and I think they're... To kind of get to your first question, I think they're fairly traditional enterprise developers and when we break that down, we look at it in terms of what the developer persona is, are they a front-end developer? Like they're writing that front-end app, they don't care so much about the infrastructure behind or are they a full stack developer and they're really involved in the entire application development lifecycle? Or are they living at the backend and they're really wanting to just focus in on that data layer? So we lend towards all of those different personas and we think about them in terms of the APIs that we create, so that's really what the developers are for telcos is, there's a combination of those front-end and full stack developers and so for them to continue to innovate they need to appeal to those developers and that's technology, like Couchbase, is what helps them do that. >> Yeah and you think about the Apples, you know, the app store model or Apple sort of says, "Okay, here's a developer kit, go create." >> John: Yeah. >> "And then if it's successful, you're going to be successful and we're going to take a vig," okay, good model. >> John: Yeah. >> I think I'm hearing, and maybe I misunderstood this, but I think it was the CEO or chairman of Ericsson on the day one keynotes, was saying, "We are going to monetize the, essentially the telemetry data, you know, through APIs, we're going to charge for that," you know, maybe that's not the best approach, I don't know, I think there's got to be some innovation on top. >> John: Yeah. >> Now maybe some of these greenfield telcos are going to do like, you take like a dish networks, what they're doing, they're really trying to drive development layers. So I think it's like this wild west open, you know, community that's got to be formed and right now it's very unclear to me, do you have any insights there? >> I think it is more, like you said, Wild West, I think there's no emerging standard per se for across those different company types and sort of different pieces of the industry. So consequently, it does need to form some more standards in order to really help it grow and I think you're right, you have to have the right APIs and the right access in order to properly monetize, you have to attract those developers or you're not going to be able to monetize properly. >> Do you think that if, in thinking about your business and you know, you've always sold to telcos, but now it's like there's this transformation going on in telcos, will that become an increasingly larger piece of your business or maybe even a more important piece of your business? Or it's kind of be steady state because it's such a slow moving industry? >> No, it is a big and increasing piece of our business, I think telcos like other enterprises, want to continue to innovate and so they look to, you know, technologies like, Couchbase document database that allows them to have more flexibility and deliver the speed that they need to deliver those kinds of applications. So we see a lot of migration off of traditional legacy infrastructure in order to build that new age interface and new age experience that they want to deliver. >> A lot of buzz in Silicon Valley about open AI and Chat GPT- >> Yeah. >> You know, what's your take on all that? >> Yeah, we're looking at it, I think it's exciting technology, I think there's a lot of applications that are kind of, a little, sort of innovate traditional interfaces, so for example, you can train Chat GPT to create code, sample code for Couchbase, right? You can go and get it to give you that sample app which gets you a headstart or you can actually get it to do a better job of, you know, sorting through your documentation, like Chat GPT can do a better job of helping you get access. So it improves the experience overall for developers, so we're excited about, you know, what the prospect of that is. >> So you're playing around with it, like everybody is- >> Yeah. >> And potentially- >> Looking at use cases- >> Ways tO integrate, yeah. >> Hundred percent. >> So are we. John, thanks for coming on theCUBE. Always great to see you, my friend. >> Great, thanks very much. >> All right, you're welcome. All right, keep it right there, theCUBE will be back live from Barcelona at the theater. SiliconANGLE's continuous coverage of MWC23. Go to siliconangle.com for all the news, theCUBE.net is where all the videos are, keep it right there. (cheerful upbeat music outro)

>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.

>> From around the globe, it's theCUBE, covering Data Citizens'21. Brought to you by Collibra. >> We're back talking all things data at Data Citizens '21. My name is Dave Vellante and you're watching theCUBE's continuous coverage, virtual coverage #DataCitizens21. I'm here with Jim Cushman who is Collibra's Chief Product Officer who shared the company's product vision at the event. Jim, welcome, good to see you. >> Thanks Dave, glad to be here. >> Now one of the themes of your session was all around self-service and access to data. This is a big big point of discussion amongst organizations that we talk to. I wonder if you could speak a little more toward what that means for Collibra and your customers and maybe some of the challenges of getting there. >> So Dave our ultimate goal at Collibra has always been to enable service access for all customers. Now, one of the challenges is they're limited to how they can access information, these knowledge workers. So our goal is to totally liberate them and so, why is this important? Well, in and of itself, self-service liberates, tens of millions of data lyric knowledge workers. This will drive more rapid, insightful decision-making, it'll drive productivity and competitiveness. And to make this level of adoption possible, the user experience has to be as intuitive as say, retail shopping, like I mentioned in my previous bit, like you're buying shoes online. But this is a little bit of foreshadowing and there's even a more profound future than just enabling a self-service, that we believe that a new class of shopper is coming online and she may not be as data-literate as our knowledge worker of today. Think of her as an algorithm developer, she builds machine learning or AI. The engagement model for this user will be, to kind of build automation, personalized experiences for people to engage with data. But in order to build that automation, she too needs data. Because she's not data literate, she needs the equivalent of a personal shopper. Someone that can guide her through the experience without actually having her know all the answers to the questions that would be asked. So this level of self-service goes one step further and becomes an automated service. One to really help find the best unbiased in a labeled training data to help train an algorithm in the future. >> That's, okay please continue. >> No please, and so all of this self and automated service, needs to be complemented with kind of a peace of mind that you're letting the right people gain access to it. So when you automate it, it's like, well, geez are the right people getting access to this. So it has to be governed and secured. This can't become like the Wild Wild West or like a data, what we call a data flea market or you know, data's everywhere. So, you know, history does quickly forget the companies that do not adjust to remain relevant. And I think we're in the midst of an exponential differentiation in Collibra data intelligence cloud is really kind of established to be the key catalyst for companies that will be on the winning side. >> Well, that's big because I mean, I'm a big believer in putting data in the hands of those folks in the line of business. And of course the big question that always comes up is, well, what about governance? What about security? So to the extent that you can federate that, that's huge. Because data is distributed by its very nature, it's going to stay that way. It's complex. You have to make the technology work in that complex environment, which brings me to this idea of low code or no code. It's gaining a lot of momentum in the industry. Everybody's talking about it, but there are a lot of questions, you know, what can you actually expect from no code and low code who were the right, you know potential users of that? Is there a difference between low and no? And so from your standpoint, why is this getting so much attention and why now, Jim? >> You don't want me to go back even 25 years ago we were talking about four and five generational languages that people were building. And it really didn't re reach the total value that folks were looking for because it always fell short. And you'd say, listen, if you didn't do all the work it took to get to a certain point how are you possibly going to finish it? And that's where the four GLs and five GLs fell short as capability. With our stuff where if you really get a great self-service how are you going to be self-service if it still requires somebody right though? Well, I guess you could do it if the only self-service people are people who write code, well, that's not bad factor. So if you truly want the ability to have something show up at your front door, without you having to call somebody or make any efforts to get it, then it needs to generate itself. The beauty of doing a catalog, new governance, understanding all the data that is available for choice, giving someone the selection that is using objective criteria, like this is the best objective cause if it's quality for what you want or it's labeled or it's unbiased and it has that level of deterministic value to it versus guessing or civic activity or what my neighbor used or what I used on my last job. Now that we've given people the power with confidence to say, this is the one that I want, the next step is okay, can you deliver it to them without them having to write any code? So imagine being able to generate those instructions from everything that we have in our metadata repository to say this is exactly the data I need you to go get and perform what we call a distributed query against those data sets and bringing it back to them. No code written. And here's the real beauty Dave, pipeline development, data pipeline development is a relatively expensive thing today and that's why people spend a lot of money maintaining these pipelines but imagine if there was zero cost to building your pipeline would you spend any money to maintain it? Probably not. So if we can build it for no cost, then why maintain it? Just build it every time you need it. And it then again, done on a self-service basis. >> I really liked the way you're thinking about this cause you're right. A lot of times when you hear self self-service it's about making the hardcore developers, you know be able to do self service. But the reality is, and you talk about that data pipeline it's complex a business person sitting there waiting for data or wants to put in new data and it turns out that the smallest unit is actually that entire team. And so you sit back and wait. And so to the extent that you can actually enable self-serve for the business by simplification that is it's been the holy grail for a while, isn't it? >> I agree. >> Let's look a little bit dig into where you're placing your bets. I mean, your head of products, you got to make bets, you know, certainly many many months if not years in advance. What are your big focus areas of investment right now? >> Yeah, certainly. So one of the things we've done very successfully since our origin over a decade ago, was building a business user-friendly software and it was predominantly kind of a plumbing or infrastructure area. So, business users love working with our software. They can find what they're looking for and they don't need to have some cryptic key of how to work with it. They can think about things in their terms and use our business glossary and they can navigate through what we call our data intelligence graph and find just what they're looking for. And we don't require a business to change everything just to make it happen. We give them kind of a universal translator to talk to the data. But with all that wonderful usability the common compromise that you make as well, its only good up to a certain amount of information, kind of like Excel. You know, you can do almost anything with Excel, right? But when you get to into large volumes, it becomes problematic and now you need that, you know go with a hardcore database and application on top. So what the industry is pulling us towards is far greater amounts of data not that just millions or even tens of millions but into the hundreds of millions and billions of things that we need to manage. So we have a huge focus on scale and performance on a global basis and that's a mouthful, right? Not only are you dealing with large amounts at performance but you have to do it in a global fashion and make it possible for somebody who might be operating in a Southeast Asia to have the same experience with the environment as they would be in Los Angeles. And the data needs to therefore go to the user as opposed to having the user come to the data as much as possible. So it really does put a lot of emphasis on some of what you call the non-functional requirements also known as the ilities and so our ability to bring the data and handle those large enterprise grade capabilities at scale and performance globally is what's really driving a good number of our investments today. >> I want to talk about data quality. This is a hard topic, but it's one that's so important. And I think it's been really challenging and somewhat misunderstood when you think about the chief data officer role itself, it kind of emerged from these highly regulated industries. And it came out of the data quality, kind of a back office role that's kind of gone front and center and now is, you know pretty strategic. Having said that, the you know, the prevailing philosophy is okay, we got to have this centralized data quality approach and that it's going to be imposed throughout. And it really is a hard problem and I think about, you know these hyper specialized roles, like, you know the quality engineer and so forth. And again, the prevailing wisdom is, if I could centralize that it can be lower cost and I can service these lines of business when in reality, the real value is, you know speed. And so how are you thinking about data quality? You hear so much about it. Why is it such a big deal and why is it so hard in a priority in the marketplace? You're thoughts. >> Thanks for that. So we of course acquired a data quality company, not burying delete, earlier this year LGQ and the big question is, okay, so why, why them and why now, not before? Well, at least a decade ago you started hearing people talk about big data. It was probably around 2009, it was becoming the big talk and what we don't really talk about when we talk about this ever expanding data, the byproduct is, this velocity of data, is increasing dramatically. So the speed of which new data is being presented the way in which data is changing is dramatic. And why is that important to data quality? Cause data quality historically for the last 30 years or so has been a rules-based business where you analyze the data at a certain point in time and you write a rule for it. Now there's already a room for error there cause humans are involved in writing those rules, but now with the increased velocity, the likelihood that it's going to atrophy and become no longer a valid or useful rule to you increases exponentially. So we were looking for a technology that was doing it in a new way similar to the way that we do auto classification when we're cataloging attributes is how do we look at millions of pieces of information around metadata and decide what it is to put it into context? The ability to automatically generate these rules and then continuously adapt as data changes to adjust these rules, is really a game changer for the industry itself. So we chose OwlDQ for that very reason. It's not only where they had this really kind of modern architecture to automatically generate rules but then to continuously monitor the data and adjust those rules, cutting out the huge amounts of costs, clearly having rules that aren't helping you save and frankly, you know how this works is, you know no one really complains about it until there's the squeaky wheel, you know, you get a fine or exposes and that's what is causing a lot of issues with data quality. And then why now? Well, I think and this is my speculation, but there's so much movement of data moving to the cloud right now. And so anyone who's made big investments in data quality historically for their on-premise data warehouses, Netezzas, Teradatas, Oracles, et cetera or even their data lakes are now moving to the cloud. And they're saying, hmm, what investments are we going to carry forward that we had on premise? And which ones are we going to start a new from and data quality seems to be ripe for something new and so these new investments in data in the cloud are now looking up. Let's look at new next generation method of doing data quality. And that's where we're really fitting in nicely. And of course, finally, you can't really do data governance and cataloging without data quality and data quality without data governance and cataloging is kind of a hollow a long-term story. So the three working together is very a powerful story. >> I got to ask you some Colombo questions about this cause you know, you're right. It's rules-based and so my, you know, immediate like, okay what are the rules around COVID or hybrid work, right? If there's static rules, there's so much unknown and so what you're saying is you've got a dynamic process to do that. So and one of the my gripes about the whole big data thing and you know, you referenced that 2009, 2010, I loved it, because there was a lot of profound things about Hadoop and a lot of failings. And one of the challenges is really that there's no context in the big data system. You know, the data, the folks in the data pipeline, they don't have the business context. So my question is, as you it's and it sounds like you've got this awesome magic to automate, who would adjudicates the dynamic rules? How does, do humans play a role? What role do they play there? >> Absolutely. There's the notion of sampling. So you can only trust a machine for certain point