(upbeat music) >> Man: We're good. >> Hey everyone. Welcome back to theCube's live coverage of AWS Summit NYC. We're in New York City, been here all day. Lisa Martin, John Furrier, talking with AWS partners ecosystem folks, customers, AWS folks, you name it. Next up, one of our alumni, rejoins us. Please welcome Anshu Sharma the co-founder and CEO of Skyflow. Anshu great to have you back on theCube. >> Likewise, I'm excited to be back. >> So I love how you guys founded this company. Your inspiration was the zero trust data privacy vault pioneered by two of our favorites, Apple and Netflix. You started with a simple question. What if privacy had an API? So you built a data privacy vault delivered as an API. Talk to us, and it's only in the last three and a half years. Talk to us about a data privacy vault and what's so unique about it. >> Sure. I think if you think about all the key challenges we are seeing in our personal lives when we are dealing with technology companies a lot of anxiety is around what happens to my data, right? If you want to go to a pharmacy they want to know not just your health ID number but they want to know your social security number your credit card number, your phone number and all of that information is actually useful because they need to be able to engage with you. And it's true for hospitals, health systems. It's true for your bank. It's true for pretty much anybody you do business with even an event like this. But then question that keeps coming up is where does this data go? And how is it protected? And the state of the art here has always been to keep kind of, keep it protected when it's in storage but almost all the breaches, all the hacks happen not because you've steal somebody's disc, but because someone enters through an API or a portal. So the question we asked was we've been building different shapes of containers for different types of data. You don't store your logs in a data warehouse. You don't store your analytical data in a regular RDBMS. Similarly, you don't store your passwords and usernames you store them in identity systems. So if PI is so special why isn't it a container that's used for storing PII? So that's how the idea of Pii.World came up. >> So you guys just got a recent funding, a series B financing which means for the folks out there that don't know the inside baseball, must people do, means you're doing well. It's hard to get that round of funding means you're up and growing to the right. What's the differentiator? Why are you guys so successful? Why the investment growth, what's the momentum driver? >> So I think in some ways we took one of the most complex problems, data privacy, like half the people can't even describe like, does data privacy mean like I have to be GDPR compliant or does it actually mean I'm protecting the data? So you have multiple stakeholders in any company. If you're a pharma company, you may have a chief privacy officer, a data officer, this officer, that officer, and all of these people were talking and the answer was buy more tools. So if you look around behind our back, there's probably dozens of companies out there. One protecting data in an API call another protecting data in a database, another one data warehouse. But as a CEO, CTO, I want to know what happens to my social security number from a customer end to end. So we said, if you can radically simplify the whole thing and the key insight was you can simplify it by actually isolating and protecting this data. And this architecture evolved on its own at companies like Apple and other places, but it takes dozens of engineers for those companies to build it out. So we like, well, the pattern will makes sense. It logically kind is just common sense. So instead of selling dozens of tools, we can just give you a very simple product, which is like one API call, you know, protect this data... >> So like Stripe is for a plugin for a financial transaction you plug it into the app, similar dynamic here, right? >> Exactly. So it's Stripe for payments, Twilio for Telephony. We have API for everything, but if you have social security numbers or pan numbers you still are like relying on DIY. So I think what differentiated us and attracted the investors was, if this works, >> It's huge. every company needs it. >> Well, that's the integration has become the key thing. I got to ask you because you mentioned GDPR and all the complexities around the laws and the different regulations. That could be a real blocker in a wet blanket for innovation. >> Anshu: Yes. >> And with the market we're seeing here at, at your Summit New York, small event. 10,000 people, more people here than were at Snowflake Summit as an example. And they're the hottest company in data. So this small little New York event is proven that that world is growing. So why should this wet blanket, these rules slow it down? How do you balance it? 'Cause that's a concern. If you checking all the boxes you're never actually building anything. >> So, you know, we just ran into a couple of customers who still are struggling with moving from the data center to AWS Cloud. Now the fact that here means they want to but something is holding them back. I also met the AI team of Amazon. They're doing some amazing work and they're like, the biggest hindrance for them is making customers feel safe when they do the machine learning. Because now you're opening up the data sets to more people. And in all of those cases your innovation basically stops because CSO is like, look you can't put PII in the cloud unprotected. And with the vault architecture we call it privacy by architecture. So there's a term called privacy by design. I'm like what the, is privacy by design, right? >> John: It's an architecture. (John laughing) >> But if you are an architecture and a developer like me I was like, I know what architecture is. I don't know what privacy by design is. >> So you guys are basically have that architecture by design which means foundational based services. So you're providing that as a service. So other people don't have to build the complex. >> Anshu: Exactly. >> You know that you will be Apple's backend team to build that privacy with you you get all that benefit. >> Exactly. And traditionally, people have had to make compromises. If you encrypt the data and secure it, then you can't use it. Using a proprietary polymorphic encryption technology you can actually have your cake and eat it to. So what that means for customers is, if you want to protect data in Snowflake or REDshare, use Skyflow with it. We have integrations to databases, to data lakes, all the common workflow tools. >> Can you give us a customer example that you think really articulates the value of what Skyflow is delivering? >> Well, I'll give you two examples. One in the FinTech space, one in the health space. So in the FinTech space this is a company called Nomi Health. They're a large payments processor for the health insurance market. And funnily enough, their CTO actually came from Goldman Sachs. He actually built apple card. (John laughing) Right? That if we all have in our phones. And he saw our product and he's like, for my new company, I'm going to just use you guys because I don't want to go hire 20 engineers. So for them, we had a HIPAA compliant environment a PCI compliant environment, SOC 2 compliant environment. And he can sleep better at night because he doesn't have to worry what is my engineer in Poland or Ukraine doing right now? I have a vault. I have rules set up. I can audit it. Everything is logged. Similarly for Science 37, they run clinical trials globally. They wanted to solve data residency. So for them the problem was, how do I run one common global instance? When the rules say you have to break everything up and that's very expensive. >> And so I love this. I'm a customer. For them a customer. I love it. You had me at hello, API integration. I love it. How much does it cost? What's it going to cost me? How do I need to think about my operationalizing? 'Cause I know with an API, I can do that. Am I paying by the usage, by the drink? How do I figure out? >> So we have programs for startups where it's really really inexpensive. We get them credits. And then for enterprises, we basically have a platform fee. And then based on the amount of data PII, we charge them. We don't nickel and dime the customers. We don't like the usage based model because, you don't know how many times you're going to hit an API. So we usually just based on the number of customer records that you have and you can hit them as many time as you want. There's no API limits. >> So unlimited record based. >> Exactly. that's your variable. >> Exactly. We think about you buying odd zero, for example, for authentication you pay them by the number of active users you have. So something similar. >> So you run on AWS, but you just announced a couple of new GTM partners, MuleSoft and plan. Can you talk to us about, start with MuleSoft? What are you doing and why? And the same with VLA? >> Sure. I mean, MuleSoft was very interesting customers who were adopting our products at, you know, we are buying this product for our new applications but what about our legacy code? We can't go in there and add APIs there. So the simplest way to do integration in the legacy world is to use an integration broker. So that's where MuleSoft integration came out and we announced that. It's a logical place for you to swap out real social security numbers with, you know, fake ones. And then we also announced a partnership with SnowFlake, same thing. I think every workload as it's moving to the cloud needs some kind of data protection with it. So I think going forward we are going to be announcing even more partnerships. So you can imagine all the places you're storing PII today whether it's in a call center solution or analytics solution, there's a PII story there. >> Talk about the integration aspect because I love the momentum. I get everything makes secure the customers all these environments, integrations are super important to plug into. And then how do I essentially operate you on my side? Do I import the records? How do you connect to my environment in my databases? >> So it's really, really easy when you encrypt the data and use Skyflow wall, we create what is called a format preserving token, which is essentially replacing a social security number with something that looks like an SSN but it's not. So that there's no schema changes involved. You just have to do that one time swap over and then in terms of integrations, most of these integrations are prebuilt. So Snowflake integration is prebuilt. MuleSoft integration is prebuilt. We're going to announce some new ones. So the goal is for off the table in platforms like Snowflake and MuleSoft, we prebuilt all the integrations. You can build your own. It takes about like a day. And then in terms of data import basically it's the same standard process that you would use with any other data store. >> Got to ask you about data breaches. Obviously the numbers in 2021 were huge. We're seeing so much change in the cyber security landscape ransomware becoming a household word, a matter of when but not if... How does Skyflow help organizations protect themselves or reduce the number of breaches so that they are not the next headline? >> You know, the funny thing about breaches is again and again, we see people doing the same mistakes, right? So Equifax had a breach four years ago where a customer portal, you know, no customer support rep should have access to a 100 million people's data. Like is that customer agent really accessing 100 million? But because we've been using legacy security tools they either give you access or don't give you access. And that's not how it's going to work. Because if I'm going to engage with the pharmacy and airline they need to be able to use my data in multiple different places. So you need to have fine grain controls around it. So I think the reason we keep getting breaches is cybersecurity industry is selling, 10s of billions of dollars worth of tools in the name of security but they cannot be applied at a fine grain level enough. I can't say things like for my call center agent that's living in Phoenix, Arizona they can only verify last four digits, but the same call center worker in Philippines can't even see that. So how do you get all that granular control in place? Is really why we keep seeing data breaches. So the Equifax breach, the Shopify breach the Twitter breaches, they're all the same. Like again and again, it's either an inside person or an external person who's gotten in. And once you're in and this is the whole idea of zero trust as you know. Once you're in, you can access all the data. Zero trust means that you don't assume that you actually isolate PII separately. >> A lot of the cybersecurity issues as you were talking about, are people based. Somebody clicking on something or gaining access. And I always talk to security experts about how do you control for the people aspect besides training, awareness, education. Is Skyflow a facilitator of that in a way that we haven't seen before? >> Yeah. So I think what ends up happening is, people even after they have breaches, they will lock down the system that had the breach, but then they have the same data sitting in a partner database, maybe a customer database maybe a billing system. So by centralizing and isolating PII in one system you can then post roles based access control rules. You can put limitations around it. But if you try to do that across hundreds of DS bases, you're just not going to be able to do it because it's basically just literally impossible, so... >> My final question for you is on, for me is you're here at AWS Summits, 10,000 people like I said. More people here than some big events and we're just in New York city. Okay. You actually work with AWS. What's next for you guys as you got the fresh funding, you guys looking for more talent, what's your next mountain you're going to climb? Tell us what's next for the company. Share your vision, put a plug in for the company. >> Well, it's actually very simple. Today we actually announced that we have a new chief revenue officer who's joining us. Tammy, she's joined us from LaunchDarkly which is it grew from like, you know, single digits to like over nine digits in revenue. And the reason she's joining Skyflow is because she sees the same inflection point hitting