before you want to have some type of a steward or a assisted or supervised learning that goes on. So, you know, suspect maybe one out of 10, one out of 20 rules that are generated, you might want to have somebody look at it. Like there's ways to do the equivalent of supervised learning without actually paying the cost of the supervisor. Let's suppose that you've written a thousand rules for your system that are five years old. And we come in with our ability and we analyze the same data and we generate rules ourselves. We compare the two themselves and there's absolutely going to be some exact matching some overlap that validates one another. And that gives you confidence that the machine learning did exactly what you did and what's likelihood that you guessed wrong and machine learning guessed wrong exactly the right way that seems pretty, pretty small concern. So now you're really saying, well, why are they different? And now you start to study the samples. And what we learned, is that our ability to generate between 60 and 70% of these rules anytime we were different, we were right. Almost every single time, like almost every, like only one out of a hundred where was it proven that the handwritten rule was a more profound outcome. And of course, it's machine learning. So it learned, and it caught up the next time. So that's the true power of this innovation is it learns from the data as well as the stewards and it gives you confidence that you're not missing things and you start to trust it, but you should never completely walk away. You should constantly do your periodic sampling. >> And the secret sauce is math. I mean, I remember back in the mid two thousands it was like 2006 timeframe. You mentioned, you know, auto classification. That was a big problem with the federal rules of civil procedure trying to figure out, okay, you know, had humans classifying humans don't scale, until you had, you know, all kinds of support, vector machines and probabilistic, latent semantic indexing, but you didn't have the compute power or the data corpus to really do it well. So it sounds like a combination of you know, cheaper compute, a lot more data and machine intelligence have really changed the game there. Is that a fair assumption? >> That's absolutely fair. I think the other aspect that to keep in mind is that it's an innovative technology that actually brings all that compute as close into the data as possible. One of the greatest expenses of doing data quality was of course, the profiling concept bringing up the statistics of what the data represents. And in most traditional senses that data is completely pulled out of the database itself, into a separate area and now you start talking about terabytes or petabytes of data that takes a long time to extract that much information from a database and then to process through it all. Imagine bringing that profiling closer into the database, what's happening in the NAPE the same space as the data, that cuts out like 90% of the unnecessary processing speed. It also gives you the ability to do it incrementally. So you're not doing a full analysis each time, you have kind of an expensive play when you're first looking at a full database and then maybe over the course of a day, an hour, 15 minutes you've only seen a small segment of change. So now it feels more like a transactional analysis process. >> Yeah and that's, you know, again, we talked about the old days of big data, you know the Hadoop days and the boat was profound was it was all about bringing five megabytes of code to a petabyte of data, but that didn't happen. We shoved it all into a central data lake. I'm really excited for Collibra. It sounds like you guys are really on the cutting edge and doing some really interesting things. I'll give you the last word, Jim, please bring us on. >> Yeah thanks Dave. So one of the really exciting things about our solution is, it trying to be a combination of best of breed capabilities but also integrated. So to actually create a full and complete story that customers are looking for, you don't want to have them worry about a complex integration in trying to manage multiple vendors and the times of their releases, et cetera. If you can find one customer that you don't have to say well, that's good enough, but every single component is in fact best of breed that you can find in it's integrated and they'll manage it as a service. You truly unlock the power of your data, literate individuals in your organization. And again, that goes back to our overall goal. How do we empower the hundreds of millions of people around the world who are just looking for insightful decision? Did they feel completely locked it's as if they're looking for information before the internet and they're kind of limited to whatever their local library has and if we can truly become somewhat like the internet of data, we make it possible for anyone to access it without controls but we still govern it and secure it for privacy laws, I think we do have a chance to to change the world for better. >> Great. Thank you so much, Jim. Great conversation really appreciate your time and your insights. >> Yeah, thank you, Dave. Appreciate it. >> All right and thank you for watching theCUBE's continuous coverage of Data Citizens'21. My name is Dave Vellante. Keep it right there for more great content. (upbeat music)

>> Announcer: Live from San Diego, California it's The Cube! Covering Cisco Live US 2019. Brought to you by Cisco and it's ecosystem partners. >> Welcome back to The Cube's coverage of Cisco Live Day 2 from sunny San Diego. I'm Lisa Martin joined by Dave Vallante. Dave and I have an alumni, a Cube alumni back with us, Jeff Moncrief, consulting systems engineer from Cisco. Jeff, welcome back! >> Thank you very much, it's great to be back! >> So, we're in the DevNet Zone, loads of buzz going on behind us. This community is nearly 600,000 strong. We want to talk with you about Stealthwatch. You did a very interesting talk yesterday. You said, it had a couple hundred folks in there. War stories from real networks. War stories ... strong descriptor. Talk to us about what that means, what some of those war stories are, and how Stealthwatch can help customers learn from that and eradicate those. >> So it's called Saved by Stealthwatch. It was a really good session. This is the third Cisco Live that I've presented this session at. And it's really just stories from actual customer networks where I've actually deployed Stealthwatch into. I've been selling Stealthwatch for about five years now. And I've compiled quite a list of stories, right? And it really ... if you think about advanced threats and insider threats and those kinds of exciting things, the presentation was really about getting back to fundamentals. Getting back to the fact that in all these years that I've been working with customers and using Stealthwatch, a lot of the scary things that I have found have nothing to do with that. With the advanced type threat stuff. It really has to do with the fact that they're forgetting the basics. Their firewalls are wide open, their networks are flat. Their segmentation boundaries aren't being adhered to. So it's allowed us to come in and expose a lot of scary things that were going on and they were just completely oblivious to it. >> Why are those gaps there? Is it because of a change management issue? Technology's moving so quickly? Lack of automation? >> Yeah, I think there's a couple reasons that I've seen. It's a recurring theme really. Limited resources ... number one. Number two, limited budgets, so your priorities have to shift. But I think a big one that I've seen a lot is turnover and attrition. A lot of times we'll go in with Stealthwatch and we'll kick off an evaluation or whatnot and the customer will say, I just don't know what's there. I don't know if I have 100 machines that need visibility or for a thousand. And I'm a Stealthwatch cloud consulting systems engineer so the cloud world is where I spend a lot of my time now and what I'm seeing as it relates to the cloud realm is that's exponentially worse now. Because now you've got things like devops and shadow IT that are all playing in the customer's public cloud environment deploying workloads, deploying instances and building things that the security team has no awareness of. So there's a lot of things that are living and breathing on the network that they just don't know about. >> And so the tribal knowledge leaves the building, how do you guys help solve that problem? >> So we come in ... and you know the last time that you and I spoke, you used the term cockroaches, I think, which I loved. I actually have used that a lot since then, so thank you for that. >> Dave: Yeah, you're welcome. >> No, but, you know ... we come in and we actually, we turn the customer's network infrastructure ... Whether it's on-prem or in the public cloud into a giant security sensor grid. And we leverage something called NetFlow, which you've probably heard of. And it's essentially allowing us to account for every conversation throughout the entire infrastructure, whether or not it's on-prem or in the public cloud or maybe even in a private cloud. We've got you covered in that area. And it allows us to expose every one of those living, breathing things. And then we can just query the system. So think of us like a giant network DVR on steroids. We see everything, you can't hide from us, because we're using the network to look at everything. And then we can just set little trip wires up. And that's kind of what I go into in my presentation also is how you can set these trip wires ahead of time to find things that are going on that you just didn't know about and frankly, they're probably going to scare ya. >> One of the stories that you shared in your talk yesterday. You talk about people really forgetting the basics. A university that had a vending machine breach. You just think, a vending machine in a cafeteria? >> Jeff: That's right. >> Really? Tell us about that. What kind of data was exposed from a vending machine? >> So that's one of my favorite stories to tell. We had gone in and we'd installed Stealthwatch at a small university in the US. And they had a very small team. Okay, you're going to see that recurring theme. Limited staff. And they really just had a firewall. Okay, that was what they were doing for security. So we came in, we enabled NetFlow, we kind of let Stealthwatch do it's thing for a couple of days, and I just queried the system. Okay, it's not rocket science, it's not AI a lot of times, it's really the fundamentals. And I just said, tell me anything talking on remote desktop protocols inside the network out to the internet. And lo and behold, there was one IP address that had communication from it to every bad country you can imagine ... actively. And I said to them ... I said, what is this IP address? What's it doing? And that was in the conference room in the university with their staff and the guy looked it up in the asset inventory system, and he looked at me and he goes, that's a vending machine. And I said, a vending machine? And he said, yeah. And then I was like, okay, well that's a first, I've never heard of that before. And he goes wait a minute, it's a dirty tray return machine. You ever heard of one of those? >> Lisa: No. >> I hadn't either. >> Lisa: Explain. >> So for loss prevention, I guess universities and other public institutions, they will buy these unique vending machines that are designed for loss prevention. So that the college students don't go around and you know, steal or throw away the trays from the cafeteria. You have to return the tray to get a coin. There's a common supermarket chain that does the same thing with their shopping carts. And it's for loss prevention. So I said, okay, that's pretty strange. Even stranger than just vending machine. And I said, well did you realize that it was talking to a remote desktop all over the world? And he said no. And I said so, can you tell me what it has access to? So he looked it up in the firewall manager right there and he said, it has access to the entire network. Flat network, no segmentation. No telling how long this had been going on, and we exposed it. >> And Stealthwatch exposes those gaps with just kind of old school knock on the door. >> Yeah, it really is. We're talking about fundamental network telemetry that we're gathering off the route switch infrastructure itself. You know, obviously, we're at Cisco Live, we work really well with Cisco gear. Cisco actually invented NetFlow about 20 years ago. And we leveraged that to give visibility footprint that allow us to expose things like the vending machine. I've found hospital x-ray machines that were scanning all the US military, for instance. I find things in the cloud that are just completely wide open from a security ACL standpoint. So we've got that fundamental level of visibility with Stealthwatch, and then we kick in some really cool machine learning and statistical analytics and machine running analytics and that allows us to look for anomalies that would be indicators of compromise. So we're taking that visibility footprint and we're taking it to that next level looking for threats that might be in the customer's environment. >> So before we get to the machine intelligence, I presume that cloud and containers only makes this problem worse. What are you seeing in the field? How are you dealing with that? >> So we're in a landscape today where we've got a lot of customers that might be cloud averse. But we've also got a lot of customers that are on the wide other side of that spectrum and they're very cloud progressive. And a lot of them are doing things like server-less micro services, containers and, when you think of containers you think of container orchestration ... kubernetes. So Stealthwatch Cloud is actually in that realm right now today, able to protect and illuminate those environments. That's really the Wild West right now, is trying to protect those very abstract server-less and containerized environments but yeah, we come in, we are able to deploy inside kubernetes clusters or AWS or azure or GCP, and tell the Stealthwatch story in those environments, find segmentation violations, find firewall holes just like we would on premise, and then look for anomalies that would be interesting. >> So the security paradigm for those three you mentioned, those three cloud vendors, and you're on-prem, and maybe even some of your partners, is a lot of variability there. How should customers deal with maintaining the edicts of the organization and sort of busting down those silos? >> Yeah, so you think about like Stealthwatch Cloud which is the product that I'm a CSE for, we're really focusing on automation, high efficacy and accuracy. All right, we're not going to be triggering hundreds or thousands of alerts whenever you plug us in. It's going to further bog down a limited team. They've got limited time and they have to change their priorities constantly. This solution is designed to work immediately out of the box quickly deploy within a matter of hours. It's all SAAS based so actually it lives in the cloud. And it really takes that burden off of the organization of having to go and set a bunch of policies and trip wires and alerts. It does it automatically. It's going to let you know when you need to take a look at it so that you can focus on your other priorities. >> So curious where your conversations are within an organization - whether it's a hospital, or a university when what you're finding is in this multi-cloud world that we live in where there's attrition and all of these other factors contributing to organizations that don't know what they have with multi-cloud edge comes this very amorphous perimeter, right? Where are those conversations because if data is the lifeblood of an organization, if it's not secure and protected, if it's exposed there's a waterfall of problems that could come with that. So is this being elevated into the C-Suite of an organization? How do you start those conversations? >> So it's not just the C-Suite and the executive type structure that we're having to talk to now, traditionally we would go in with the Stealthwatch opportunity and talk to the teams in the organization it's going to be the InfoSec team, right? As we move to the cloud though, we're talking about a whole bunch of different teams. You've got the InfoSec team, you've got the network operations team now, they're deploying those workloads. The big one though that we've really got to think about and what we've really got to educate our customers on is the Dev Ops teams. Because the Dev Ops teams, they're really the ones that are deploying those cloud workloads now. You've got to think about ... they've got API access, they've got direct console login access. So you've got multiple different entry points now into all these different heterogeneous environments. And a lot of times, we'll go in and we'll turn on Stealthwatch and we show the organization, yeah, you knew that Dev Ops was in the VPC's deploying things, but you didn't know the extent that they were deploying them. >> Lights up like a Christmas tree? >> Yeah, lights up like a Christmas tree and like a conversation I had last week with a customer. I asked them, I said, all right so you're in AWS, are we talking do you have 50 instances or do you have 500? He said, I have no idea. Because I'm not the one deploying these instances. I'm just lucky enough to get permission to have access to them to let you plug your stuff in to show me what's going on in that environment. But yet they're in charge of securing that data. So it's quite frightening. >> So you've got discovery, you've got ways to expose the gaps, and then you're obviously advising on remediation activity. And you're also bringing in machine intelligence. So what's the endgame there? Is it automation? Is it systems of agency where the machine is actually taking action? Can you explain that? So when the statistical analysis comes in and the anomaly detection comes in, it's really that network DVR, so we've got the data, now let's do some really cool things with it. And that's where we're in actually, for every single one of these entities, and I do stress entities because the days of operating systems and IP addresses are going away. Face it, it's happening. Things are becoming more and more abstract. You know, API keys, user accounts, lambda's and runtime