us. And for us that means more marketing, more sales, more growth in more geographies and more partnerships. And we think there's never been a better time to solve privacy. Literally everything that we deal with even things like rove evade issues eventually ties back into a issue around privacy. >> Lisa: Yes. >> AWS gets the model API, you know, come on, right? That's their model. >> Exactly. So I think if you look at the largest best companies that have been built in the last 20 years they took something that should have been simple but was not. There used to be Avayas of the world, selling Telephony intel, Twilio came and said, look an API. And we are trying to do the same to the entire security compliance and privacy industry is to narrow the problem down and solve it once. >> (indistinct) have it. We're going to get theCube API. (Lisa laughing) That's what we're going to do. All right. >> Thank you so much. >> Awesome. Anshu, thank you for joining us, talking to us about what's new at Skyflow. It sounds like you got that big funding investment. Probably lots of strategic innovation about to happen. So you'll have to come back in a few months and maybe at next reinvent in six months and tell us what's new, what's going on. >> Last theCube interview was very well received. People really like the kind of questions you guys asked. So I love this show and I think... >> It's great when you're a star like you, you got good market, great team, smart. I mean, look at this. I mean, what slow down are we talking about here? >> Yeah. I don't see... >> There is no slow down on the enterprise. >> Privacy's hot and it's incredibly important and we're only going to be seeing more and more of it. >> You can talk to any CIO, CSO, CTO or the board and they will tell you there is no limit to the budget they have for solving the core privacy issues. We love that. >> John: So you want to move on to building? >> Lisa: Obviously that must make you smile. >> John: You solved a big problem. >> Thank you. >> Awesome. Anshu, thank you again. Congrats on the momentum and we'll see you next time and hear more on the evolution of Skyflow. Thank you for your time. >> Thank you. >> For John furrier, I'm Lisa Martin. You're watching theCube live from New York City at AWS Summit NYC 22. We'll be right back with our next guest. So stick around. (upbeat music)

>>Hi, everybody. Welcome back to Caesars in Las Vegas. My name is Dave ante. We're here with the chairman and CEO of snowflake, Frank Luman. Good to see you again, Frank. Thanks for coming on. Yeah, >>You, you as well, Dave. Good to be with you. >>No, it's, it's awesome to be, obviously everybody's excited to be back. You mentioned that in your, in your keynote, the most amazing thing to me is the progression of what we're seeing here in the ecosystem and of your data cloud. Um, you wrote a book, the rise of the data cloud, and it was very cogent. You talked about network effects, but now you've executed on that. I call it the super cloud. You have AWS, you know, I use that term, AWS. You're building on top of that. And now you have customers building on top of your cloud. So there's these layers of value that's unique in the industry. Was this by design >>Or, well, you know, when you, uh, are a data clouding, you have data, people wanna do things, you know, with that data, they don't want to just, you know, run data operations, populate dashboards, you know, run reports pretty soon. They want to build applications and after they build applications, they wanna build businesses on it. So it goes on and on and on. So it, it drives your development to enable more and more functionality on that data cloud. Didn't start out that way. You know, we were very, very much focused on data operations, then it becomes application development and then it becomes, Hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many, in many ways, you know, >>There was some confusion I think, and there still is in the community of, particularly on wall street, about your quarter, your con the consumption model I loved on the earnings call. One of the analysts asked Mike, you know, do you ever consider going to a subscription model? And Mike got cut him off, then let finish. No, that would really defeat the purpose. Um, and so there's also a narrative around, well, maybe snowflake, consumption's easier to dial down. Maybe it's more discretionary, but I, I, I would say this, that if you're building apps on top of snowflake and you're actually monetizing, which is a big theme here, now, your revenue is aligned, you know, with those cloud costs. And so unless you're selling it for more, you know, than it costs more than, than you're selling it for, you're gonna dial that up. And that is the future of, I see this ecosystem in your company. Is that, is that fair? You buy that. >>Yeah, it, it is fair. Obviously the public cloud runs on a consumption model. So, you know, you start looking all the layers of the stack, um, you know, snowflake, you know, we have to be a consumption model because we run on top of other people's, uh, consumption models. Otherwise you don't have alignment. I mean, we have conversations, uh, with people that build on snowflake, um, you know, they have trouble, you know, with their financial model because they're not running a consumption model. So it's like square pack around hole. So we all have to align ourselves. So that's when they pay a dollar, you know, a portion goes to, let's say, AWS portion goes to the snowflake of that dollar. And the portion goes to whatever the uplift is, application value, data value, whatever it is to that goes on top of that. So the whole dollar, you know, gets allocated depending on whose value at it. Um, we're talking about. >>Yeah, but you sell value. Um, so you're not a SaaS company. Uh, at least I don't look at you that that way I I've always felt like the SAS pricing model is flawed because it's not aligned with customers. Right. If you, if you get stuck with orphaned licenses too bad, you know, pay us. >>Yeah. We're, we're, we're obviously a SaaS model in the sense that it is software as a service, but it's not a SaaS model in the sense that we don't sell use rights. Right. And that's the big difference. I mean, when you buy, you know, so many users from, you know, Salesforce and ServiceNow or whoever you have just purchased the right, you know, for so many users to use that software for this period of time, and the revenue gets recognized, you know, radically, you know, one month at a time, the same amount. Now we're not that different because we still do a contract the exact same way as SA vendor does it, but we don't recognize the revenue radically. We recognize the revenue based on the consumption, but over the term of the contract, we recognize the entire amount. It just is not neatly organized in these monthly buckets. >>You know? So what happens if they underspend one quarter, they have to catch up by the end of the, the term, is that how it works or is that a negotiation or it's >>The, the, the spending is a totally, totally separate from the consumption itself, you know, because you know how they pay for the contract. Let's say they do a three year contract. Um, you know, they, they will probably pay for that, you know, on an annual basis, you know, that three year contract. Um, but it's how they recognize their expenses for snowflake and how we recognize the revenue is based on what they actually consume. But it's not like you're on demand where you can just decide to not use it. And then I don't have any cost, but over the three year period, you know, all of that, you know, uh, needs to get consumed or they expire. And that's the same way with Amazon. If I don't consume what I buy from Amazon, I still gotta pay for it. You know, so, >>Well, you're right. Well, I guess you could buy by the drink, but it's way, way more expensive and nobody really correct. Does that, so, yep. Okay. Phase one, better simpler, you know, cloud enterprise data warehouse, phase two, you introduced the, the data cloud and, and now we're seeing the rise of the data cloud. What, what does phase three look like >>Now? Phase, phase three is all about applications. Um, and we've just learned, uh, you know, from the beginning that people were trying to do this, but we weren't instrumental at all to do it. So people would ODBC, you know, JDBC drivers just uses as database, right? So the entire application would happen outside, you know, snowflake, we're just a database. You connect to the database, you know, you read or right data, you know, you do data, data manipulations. And then the application, uh, processing all happens outside of snowflake. Now there's issues with that because we start to exfil trade data, meaning that we started to take data out of snowflake and, and put it, uh, in other places. Now there's risk for that. There's operational risk, there's governance, exposure, security issues, you know, all this kind of stuff. And the other problem is, you know, data gets Reed. >>It proliferates. And then, you know, data science tests are like, well, I, I need that data to stay in one place. That's the whole idea behind the data cloud. You know, we have very big infrastructure clouds. We have very big application clouds and then data, you know, sort of became the victim there and became more proliferated and more segment. And it's ever been. So all we do is just send data to the work all day. And we said, no, we're gonna enable the work to get to the data. And the data that stays in more in place, we don't have latency issue. We don't have data quality issues. We don't have lineage issues. So, you know, people have responded very, very well to the data cloud idea, like, yeah, you know, as an enterprise or an institution, you know, I'm the epicenter of my own data cloud because it's not just my own data. >>It's also my ecosystem. It's the people that I have data networking relationships with, you know, for example, you know, take, you know, uh, an investment bank, you know, in, in, in, in New York city, they send data to fidelity. They send data to BlackRock. They send data to, you know, bank of New York, all the regulatory clearing houses, all on and on and on, you know, every night they're running thousands, tens of thousands, you know, of jobs pushing that data, you know, out there. It just, and they they're all on snowflake already. So it doesn't have to be this way. Right. So, >>Yes. So I, I asked the guys before, you know, last week, Hey, what, what would you ask Frank? Now? You might remember you came on, uh, our program during COVID and I was asking you how you're dealing with it, turn off the news. And it was, that was cool. And I asked you at the time, you know, were you ever, you go on Preem and you said, look, I'll never say never, but it defeats the purpose. And you said, we're not gonna do a halfway house. Actually, you were more declarative. We're not doing a halfway house, one foot in one foot out. And then the guy said, well, what about that Dell deal? And that pure deal that you just did. And I, I think I know the answer, but I want to hear from you did a customer come to you and say, get you in the headlock and say, you gotta do this. >>Or it did happen that way. Uh, it, uh, it started with a conversation, um, you know, via with, uh, with Michael Dell. Um, it was supposed to be just a friendly chat, you know, Hey, how's it going? And I mean, obviously Dell is the owner of data, the main, or our first company, you know? Um, but it's, it, wasn't easy for, for Dell and snowflake to have a conversation because they're the epitome of the on-premise company and we're the epitome of a cloud company. And it's like, how, what do we have in common here? Right. What can we talk about? But, you know, Michael's a very smart, uh, engaging guy, you know, always looking for, for opportunity. And of course they decided we're gonna hook up our CTOs, our product teams and, you know, explore, you know, somebody's, uh, ideas and, you know, yeah. We had some, you know, starts and restarts and all of that because it's just naturally, you know, uh, not an easy thing to conceive of, but, you know, in the end it was like, you know what? >>It makes a lot of sense. You know, we can virtualize, you know, Dell object storage, you know, as if it's, you know, an S three storage, you know, from Amazon and then, you know, snowflake in its analytical processing. We'll just reference that data because to us, it just looks like a file that's sitting on, on S3. And we have, we have such a thing it's called an external table, right. That's, that's how we basically, it projects, you know, a snowflake, uh, semantic and structural model, you know, on an external object. And we process against it exactly the same way as if it was an internal, uh, table. So we just extended that, um, you know, with, um, with our storage partners, like Dell and pure storage, um, for it to happen, you know, across a network to an on-prem place. So it's very elegant and it, it, um, it becomes an, an enterprise architecture rather than just a cloud architecture. And I'm, I just don't know what will come of it. And, but I've already talked to customers who have to have data on premises just can't go anywhere because they process against it, you know, where it originates, but there are analytical processes that wanna reference attributes of that data. Well, this is what we'll do that. >>Yeah. I'm, it is interesting. I'm gonna ask Dell if I were them, I'd be talking to you about, Hey, I'm gonna try to separate compute from storage on prem and maybe do some of the, the work there. I don't even know if it's technically feasible. It's, I'll ask OI. But, um, but, but, but to me, that's an example of your extending your ecosystem. Um, so you're talking now about applications and that's an example of increasing your Tam. I don't know if you ever get to the edge, you know, we'll see, we're not quite quite there yet, but, um, but as you've said before, there's no lack of market for you. >>Yeah. I mean, obviously snowflake it it's, it's Genesis was reinventing database management in, in a cloud computing environment, which is so different from a, a machine environment or a cluster environment. So that's why, you know, we're, we're, we're not a, a fit for a machine centric, uh, environment sort of defeats the purpose of, you know, how we were built. We, we are truly a native solution. Most products, uh, in the clouds are actually not cloud native. You know, they, they originated the machine environments and you still see that, you know, almost everything you see in the cloud by the way is not cloud native, our generation of applications. They only run the cloud. They can only run the cloud. They are cloud native. They don't know anything else, >>You know? Yeah, you're right. A lot of companies would just wrap something in wrap their stack in Kubernetes and throw it into the cloud and say, we're in the cloud too. And you basically get, you just shifted. It >>Didn't make sense. Oh. They throw it in the container and run it. Right. Yeah. >>So, okay. That's cool. But what does that get you that doesn't change your operational model? Um, so coming back to software development and what you're doing in, in that regard, it seems one of the things we said about Supercloud is in order to have a Supercloud, you gotta have an ecosystem, you gotta have optionality. Hence you're doing things like Apache iceberg, you know, you said today, well, we're not sure where it's gonna go, but we offering options. Uh, but, but my, my question is, um, as it pertains to software developments specifically, how do you, so one of the things we said, sorry, I've lost my train there. One of the things we said is you have to have a super PAs in order to have a super cloud ecosystem, PAs layer. That's essentially what you've introduced here. Is it not a platform for our application development? >>Yeah. I mean, what happens today? I mean, how do you enable a developer, you know, on snowflake, without the developer, you know, reading the, the files out of snowflake, you know, processing, you know, against that data, wherever they are, and then putting the results set, God knows where, right. And that's what happens today. It's the wild west it's completely UN uncovered, right? And that's the reason why lots of enterprises will not allow Python anything anywhere near, you know, their enterprise data. We just know that, uh, we also know it from streamlet, um, or the acquisition, um, large acquisition that we made this year because they said, look, you know, we're, we have a lot of demand, you know, uh, in the Python community, but that's the wild west. That's not the enterprise grade high trust, uh, you know, corporate environment. They are strictly segregated, uh, today. >>Now do some, do these, do these things sometimes dribble up in the enterprise? Yes, they do. And it's actually intolerable the risk that enterprises, you know, take, you know, with things being UN uncovered. I mean the whole snowflake strategy and promises that you're in snowflake, it is a, an absolute enterprise grade environment experience. And it's really hard to do. It takes enormous investment. Uh, but that is what you buy from us. Just having Python is not particularly hard. You know, we can do that in a week. This has taken us years to get it to this level, you know, of, of, you know, governance, security and, and, you know, having all the risks around exfiltration and so on, really understood and dealt with. That's also why these things run in private previews and public previews for so long because we have to squeeze out, you know, everything that may not have been, you know, understood or foreseen, you know, >>So there are trade offs of, of going into this snowflake cloud, you get all this great functionality. Some people might think it's a walled garden. How, how would you respond to that? >>Yeah. And it's true when you have a, you know, a snowflake object, like a snowflake, uh, table only snowflake, you know, runs that table. And, um, you know, that, that is, you know, it's very high function. It's very sort of analogous to what apple did, you know, they have very high functioning, but you do have to accept the fact that it's, that it's not, uh, you know, other, other things in apple cannot, you know, get that these objects. So this is the reason why we introduce an open file format, you know, like, like iceberg, uh, because what iceberg effectively does is it allows any tool, uh, you know, to access that particular object. We do it in such a way that a lot of the functionality of snowflake, you know, will address the iceberg format, which is great because it's, you're gonna get much more function out of our, you know, iceberg implementation than you would get from iceberg on its own. So we do it in a very high value addeds, uh, you know, manner, but other tools can still access the same object in a read to write, uh, manner. So it, it really sort of delivers the original, uh, promise of the data lake, which is just like, Hey, I have all these objects tools come and go. I can use what I want. Um, so you get, you get the best of both worlds for the most part. >>Have you reminds me a little bit of VMware? I mean, VMware's a software mainframe, it's just better than >>Doing >>It on your own. Yep. Um, one of the other hallmarks of a cloud company, and you guys clearly are a cloud company is startups and innovation. Um, now of course you see that in, in the, in the ecosystem, uh, and maybe that's the answer to my question, but you guys are kind of whale hunters, <laugh> your customers are, tend to be bigger. Uh, is the, is the innovation now the extension of that, the ecosystem is that by design. >>Oh, um, you know, we have a enormous, uh, ISV following and, um, we're gonna have a whole separate conference like this, by the way, just for, yeah. >>For developers. I hope you guys will up there too. Yeah. Um, you know, the, the reason that, that the ISV strategy is very important for, you know, for, for, for, for many reasons, but, you know, ISVs are the people that are really going to unlock a lot of the value and a lot of the promise of data, right? Because you, you can never do that on your own. And the problem has been that for ISVs, it is so expensive and so difficult to build a product that can be used because the entire enterprise platform infrastructure needs to be built by somebody, you know, I mean, are you really gonna run infrastructure, database, operations, security, compliance, scalability, economics. How do you do that as a software company where really you only have your, your domain expertise that you want to deliver on a platform. You don't wanna do all these things. >>First of all, you don't know how to do it, how to do it well. Um, so it is much easier, much faster when there is already platform to actually build done in the world of clout that just doesn't, you know, exist. And then beyond that, you know, okay, fine building. It is sort of step one. Now I gotta sell it. I gotta market it. So how do I do that? Well, in the snowflake community, you have already market <laugh>, there's thousands and thousands of customers that are also on self lake. Okay. So their, their ability to consume that service that you just built, you know, they can search it, they can try it, they can test it and decide whether they want to consume it. And then, you know, we can monetize it. So all they have to do is cash the check. So the net effecti of it is we drastically lowered the barriers to entry into the world, you know, of software, you know, two men or two women in a dog, and a handful of files can build something that then can be sold, sort of to, for software developers. >>I wrote a piece 2012 after the first reinvent. And I, you know, and I, and I put a big gorilla on the front page and I said, how do you compete with Amazon gorilla? And then one of my answers was you build data ecosystems and you verticalize, and that's, that's what you're doing >>Here. Yeah. There certain verticals that are farther along than others, uh, obviously, but for example, in financial, uh, which is our largest vertical, I mean, the, the data ecosystem is really developing hardcore now. And that's, that's because they so rely on those relationships between all the big financial institutions and entities, regulatory, you know, clearing houses, investment bankers, uh, retail banks, all this kind of stuff. Um, so they're like, it becomes a no brainer. The network affects kick in so strongly because they're like, well, this is really the only way to do it. I mean, if you and I work in different companies and we do, and we want to create a secure, compliant data network and connection between us, I mean, it would take forever to get our lawyers to agree that yeah, it's okay. <laugh> right now, it's like a matter of minutes to set it up. If we're both on snowflake, >>It's like procurement, do they, do you have an MSA yeah. Check? And it just sail right through versus back and forth and endless negotiations >>Today. Data networking is becoming core ecosystem in the world of computing. You know, >>I mean, you talked about the network effects in rise of the data cloud and correct. Again, you know, you, weren't the first to come up with that notion, but you are applying it here. Um, I wanna switch topics a little bit. I, when I read your press releases, I laugh every time. Cause this says no HQ, Bozeman. And so where, where do you, I think I know where you land on, on hybrid work and remote work, but what are your thoughts on that? You, you see Elon the other day said you can't work for us unless you come to the office. Where, where do you stand? >>Yeah. Well, the, well, the, the first aspect is, uh, we really wanted to, uh, separate from the idea of a headquarters location, because I feel it's very antiquated. You know, we have many different hubs. There's not one place in the world where all the important people are and where we make all the important positions, that whole way of thinking, uh, you know, it is obsolete. I mean, I am where I need to be. And it it's many different places. It's not like I, I sit in this incredible place, you know, and that's, you know, that's where I sit and everybody comes to me. No, we are constantly moving around and we have engineering hubs. You know, we have your regional, uh, you know, headquarters for, for sales. Obviously we have in Malaysia, we have in Europe, you know? And, um, so I wanted to get rid of this headquarters designation. >>And, you know, the, the, the other issue obviously is that, you know, we were obviously in California, but you know, California is, is no longer, uh, the dominant place of where we are resident. I mean, 40% of our engineering people are now in be Washington. You know, we have hundreds of people in Poland where people, you know, we are gonna have very stressed location in Toronto. Um, yeah. Obviously our customers are, are everywhere, right? So this idea that, you know, everything is happening in, in one state is just, um, you know, not, not correct. So we wanted to go to no headquarters. Of course the SCC doesn't let you do that. Um, because they want, they want you to have a street address where the government can send you a mail and then it becomes, the question is, well, what's an acceptable location. Well, it has to be a place where the CEO and the CFO have residency by hooker, by crook. >>That happened to be in Bozeman Montana because Mike and I are both, it was not by design. We just did that because we were, uh, required to, you know, you know, comply with government, uh, requirements, which of course we do, but that's why it, it says what it says now on, on the topic of, you know, where did we work? Um, we are super situational about it. It's not like, Hey, um, you know, everybody in the office or, or everybody is remote, we're not categorical about it. Depends on the function, depends on the location. Um, but everybody is tethered to an office. Okay. In words, everybody has a relationship with an office. There's, there's almost nobody, there are a few exceptions of people that are completely remote. Uh, but you know, if you get hired on with snowflake, you will always have an office affiliation and you can be called into the office by your manager. But for purpose, you know, a meeting, a training, an event, you don't get called in just to hang out. And like, the office is no longer your home away from home. Right. And we're now into hotel, right? So you don't have a fixed place, you know? So >>You talked in your keynote a lot about last question. I let you go customer alignment, obviously a big deal. I have been watching, you know, we go to a lot of events, you'll see a technology company tell a story, you know, about their widget or whatever it was their box. And then you'll see an outcome and you look at it and you shake your head and say, well, that the difference between this and that is the square root of zero, right. When you talk about customer alignment today, we're talking about monetizing data. Um, so that's a whole different conversation. Um, and I, I wonder if you could sort of close on how that's different. Um, I mean, at ServiceNow, you transformed it. You know, I get that, you know, data, the domain was okay, tape, blow it out, but this is a, feels like a whole new vector or wave of growth. >>Yeah. You know, monetizing, uh, data becomes sort of a, you know, a byproduct of having a data cloud you all of a sudden, you know, become aware of the fact that, Hey, Hey, I have data and be that data might actually be quite valuable to parties. And then C you know, it's really easy to then, you know, uh, sell that and, and monetize that. Cause if it was hard, forget it, you know, I don't have time for it. Right. But if it's relatively, if it's compliant, it's relatively effortless, it's pure profit. Um, I just want to reference one attribute, two attributes of what you have, by the way, you know, uh, hedge funds have been into this sort of thing, you know, for a long time, because they procure data from hundreds and hundreds of sources, right. Because they're, they are the original data scientists. >>Um, but the, the bigger thing with data is that a lot of, you know, digital transformation is, is, is finally becoming real. You know, for years it was arm waving and conceptual and abstract, but it's becoming real. I mean, how do we, how do we run a supply chain? You know, how do we run, you know, healthcare, um, all these things are become are, and how do we run cyber security? They're being redefined as data problems and data challenges. And they have data solutions. So that's right. Data strategies are insanely important because, you know, if, if the solution is through data, then you need to have, you know, a data strategy, you know, and in our world, that means you have a data cloud and you have all the enablement that allows you to do that. But, you know, hospitals, you know, are, are saying, you know, data science is gonna have a bigger impact on healthcare than life science, you know, in the coming, whatever, you know, 10, 20 years, how do you enable that? >>Right. I, I have conversations with, with, with hospital executives are like, I got generations of data, you know, clinical diagnostic, demographic, genomic. And then I, I am envisioning these predictive outcomes over here. I wanna be able to predict, you know, once somebody's gonna get what disease and you know, what I have to do about it, um, how do I do that? <laugh> right. The day you go from, uh, you know, I have a lot of data too. I have these outcomes and then do me a miracle in the middle, in the middle of somewhere. Well, that's where we come in. We're gonna organize ourselves and then unpack thats, you know, and then we, we work, we through training models, you know, we can start delivering some of these insights, but the, the promise is extraordinary. We can change whole industries like pharma and, and, and healthcare. Um, you know, 30 effects of data, the economics will change. And you know, the societal outcomes, you know, um, quality of life disease, longevity of life is quite extraordinary. Supply chain management. That's all around us right >>Now. Well, there's a lot of, you know, high growth companies that were kind of COVID companies, valuations shot up. And now they're trying to figure out what to do. You've been pretty clear because of what you just talked about, the opportunities enormous. You're not slowing down, you're amping it up, you know, pun intended. So Frank Luman, thanks so much for coming on the cube. Really appreciate your time. >>My pleasure. >>All right. And thank you for watching. Keep it right there for more coverage from the snowflake summit, 2022, you're watching the cube.