compute, we have to think about those. So what we do for all these different entities is we build a model for each one of these, and that model, that's where all the math and the AI comes in. We're going to learn Known Good for it. Who do they talk to? How much data's sent or received? And then we start looking for activity in that infrastructure as it relates to that entity that's outside of that Known Good model. So that would be the anomaly detection and you know, our anomaly detection, it really can be attributed to two different major categories. Number one is going to be, we're looking for things that cross the cyber kill chain. So those different IOC's as a threat actually manifests. That's what the anomaly detection's doing. And then we're also looking for just straight compliance and configuration violations in the customer's cloud infrastructure, for instance, that would just be a flat out security risk today, day one, forget base lining anomaly detection, it should just not be configured that way. >> Let's see, roughly 25% of Cisco's revenue is in services, what role does the customer service team play in all this? How do you interact ... how do the product guys and the service guys work together? >> So we've got a great customer experience team, customer services team for Stealthwatch and it doesn't matter if we're talking Stealthwatch on-premise or the Stealthwatch cloud, they cover both. And what will happen is we'll come in from a pre-sales standpoint, we do the evaluation, show good value, and then we've got a good relationship with the CX team where we'll hand that off to them, and then we'll work with the CX team to make sure that customer is good to go, they're taken care of, and it's not we've sold this and we're just going to forget you type scenario. They do a good job of coming in, they make sure that the customer's needs are met, any feature requests that they like taken care of. You know, they have routine touchpoints with the customers and they make sure that the product, for all intents and purposes, doesn't lose interest or visibility in the customer's environment. That they're using it, they're getting good value out of it, and we're going to build a relationship. I call it cradle to grave. We're going to be with that customer cradle to grave. >> Now Jeff, one of the things I didn't talk to you about at Google Next was ... first I got to ask you, you're a security guy, right? Have you always been a security guy? >> Yeah, security for about 20 years now, dating back to internet security systems. >> The question I often ask security guys is who's your favorite superhero? >> My favorite superhero ... I'd say Batman. >> Dave: Batman? >> Yeah. >> I like Batman. (chuckles) The reason I ask is that somebody told me one time that true security guys, they love superheroes because they grew up kind of wanting to save the world and protect the innocent. So ... just had to ask. >> Yeah there you go .. Batman. >> I'm sensing a tattoo coming. Last question for you Jeff is in terms of time to business impact, the vending machine story is just so polarizing because it's such a shocking massive exposure point, did they ever discover how long it had been open and in terms of being able to remedy that, how quickly can Stealthwatch come in, identify these- >> So very quick operation wise. So like the vending machine story, that's something that if you turn on Flow, and you send it to Stealthwatch right now, we can pick that up in 10 minutes. That quick to visibility and value. Now how long has it been going on? A lot of times they can't answer that question because they've never had anything to illuminate that to begin with. But moving forward, now they've got a forensic incident response audit trail capability with Stealthwatch which is actually a pretty common use case. Especially if you think about things like PCI that have got auto requirements and whatnot. A lot of organizations if they're not using a Flow based security analytics tool, they can't always meet those audit and forensic requirements. So at least from the point of installing Stealthwatch they'll be good to go from that point forward. >> So if they can find an anomaly that needs to be rectified in 10 minutes, what's the next step for them to actually completely close that gap? >> So like with Cisco Identity Services engine, we've got a great integration there where we can actually take action, shut off that machine instantly. We can shut off a switch port. We can isolate that machine to an isolated sandboxed VLAN, get it off the network, and then in the cloud, we can do things like automated remediation. We can use things like Amazon and Lambda to actually shut off an instance that might be compromised. We can actually use Lambda's to insert firewall rules. So if we find a hole, we can plug it. Very easily, automated- >> Ship a function to it and plug a hole. >> Batman slash detective. I think you need a tattoo and a badge. >> I can work on that, I like it. >> Jeff thank you so much for joining Dave and me on The Cube this afternoon. >> My pleasure. >> Really interesting stuff, we appreciate your time. >> Absolutely. >> For Dave Vallante, I'm Lisa Martin. You're watching The Cube's second day of coverage of Cisco Live from San Diego. Thanks for watching. (upbeat music)

>> Live from San Diego, California, it's the Cube. Covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Hi, welcome back to Cisco Live from sunny San Diego. I'm Lisa Martin with Dave Vellante and David are joined by a couple of guests from DXC. To my right we've got Jake Sager, principal client executive TMT, Tech Media Telecom. Jake, great to have you on the program. >> Thank you. >> Now we're broadcasting from the sun. And Randy Redman, the director of security services Product Management. Randy welcome. >> Thank you very much. Glad to be here. >> So we're in the definite zone. You can imagine all of the exciting conversations going on behind us here. Guys, I just noticed that DXC, guys have been around for a couple of years IT services company with 25 billion in annual revenue, but you guys were just named, I think it's this morning, number three on CLUS 2019 solution provider list up from number 10 last year. Pretty good momentum. Jake, we'll start with you. What do you see in feed on the street, in the market with respect to digital transformation, what are customers pains and how is the DXC helping knock him out of the park? >> Well, I think you know, DXC has a long legacy history over 60 years of business together from CSC, EDS, and obviously HP heritage. So we've kind of seen it all and seen the business transform from a highly on the ground business to now a lot of things in the cloud. With that obviously customers are looking to do business in different ways. There's a lot of digital disruptors out there. So they're looking to find the new solution that's going to shade off the competition, kind of skirt it, find the newest best thing before they can and find customer driven solutions rather than just cost driven solutions and other things like that. >> So when you say customer driven solution, let's dig into that a little bit more. What does that mean? And how is it actually, how does it manifest? >> Well, I think the customer can be a lot of different things to a lot of different people. In retail, it can be somebody walking into your store and banking, it can be somebody using an app. But what does that end consumer want? What's going to make their life easier and make them go to you versus another company? And that's really what companies need to be looking at. There's no one answer to anything. But it's a lot of thought-lead leadership to try to come up with something brand new, that is not going to be disrupted by the next Airbnb or Uber. >> So you are a CEO, Michael, talks a lot about digital transformation. >> Right. >> Right here in the security side of things. So we going to dig into that a little bit. But in terms of the evolution of digital transformation, generally and specifically, how people are rethinking security as a result, because we often say, what's the difference between a business and a digital business? Well, it's how they use data. Okay, well and that opens up a whole can of worms on security. So what are you seeing in terms of the evolution of the so called digital transformation, but specifically how it's affecting their posture towards security? >> Yeah, absolutely, because in a digital environment, customers are completely rethinking both how their infrastructure is deployed and how their applications are deployed. And so really, it's opening up whole new avenues for security threats to enter their environments. At the same time, there are so many individual security technologies and customers are really struggling with what are the right technology choices to make and then more importantly how to operate them effectively, how to implement appropriate security policies, how to actually monitor effectively for threats across the environment. So digital transformation is changing their business environment, but it's really completely opening up the sphere on the security side of the house. >> So Jake, we were talking and I had asked you what your favorite topics are, you said, smart city, IoT and connected cars. Sounds like a security nightmare. >> Yeah. >> But it's an opportunity as well for you guys. >> Absolutely. >> So you go in, what's the customer conversation like? I mean, pick one or all three, if you can generalize, in terms of I mean, these are all new things, right? It's the Wild West right now. What's customers mindset? Like you said, they don't want to get disrupted. They're looking at new opportunities. What are they looking at? How are you guys helping them? >> Well, it depends industry by industry. You know, when it comes to healthcare, we can help with remote telemedicine, operating medical equipment remotely. But again, that's going to bring in a whole bunch of new security threats, which Randy is going to be more than equipped to talk about. But I think securing that is really a big problem. When you start talking about massive IoT, you're talking about thousands and thousands of sensors out there in a smart city or oil mining gas utility, like they were talking about earlier today. You're talking about tons of different entry points, lots of different vulnerabilities. So that's definitely a huge issue for them. It's also a ton of new data that they don't know how to manage, that they don't know how to make sense out of, through artificial intelligence or other means. So for a company like us that really has strength in security, artificial intelligence, machine learning, as well as a strong background of data center, data lake management, helping them kind of figure out what data to use and how to use it most effectively. That's really where we shine. Cause we're not necessarily the company providing the hardware. We're not the company writing the software. But we're really the glue that integrates it all together, and brings all those multi solutions together. 'Cause in IoT, it's an ecosystem. It's not solution in a box. >> Let's dig into the Smart City concept. It's so fascinating. I've read up on the Las Vegas city of Las Vegas, which is been on the Cube. Done a lot to really transform that city. But to your point take about data, I think Chuck Robbins said this morning in the keynote that organizations are only really getting insight from less than 1% of their data. >> Right. >> It must be one of those where do we start? >> Right. >> So you are talking about working with municipalities on becoming smart cities and being able to apply some of your expertise and AI. Where do you start that conversation? >> Well, I mean, the terms over abused, I think data is a new oil, right? So if you don't know which data you're getting it from and you're only getting 10%, you're not doing a very good job as an oil producer, right? So our company is very good at identifying where the data is. 'Cause a lot of times, that's half the problem, is finding where that data resides, getting it into a place where you can actually ingest it, and then actually analyze it and get something useful out of it. Companies typically don't know where all their data is, they don't know how to analyze it and they definitely don't know how to turn it into something useful. So that's something DXC does across the board. >> What about the partnership with Cisco? So Cisco, obviously, it's got the networks, it's got, you know, packets flying around. It's got to secure those. What's the partnership like? Are you leveraging their products? I'm sure you are. You guys use everybody's products. >> Right. >> What's the partnership like? And what specifically are you doing in the security area Randy? >> Yeah, so in terms of the partnership with Cisco, we're certainly looking in several areas frankly, because right, we're looking with our clients at a solution letter approach, right. And that's one of the things that we like with Cisco is the broad portfolio meshes with our broad portfolio. So certainly key areas of focus for us right now are in the Unified Communication space and how we're helping with collaboration for our clients, but also in the security area, technologies, such as Cisco stealth watch, which is helping provide more visibility to what's happening in networks today. Because more and more our view is that security as we were just talking about, even in the IoT space becomes more of an analytics exercise. It's less about really being able to detect what you already know, it's really about being able to drive detection from the unknown. And so the more data that we can get, the more visibility into network environments the better. >> How do you work with Cisco? 25% of Cisco's revenue is they called services. So, where do they leave off? I mean they're a product company. You guys are a services firm, but they have services. >> Right. >> How do you interact with them? You don't compete, I presume. At least there's maybe some overlap. But, where do they leave off and you guys pick up? >> Yeah, so certainly, we're not competing with Cisco from a services perspective. We're certainly relying on Cisco services for hardware and professional support around their technology. We're really there to provide overall solution design, architecture installation and we'll leverage Cisco professional services where that's appropriate. And then we provide managed services on the back end as well. >> So you're saying their role is to make sure it's architected properly and it's working, in the way it's promised. Your role is to say it my way and you can correct me is help the customer figure out how to apply those technologies to create business value. >> Well, exactly and also typically in a client solution. Cisco maybe one of several technologies that are involved in a broader solutions-- >> you got to make it all work together tomorrow-- >> And part of our role is to act as that integrator to bring the core Cisco elements with the DXC services and-- >> So your jobs getting harder and harder and harder. >> Fully it is. It's a security perspective. >> Dave: As a consumer things are getting easier, right? Oh, yeah, Google, Facebook, Instagram is so easy. But the back end with, you know, cloud and DevOps, the pace of change. How have you seen that affect your business? How are you dealing with that rapid change? >> Yeah, so I think that from a couple of perspectives here. One is that it's changing how we go about the process in terms of developing services and capabilities for our clients. Just as Agile has taken over actually in the application space, It's really driving how we think about actually developing offerings now around getting technology out into the market more quickly, evolving and growing capability from there. And so really, it's all about how we get proof of value for our clients quickly by getting technology into their hands as quickly as possible. >> Lisa: So let's talk about some of these waves of innovation Cisco was talking about this morning. Talking about this explosion of 5G, Wi-Fi 6 being able to have this access that works really well indoors outdoors, how that's changing even Jake you know, consumer demand. What opportunities, and Jake I'll start with you, what opportunities and some of the things that Cisco was talking about with respect to connectivity, AI with GPUs being everywhere, edge mobile, architectures becoming so a Morpheus opportunity for DXC to help customers really not just integrate the technologies but to excel and accelerate themselves to define new services, new business models. What's your differentiation point there? >> I mean, our main differentiation point from DXC is agnostic to the technology. We really specialize in being vendor agnostic, finding the best of breed companies out there and integrating it into our portfolio and offering it to our clients. If our client wants Azure, we're not going to try to sell them on Google Cloud. If they want one or the other, we're going to be hand in hand with the customer either way. With these new technologies that come around, it's just going to open the doors for so many new types of business, so many more disruptive businesses. No matter what comes along our goal is to have that portfolio in hand, which Cisco rounds out to be able to offer to our over 6000 enterprise clients. So we need to be able to manage every shape, size, variety, industry, anything you can think of. >> What's the trend? Is the trend, yeah, we want as you say, okay, we'll make it make it work for you or is the trend like, you guys figure it out. We're not sure what the right fit is. How much of that is going on? >> I'd say you probably see 50 50. (Jake laughs) >> I think we're seeing a lot of that. Certainly as clients are migrating applications to the cloud. They may be starting with a particular cloud platform, but clients are really frankly fairly agnostic in terms of the cloud platform they're migrating to. They're taking advantage of more and more SAS applications. So one of the trends that we're definitely seeing is how to address client security concerns in a hybrid cloud environment because that's more and more what we expect the future to be, even if clients are focusing on a particular cloud platform as their starting point today. >> So as data is traversing the network and one of the one of the things that I heard this morning from Chuck Robbins keynote was that the common denominator as all of these changes and waves in innovation are coming is the network. Data is traversing the network. Given that is a given and there's only going to be more and more data and more connected devices, more mobile data traffic. Randy question for you. How can DXC, how can you help customers leverage your expertise and say security and AI, as you mentioned, to extract more value from their data and allow them to become far more secure as the it's no longer acceptable, you can't just simply put a firewall around a perimeter that has so many a Morpheus points? >> Yeah and absolutely. And as we mentioned, with all of the data that's available today, it really becomes more of an analytics problem. And one of the investments that the DXC is making is specifically in our security platform that allows us to ingest data from pretty much any infrastructure data source and be able to leverage capabilities to provide analytics, machine learning and automation on top of that, to help clients leverage the power of the data and specifically from a security perspective, not just drive detection, because that's interesting. The question I get from clients is well now, what do I do about it? >> Right. >> And we're leveraging investment, our platform automation is actually to begin to take automated actions on behalf of our clients in order to solve security problems. >> Excellent, guys. Well, thank you so much, Jake, and Randy for stopping by the Cube and talking with Dave and me about what you guys are doing at DXC. The next time we'll have to talk about connected cars. >> Sure. >> Thank you. >> Alright. For Dave Vellante I'm Lisa Martin, you're watching the Cube live from Cisco Live in sunny San Diego. Thanks for watching. (techy music)

(upbeat music) >> Live from Las Vegas, it's theCUBE! Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World here in Las Vegas. I am your host, Rebecca Knight. We are joined by John Lieto. He is the Director, Data Management at Wolters Kluwer. Thank you so much for coming on the show. >> Very welcome. >> So, Wolters Kluwer is a global provider of professional information, software solutions, tax information. Tell our viewers a little bit more about the company and about your role at the company. >> Yeah, so Wolters Kluwer, I would say probably 20 years ago, was a typical holding company. Has a very long history of publishing in Europe. It's over 185 years old in Europe. But, went on a journey to acquire businesses that were in the services business with a focus on legal, but there are also big concentrations in health divisions, tax and accounting, really a professional company. Very, very, very big in print. What happened over the last 10, 15 years though, it's completely flipped over to digital. In fact, it's been one of the more successful transformations. So now we're mostly in the digital space and electronic space. So where I come in, and my business unit comes in, CT Corporation is a 126-year-old company. Number one player in registered agent services. Legal information, helping companies like Informatica stay in compliance. United States is 50 states with 50 sets of rules, plus international. So typically, companies of any size get a provider. Sometimes their law firms will do it, but a lot of times, it's going to be CT Corporations, things like that. My role in the company, I've been there 19 years, I've had a mix of roles, mostly in the business but a little technical. I'm the Director of Data Management, I am basically in charge of managing governance and data quality for the business. It is focused on the customer right now and all things related to customer, but we're expanding into other domains like vendors, products, suppliers and supporting of pretty large digital transformation. >> So I'm sure in your role you have a lot of practical insights for MDM practitioners but before we go there, I want to hear from you about the customer mindset, I mean, this is a moment for data governance and security... >> Sure >> and privacy, a real inflection point, and like Wolters Kluwer, so many companies undergoing their own digital transformations. How would you describe the customer mindset about all of this? How are customers wrapping their brains around it? >> So for us, we're not in a very regulated business. We touch customers that are heavily regulated, but we're not, we're a service company, right? Most of the stuff, the data we deal with is public knowledge, right? A company's data is public knowledge, you can go in any state website and find out when Informatica was formed, who the board of directors are, so it's all public. But customers are extremely sensitive about where their data is, and what we're doing with it, so we were on top of that, especially for our foreign customers. Internally the CT and Wolters Kluwer we have to be very, very, very customer-focused 'cause it's a very direct service, right? So it's all about the customer. How we got to this point of using Informatica MDM, Massive Data Management, is trying to get close to the customer, trying to understand the customer. Our customers go from J P Morgan to these big, big, big companies that have investments in companies that you wouldn't even know they're related to that customer. So they rely on us to help them stay compliant. How do I deal with these diverse businesses that are under my portfolio, and how do I keep them compliant in the States? So we have all this data and we help our customers understand it, and know what to do next, almost anticipate where they're going to fall out of compliance in the State. >> So what is your advice for the people who are really starting, for the executives starting at square one, trying to think about a master data management solution? >> Yeah, great question. And it's really where the heart of my devotion has been the last year. I would say the most important thing is start with a business case. Understand where your business is going. Make it about what outcomes are you looking for. Really thoroughly understand that. Also take the systems or the subjects that are important to you, your company, and profile it. Understand that data. You can come to an MDM project, a master data management project, with so much knowledge first, don't just say, well everybody is doing master data management, we should do it too. I mean, it might be true, but you're really not going to get the outcomes. And then focus your project to hit those business goals, 'cause MDM is a process and a tool, it's not an answer. You need to use that tool to get to where you are, so for us the number one thing was reduce duplication, okay, MDM tools do that, so we're trying to get to the golden record, okay. Data quality, I don't have the good phone numbers I have bad email addresses, oh, mass data management does that too. So, again, it's going for the outcomes you're driving for, and MDM happens to be a good tool for that. >> So it's really about defining the objectives before you even jump in. >> Absolutely. >> Do you recommend experiments? What's the approach you... >> Wonderful question. In data we call it profiling, right? And you want to go in small wins, because one of the things that will happen to anyone in this space is the business is really not sure about this investment. These days, data is becoming so huge that's becoming a lot easier for guys like me to win a business case, but two years ago it was pretty hard. I'm sorry I just lost my train of thought. >> But that's an interesting point, just talking about the overcoming the skepticism within these companies to latch on to this idea, and as you were saying, the announcing the small wins, really getting everyone on board. >> Thank you. What we did is, we had profiled, found a problem, oh, we have definitive cost duplication, we've got email addresses that are completely bogus. Let's just to take those two. And we did small little pilots. We'd use tools we had, completely manual ad-hoc, let's fix 200 records, let's take a really important customer that we're trying to onboard, or expand, and let's fix that data, and then show the outcomes. Go for the quick wins. Communicate, communicate, communicate. Once we did that, and we did a series of, I want to say, 30 or 40 of these. That built our requirement set. We built the requirement set by doing. It was so easy that way to show victories, but too, to really get the requirements to a point where we could build the system. We happened to fall on that method, from prior learnings of not doing well on projects that had nothing to do with MDM. So for this one, I think the other piece of advice that I would give folks, is we built a data management team of business analysts that know our business and data. It is really critical that you keep this function out of IT. IT is your supporter and your partner. This does not go to IT. So we know our data. I have a guy on my team that's 45 years in the company, a woman who's 28 years in the company, just for example. So we can do a lot without a tool, and what's happening is now we are live for going on eight months now, and we're staying on top, making sure the tool's delivering what it's supposed to deliver, based on our deep knowledge. >> And I think that what you're talking about really, is introducing this technology and this new way of thinking, and it's really all about change management. >> It truly is. >> One of the things that we're talking a lot here in theCUBE about is the skills gap, and this is a problem throughout the technology industry. How big a problem is it for you at Wolters Kluwer? And what are you doing to make sure that you have the right technical talent on your team, and as we're saying, not just the technical talent but also the understanding of the business? >> One thing to understand is Wolters Kluwer is a fairly big company, and we as a company are just starting this journey. I have a small data management team in one business unit at Wolters Kluwer. There's another business unit within our health division that has data management, and that's all that I know of that is a formal data management. That's pretty small, so it's just beginning. What we're doing, we're trying to communicate, communicate, communicate. I am having some success because in our next huge journey, which is a digital transformation, a six-year project, data now is center. I've been asked to actually be the business sponsor for the data track, which, two years ago, that would not have happened. So I take that as a win, but you make a fair point, skills and understanding, both at the business and technical level is always a challenge, and it's justifying bringing in that skill set. No we can just outsource that, or we'll just use a consultant. I'm right now fighting a battle to bring in a data architect, full-time, they don't understand that... >> Just that role. >> You have to architect things. We've now done that, so what you have, because I' doing the data governance piece right now, and what I'm finding is, it's not the Wild West, but you can't always know what the parts of the organization is doing, and a lack of an architect is not keeping all the plumbing all centralized. So, a I build this data governance, I'm going to centralize data definitions and data glossary, data catalog, but I'm going to be looking around and going, okay, how do I actually have the technology piece architected correctly and that's the piece I'm really trying to pump, so hopefully when we build this data layer we're building my goal is to prove to the business that you need to fill this role. It's not me, it's going to be someone who really is deep, deep, deep in architecture. >> Hire a contractor, get that small win. >> That's what we're doing. (laughing) >> And then, the proof. I learned that from you, John. >> I'm actually in the process of just doing that. >> Excellent! >> One of those vendors is here. >> Well, we'll look forward to talking to you next year and hearing an update. >> Yeah, there you go. >> John Lieto, thank you so much for coming on theCUBE. >> You're very welcome, thank you. >> I'm Rebecca Knight, we will have more of theCUBE's live coverage of Informatica World. Stay tuned! (upbeat musing)

from the Hard Rock Hotel in Las Vegas it's the cube covering no joke on 2018 brought to you by osho everyone welcome back to our live coverage here in Las Vegas for Osho Khan's first industry security conference dedicated to security in the blockchain it's presented by ho show and also the industry it's an industry conference it's not necessarily a host show cause I'm John Ford's the cue for our coverage our next guest is Kenzie Crone and vice president of business development prime trust welcome to the cube thanks for joining us thanks for having me here so crowdsourcing and crowdfunding all this has been a big part of it I mean terrorists are funding through Bitcoin you've got all kinds of things going on in entrepreneurial spaces so it's clearly the money's flowing with with with crypto what do you guys do if we're getting into some of the things that we want to talk about what is prime trust to take a minute to explain your business business model value proposition absolutely so prime trust is a trust company so it's a regulated financial institution that holds funds between transactions between businesses you could also use prime trust to created a trust account for an individual as well so what our value is in this industry is that we hold crypto assets which very few qualified custodians like us exist to do that so that's a really important part of bringing in institutional funding because institutions are looking for qualified custodians as a regulated place to keep funds and they want to get into crypto so it's a it's a very important part of the puzzle so custody and custodial service has been a big topic here at O joke on controversial on the keynotes as well because you know the purists will say hey like Andreas why don't we need custody if it's working it's just it's the same old guard with new faces new business cards it's not really revolutionary and that's on one answer on the other inspection is there's so much growth in activity we've got a trusted partners to actually help us manage the risk and do these things so you have again two spectrums what's the story what should people understand about these two dynamics well what I think yeah what I think the key note you're talking about the the idea is we are just trading one type of banker for another type of banker right that's happening anyway so you are you're trading one type of financial system for another type of financial system the question is what does that look like and how can we be secure and safe in that space right personally I'm a big fan of anything that requires some kind of a license right and it's not because I think it's really fun to go through the bureaucratic process of getting a license or filling out paperwork but it's really because that once you have a license that license can be taken away from you if you misbehave right and that's really important so if you're following the laws that are set forth that are designed to protect people and then you break those laws then you're not you're not allowed to do that anymore right so that's what you get out of having regulation involved in this space is its protection and it's making sure that they're really by the way the regulation is happening anyway so that's another the regulation is happening anyway and that's why these very smart people who are managing billions of dollars are looking for that they're not saying oh cool you have a website that with technology that I don't understand you're telling me that you can safely hold something but there's no other protection there there's no liability you could just mount GOx me right and so there's got to be a way to get some sort of some sort of regulation in there and I know there's a lot of opinions in the space and obviously I'm very much on the side of regulation yeah and it also made some balance within the day those are polarized positions but I think the industry recognizes growth by recognizing the domicile problem of companies and governments so the question is you know really than a licenses legitimacy is people want legitimacy trust and growth yes at the same time but the other side says is hey you know who are those people making the laws so who's taking what away so again this is the ecosystem will solve these problems in my opinion and I believe that you know as much as I love the purist view and I think this architectural technical things that make that happen the end of the day is the self-governance of the community really is is what me happen here and so that's where the growth comes in because if real money is coming in to the sector you got to have parties that are trusted it's my opinion all right so what do you think about the conference here what's your take away so far I'll see its kind of diverse background you got you know people walking around with colorful costumes too you know buttoned up bankers and FBI agents and NSA agency folks yes we're in a really funny time in this space I think because you still have yet the Bitcoin garb and the like you know the flashing glasses and and then you've got people who spent 20 years on Wall Street and now they're in the space so I've seen that actually a lot lately in the last year at these conferences and it's very interesting I love when both sides can come in with an open mind to the other because you think there's something to be learned on both sides absolutely it's so for the people who have been in the traditional regulated space they are getting all this inspiration and the possibility of doing things differently the system that the financial system that we have now is one it's essentially you know a very old house that's just been added on to and built and there's corridors going into stairways that you know don't go anywhere right and that's that's something that needs to be fixed and and it is being fixed well Security's a driver in all this and I think one of the things I've observed you'd love to get your reaction to is you have the crypto world that's certainly changing a lot of in dynamics on the global scale you have a cyber security and then you have fin tech so you guys this is where everything I think is a melting pot which is interesting you have all these things happening but at the center of all this is security absolutely it's almost