(upbeat music) >> We're back at VeeamON 2022. We're here at the Aria in Las Vegas Dave Vellante with Dave Nicholson. Bill Andrews is here. He's the president and CEO of ExaGrid, mass boy. Bill, thanks for coming on theCUBE. >> Thanks for having me. >> So I hear a lot about obviously data protection, cyber resiliency, what's the big picture trends that you're seeing when you talk to customers? >> Well, I think clearly we were talking just a few minutes ago, data's growing like crazy, right This morning, I think they said it was 28% growth a year, right? So data's doubling almost just a little less than every three years. And then you get the attacks on the data which was the keynote speech this morning as well, right. All about the ransomware attacks. So we've got more and more data, and that data is more and more under attack. So I think those are the two big themes. >> So ExaGrid as a company been around for a long time. You've kind of been the steady kind of Eddy, if you will. Tell us about ExaGrid, maybe share with us some of the differentiators that you share with customers. >> Sure, so specifically, let's say in the Veeam world you're backing up your data, and you really only have two choices. You can back that up to disc. So some primary storage disc from a Dell, or a Hewlett Packard, or an NetApp or somebody, or you're going to back it up to what's called an inline deduplication appliance maybe a Dell Data Domain or an HPE StoreOnce, right? So what ExaGrid does is we've taken the best of both those but not the challenges of both those and put 'em together. So with disc, you're going to get fast backups and fast restores, but because in backup you keep weekly's, monthly's, yearly retention, the cost of this becomes exorbitant. If you go to a deduplication appliance, and let's say the Dell or the HPs, the data comes in, has to be deduplicated, compare one backup to the next to reduce that storage, which lowers the cost. So fixes that problem, but the fact that they do it inline slows the backups down dramatically. All the data is deduplicated so the restores are slow, and then the backup window keeps growing as the data grows 'cause they're all scale up technologies. >> And the restores are slow 'cause you got to rehydrate. >> You got to rehydrate every time. So what we did is we said, you got to have both. So our appliances have a front end disc cache landing zone. So you're right directed to the disc., Nothing else happens to it, whatever speed the backup app could write at that's the speed we take it in at. And then we keep the most recent backups in that landing zone ready to go. So you want to boot a VM, it's not an hour like a deduplication appliance it's a minute or two. Secondly, we then deduplicate the data into a second tier which is a repository tier, but we have all the deduplicated data for the long term retention, which gets the cost down. And on top of that, we're scale out. Every appliance has networking processor memory end disc. So if you double, triple, quadruple the data you double, triple, quadruple everything. And if the backup window is six hours at 100 terabyte it's six hours at 200 terabyte, 500 terabyte, a petabyte it doesn't matter. >> 'Cause you scale out. >> Right, and then lastly, our repository tier is non-network facing. We're the only ones in the industry with this. So that under a ransomware attack, if you get hold of a rogue server or you hack the media server, get to the backup storage whether it's disc or deduplication appliance, you can wipe out all the backup data. So you have nothing to recover from. In our case, you wipe it out, our landing zone will be wiped out. We're no different than anything else that's network facing. However, the only thing that talks to our repository tier is our object code. And we've set up security policies as to how long before you want us to delete data, let's say 10 days. So if you have an attack on Monday that data doesn't get deleted till like a week from Thursday, let's say. So you can freeze the system at any time and do restores. And then we have immutable data objects and all the other stuff. But the culmination of a non-network facing tier and the fact that we do the delayed deletes makes us the only one in the industry that can actually truly recover. And that's accelerating our growth, of course. >> Wow, great description. So that disc cache layer is a memory, it's a flash? >> It's disc, it's spinning disc. >> Spinning disc, okay. >> Yeah, no different than any other disc. >> And then the tiered is what, less expensive spinning disc? >> No, it's still the same. It's all SaaS disc 'cause you want the quality, right? So it's all SaaS, and so we use Western Digital or Seagate drives just like everybody else. The difference is that we're not doing any deduplication coming in or out of that landing zone to have fast backups and fast restores. So think of it like this, you've got disc and you say, boy it's too expensive. What I really want to do then is put maybe a deduplication appliance behind it to lower the cost or reverse it. I've got a deduplication appliance, ugh, it's too slow for backups and restores. I really want to throw this in front of it to have fast backups first. Basically, that's what we did. >> So where does the cost savings, Bill come in though, on the tier? >> The cost savings comes in the fact that we got deduplication in that repository. So only the most recent backup >> Ah okay, so I get it. >> are the duplicated data. But let's say you had 40 copies of retention. You know, 10 weekly's, 36 monthly's, a few yearly. All of that's deduplicated >> Okay, so you're deduping the stuff that's not as current. >> Right. >> Okay. >> And only a handful of us deduplicate at the layer we do. In other words, deduplication could be anywhere from two to one, up to 50 to one. I mean it's all over the place depending on the algorithm. Now it's what everybody's algorithms do. Some backup apps do two to one, some do five to one, we do 20 to one as well as much as 50 to one depending on the data types. >> Yeah, so the workload is going to largely determine the combination >> The content type, right. with the algos, right? >> Yeah, the content type. >> So the part of the environment that's behind the illogical air gap, if you will, is deduped data. >> Yes. >> So in this case, is it fair to say that you're trading a positive economic value for a little bit longer restore from that environment? >> No, because if you think about backup 95% of the customers restores are from the most recent data. >> From the disc cache. >> 95% of the time 'cause you think about why do you need fast restores? Somebody deleted a file, somebody overwrote a file. They can't go work, they can't open a file. It's encrypted, it's corrupted. That's what IT people are trying to keep users productive. When do you go for longer-term retention data? It's an SEC audit. It's a HIPAA audit. It's a legal discovery, you don't need that data right away. You have days and weeks to get that ready for that legal discovery or that audit. So we found that boundary where you keep users productive by keeping the most recent data in the disc cache landing zone, but anything that's long term. And by the way, everyone else is long term, at that point. >> Yeah, so the economics are comparable to the dedupe upfront. Are they better, obviously get the performance advance? >> So we would be a lot looped. The thing we replaced the most believe it or not is disc, we're a lot less expensive than the disc. I was meeting with some Veeam folks this morning and we were up against Cisco 3260 disc at a children's hospital. And on our quote was $500,000. The disc was 1.4 million. Just to give you an example of the savings. On a Data Domain we're typically about half the price of a Data Domain. >> Really now? >> The reason why is their front end control are so expensive. They need the fastest trip on the planet 'cause they're trying to do inline deduplication. >> Yeah, so they're chasing >> They need the fastest memory >> on the planet. >> this chips all the time. They need SSD on data to move in and out of the hash table. In order to keep up with inline, they've got to throw so much compute at it that it drives their cost up. >> But now in the case of ransomware attack, are you saying that the landing zone is still available for recovery in some circumstances? Or are you expecting that that disc landing zone would be encrypted by the attacker? >> Those are two different things. One is deletion, one is encryption. So let's do the first scenario. >> I'm talking about malicious encryption. >> Yeah, absolutely. So the first scenario is the threat actor encrypts all your primary data. What's does he go for next? The backup data. 'Cause he knows that's your belt and suspend is to not pay the ransom. If it's disc he's going to go in and put delete commands at the disc, wipe out the disc. If it's a data domain or HPE StoreOnce, it's all going to be gone 'cause it's one tier. He's going to go after our landing zone, it's going to be gone too. It's going to wipe out our landing zone. Except behind that we have the most recent backup deduplicate in the repository as well as all the other backups. So what'll happen is they'll freeze the system 'cause we weren't going to delete anything in the repository for X days 'cause you set up a policy, and then you restore the most recent backup into the landing zone or we can restore it directly to your primary storage area, right? >> Because that tier is not network facing. >> That's right. >> It's fenced off essentially. >> People call us every day of the week saying, you saved me, you saved me again. People are coming up to me here, you saved me, you saved me. >> Tell us a story about that, I mean don't give me the names but how so. >> I'll actually do a funnier story, 'cause these are the ones that our vendors like to tell. 'Cause I'm self-serving as the CEO that's good of course, a little humor. >> It's your 15 minutes of job. >> That is my 15 minutes of fame. So we had one international company who had one ExaGrid at one location, 19 Data Domains at the other locations. Ransomware attack guess what? 19 Data Domains wiped out. The one ExaGrid, the only place they could restore. So now all 20 locations of course are ExaGrids, China, Russia, Mexico, Germany, US, et cetera. They rolled us out worldwide. So it's very common for that to occur. And think about why that is, everyone who's network facing you can get to the storage. You can say all the media servers are buttoned up, but I can find a rogue server and snake my way over the storage, I can. Now, we also of course support the Veeam Data Mover. So let's talk about that since we're at a Veeam conference. We were the first company to ever integrate the Veeam Data Mover. So we were the first actually ever integration with Veeam. And so that Veeam Data Mover is a protocol that goes from Veeam to the ExaGrid, and we run it on both ends. So that's a more secure protocol 'cause it's not an open format protocol like SaaS. So with running the Veeam Data Mover we get about 30% more performance, but you do have a more secure protocol layer. So if you don't get through Veeam but you get through the protocol, boom, we've got a stronger protocol. If you make it through that somehow, or you get to it from a rogue server somewhere else we still have the repository. So we have all these layers so that you can't get at it. >> So you guys have been at this for a while, I mean decade and a half plus. And you've raised a fair amount of money but in today's terms, not really. So you've just had really strong growth, sequential growth. I understand it, and double digit growth year on year. >> Yeah, about 25% a year right now >> 25%, what's your global strategy? >> So we have sales offices in about 30 countries already. So we have three sales teams in Brazil, and three in Germany, and three in the UK, and two in France, and a lot of individual countries, Chile, Argentina, Columbia, Mexico, South Africa, Saudi, Czech Republic, Poland, Dubai, Hong Kong, Australia, Singapore, et cetera. We've just added two sales territories in Japan. We're adding two in India. And we're installed in over 50 countries. So we've been international all along the way. The goal of the company is we're growing nicely. We have not raised money in almost 10 years. >> So you're self-funding. You're cash positive. >> We are cash positive and self-funded and people say, how have you done that for 10 years? >> You know what's interesting is I remember, Dave Scott, Dave Scott was the CEO of 3PAR, and he told me when he came into that job, he told the VCs, they wanted to give him 30 million. He said, I need 80 million. I think he might have raised closer to a hundred which is right around what you guys have raised. But like you said, you haven't raised it in a long time. And in today's terms, that's nothing, right? >> 100 is 500 in today's terms. >> Yeah, right, exactly. And so the thing that really hurt 3PAR, they were public companies so you could see all this stuff is they couldn't expand internationally. It was just too damn expensive to set up the channels, and somehow you guys have figured that out. >> 40% of our business comes out of international. We're growing faster internationally than we are domestically. >> What was the formula there, Bill, was that just slow and steady or? >> It's a great question. >> No, so what we did, we said let's build ExaGrid like a McDonald's franchise, nobody's ever done that before in high tech. So what does that mean? That means you have to have the same product worldwide. You have to have the same spares model worldwide. You have to have the same support model worldwide. So we early on built the installation. So we do 100% of our installs remotely. 