like we're all swimming out to the to the raft and whoever gets there first and wins a security model wins at all well I thought I think well I think this the conversations all threads through security so the cyber conversations we've had are like okay Cyrus security for individuals and nation-states crypto currency for protection and freedom and and you know in immutability Ledger's almost great supply-chain aspects and then you get the FinTech which is like hey people want to do business so you have the entire changeover on the financial services side all kind of happening yeah yeah I think that they're all gonna be contributing to a solution it's it's each one is going to learn we're really open-minded at prime trust we want to build and grow we know that this we're in the most embryonic stage of this and so we don't know exactly what's gonna come next or what's going to be down the road and we want to be informed by everybody that's around us at a place that makes sense do you have to work with with the industries so take me through I want to ask you a question about your job so we'll take me through the day in the life of what's going on in prime chess what are some of the things that you guys do customers and what are they asking for what's like what's the some of the issues you guys are solving what did some of the dynamics can you share some color around that sure so our main services are so we are a trust company so we do escrow services and we do compliance on all of the escrow that comes through our ICS and stos that come through so that's a ml and kyc that's really important what distinguishes us I think is a real a real game changer for our customers is that we're really a technology company and we have API stocks that allow for companies to build their businesses on top of integration so that they have customers coming in and making accounts on their their their website their dashboard their platform and that's all feeding directly and they're actually making an account so you're building your you're targeting folks saying hey we'll take care of the heavy lifting on kyc ma ml and all the stuff that needs to happens that's heavy lifting that's around DoDEA services custodial service all comes through you yes so it comes in we can hold it we can review it you're not having asset managers also holding funds which is a problem so you're not needing to touch the funds at all you can just you can just do you at you're trying to do in this space and we'll take care of that aspect that's entrepreneurial side that's the stos and the IC knows what's the alternative for the your customer build their own go with unknown shop of their other so what so if I if it's a great service sounds like a great service and takes a lot of pressure off the build out of a opportunity what's the alternative if someone doesn't go with you well there's a few I mean it's to hold your own funds right figure that out on your own in the case of many different types of funds and businesses their boards are not okay with that because it's it's too much risk and liability so in many cases the alternative is don't do it yet just keep watching and waiting and wanting to be in crypto but you can't yet so and when we're seeing that a lot that there's like a sigh of relief when we finally have this conversation and it turns out it's extremely easy to make an account with us and suddenly that major roadblock is just gone so that's what that's the career opportunity takes the risk off the table little bit and accelerates the opportunity when the sec bomb decrypt yesterday was reporting that the sec in the united states is actually going into IC OS and having them return their money because of of course they are like well of course they are that makes sense that's they were always going to do that just because they make a statement and slowly decide how to act because look last july is when they said we're going to do this and most of the crypto community said you can't because we really don't want you to and we are gonna tell ourselves all these excuses for why it's not possible for the US government to actually pursue this and why they won't really do it because they're dinosaurs and that's just not how the government works so the way the government does work is that they everything takes a long time and it's all thought through and there are a million different approval processes within the system and they don't tell you anything until they're really ready to stand by whatever same and they make so they leave you in the dark for eight months a year whatever well you guys have a good opportunity so I had to ask the question what's the business model how does someone engage with you guys sounds likely to go in and create an account is there a fee involved what's the fee can you share the engagement that somewhere would would engage with you young sure so they can visit our website which is prime trust com they can email me at Kinsey at prime trust pretty easy and we have different pricing for escort services versus custodial services and we actually pay interest on any Fiat that we held in custody and we charge a monthly basis point fee based on how much is in in custody with us and where's you guys located was the company located headquarters this here in Nevada in Las Vegas I'm based out of Los Angeles we've got some team members in San Francisco in New York as well that's awesome so it's a question how did you get into the space what's your story I got into the space I started out an equity crowdfunding so I was working with companies that were raising capital under A+ reg D and reg CF and I was in the trenches with them figuring out from like the very earliest days how what the laws were gonna look like you know launching companies the day the regulations came out barking into effect and then sort of working through that so it's been an adventure on that side and then my first experience in crypto was at an at a meet up in Santa Monica where companies were talking about raising 40 million dollars in ten seconds and that and they were also pitching in methods like I knew were not legal so it was it's kind of just dropping to me well one was how did you manage to get that many people to want to invest in you so quickly because it's a struggle for for many companies and then so that's amazing I want to learn more about that and then also did you know that there's a more legal way to do this and that you're putting yourself at a lot of risk so that made me really want to jump in and figure this out so you got totally intoxicated by the Wild West yeah there's a problem they gotta be solved in there it's kind of fun at the same time because you know all those those days are over thankfully so because you know it should be it should be more legitimize and it is getting there I think security tokens are a good sign that people are moving border security tokens at least in the u.s. the legal firms the service providers are starting to get hold up on some of the new things and that's good still expensive to run the run the process it's like own public almost as a start-up it's almost ridiculous and I kinda had the same view we're the gaps in your opinion so you now look at the crowdfunding which has been great you see all that stuff happening as essentially as a decentralized you know efficiency around disrupting venture capital and other fundraising which is great where are the gaps in your mind from a service provider standpoint from an ecosystem where's the to-do items what needs to get done faster where are the gaps I think everybody's building out their technology to make everything easier currently there's a lot that's done manually or just to manually and needs to be more automated and then I think there's also a lot of education on both sides that needs to be done that's that's I think a huge gap there's a tendency to create echo chambers and so you end up talking with people who just won't even consider the other side of it with the possibility for change in whichever area they're in and that is I think we are gonna see that come together but that tends to hold people back because you thanks for coming on and sharing your insights great to have you on the cube and good luck with prime trust thank you okay this is a cube live coverage here at hosts show con I'm John furrow your stay with us more live coverage after the short break

(electronic music) - Welcome to theCube Insights. A podcast that is typically taken from Siliconangle media's theCube interviews, where we share the best of our teams insights from all events we go to and from time to time we want to be able to extract some of our learnings when we're back at the ranch. Joining me for this segment is co-founder, co-CEO, benevolent dictator of a community, my boss, Dave Vellante. - Hey Stu. - Dave. Good to see you dressed down. - Yeah, well. Podcast, right? We got toys, props and no tie. - Yeah, I love seeing this ... we were just talking, John Furrier, who we could really make a claim to say we wouldn't have the state of podcasting today, definitely in tech, if it wasn't for what John had done back in the day with PodTech and it's one of those things, we've talked about podcasts for years but I'd gotten feedback from the community that said, "Wow, you guys have grown and go to so many shows that we want to listen to you guys as to: what was interesting at this show, what did you guys take out of it, what cool people did you interview?" We said, "Well, of course all over youtube, our website thecube.net but it made a lot of sense to put them in podcast form because podcasts have had a great renaissance over the last couple of years. - Yeah, and it's pretty straight forward, as Stu, for us to do this because virtually every show we do, even if it's a sponsor show, we do our own independent analysis upfront and at the tail end, a lot of our people in our community said, "We listen to that, to get the low down on the show and get your unfiltered opinion." And so, why not? - Yeah, Dave. Great point. I love, from when I first came on board, you always said, "Stu, speak your mind. Say what the community; what are the users saying? What does everybody talk about?" As I always say, if there is an elephant in the room we want to put it on the table and take a bite out it. And even, yes, we get sponsored by the companies to be there. We're fully transparent as to who pays us. But from the first Cube event, at the end of the day, where after keynote, we're gonna tell you exactly what we think and we're always welcome for debate. For people to come back, push on what we're saying and help bring us more data because at the end of the day, data and what's actually happening in the world will help shape our opinions and help us move in the direction where we think things should go. - I think the other thing is too, is a lot of folks ask us to come in and talk to them about what we've learned over the past year, the past six months. This is a great way for us to just hit the podcast and just go through, and this is what I do, just go through some of the shows that I wasn't able to attend and see what the other hosts were saying. So, how do you find these things? - Yeah, so first of all, great. theCube insights is the branding we have on it. We're on iTunes, We're on Spotify, We're on Google Play, Buzzsprout's what we use to be able to get it out there. It's an RSS on wikibon.com. I will embed them every once in a while or link to them. We plan to put them out, on average, it's once a week. We wanna have that regular cadence Typically on Thursday from a show that we've been out the spring season is really busy, so we've often been doing two a week at this point, but regular cadence, just podcasts are often a little tough to Google for so if you go into your favorite player and look at thecube insights and if you can't find it just hit you, me, somebody on the team up. - So you just searched thecube insights in one of those players? - Yeah absolutely, I've been sitting with a lot of people and right now it's been word of mouth, this is the first time we're actually really explaining what we're doing but thecube one word, insights is the second word I found it real quick in iTunes I find it in Google Play, Spotify is great for that and or your favorite podcast player Let us know if we're not there. - So maybe talk about some of the things we're seeing. - Yeah absolutely - The last few months. - So, right when we're here, what are our key learning? So for the last year or two Dave, I've really been helping look at the companies that are in this space, How are they dealing with multi cloud? And the refinement I've had in 2018 right now is that multi cloud or hybrid cloud seems to be, where everyone's Landing up and part of it is that everything in IT is heterogeneous but when I talk about a software company, really, where is their strength? are they an infrastructure company that really is trying to modernize what's happening in the data center are they born with cloud are they helping there? or are they really a software that can live in SAAS, in private cloud and public cloud? I kinda picture a company and where's their center of gravity? Do they lean very heavily towards private cloud, and they say public cloud it's too expensive and it's hard and You're gonna lose your job over it or are they somebody that's in the public cloud saying: there's nothing that should live in the data center and you should be a 100% public cloud, go adopt severless and it's great and the reality is that customers use a lot of these tools, lots of SAAS, multiple public Cloud for what they're doing and absolutely their stuff that's living in the data center And will continue for a long time. what do you see in it Dave? - My sort of takeaway in the last several months, half a year, a year is we used to talk about cloud big data, mobile and social as the forward drivers. I feel like it's kinda been there done that, That's getting a little bit long in the tooth and I think there's like the 3DS now, it's digital transformation, it's data first, is sort of the second D and disruption is the 3rd D And I think if you check on one of the podcast we did on scene digital, with David Michella. I think he did a really of laying out how the industry is changing there's a whole new set of words coming in, we're moving beyond that cloud big data, social mobile era into an era that's really defined by this matrix that he talks about. So check that out I won't go into it in detail here but at the top of that matrix is machine intelligence or what people call AI. And it's powering virtually everything and it's been embedded in all types of different applications and you clearly see that to the extent that organizations are able to Leverage the services, those digital services in that matrix, which are all about data, they're driving change. So it's digital transformation actually is real, data first really means You gotta put data at the core of your enterprise and if you look at the top five companies in terms of market cap the Googles, the Facebooks, the Amazons, the Microsofts Etc. Those top five companies are really data first. But People sometimes call data-driven, and then disruption everywhere, one of my favorite disruptions scenarios is of course crypto and blockchain And of course I have my book "The Enigma war" which is all about crypto, cryptography and we're seeing just massive Innovation going on as a result of both blockchain and crypto economics, so we've been really excited to cover, I think we've done eight or nine shows this year on crypto and blockchain. - Yeah it's an interesting one Dave because absolutely when you mention cryptocurrency and Bitcoin, there's still a lot of people in the room that look at you, Come on, there's crazy folks and it's money, it's speculation and it's ridiculous. What does that have to do with technology? But we've been covering for a couple of years now, the hyper ledger and some of these underlying pieces. You and I both watch Silicon Valley and I thought they actually did a really good job this year talking about the new distributed internet and how we're gonna build these things and that's really underneath one of the things that these technologies are building towards. - Well the internet was originally conceived as this decentralized network and well it physically is a decentralized network, it's owned essentially controlled by an oligopoly of behemoths and so what I've learned about cryptocurrency is that internet was built on protocols that were funded by the government and university collaboration so for instance SMTP Gmail's built on SMTP (mumbles) TCPIP, DNS Etc. Are all protocols that were funded essentially by the government, Linux itself came out of universities early developers didn't get paid for developing the technologies there and what happened after the big giants co-opted those protocols and basically now run the internet, development in those protocol stopped. Well Bitcoin and Ethereum and all these other protocols that are been developed around tokens, are driving innovation and building out really a new decentralized internet. So there's tons of innovation and funding going on, that I think people overlook the mainstream media talks all about fraud and these ICO's that are BS Etc. And there's certainly a lot of that it's the Wild West right now. But there's really a lot of high quality innovation going on, hard to tell what's gonna last and what's gonna fizzle but I guarantee there's some tech that's being developed that will stay the course. - Yeah I love....I believe you've read the Nick Carr book "The Shallows", Dave. He really talked about when we built the internet, there's two things one is like a push information, And that easy but building community and being able to share is really tough. I actually saw at an innovation conference I went to, the guy that created the pop-up ad like comes and he apologizes greatly, he said "I did a horrible horrible thing to the internet". - Yeah he did - Because I helped make it easier to have ads be how we monetize things, and the idea around the internet originally was how do I do micropayments? how do I really incent people to share? and that's one of the things we're looking at. - Ad base business models have an inherent incentive for large organizations that are centralized to basically co-opt our data and do onerous things with them And that's clearly what's happened. users wanna take back control of their data and so you're seeing this, they call it a Matrix. Silicon Valley I think you're right did a good job of laying that out, the show was actually sometimes half amazingly accurate and so a lot of development going on there. Anywhere you see a centralized, so called trusted third-party where they're a gatekeeper and they're adjudicating essentially. That's where crypto and token economics is really attacking, it's the confluence of software engineering, Cryptography and game theory. This is the other beautiful thing about crypto is that there is alignment of incentives between the investor, the entrepreneur, the customer and the product community. and so right now everybody is winning, maybe it's a bubble but usually when these bubbles burst something lives on, i got some beautiful tulips in my front yard. - Yeah so I love getting Insight into the things that you've been thinking of, John Furrier, the team, Peter Borus, our whole analyst team. Let's bring it back to thecube for a second Dave, we've done a ton of interviews I'm almost up to 200 views this year we did 1600 as a team last year. I'll mention two because one, I was absolutely giddy and you helped me get this interview, Walter isaacson at The Dell Show, One of my favorite authors I'm working through his DaVinci book right now which is amazing he talks about how a humanities and technology, the Marrying of that. Of course a lot of people read the Steve Jobs interview, I love the Einstein book that he did, the innovators. But if you listen to the Michael Dell interview that I did and then the Walter isaacson I think he might be working on a biography of Michael Dell, which i've talk to a lot of people, and they're like i'd love to read that. He's brilliant, amazing guy I can't tell you how many people have stopped me and said I listened to that Michael Dell interview. The other one, Customers. Love talking about customers especially people that they're chewing glass, they're breaking down new barriers. Key Toms and I interviewed It was Vijay Luthra from Northern trust. Kissed a chicago guy And he's like "this is one of the oldest and most conservative financial institutions out there". And they're actually gonna be on the stage at DockerCon talking about containers they're playing with severless technology, how the financial institutions get involved in the data economy, Leverage this kind of environment while still maintaining security so it was one that I really enjoyed. How about...... what's jumped out of you in all your years? - (Mumbles) reminds me of the quote (mumbles) software is eating the world, well data is eating software so every company is.... it reminds me of the NASDAQ interview that I did Recently and all we talked about, we didn't talk about their IT, we talked about how they're pointing their technology to help other exchanges get launched around the world and so it's a classic case of procurer of technology now becoming a seller of technology, and we've seen that everywhere. I think what's gonna be interesting Stu is AI, I think that more AI is gonna be bought, than built by these companies and that's how they will close the gap, I don't think the average everyday global 2000 company is gonna be an AI innovator in terms of what they develop, I think how they apply it is where the Innovation is gonna be. - Yeah Dave we had this discussion when it was (mumbles) It was the practitioners that will Leverage this will make a whole lot more money than the people that made it. - We're certainly seeing that. - Yeah I saw.....I said like Linux became pervasive, it took RedHat a long time to become a billion dollar company, because the open stack go along way there. Any final thoughts you wanna go on Dave? - Well so yeah, check out thecube.net, check out thecube insights, find that on whatever your favorite podcast player is, we're gonna be all over the place thecube.net will tell you where we're gonna be obviously, siliconangle.com, wikibon.com for all the research. - Alright and be sure to hit us up on Twitter if you have questions. He's D Villante on twitter, Angus stu S-T-U, Furrier is @Furrier, Peter Borus is PL Borus on twitter, Our whole team. wikibon.com for the research, siliconangle.com for the news and of course thecube.net for all the video. - And @ TheCube - And @TheCube of course on Twitter for our main feed And we're also up on Instagram now, so check out thecube signal on one word, give you a little bit of behind the scenes fun our phenomenal production team help to bring the buzz and the energy for all the things we do so for Dave Vellante, I'm Stu Miniman, thanks so much for listening to this special episode of thecube insights. 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>> Narrator: Live, from San Jose, it's theCUBE. Presenting Big Data Silicon Valley. Brought to you by SiliconANGLE Media and its ecosystem partners (mellow electronic music) >> Welcome back to theCUBE, on day two of our coverage of our event, Big Data SV. I'm Lisa Martin, my co-host is Peter Burris. We are the down the street from the Strata Data Conference, we've had a great day yesterday, and great morning already, really learning and peeling back the layers of big data, challenges, opportunities, next generation, we're welcoming back to theCUBE an alumni, the CMO of Kinetica, Dan Raskin. Hey Dan, welcome back to theCUBE. >> Thank you, thank you for having me. >> So, I'm a messaging girl, look at your website, the insight engine for the extreme data economy. Tell us about the extreme data economy, and what is that, what does it mean for your customers? >> Yeah, so it's a great question, and, from our perspective, we sit, we're here at Strata, and you see all the different vendors kind of talking about what's going on, and there's a little bit of word spaghetti out there that makes it really hard for customers to think about how big data is affecting them today, right? And so, what we're actually looking at is the idea of, the world's changed. That, big data from five years ago, doesn't necessarily address all the use cases today. If you think about what customers are going through, you have more users, devices, and things coming on, there's more data coming back than ever before, and it's not just about creating the data driven business, and building these massive data lakes that turn into data swamps, it's really about how do you create the data-powered business. So when we're using that term, we're really trying to call out that the world's changed, that, in order for businesses to compete in this new world, they have to think about to take data and create CoreIP that differentiates, how do I use it to affect the omnichannel, how do I use it to deal with new things in the realm of banking and Fintech, how do I use it to protect myself against disruption in telco, and so, the extreme data economy is really this idea that you have business in motion, more things coming online ever before, how do I create a data strategy, where data is infused in my business, and creates CoreIP that helps me maintain category leadership or grow. >> So as you think about that challenge, there's a number of technologies that come into play. Not least of which is the industry, while it's always to a degree been driven by what hardware can do, that's moderated a bit over time, but today, in many respects, a lot of what is possible is made possible, by what hardware can do, and what hardware's going to be able to do. We've been using similar AI algorithms for a long time. But we didn't have the power to use them! We had access to data, but we didn't have the power to acquire and bring it in. So how is the relationship between your software, and your platform, and some of the new hardware that's becoming available, starting to play out in a way of creating value for customers? >> Right, so, if you think about this in terms of this extreme data concept, and you think about it in terms of a couple of things, one, streaming data, just massive amounts of streaming data coming in. Billions of rows that people want to take and translate into value. >> And that data coming from-- >> It's coming from users, devices, things, interacting with all the different assets, more edge devices that are coming online, and the Wild West essentially. You look at the world of IoT and it's absolutely insane, with the number of protocols, and device data that's coming back to a company, and then you think about how do you actually translate this into real-time insight. Not near real-time, where it's taking seconds, but true millisecond response times where you can infuse this into your business, and one of our whole premises about Kinetica is the idea of this massive parallel compute. So the idea of not using CPUs anymore, to actually drive the powering behind your intelligence, but leveraging GPUs, and if you think about this, a CPU has 64 cores, 64 parallel things that you can do at a time, a GPU can have up to 6,000 cores, 6,000 parallel things, so it's kind of like lizard brain verse modern brain. How do you actually create this next generation brain that has all these neural networks, for processing the data, in a way that you couldn't. And then on top of that, you're using not just the technology of GPUs, you're trying to operationalize it. So how do you actually bring the data scientist, the BI folks, the business folks all together to actually create a unified operational process, and the underlying piece is the Kinetica engine and the GPU used to do this, but the power is really in the use cases of what you can do with it, and how you actually affect different industries. >> So can you elaborate a little bit more on the use cases, in this kind of game changing environment? >> Yeah, so there's a couple of common use cases that we're seeing, one that affects every enterprise is the idea of breaking down silos of business units, and creating the customer 360 view. How do I actually take all these disparate data feeds, bring them into an engine where I can visualize concepts about my customer and the environment that they're living in, and provide more insight? So if you think about things like Whole Foods and Amazon merging together, you now have this power of, how do I actually bridge the digital and physical world to create a better omnichannel experience for the user, how do I think about things in terms of what preferences they have, personalization, how to actually pair that with sensor data to affect how they actually navigate in a Whole Foods store more efficiently, and that's affecting every industry, you could take that to banking as well and think about the banking omminchannel, and ATMs, and the digital bank, and all these Fintech upstarts that are working to disrupt them. A great example for us is the United States Postal Service, where we're actually looking at all the data, the environmental data, around the US Postal Service, we're able to visualize it in real-time, we're able to affect the logistics of how they actually navigate through their routes, we're able to look things like postal workers separating out of their zones, and potentially kicking off alerts around that, so effectively making the business more efficient. But, we've moved into this world where we always used to talk about brick and mortar going to cloud, we're now in this world where the true value is how you bridge the digital and physical world, and create more transformative experiences, and that's what we want to do with data. So it could be logistics, it could be omnichannel, it could be security, you name it. It affects every single industry that we're talking about. >> So I got two questions, what is Kinetica's contribution to that, and then, very importantly, as a CMO, how are you thinking about making sure that the value that people are creating, or can create with Kinetica, gets more broadly diffused into an ecosystem. >> Yeah, so the power that we're bringing is the idea of how to operationalize this in a way where again, you're using your data to create value, so, having a single engine where you're collecting all of this data, massive volumes of data, terabytes upon terabytes of data, enabling it where you can query the data, with millisecond response times, and visualize it, with millisecond response times, run machine learning algorithms against it to augment it, you still have that human ability to look at massive sets of data, and do ad hoc discovery, but can run machining learning algorithms against that and complement it with machine learning. And then the operational piece of bringing the data scientists into the same platform that the business is using, so you don't have data recency issues, is a really powerful mix. The other piece I would just add is the whole piece around data discovery, you can't really call it big data if, in order to analyze the data, you have to downsize and downsample to look at a subset of data. It's all about looking at the entire set. So that's where we really bring value. >> So, to summarize very quickly, you are providing a platform that can run very, very fast, in a parallel system, and memories in these parallel systems, so that large amounts of data can be acted upon. >> That's right. >> Now, so, the next question is, there's not going to be a billion people that are going to use your tool to do things, how are you going to work with an ecosystem and partners to get the value that you're able to create with this data, out into the engine enterprise. >> It's a great question, and probably the biggest challenge that I have, which is, how do you get above the word spaghetti, and just get into education around this. And so I think the key is getting into examples, of how it's affecting the industry. So don't talk about the technology, and streaming from Kafka into a GPU-powered engine, talk about the impact to the business in terms of what it brings in terms of the omnichannel. You look at something like Japan in the 2020 Olympics, and you think about that in terms of telco, and how are the mobile providers going to be able to take all the data of what people are doing, and to related that to ad-tech, to relate that to customer insight, to relate that to new business models of how they could sell the data, that's the world of education we have to focus on, is talk about the transformative value it brings from the customer perspective, the outside-in as opposed to the inside-out. >> On that educational perspective, as a CMO, I'm sure you meet with a lot of customers, do you find that you might be in this role of trying to help bridge the gaps between different roles in an organization, where there's data silos, and there's probably still some territorial culture going on? What are you finding in terms of Kinetica's ability to really help educate and maybe bring more stakeholders, not just to the table, but kind of build a foundation of collaboration? >> Yeah, it's a really interesting question because I think it means, not just for Kinetica, but all vendors in the space, have to get out of their comfort zone, and just stop talking speeds and feeds and scale, and in fact, when we were looking at how to tell our story, we did an analysis of where most companies were talking, and they were focusing a lot more on the technical aspirations that developers sell, which is important, you still need to court the developer, you have community products that they can download, and kick the tires with, but we need to extend our dialogue, get out of our customer comfort zone, and start talking more to CIOs, CTOs, CDOs, and that's just reaching out to different avenues of communication, different ways of engaging. And so, I think that's kind of a core piece that I'm taking away from Strata, is we do a wonderful job of speaking to developers, we all need to get out of our comfort zone and talk to a broader set of folks, so business folks. >> Right, 'cause that opens up so many new potential products, new revenue streams, on the marketing side being able to really target your customer base audience, with relevant, timely offers, to be able to be more connected. >> Yeah, the worst scenario is talking to an enterprise around the wonders of a technology that they're super excited about, but they don't know the use case that they're trying to solve, start with the use case they're trying to solve, start with thinking about how this could affect their position in the market, and work on that, in partnership. We have to do that in collaboration with the customers. We can't just do that alone, it's about building a partnership and learning together around how you use data in a different way. >> So as you imagine, the investments that Kinetica is going to make over the next few years, with partners, with customers, what do you hope Kinetica will be in 2020? >> So, we want it to be that transformative engine for enterprises, we think we are delivering something that's quite unique in the world, and, you want to see this on a global basis, affecting our customer's value. I almost want to take us out of the story, and if I'm successful, you're going to hear wonderful enterprise companies across telco, banking, and other areas just telling their story, and we happen to be the engine behind it. >> So you're an ingredient in their success. >> Yes, a core ingredient in their success. >> So if we think about over the course of the next technology, set of technology waves, are they any particular applications that you think you're going to be stronger in? So I'll give you an example, do you envision that Kinetica can have a major play in how automation happens inside infrastructure, or how developers start seeing patterns in data, imagine how those assets get created. Where are some of the kind of practical, but not really, or rarely talked about applications that you might find yourselves becoming more of an ingredient because they themselves become ingredients to some of these other big use cases? >> There are a lot of commonalities that we're starting to see, and the interesting piece is the architecture that you implement tends to be the same, but the context of how you talk about it, and the impact it has tends to be different, so, I already mentioned the customer 360 view? First and foremost, break down silos across your organization, figure out how do you get your data into one place where you can run queries against it, you can visualize it, you can do machine learning analysis, that's a foundational element, and, I have