100% of our support remotely, yet we're in large enterprises. Customers racks and stacks the appliances we get on with them. We do the entire install on 30 minutes to about three hours. And we've been developing that into the product since day one. So we can remotely install anywhere in the world. We keep spares depots all over the world. We can bring 'em up really quick. Our support model is we have in theater support people. So they're in Europe, they're in APAC, they're in the US, et cetera. And we assign customers to the support people. So they deal with the same support person all the time. So everything is scalable. So right now we're going to open up India. It's the same way we've opened up every other country. Once you've got the McDonald's formula we just stamp it all over the world. >> That's amazing. >> Same pricing, same product same model, same everything. >> So what was the inspiration for that? I mean, you've done this since day one, which is what like 15, 16 years ago. Or just you do engineering or? >> No, so our whole thought was, first of all you can't survive anymore in this world without being an international company. 'Cause if you're going to go after large companies they have offices all over the world. We have companies now that have 17, 18, 20, 30 locations. And there were in every country in the world, you can't go into this business without being able to ship anywhere in the world and support it for a single customer. You're not going into Singapore because of that. You're going to Singapore because some company in Germany has offices in the U.S, Mexico Singapore and Australia. You have to be international. It's a must now. So that was the initial thing is that, our goal is to become a billion dollar company. And we're on path to do that, right. >> You can see a billion. >> Well, I can absolutely see a billion. And we're bigger than everybody thinks. Everybody guesses our revenue always guesses low. So we're bigger than you think. The reason why we don't talk about it is we don't need to. >> That's the headline for our writers, ExaGrid is a billion dollar company and nobody's know about it. >> Million dollar company. >> On its way to a billion. >> That's right. >> You're not disclosing. (Bill laughing) But that's awesome. I mean, that's a great story. I mean, you kind of are a well kept secret, aren't you? >> Well, I dunno if it's a well kept secret. You know, smaller companies never have their awareness of big companies, right? The Dells of the world are a hundred billion. IBM is 70 billion, Cisco is 60 billion. Easy to have awareness, right? If you're under a billion, I got to give a funny story then I think we got to close out here. >> Oh go ahead please. >> So there's one funny story. So I was talking to the CIO of a super large Fortune 500 company. And I said to him, "Just so who do you use?" "I use IBM Db2, and I use, Cisco routers, and I use EMC primary storage, et cetera. And I use all these big." And I said, "Would you ever switch from Db2?" "Oh no, the switching costs would kill me. I could never go to Oracle." So I said to him, "Look would you ever use like a Pure Storage, right. A couple billion dollar company." He says, "Who?" >> Huh, interesting. >> I said to him, all right so skip that. I said, "VMware, would you ever think about going with Nutanix?" "Who?" Those are billion dollar plus companies. And he was saying who? >> Public companies. >> And he was saying who? That's not uncommon when I talk to CIOs. They see the big 30 and that's it. >> Oh, that's interesting. What about your partnership with Veeam? Tell us more about that. >> Yeah, so I would actually, and I'm going to be bold when I say this 'cause I think you can ask anybody here at the conference. We're probably closer first of all, to the Veeam sales force than any company there is. You talk to any Veeam sales rep, they work closer with ExaGrid than any other. Yeah, we are very tight in the field and have been for a long time. We're integrated with the Veeam Data Boomer. We're integrated with SOBR. We're integrated with all the integrations or with the product as well. We have a lot of joint customers. We actually do a lot of selling together, where we go in as Veeam ExaGrid 'cause it's a great end to end story. Especially when we're replacing, let's say a Dell Avamar to Dell Data Domain or a Dell Network with a Dell Data Domain, very commonly Veeam ExaGrid go in together on those types of sales. So we do a lot of co-selling together. We constantly train their systems engineers around the world, every given week we're training either inside sales teams, and we've trained their customer support teams in Columbus and Prague. So we're very tight with 'em we've been tight for over a decade. >> Is your head count public? Can you share that with us? >> So we're just over 300 employees. >> Really, wow. >> We have 70 open positions, so. >> Yeah, what are you looking for? Yeah, everything, right? >> We are looking for engineers. We are looking for customer support people. We're looking for marketing people. We're looking for inside sales people, field people. And we've been hiring, as of late, major account reps that just focus on the Fortune 500. So we've separated that out now. >> When you hire engineers, I mean I think I saw you were long time ago, DG, right? Is that true? >> Yeah, way back in the '80s. >> But systems guy. >> That's how old I am. >> Right, systems guy. I mean, I remember them well Eddie Castro and company. >> Tom West. >> EMV series. >> Tom West was the hero of course. >> The EMV 4000, the EMV 20,000, right? >> When were kids, "The Soul of a New Machine" was the inspirational book but anyway, >> Yeah Tracy Kidder, it was great. >> Are you looking for systems people, what kind of talent are you looking for in engineering? >> So it's a lot of Linux programming type stuff in the product 'cause we run on a Linux space. So it's a lot of Linux programs so its people in those storage. >> Yeah, cool, Bill, hey, thanks for coming on to theCUBE. Well learned a lot, great story. >> It's a pleasure. >> That was fun. >> Congratulations. >> Thanks. >> And good luck. >> All right, thank you. >> All right, and thank you for watching theCUBE's coverage of VeeamON 2022, Dave Vellante for Dave Nicholson. We'll be right back right after this short break, stay with us. (soft beat music)

welcome back to the cube's presentation of the aws executive summit at re invent 2021 made possible by accenture my name is dave vellante we're going to look at how digital infrastructure is helping to transform consumer experiences specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who change their behavior to live healthier lives a real passion of of mine and getting to the really root cause of health with me now are simon guest who's the chief executive officer of generality vitality gmbh and niels mueller who's the managing director at the cloud first application engineering lead for the european market at accenture gentlemen welcome to the cube thanks for having us you're very welcome simon generally vitality it's a really interesting concept that you guys have envisioned and now put into practice tell us how does it all work sure no problem and thanks for for having us on dave it's a pleasure to be here so look uh generally vitality is in its uh it's core pretty simple concepts so it's uh it's a program that you have on your phone and the idea of this program is that it's a it's a wellness coach for you as an individual and it's going to help you to understand your health and where you are in terms of the state of your health at the moment and it's going to take you on a journey to improve your your lifestyle and your wellness and hopefully help you to lead a healthier and a more sort of mindful life i guess is is the best way of summarizing it from um from our point of view with insurance company of course you know our historical role has always been to uh be the company that's there if something goes wrong you know so if unfortunately you pass away or you have sickness in your in your life or in your family's life that's that's historically been our role but what we see with generality vitality is something a little bit different so it's a program that really is uh supposed to be with you every day of your life to help you to live a healthier life it's something that we already have in in four european markets in fact in five from this week i'm a little bit behind the time so we're live already in in germany in france in austria and italy and in spain and fundamentally what we what we do dave is too is to say to customers look if you want to understand your health if you want to improve it by moving a little bit more by visiting the doctor more by eating healthier by healthy choices on a daily basis we're going to help you to do that and we're going to incentivize you for going on this journey and making healthy choices and we're going to reward you for for doing the same so you know we partner up with with great companies like garmin like adidas like big brands that are let's say invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well make good choices be healthy have an insurance company that partners you along that journey and if you do that we're going to reward you for for that so you know we're here not just in the difficult times which of course is one of our main roles but we're here as a partner as a lifetime partner to you too to help you feel better and live a better life i love it i mean it sounds so simple but but it's i'm sure it's very complicated to to make the technology simple for the user you've got mobile involved you've got the back end and we're going to get into some of the tech but first i want to understand the member engagement and some of the lifestyle changes simon that you've analyzed what's the feedback that you're getting from your customers what does the data tell you how do the incentives work as well what what is the incentive for the the member to actually do the right thing sure look i think actually the the covered uh situation that we've had in the last sort of two years has really crystallized the fact that this is something that we really ought to be doing and something that our customers really value so i mean look just to give you a bit of a sort of information about how it works for for customers so what we try to do with them is is to get customers to understand uh their current health situation you know using their phone so uh you know we ask our customers to go through a sort of health assessment around how they live what they eat how they sleep you know and to go through that sort of process uh and to give them what a vitality age which is a sort of uh you know sort of actuarial comparison with their real age so i'm i'm 45 but unfortunately my my vitality age is 49 and it means i have some work to do to bring that back together uh and what we see is that you know two-thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life and if what if what they are doing is having an impact on their life expectancy and their lifespan and their health span so how long are they going to live healthier for so you see them really engaging in this in this approach of understanding their current situation then what we know actually because the program is built around this model that uh really activity and moving and exercise is the biggest contributor to living a healthier life we know that the majority of deaths are caused by lifestyle illness is like you know poor nutrition and smoking and drinking alcohol and not exercising and so a lot of the program is really built around getting people to move more and it's not about being an athlete it's about you know getting off the the underground one station earlier walking home or making sure you do your 10 000 steps a day and what we see is that that sort of 40 of our customers are on a regularly basis linking either their phone or their their exercise device to our program and downloading that data so that they can see how how much they are exercising and at the same time what we do is we set we set our customers weekly challenges to say look if you can move a little bit more than last week we are going to to reward you for that and we see that you know almost half of our customers are achieving this weekly goal every week and it's really a fantastic level of engagement that normally is an insurer uh we don't see the way the rewards work is is pretty simple it's similar in a way to an airline program so every good choice you make every activity you do every piece of good food that you eat when you check your on your health situation we'll give you points and the more points you get you go through through a sort of status approach of starting off at the bottom status and ending up at a gold and then a platinum status and the the higher up you get in the status that the higher the value of the rewards that we give you so almost a quarter of our customers now and this is accelerated through provide they've reached that platinum status so they are the most engaged customers that we we have and those ones who are really engaging in the in the program and what we really try to create is this sort of virtuous circle that says if you live well you make good choices you improve your health you you progress through the program and we give you better and stronger and more uh valuable rewards for for doing that and some of those rewards are are around health and wellness so it might be that you get you get a discount on on gym gear from adidas it might be that you get a discount on a uh on a device from garmin or it might be actually on other things so we also give people amazon vouchers we also give people uh discounts on holidays and another thing that we we did actually in the last year which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations because we we work in generality with a with a sort of um campaign called the human safety net which is helping out the poorest people in society and some what our customers do a lot of the time is instead of taking those financial rewards for themselves they convert it into a charitable donation so we're actually also thinking wellness and feeling good and insurance and some societal good so we're really trying to create a virtuous circle of uh of engagement with our customers i mean that's a powerful cocktail i love it you got the the data because if i see the data then i can change my behavior you got the gamification piece you actually have you know hard dollar rewards you could give those to charities and and you've got the the most important which is priceless can't put a value on good health i got one more question for simon and niels i'd love you to chime in as well on this question how did you guys decide simon to engage with accenture and aws and the cloud to build out this platform what's the story behind that collaboration was there unique value that you saw that that you wanted to tap that you feel like they bring to the table what was your experience yeah look i mean we worked at accenture as well because the the the sort of construct of this vitality proposition is a pretty a pretty complex one so you mentioned that the idea is simple but the the build is not so uh is not so simple and that that's the case so accenture's been part of that journey uh from the beginning they're one of the partners that we work with but specifically around the topic of rewards uh you know we're we're a primarily european focused organization but when you take those countries that i mentioned even though we're next to each other geographically we're quite diverse and what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go and get to market with an increasing amount of efficiency and and to do that we needed to work with somebody who understood our business has this historical let's say investment in in the vitality concept so so knows how to bring it to life but that what then could really support us in making uh what can be a complex piece of work as simple and as as replicable as possible across multiple markets because we don't want to go reinventing the wheel every time we do we move to a new market so we need to find a balance between having a consistent product a consistent technology offer a consistent customer experience with the fact that we we operate in quite diverse markets so this was let's say the the reason for more deeply engaging with accenture on this journey thank you very much niels why don't you comment on on that as well i'd love to to get your thoughts and and really really it's kind of your role here i mean accenture global si deep expertise in industry but also technology what are your thoughts on this topic yeah i'd love to love to comment so when we started the journey it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets have a central solution that can act as a template for the different markets but then also have the opportunity to localize different languages different partners for the rewards there's different reward partners in the different markets so we needed to build in an asset basically that could work as a tempos centrally standardizing things but also leaving enough flexibility to to then localize in the individual markets and if we talk about some of the more specific requirements so one one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the basically the authentication needs to happen and we somehow needed to still find a holistic solution that comes through the central platform and we were able to do that at the end through the aws cognito service sort of wrapping the individual markets uh local idp systems and by now we've even extended that solution to have a standalone cloud native kind of idp solution in place for markets that do not have a local idp solution in place or don't want to use it for for this purpose yeah so you had you had data you have you had the integration you've got local laws you mentioned the flexibility you're building ecosystems that are unique to the to the local uh both language and and cultures uh please you had another comment i interrupted you yeah i know i just wanted to expand basically on the on the requirements so that was the central one being able to roll this out in a standardized way across the markets but then there were further requirements for example like being able to operate that platform with very low operations overhead there is no large i.t team behind generally vitality that you know works to serve us or can can act as this itis backbone support so we needed to have basically a solution that runs itself that runs on autopilot and that was another big big driver for first of all going to cloud but second of all making specific choices within cloud so we specifically chose to build this as a cloud native solution using for example manage database services you know with automatic backup with automatic ability to restore data that scales automatically that you know has all this built in which usually maybe a database administrator would take care of and we applied that concept basically to every component to everything we looked at we we applied this requirement of how can this run on autopilot how can we make this as much managed by itself within the cloud as possible and then land it on these services and for example we also used the the api gateway from from aws for our api services that also came in handy when for example we had some response time issues with the third party we needed to call and then we could just with a flick of a button basically introduce caching on the level of the api gateway and really improve the user experience because the data you know wasn't updated so much so it was easier to cache so these are all experiences i think that that proved in the end that we made the right choices here and the requirements that that drove that to to have a good user experience niels would you say that the architecture is is a sort of a data architecture specifically is it a decentralized data architecture with sort of federated you know centralized governance or is it more of a centralized view what if you could talk about that yeah it's it's actually a centralized platform basically so the core product is the same for all the markets and we run them as different tenants basically on top of that infrastructure so the data is separated in a way obviously by the different tenants but it's in a central place and we can analyze it in a central fashion if if the need arises from from the business and the reason i ask that simon is because essentially i look at this as a as largely a data offering for your customers and so niels you were talking about the local language and simon as well i would imagine that that the local business lines have specific requirements and specific data requirements and so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security that's not a trivial challenge i wonder if you both could comment on that yeah maybe maybe i'll give a start and then simon can chime in so um what we're specifically doing is managing the rewards experience right so so our solution will take care of tracking what rewards have been earned for what customer what rewards have been redeemed what rewards can be unlocked on the next level and we we foreshadow a little bit to to motivate to incentivize the customer and as that data sits in an aws database in a tenant by tenant fashion and you can run analysis on top of that maybe what you're getting into is also the let's say the exercise data the fitness device tracking data that is not specifically part of what my team has built but i'm sure simon can comment a little bit on that angle as well yeah please yeah sure sure yeah sure so look i think them the topic of data and how we use it uh in our business is a very is very interesting one because it's um it's not historically being seen let's say as the remit of insurers to go beyond the you know the the data that you need to underwrite policies or process claims or whatever it might be but actually we see that this is a whole point around being able to create some shared value in in this kind of product and and what i mean by that is uh look if you are a customer and you're buying an insurance policy it might be a life insurance or health insurance policy from from generali and we are giving you access to this uh to this program and through that program you are living a healthier life and that might have a you know a positive impact on generali in terms of you know maybe we're going to increase our market share or maybe we're going to lower claims or we're going to generate value out of that then one of the points of this program is that we then share that value back with customers through the rewards on the platform that we that we've built here and of course being able to understand that data and to quantify it and to value that data is an important part of the of the the different stages of how you of how much value you are creating and it's also interesting to know that you know in a couple of our markets we we operate in the corporate space so not with retail customers but with with organizations and one of the reasons that those companies give vitality to their employees is that they want to see things like the improved health of a workforce they want to see higher presenteeism lower absenteeism of employees and of course being able to demonstrate that there's a sort of correlation between participation in the vitality program and things like that is also is also important and as we've said the markets are very different so we need to be able to to take the data uh that we have out of the vitality program uh and be able in in the company that that i'm managing to to interpret that data so that in our insurance businesses we are able to make good decisions about the kind of insurance products we i think what's interesting to uh to make clear is that actually that the kind of health data that we generate stays purely within the vitality business itself and what we do inside the vitality business is to analyze that data and say okay is this is this also helping our insurance businesses to to drive uh yeah you know better top line and bottom line in the in the relevant business lines and this is different per company and per mark so yeah being able to interrogate that data understand it apply it in different markets and different uh distribution systems and different kinds of approaches to insurance is an is an important one yes it's an excellent example of a digital business in in you know we talk about digital transformation what does that mean this is what it means i i'd love i mean it must be really interesting board discussions because you're transforming an industry you're lowering overall cost i mean if people are getting less sick that's more profit for your company and you can choose to invest that in new products you can give back some to your corporate clients you can play that balancing act you can gain market share and and you've got some knobs to turn some levers uh for your stakeholders which is which is awesome neil something that i'm interested in i mean it must have been really important for you to figure out how to determine and measure success i mean you're obviously removed it's up it's up to generality vitality to get adoption for for their customers but at the same time the efficacy of your solution is going to determine you know the ease of of of delivery and consumption so so how did you map to the specific goals what were some of the key kpis in terms of mapping to their you know aggressive goals besides the things we already touched on i think one thing i would mention is the timeline right so we we started the team ramping in january or february and then within six months basically we had the solution built and then we went through a extensive test phase and within the next six months we had the product rolled out to three markets so this speed to value speed to market that we were able to achieve i think is one of the key um key criteria that also simon and team gave to us right there was a timeline and that timeline was not going to move so we needed to make a plan adjust to that timeline and i think it's both a testament to to the team's work that they did that we made this timeline but it also is enabled by technologies like cloud i have to say if i go back five years ten years if if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally there would have been no way to do this in 12 months right that's for sure yeah i mean simon you're a technology company i mean insurance has always been a tech heavy company but but as niels just mentioned if you had to do that with it departments in each region so my question is is now you've got this it's almost like non-recurring engineering costs you've got that it took one year to actually get the first one done how fast are you able to launch into new markets just from a technology perspective not withstanding any you know local regulations and figuring out to go to market is that compressed yeah so if you are specifically technology-wise i think we would be able to set up a new market including localizations that often involves translation of because in europe you have all the different languages and so on at i would say four to six weeks we probably could stand up a localized solution in reality it takes more like six to nine months to get it rolled out because there's many other things involved obviously but just our piece of the solution we can pretty quickly localize it to a new market but but simon that