a company in Asia called Lippo that is doing that in their space, where all of the sudden they're starting to glean things they didn't know about their customer before to create, doing that ad hoc discovery, so that's one area. The other piece is this use case of how do you actually operationalize data scientists, and machine learning, into your core business? So, that's another area that we focus on. There are simple entry points, things like Tableau Acceleration, where you put us underneath the existing BI infrastructure, and all of the sudden, you're a hundred times faster, and now your business folks can sit at the table, and make real-time business decisions, where in the past, if they clicked on certain things, they'd have to wait to get those results. Geospatial visualization's a no-brainer, the idea of taking environmental data, pairing it with your customer data, for example, and now learning about interactions. And I'd say the other piece is more innovation driven, where we would love sit down with different innovation groups in different verticals and talk with them about, how are you looking to monetize your data in the future, what are the new business models, how does things like voice interaction affect your data strategy, what are the different ways you want to engage with your data, so there's a lot of different realms we can go to. >> One of the things you said as we wrap up here, that I couldn't agree with more, is, the best value articulation I think a brand can have, period, is through the voice of their customer. And being able to be, and I think that's one of the things that Paul said yesterday is, defining Kinetica's success based on the success of your customers across industry, and I think really doesn't get more objective than a customer who has, not just from a developer perspective, maybe improved productivity, or workforce productivity, but actually moved the business forward, to a point where you're maybe bridging the gaps between the digital and physical, and actually enabling that business to be more profitable, open up new revenue streams because this foundation of collaboration has been established. >> I think that's a great way to think about it-- >> Which is good, 'cause he's your CEO. >> (laughs) Yes, that sustains my job. But the other piece is, I almost get embarrassed talking about Kinetica, I don't want to be the car salesman, or the vacuum salesman, that sprinkles dirt on the floor and then vacuums it up, I'd rather us kind of fade to the behind the scenes power where our customers are out there telling wonderful stories that have an impact on how people live in this world. To me, that's the best marketing you can do, is real stories, real value. >> Couldn't agree more. Well Dan, thanks so much for stopping by, sharing what things that Kinetica is doing, some of the things you're hearing, and how you're working to really build this foundation of collaboration and enablement within your customers across industries. We look forward to hearing the kind of cool stuff that happens with Kinetica, throughout the rest of the year, and again, thanks for stopping by and sharing your insights. >> Thank you for having me. >> I want to thank you for watching theCUBE, I'm Lisa Martin with my co-host Peter Burris, we are at Big Data SV, our second day of coverage, at a cool place called the Forager Tasting Room, in downtown San Jose, stop by, check us out, and have a chance to talk with some of our amazing analysts on all things big data. Stick around though, we'll be right back with our next guest after a short break. (mellow electronic music)

>> Announcer: Live from Madrid, Spain. It's the Cube. Covering HP Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> Good afternoon from Madrid everybody. Good morning on the East Coast. Good really early morning on the West Coast. This is the Cube, the leader in live tech coverage. We're here day one at HPE Discover Madrid 2017. My name is Dave Velonte, I'm here with my cohost Peter Berse. Randy Meyers here is the Vice President and General Manager of the Mission Critical business unit at Hewlett Packard Enterprise. And he's joined by Alexander Zhuk, who is the SAP practice lead at Eldorado. Welcome to the Cube, thanks for coming on. >> Thanks for having us. >> Thank you. >> Randy we were just reminiscing about the number of times you've been on the Cube, consecutive years, it's like the Patriots winning the AFC East it just keeps happening. >> Or Cal Ripkin would probably be you. >> Me and Tom Brady. >> You're the Cal Ripken of the Cube. So give us the update, what's happening in the Mission Critical Business unit. What's going on here at Discover. >> Well, actually just lots of exciting things going on, in fact we just finished the main general session keynote. And that was the coming out party for our new Superdome Flex product. So, we've been in the Mission Critical space for quite some time now. Driving the HANA business, we've got 2500 customers around the world, small, large. And with out acquisition last year of SGI, we got this fabulous technology, that not only scales up to the biggest and most baddest thing that you can imagine to the point where we're talking about Stephen Hawking using that to explore the universe. But it scales down, four sockets, one terabyte, for lots of customers doing various things. So I look at that part of the Mission Critical business, and it's just so exciting to take technology, and watch it scale both directions, to the biggest problems that are out there, whether they are commercial and enterprise, and Alexander will talk about lots of things we're doing in that space. Or even high performance computing now, so we've kind of expanded into that arena. So, that's really the big news Super Dome Flex coming out, and really expanding that customer base. >> Yeah, Super Dome Flex, any memory in that baby? (laughing) >> 32 sockets, 48 terabyte if you want to go that big, and it will get bigger and bigger and bigger over time as we get more density that's there. And we really do have customers in the commercial space using that. I've got customers that are building massive ERP systems, massive data warehouses to address that kind of memory. >> Alright, let's hear from the customer. Alexander, first of all, tell us about your role, and tell us about Eldorado. >> I'm responsible for SAP basis and infrastructure. I'm working in Eldorado who is one of the largest consumer electronics network in Russia. We have more than 600 shops all over the country in more than 200 cities and towns, and have more than 16,000 employees. We have more than 50,000 stock keeping units, and proceeding over three and a half million orders with our international primarily. >> SAP practice lead, obviously this is a HANA story, so can you take us through your HANA journey, what led to the decision for HANA, maybe give us the before, during and after. Leading up to the decision to move to HANA, what was life like, and why HANA? >> We first moved our business warehouse system to HANA back in 2011. It's a time we got strong business requirements to have weak reporting. So, retail business, it's a business whose needs and very rapid decision making. So after we moved to HANA, we get the speed increasing of reports giving at 15 times. We got stock replenishment reports nine times faster. We got 50 minute sales reports every hour, instead of two hours. May I repeat this? >> No, it makes sense. So, the move to HANA was really precipitated by a need to get more data faster, so in memory allows you to do that. What about the infrastructure platform underneath, was it always HP at the time, that was 2011. What's HP's role, HPE's role in that, HANA? >> Initially we were on our business system in Germany, primarily on IBM solutions. But then according to the law requirements, we intended to go to Russia. And here we choose HP solutions as the main platform for our HANA database and traditional data bases. >> Okay Data residency forced you to move this whole solution back to Russia. If I may, Dave, one of the things that we're talking about and I want to test this with you, Alexander, is businesses not only have to be able to scale, but we talk about plastic infrastructure, where they have to be able to change their work loads. They have to be able to go up and down, but they also have to be able to add quickly. As you went through the migration process, how were you able to use the technology to introduce new capabilities into the systems to help your business to grow even faster? >> At that time, before migration, we had strong business requirements for our business growing and had some forecasts how HANA will grow. So we represented to our possible partners, our needs, for example, our main requirement was the possibility to scale up our CRM system up to nine terabytes memory. So, at that time, there was only HP who could provide that kind of solution. >> So, you migrated from a traditional RDBMS environment, your data warehouse previously was a traditional data base, is that right? And then you moved to HANA? >> Not all systems, but the most critical, the most speed critical system, it's our business warehouse and our CRM system. >> How hard was that? So, the EDW and the CRM, how difficult was that migration, did you have to freeze code, was it a painful migration? >> Yes, from the application point of view it was very painful, because we had to change everything, some our reports they had to be completely changed, reviewed, they had to adopt some abap code for the new data base. Also, we got some HANA level troubles, because it was very elaborate. >> Early days of HANA, I think it was announced in 2011. Maybe 2012... (laughing) >> That's one of the things for most customers that we talk to, it's a journey. You're moving from a tried and true environment that you've run for years, but you want the benefits in memory of speed, of massive data that you can use to change your business. But you have to plan that. It was a great point. You have to plan it's gonna scale up, some things might have to scale out, and at the same time you have to think about the application migration, the data migration, the data residency rules, different countries have different rules on what has to be there. And I think that's one of the things we try to take into account as HPE when we're designing systems. I want to let you partition them. I want to let you scale them up or down depending on the work load that's there. Because you don't just have one, you have BW and CRM, you have development environments, test environments, staging environments. The more we can help that look similar, and give you flexibility, the easier that is for customers. And then I think it's incumbent on us also to make sure we support our customers with knowledge, service, expertise, because it really is a journey, but you're right, 2011 it was the Wild West. >> So, give us the HPE HANA commercial. Everybody always tells us, we're great at HANA, we're best at HANA. What makes HPE best at HANA, different with HANA? >> What makes us best at HANA, one, we're all in on this, we have a partnership with SAP, we're designing for the large scale, as you said, that nobody else is building up into this space. Lots of people are building one terabyte things, okay. But when you really want to get real, when you want to get to 12 terabytes, when you want to get to 24 to 48. We're not only building systems capable of that, we're doing co-engineering and co-innovation work with SAP to make that work, to test that. I put systems on site in Waldorf, Germany, to allow them to go do that. We'll go diagnose software issues in the HANA code jointly, and say, here's where you're stressing that, and how we can go leverage that. You couple that with our services capability, and our move towards, you'll consume HANA in a lot of different ways. There will be some of it that you want on premise, in house, there will be some things that you say, that part of it might want to be in the Cloud. Yes, my answer to all of those things is yes. How do I make it easy to fit your business model, your business requirements, and the way you want to consume things economically? How do I alow you to say yes to that? 2500 customers, more than half of the installed base of all HANA systems worldwide reside on Hewlett Packard Enterprise. I think we're doing a pretty good job of enabling customers to say, that's a real choice that we can go forward with, not just today, but tomorrow. >> Alexander, are you doing things in the Cloud? I'm sure you are, what are you doing in the Cloud? Are you doing HANA in the Cloud? >> We have not traditional Cloud, as to use it to say, now we have a private Cloud. We have during some circumstance, we got all the hardware into our property. Now, it's operating by our partner. Between two company they are responsible for all those layers from hardware layer, service contracts, hardware maintenance, to the basic operation systems support, SEP support. >> So, if you had to do it all over again, what might you do differently? What advice would you give to other customers going down this journey? >> My advice is to at first, choose the right team and the right service provider. Because when you go to solution, some technical overview, architectural overview, you should get some confirmation from vendor. At first, it should be confirmed by HP. It should be confirmed by SEP. Also, there is a financial question, how to sponsor all this thing. And we got all these things from HP and our service partner. >> Right, give you the last word. >> So, one, it's an exciting time. We're watching this explosion of data happening. I believe we've only just scratched the surface. Today, we're looking at tens of thousands of skews for a customer, and looking at the velocity of that going through a retail chain. But every device that we have, is gonna have a sensor in it, it's gonna be connected all the time. It's gonna be generating data to the point where you say, I'm gonna keep it, and I'm gonna use it, because it's gonna let me take real time action. Some day they will be able to know that the mobile phone they care about is in their store, and pop up an offer to a customer that's exactly meaningful to do that. That confluence of sensor data, location data, all the things that we will generate over time. The ability to take action on that in real time, whether it's fix a part before it fails, create a marketing offer to the person that's already in the store, that allows them to buy more. That allows us to search the universe, in search for how did we all get here. That's what's happening with data. It is exploding. We are at the very front edge of what I think is gonna be transformative for businesses and organizations everywhere. It is cool. I think the advent of in memory, data analytics, real time, it's gonna change how we work, it's gonna change how we play. Frankly, it's gonna change human kind when we watch some of these researchers doing things on a massive level. It's pretty cool. >> Yeah, and the key is being able to do that wherever the data lives. >> Randy: Absolutely >> Gentlemen, thanks very much for coming on the Cube. >> Thank you for having us. >> Your welcome, great to see you guys again. Alright, keep it right there everybody, Peter and I will be back with our next guest, right after this short break. This is the Cube, we're live from HPE Discover Madrid 2017. We'll be right back. (upbeat music)

>>live from San Francisco, extracting the signal from the noise. It's the cues covering Oracle OpenWorld 2015. Brought to you by Oracle. How your hosts, John Courier and Jeff Rick Wait, >>We are here. Live in Howard's treated oracle. OpenWorld for Silicon Angles, The Cube Exclusive coverage Star flagship program. We go out to the events extract the cinnamon noise. I'm John Kerry, the founder of Silicon, and Brian gracefully lead analyst on all the cloud and all the infrastructure stuff going on here. Next guess is Jeffrey Davis, Principal Gore, Oracle, global leader for Deloitte and Touche. Legend in the industry. I've been covering Oracle for a long time. Good to see you, John Bryan allegedly knew she had to get that in there. Love that. You know you guys are. The service's angle has been something that the service's business is. It's been changing radically. Now more than ever with clouds. I really want to get your take because you are an executive looking at this transformation of cloud. But the Lloyd across all the Oracle customer base, your party with customers. So you're the front lines. I gotta ask you straight up. What is the number one thing customers are looking at right now that you partner with four Cloud to figure it out. Is it a migration? All the above, And what do you think about that? So when customers are evaluating the cloud or our clients are looking at the club, you really focus on three things. One is agility. Thea other one is time and the other one is valued. So how quickly can we adopt to the changing environment? How quickly can we leverage technologies like clouds in order to be able to respond to our customers, to adapt to the changing needs of our employees, to embrace our business strategy in a new and innovative way? So I said legend, you know, talk about the eighties for women on camera. That's important point I want to bring up. Is that Is that the old way? Big growth of client server was around software middleware right year BC around you name it that created huge consultancies like Lloyd, you participated in that create a lot of wealth creation for the customers, create value, right, but their cycles were long in the deal. That'll be about 12 13 years now, months and almost a year or two, there were all these big deployments. Now the cloud is accelerating when you compare and contrast time of then share. And now with the cloud Just how much the deployments change the software, the organizations, How you guys operate a new way to do that job well, and we're all responding to the market, right? While responding to customers needs Cloud didn't come about because of technology in it of itself. But we're really all in this ecosystem responding to our customers must customers a really demanding from us is there demanding agility and speed. As I said before, if you take a look at the way we used to do things, basically you had a a large capital investment on the part of the customers. They went, they bought the software, they bought the hardware, they had to hire the expertise of an advantage, mail the eggs, and you're looking at a transformation for them that could take anywhere from 12 to 24 months or longer before they would get time to value. And, you know, these projects didn't go as planned. No, that's this is Yeah, I know the change orders came in paid more cash on DSO. We all got a really bad reputation because of the high costs in a long time to value and even if value was ever realized in some cases, now we take a look at the environment and what the cloud enables us to do is move in a much faster pace. Way used to have what we call a waterfall approach to design and implementation went into a big room and you talked about the world and I never ran that way. And then you put it into the system and then people never really embraced it, because when it came out, it didn't look like anything they thought they were gonna get. This is completely different with cloud. Now you can take an agile approach. Now you can sit and listen to the customer demands very quickly respond to what they think they need, where they really generate value. And then you can focus on those things and very quickly there, in a design session with you And at the end of the day, >>changed management is much easier because they've been a part of the process and also, you know, looking at 90 days sprints. You're looking at things that are done. You know, in >>six months, six months, time to value that can give you compress a competitive advantage. You know, that could help you retain Maur employees or customers. So it's really some timetable. Met Lavery s V p of the Cloud Gru. Gru Integration was saying they were doing provisioning on in 24 minutes. Multiple deployments like like nobody's business. What has them in the timetable that you're seeing for some of these times of value, horizons means hurdles. These milestones said days, weeks, months, hours, minutes. I mean, when you go to a customer base where their expectations of what you guys deliver, there's some insight there. Some of it depends on the environment. So remember they're still clients. We have local customers that are in a highly regulated industry or have a very complex prisons process. Those are gonna take a longer there is they're gonna take in. Technology is not necessarily on the critical path. But when you look at those other areas that frankly, you don't differentiate yourself very much or speed with a solution concave you a competitive advantage. You know, you're looking at a client expectations of anywhere from 90 days, you know, to six months, you know, manager here, very manager, but aggressive. Visa VI the old way. Well, certainly, And the other piece that we're not really talking about is, you know, it's not enough for us to put the technology out there. It's also got to be used and adopted. You know, when you had those large transformations. It's very hard for an organization to absorb all of that change. Now we're looking at the fine entry point that you could get with clouds with that fine entry point. Now we can sub select areas with greatest impact, but we're not changing the entire organization. >>Mark Hurd has the C I. O. G. On this morning and one of the comments that he made. I've heard this a number of times over the last 12 18 months. He essentially said, I have a ton of undifferentiated applications now. They're things that that Oracle thinks are fantastic. HCM and C. R. M and Air P. But in essence, everybody has those. Every business has those very undifferentiated, but they're complicated. What? You Seymour, you see more people saying you know what take those. Help me migrate those into SAS applications, you know, save costs. Where do you see more saying, You know what? Give me the other 20%. The ones that drive business differentiation, ones that are new cloud native applications. What do you see in your mix? What's pushing your customers >>to push you? You know, it depends on the geography, and it depends on the industry and some other things. If you want to talk about North America, which tends to be one of the largest markets in the world, if not the largest market in the world, when you're looking in North America, really people have gone through a lot of the major ear piece. Remember the earlier conversation? You know, they have suffered through tens of millions, hundreds of millions of dollars, and their boards were not satisfied that they got the results of the expected. Now, when you take a look at what's happening, you know, people are now being much more strategic in their investments, much more prescriptive there. Look how they spent exactly, because now the boards have different expectations. They've already gone and spent all that money on technology. They can't go back to the board. Can't say we need to redo this. What they do are willing to fund is you want to get into a new business. If you want to spin something off, you need to stand it up right away. If a customer you know, provide you a new opportunity, you want to shift to that new opportunity. Really? Well, technology is the basis of a lot of this transformation. So Cloud provides that opportunity and it's modest investment with really quick, high value. It's a great point >>you look at I t In the past decades prior to this evolution, we're seeing the cloud consolidate, consolidate, consolidate, right? I don't know the well again. I just went to the well, apparently running, you know, whatever the model was there. But now they're under a lot of pressure to drive top line revenue. Absolute. Now, the top line revenue equations, a completely different mindset. You have to go out and oh, cut the market. You gotta use a shadow I t or your authorized go out. Do legitimate stand up new platforms are Can you give me an example of that? We're seeing more of that now. A clear Mandate. Cee Io's Go take a New Hill or let's consolidate these apt and reposition for this new use case, which is not. That's experiment, but it's certainly a new market opportunity, and they gotta do their due diligence, so it's almost unparalleled. Due diligence kills your waterfall. That's one doesn't talk about that dynamic. Where examples you give go. Take that new top line revenue driver. So you know that there are customers that are looking at new partnerships in the marketplace, and those new partnerships have dynamic new business models. You know, it's not like opening up another hamburger stand. You know, they're not necessarily expanding into our core business. They're really looking at ways to amplify growth. If you're gonna take that as a strategic position, then you know customer or client of ours would focus on, you know, let's take this innovation the market. We don't want to invest a lot in it, waste a lot of time and lose the competitive advantage. Let's >>get to market first. Let's provide a new product or service to the market where we can move very quickly, and then the >>net result is we can see the benefits right away. And if it isn't way, haven't sunk a lot of time and money and something that's not necessarily gonna have the same values. We just had Shawn Price on. And I'm gonna ask this because it's a lemon that you're in because you're part of the customer right here, the strategic partner of the customer. So that idea top line revenue growth could come from a partner. When I see How do you work in that? Quick, You're cool to work with my Aunt VI's. Bring that into the table. You're absolutely so this market is changing. You know, Cloud clearly changes everything and much more so than some of the things we've seen in the past. And so now we need to position ourselves differently now for the Deloitte Business Model way. We're really in a specialized business of focusing highly on value and value creation. We weren't necessarily in other areas and we have different partnerships now. Those partnerships are shifting. Oracle provides us a complete platform. You know, we don't >>have to really get involved in a lot of the aspects of the platform that, frankly, we're in our core competency and frankly, weren't our clients what >>you talked about that customer interaction? What do you have to do to change what we've seen? Different size, trying different approaches? We've seen some that are partnering with cloud Provider, but they want to be their own flat for acquiring them. What changes in terms of the skills you have to hire the way you expect that interaction toe happen between you and customer. Because to a certain extent, like for developers, developers love self service. They do. You know, they they are shadow I because they're driving What changes in your world for that? >>So this is really kind of an interesting question. Very early on, when Oracle made cloud product available >>in HCM, we saw an opportunity. Our clients had the demand because they wanted to create a more sticky environment from customers. What better >>way than providing them better products in the HCM space? We made major investments there. Now we're a leader in HCM, and if I look back over that experience, what do we do differently? First of all, we had to change our mindset. You know, it's not enough just to say the cloud, but you gotta live the cloud because it truly is more agile. It truly is faster. You can take your old methods and tools and approaches all the things that worked for you before. A lot of them don't work anymore. There's some but some really good winds here, especially in the change management side. Also, you know, we'd have clients that had to kind of do it yourself brain surgery that have to order their own hardware that have provisional themselves. You know, that became a real mess. Now we're looking at something that's a lot different. We're not in that business anymore. You know, we do support on Prem where our clients think it's important and strategic course. But now we've got a new, agile methodology. Now we've trained our workforce. We've got 14,500 professionals around the world. We've had to move that group, and Oracle really helped us do that. They've been very collaborative in sharing I p and sharing methods and tools with us so we can make that adjustment. Not only have we had to change that when you think about our other methodologies, all of our other methodology to create value to change management, they were all thoroughly integrated. We've had to rethink those, but it's been a great story because we could go to the client. We can say we can get you there faster because where technology was a barrier world, >>it was on the critical path. We're now changing that. And by the way, this technology is not your old technology. It's much better. It's much more robust. How >>do you you know, obviously we're here It at an oracle OpenWorld. It could be called Oracle Cloud >>World if we really wanted to. I mean, >>it's a lot of it is the red stack. A lot of it is one cloud. How do you manage that against customers saying, Well, look, there's other options as well. I wanna have the ability to leverage this cloud for something. Oracles cloud for certain things. How do you do? You find your customers want multiple clouds or one cloud is good enough? >>Well, we're all teaching right? We're all teaching the world about God because you know there's still people that look at it in a variety of different ways. I think it's an excellent question, so let's think about this. >>Do you want to be your own systems integrator for your smartphone. You want to go by an operating system? Do you want to go buy a separate peace of heart? Where do you >>want to decide what APS fit? What don't. And do you want to actually try to get those abs together? I don't think we want to do that anymore. And I try to use that as an example for my clients. Tell them. Look, let's not be your own systems integrator. You is a iittie executive. You could be an officer toe, help the organization get to their business goals. You know, you're not in another yourself a business objective, but you could be an agent for change. I try to educate them so they can help their colleagues explain cloud, take the fear out and then show the art of the possible. What about the security model? I mean, I wouldn't get your take on you little bit biased because your manager Oracle really? But what would be global, critical or complementary events? How you feel about it? But the intense security message is really a game changer in my mind. Follows on incredible theory. Incredible application. Certainly the product's gonna be ready soon. If it works, it's like a car that does the key turnover. It's like it's all good on paper. Certainly a game changer. Security outside number One thing you're hearing Get some color to that because, you know, if that plays out, if you believe that end N security on the chips and software Silicon plays out the way they say it would, that's gonna change the game. For sure. It is. So none of us and you can go through a week without hearing about a major security breach. When you think about this, you step back and think about the potential here. Our stuff is starting to talkto our stuff. But our stuff isn't unless it's based on. Oracle isn't all thoroughly integrated, so somebody can break into our stuff and they can get access to our lives and they can change our lives. That's hugely powerful. So we are very concerned about security, and Lloyd is one of the largest organizations. In fact, we have a cyber practice that looks at both Proactiv reactive aspects of security. Here's the big concern we have as all this stuff starts, get interconnected. The Internet of things, security becomes a major issue. We need more breakthroughs and security. And I think oracles on the vanguard certainly as we get into what we call a hyper hybrid cloud on Prem on Cloud. Some of that's gonna be a great emotion is no. Perimeter is nothing either. Protect is the Wild West total while and, you know, despite what you believe, boards and people are not reacting fast enough to security threats. And that's why you're seeing these breaches into my knowledge. I don't think anybody has been breached with Orgel security in place. But that said, you have to be really, But still, they probably would get out. There's not that they're hiding it, but the point is, you need to be united engine system. It's hard to do that in a open source world, right? So you have a horizontally scaled open source phenomenon, and it's growing our market and a vertically integrated product requirement. You believe I want Indian security, then you gonna go vertically integrated. You do purpose built. But if you want scale a 1,000,000,000 large scale a k a cloud, you want horizontally scalable. How do you reconcile that with your customers? Well, you know so again. It's difficult for them because unless you've had a security threat, it's very difficult to really get them to take the initiative. You know, the more that we can build security in, the more that it's covered in the Red Sea. More that we get a comprehensive end to end product. I think it allows us to help the client realize you know the risk and help them. The old Fowler said. In The Cube they had they had this done in 2005. Finally took a bunch of security breaches to get people's attention to your point. It's on everyone's agenda. Number one right it is. And yet you know how much is enough? Well, we find the people are too reactive and not not proactive enough. >>What's the What's the temperature of your customers right now? I mean, you know, Tesla's out, they're disrupting Uber's out. Their Airbnb are they? Are they sort of defensive and paranoid? You know that Andy Grove, always trying to be aggressive with a saying No, no, no, no. I'm not letting these little guys into my market. I'm gonna go be aggressive and try and push back what a general feeling. There's a lot of interesting startup disruption going on really changing industry. >>There is, and you know, there's so many sort of partnerships and alliances, mergers and new innovations. You know, right now, clients are very uncomfortable. Just the transition from on Prem to Cloud is a major change in our clients have been the expert for technology for decades for their organization. They are having trouble keeping up with all of it. It can be disruptive. They're looking at what's unique in their industry. You know what is regulation driving? You know what is innovation driving in their industry? But, you know, they're always on the learning curve. They're always trying to figure out if we want to get your final thought wrapping up here to get your take for the folks that are watching here on camera that couldn't make it here were beloved world. What is this show about it? We've been here six years. You've seen that transformation. About four years ago, Larry looked like a deer in the headlights, almost stuck in his tracks and smoke coming out of his ears like he felt that the scene felt like a pivotal moment couple years ago. And then since then, just been every year. Oracle just gets more and more energy, just like dominated that march of the crowd. Almost like four years ago. Like we're gonna win that. What's your vibe? You see that same thing here and shared some color on the take is over the years, and we've been doing this a lot in various forms Over the years. There's been the promise of riel innovation. There's been the promise, real change in the industry. We saw sort of incremental change. We really see increments. Exponential change now and now. The promises fulfilled. We have real product. We're taking the market. We're doing interesting product, right? Israel product. It's very riel, and we have work to be done. But yeah, really studies and customers? Well, it's an evolution. But this is really sort of an epiphany at the moment, because we've never had, >>you know, full sweets of product in the marketplace. Not right now. I don't know that there are any other large you know. Air Pia options in the clouds away there is for Oracle and look at the host of service is that have been announced over the last year. >>This this particular show for us, you know, really isn't accelerating. All these products and service is in the cloud that are now available. They give us a lot of different options that we never had. A great quote. Put that on a cube. Jim. Thanks for joining Us. Way are here live in San Francisco's Howard Street for the Cube Special. Exclusive coverage of Oracle OpenWorld Q. Be right back with more of this short break. Thanks for watching.