means that you can spend time on those other factors you don't have to really worry so much about the technology and so you've launched in multiple european markets what do you see for the future of this program come to america you know you can fight you can find that this program in america dave but with one of our competitors we're not we're not operating so much in uh but you can find it if you want to become a customer for sure but yes you're right so look i think from from our perspective uh you know to put this kind of business into a new market it's not it's not an easy thing because what we're doing is not offering it just as a as a service on a standalone basis to customers we want to link it with with insurance business in the end we are an insurance business and we want to to see the value that comes from that so there's you know there's a lot of effort that has to go into making sure that we land it in the right way also from a customer publishing point of view with our distribution and they are they are quite different so so yeah look coming to the question of what's next i mean it comes in three stages for me so as i mentioned we are uh in five markets already uh in next in the first half of 2022 we'll also come to to the czech republic and poland uh which we're excited to to do and that will that will basically mean that we we have this business in in the seven main uh general markets in europe related to life and health business which is the most natural uh let's say fit for something like vitality then you know the next the sort of second part of that is to say okay look we have a program that's very heavily focused around uh activity and rewards and that that's a good place to start but you know wellness these days is not just about you know can you move a bit more than you did historically it's also about mental well-being it's about sleeping good it's about mindfulness it's about being able to have a more holistic approach to well-being and and covert has taught us and customer feedback has taught us actually that this is something where we need to to go and here we need to have the technology to move there as well so to be able to work with partners that are not just based on on on physical activity but also also on mindfulness so this is how one other way we'll develop the proposition and i think the third one which is more strategic and and we are you know really looking into is there's clearly something in the whole uh perception of incentives and rewards which drives a level of engagement between an insurer like generali and its customers that it hasn't had historically so i think we need to learn you know forget you know forgetting about the specific one of vitality being a wellness program but if there's an insurer there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that and it creates value for us as an insurer then then this is probably you know a place we want to investigate more and to be able to do that in in other areas means we need to have the technology available that is as i said before replicable faster market can adapt quickly to to other ideas that we have so we can go and test those in in different markets so yes we have to we have to complete our scope on vitality we have to get that to scale and be able to manage all of this data at scale all of those rewards at real scale and uh to have the technology that allows us to do that without without thinking about it too much and then to say okay how do we widen the proposition and how do we take the concept of vitality that sits behind vitality to see if we can apply it to other areas of our business and that's really what the future is is going to look like for us you know the the isolation era really taught us that if you're not a digital business you're out of business and pre-kov a lot of these stories were kind of buried uh but the companies that have invested in digital are now thriving and this is an awesome example jeff another point is that jeff amebacher one of the founders of cloudera early facebook employee famously said about 10 12 years ago the best and greatest engineering minds of our my generation are trying to figure out how to get people to click on ads and this is a wonderful example of how to use data to change people's lives so guys congratulations best of luck really awesome example of applying technology to create an important societal outcome really appreciate you your time on the cube thank you thanks bye-bye all right and thanks for watching this segment of thecube's presentation of the aws executive summit at reinvent 2021 made possible by accenture keep it right there for more deep dives [Music] you

(upbeat music) >> Welcome back to theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. My name is Dave Vellante. We're going to look at how digital infrastructure is helping to transform consumer experiences, specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who changed their behavior to live healthier lives, a real passion of mine, and getting to the really root cause of health. With me now are Simon Guest, who's the Chief Executive Officer of Generali Vitality, GmbH, and Nils Muller-Sheffer, who's the Managing Director at the Cloud First Application Engineering Lead for the European market at Accenture. Gentlemen, welcome to theCUBE. >> Thanks for having us. >> You're very welcome Simon. Simon, Generali Vitality is a really interesting concept that you guys have envisioned and now put it into practice. Tell us how does it all work? >> Sure. No problem. And thanks for having us on David, pleasure to be here. So look, Generali Vitality is in its core a pretty simple concept. It's a program that you have on your phone. And the idea of this program is that it's a wellness coach for you as an individual, and it's going to help you to understand your health and where you are in terms of the state of your health at the moment, and it's going to take you on a journey to improve your lifestyle and your wellness, and hopefully help you to live a healthier and a more sort of mindful life, I guess, is the best way of summarizing it. From our point of view as an insurance company, of course, our historical role has always been to be the company that's there if something goes wrong. So if unfortunately you pass away or you have sickness in your life or your family's life, that's historically been our role. But what we see with Generali Vitality is something a little bit different. So it's a program that really is supposed to be with you every day of your life to help you to live a healthier life. It's something that we already have in for European markets and in fact, in five from this week, I'm a little bit behind the times. So we're live already in Germany, in France, in Austria, in Italy and in Spain. And fundamentally what we do Dave, is to say to customers, "Look, if you want to understand your health, if you want to improve it by moving a little bit more, or by visiting the doctor more, by eating healthier, by healthy choices on a daily basis, we're going to help you to do that. And we're going to incentivize you for going on this journey and making healthy choices. And we're going to reward you for doing the same." So, we partner up with great companies like Garmin, like Adidas, like big brands that are, let's say, invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well, make good choices, be healthy, have an insurance company that partners you along that journey. And if you do that, we've going to reward you for that. So, we're here not just in a difficult times, which of course is one of our main roles, but we're here as a partner, as a lifetime partner to you to help you feel better and live a better life. >> I love it, I mean, it sounds so simple, but I'm sure it's very complicated to make the technology simple for the user. You've got mobile involved, you've got the back end and we're going to get into some of the tech, but first I want to understand the member engagement and some of the lifestyle changes Simon that you've analyzed. What's the feedback that you're getting from your customers? What does the data tell you? How do the incentives work as well? What is the incentive for the member to actually do the right thing? >> Sure, I think actually that the COVID situation that we've had in the last sort of two years is really crystallized the fact that this is something that we really ought to be doing and something that our customers really value. Just to give you a bit of a sort of information about how it works for our customers. So what we try to do with them, is to get customers to understand their current health situation, using their phone. So, we asked our customers to go through a sort of health assessments around how they live, what they eat, how they sleep, and to go through that sort of process and to give them all the Vitality age, which is a sort of actuarial comparison with their real age. So I'm 45, but unfortunately my Vitality age is 49 and it means I have some work to do to bring that back together. And what we see is that, two thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life. And if what they are doing is having an impact on their life expectancy and their lifespan and their health span. So how long are they going to live healthier for? So you see them really engaging in this approach of understanding that current situation. Then what we know actually, because the program is built around this model that's really activity and moving, and exercise is the biggest contributors to living a healthier life. We know that the majority of deaths are caused by lifestyle illnesses like poor nutrition and smoking and drinking alcohol and not exercising. And so a lot of the program is really built around getting people to move more. And it's not about being an athlete. It's about, getting off the underground one station earlier and walking home or making sure you do your 10,000 steps a day. And what we see is that that sort of 40% of our customers are on a regularly basis linking either their phone or their exercise device to our program and downloading that data so that they can see how much they are exercising. And at the same time, what we do is we set our customers weekly challenges to say, look, if you can move a little bit more than last week, we are go into to reward you for that. And we see that almost half of our customers are achieving this weekly goal every week. And it's really a level of engagement that normally as an insurer, we don't see. The way that rewards work is pretty simple. It's similar in a way to an airline program. So every good choice you make every activity to every piece of good food that you eat. When you check your on your health situation, we'll give you points. And the more points you get, you go through through a sort of status approach of starting off at the bottom status and ending up at a golden and a platinum status. And the higher up you get in the status, the higher the value of the rewards that we give you. So almost a quarter of our customers now, and this has accelerated through COVID have reached that platinum status. So they are the most engaged customers that we have and those ones who are really engaging in the program. And what we really tried to create is this sort of virtuous circle that says If you live well, you make good choices, you improve your health, you progress through the program and we give you better and stronger and more valuable rewards for doing that. And some of those rewards are around health and wellness. So it might be that you get a discounts on gym gear from Adidas, it might be that you get a discount on a device from Garmin, or it might be actually on other things. We also give people Amazon vouchers. We also give people discounts on holidays. And another thing that we did actually in the last year, which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations. Because we work in generosity with a sort of campaign called The Human Safety Net, which is helping out the poorest people in society. And so what our customers do a lot of the time is instead of taking those financial rewards for themselves, they convert it into a charitable donation. So we're actually also linking wellness and feeling good and insurance and some societal goods. So we're really trying to create a virtuous circle of engagement with our customers. >> That's a powerful cocktail. I love it. You've got the data, because if I see the data, then I can change my behavior. You've got the gamification piece. You actually have hard dollar rewards. You could give those to charities and you've got the most important, which is priceless, you can't put a value on good health. I got one more question for Simon and Nils I'd love for you to chime in as well on this question. How did you guys decide, Simon, to engage with Accenture and AWS and the cloud to build out this platform? What's the story behind that collaboration? Was there unique value that you saw that you wanted to tap, that you feel like they bring to the table? What was your experience? >> Yeah, we work with Accenture as well because the sort of constructs of this Vitality proposition is a pretty complex one. So you mentioned that the idea is simple, but the build is not so simple and that's the case. So Accenture has been part of that journey from the beginning. They are one of the partners that we work with, but specifically around the topic of rewards, we're primarily European focused organization, but when you take those countries that I mentioned, even though we're next to each other geographically, we're quite diverse. And what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go get to market with an increasing amounts of efficiency. And to do that, we needed to work with somebody who understood our business, has this historical, let's say investment in the Vitality concepts and so knows how to bring it to life, but then could really support us in making what can be a complex piece of work, as simple, as replicable as possible across multiple markets, because we don't want to go reinventing the wheel every time we knew we moved to a new market. So we need to find a balance between having a consistent product, a consistent technology offer, a consistent customer experience with the fact that we operate in quite diverse markets. So this was, let's say the reason for more deeply engaging with Accenture on this journey. >> Thank you very much, Nils, why don't you comment on that as well? I'd love to get your thoughts and really is kind of your role here, an Accenture global SI, deep expertise in industry, but also technology, what are your thoughts on this topic? >> Yeah, I'd love to love to comment. So when we started the journey, it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets, have a central solution that can act as a template for the different markets, but then also have the opportunity to localize different languages, different partners for the rewards, there's different reward partners in the different markets. So we needed to build an asset basically that could work as a template, centrally standardizing things, but also leaving enough flexibility to then localize in the individual markets. And if we talk about some of the most specific requirements, so one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the, basically the authentication needs to happen. And if we somehow needed to still find a holistic solution that comes through the central platform, and we were able to do that at the end through the AWS cognitive service, sort of wrapping the individual markets, local IDP systems. And by now we've even extended that solution to have a standalone cloud native kind of IDP solution in place for markets that do not have a local IDP solution in place, or don't want to use it for this purpose. >> So you had data, you had the integration, you've got local laws, you mentioned the flexibility, you're building ecosystems that are unique to the local, both language and cultures. Please, you had another comment, I interrupted you. >> No, I just wanted to expand basically on the requirements. So that was the central one being able to roll this out in a standardized way across the markets, but then there were further requirements. For example, like being able to operate the platform with very low operations overhead. There is no large IT team behind Generali Vitality that, works disservice or can act as this backbone support. So we needed to have basically a solution that runs itself that runs on autopilot. And that was another big, big driver for first of all, going to cloud, but second of all, making specific choices within cloud. So we specifically chose to build this as a cloud native solution using for example, managed database services, with automatic backup, with automatic ability to restore data that scales automatically that has all this built in which usually maybe in a database administrator would take care of. And we applied that concept basically to every component, to everything we looked at, we applied this requirement of how can this run on autopilot? How can we make this as much managed by itself within the cloud as possible, and then lend it on these services. For example, we also use the API gateway from AWS for our API services that also came in handy when, for example, we had some response time issues with the third party we needed to call. And then we could just with a flick of a button basically, introduced caching on the level of the API gateway and really improve the user experience because the data wasn't updated so much, so it was easier to cache. So these are all experiences I think that that proved in the end that we made the right choices here and the requirements that drove that to have a good user experience. >> Would you say that the architecture is a sort of a, data architecture specifically, is it a decentralized data architecture with sort of federated, centralized governance? Or is it more of a centralized view, wonder if you could talk about that? >> Yeah, it's actually a centralized platform basically. So the core product is the same for all the markets and we run them as different tenants basically on top of the infrastructure. So the data is separated in a way, obviously by the different tenants, but it's in a central place and we can analyze it in a central fashion if the need arises from the business. >> And the reason I asked that Simon is because essentially I look at this as largely a data offering for your customers. And so Nils, you were talking about the local language and Simon as well. I would imagine that the local business lines have specific requirements and specific data requirements. And so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security. And that's not a trivial challenge. I wonder if you both could comment on that. >> Yeah, maybe I'll give a start and then Simon can chime in. So what we're specifically doing is managing the rewards experience, so our solution will take care of tracking what rewards have been earned for what customer, what rewards have been redeemed, what rewards can be unlocked on the next level, and we foreshadow a little bit to motivate incentivize the customer and asset that data sits in an AWS database by tenant fashion. And you can run analysis on top of that. Maybe what you're getting into is also the, let's say the exercise data, the fitness device tracking data that is not specifically part of what my team has built, but I'm sure Simon can comment a little bit on that angle as well. >> Yeah, please. >> Yeah, sure. I think the topic of data and how we use it in our business is a very interesting one because it's not historically been seen, let's say as the remit of insurance to go beyond the data that you need to underwrite policies or process claims or whatever it might be. But actually we see that this is a whole point around being able to create some shared value in this kind of products. And what I mean by that is, if you are a customer and you're buying an insurance policy, it might be a life insurance or health insurance policy from Generali, and we're not giving you access to this program. And through that program, you are living a healthier life and that might have a positive impact on generosity in terms of, maybe we're going to increase our market share, or maybe we are going through lower claims, or we're going to generate value of that then. One of the points of this program is we then share that value back with customers, through the rewards on the platform that we've built here. And of course, being able to understand that data and to quantify it and to value that data is an important part of the different stages of how much value you are creating. And it's also interesting to know that, in a couple of our markets, we operate in the corporate space. So not with retail customers, but with organizations. And one of the reasons that those companies give Vitality to their employees is that they want to see things like the improved health of a workforce. They want to see higher presenteeism, lower absenteeism of employees, and of course, being able to demonstrate that there's a sort of correlation between participation in the Vitality program and things like that is also important. And as we've said, the markets are very different. So we need to be able to take the data that we have out of the Vitality Program and be able in the company that I'm managing to interpret that data so that in our insurance businesses, we are able to make good decisions about kind of insurance product we have. I think what's interesting to make clear is that actually that the kind of health data that we generate states purely within the Vitality business itself and what we do inside the Vitality business is to analyze that data and say, is this also helping our insurance businesses to drive better top line and bottom line in the relevant business lines? And this is different per company. Being able to interrogate that data, understand it, apply it in different markets, in different distribution systems and different kinds of approaches to insurance is an important one, yes. >> It's an excellent example of a digital business and we talked about digital transformation. What does that mean? This is what it means. It must be really interesting board discussions because you're transforming an industry, you're lowering overall costs. I mean, if people are getting less sick, that's more profit for your company and you can choose to invest that in new products, you can give back some to your corporate clients, you can play that balancing act, you can gain market share. And you've got some knobs to turn, some levers, for your stakeholders, which is awesome. Nils, something that I'm interested in, it must've been really important for you to figure out how to determine and measure success. Obviously it's up to Generali Vitality to get adoption for their customers, but at the same time, the efficacy of your solution is going to determine, the ease of delivery and consumption. So, how did you map to the specific goals? What were some of the key KPIs in terms of mapping to their aggressive goals. >> Besides the things we already touched on, I think one thing I would mention is the timeline. So, we started the team ramping in January, February, and then within six months basically, we had the solution built and then we went through a extensive test phase. And within the next six months we had the product rolled out to three markets. So this speed to value, speed to market that we were able to achieve, I think is one of the key criteria that also Simon and team gave to us. There was a timeline and that time I was not going to move. So we needed to make a plan, adjust to that timeline. And I think it's both a testament to the team's work that we met this timeline, but it also is enabled by a technology stack cloud. I have to say, if I go back five years, 10 years, if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally, there would've been no way to do this in 12 months, that's for sure. >> Yeah, Simon, you're a technology company. I mean, insurance has always been a tech heavy company, but as Nils just mentioned, if you had to do that with IT departments in each region. So my question is now you've got this, it's almost like nonrecurring engineering costs, it took one year to actually get the first one done, how fast are you able to launch into new markets just from a technology perspective, not withstanding local regulations and figuring out the go to market? Is that compressed? >> So you asked specifically technology-wise I think we would be able to set up a new market, including localizations that often involves translation of, because in Europe you have all the different languages and so on, I would say four to six weeks, we probably could stand up a localized solution. In reality, it takes more like six to nine months to get it rolled out because there's many other things involved, obviously, but just our piece of the solution, we can pretty quickly localize it to a new market. >> But Simon, that means that you can spend time on those other factors, you don't have to really worry so much about the technology. And so you've launched in multiple European markets, what do you see for the future of this program? Come to America. >> You can find that this program in America Dave, but with one of our competitors, we're not operating so much in the US, but you can find it if you want to become a customer for sure. But yes, you're right. I think from our perspective, to put this kind of business into a new market is not an easy thing because what we're doing is not offering it just as a service on a standalone basis to customers, we want to link it with insurance business. In the end, we are an insurance business, and we want to see the value that comes from that. So there's a lot of effort that has to go into making sure that we land it in the right way, also from a customer proposition points of view with our distribution, they are all quite different. Coming to the question of what's next? It comes in three stages for me. So as I mentioned, we are in five markets already. In the first half of 2022, we'll also come to the Czech Republic and Poland, which we're excited to do. And that will basically mean that we have this business in the seven main Generali markets in Europe related to life and health business, which is the most natural at let's say fit for something like Vitality. Then, the sort of second part of that is to say, we have a program that is very heavily focused around activity and rewards, and that's a good place to start, but, wellness these days is not just about, can you move a bit more than you did historically, it's also about mental wellbeing, it's about sleeping good, it's about mindfulness, it's about being able to have a more holistic approach to wellbeing and COVID has taught us, and customer feedback has taught is actually that this is something where we need to go. And here we need to have the technology to move there as well. So to be able to work with partners that are not just based on physical activity, but also on mindfulness. So this is how one other way we will develop the proposition. And I think the third one, which is more strategic and we are really looking into is, there's clearly something in the whole perception of incentives and rewards, which drives a level of engagement between an insurer like Generali and its customers that it hasn't had historically. So I think we need to learn, forgetting about the specific one or Vitality being a wellness program, but if there's an insurer, there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that. And it creates value for us as an insurer, then this is probably a place that we'd want to investigate more. And to be able to do that in other areas means we need to have the technology available, that is, as I said before, replicable faster market can adapt quickly to other ideas that we have, so we can go and test those in different markets. So yes, we have to, we have to complete our scope on Vitality, We have to get that to scale and be able to manage all of this data at scale, all of those rewards that real scale, and to have the technology that allows us to do that without thinking about it too much. And then to say, okay, how do we widen the proposition? And how do we take the concept that sits behind Vitality to see if we can apply it to other areas of our business. And that's really what the future is going to look like for us. >> The isolation era really taught us that if you're not a digital business, you're out of business, and pre COVID, a lot of these stories were kind of buried, but the companies that have invested in digital are now thriving. And this is an awesome example, and another point is that Jeff Hammerbacher, one of the founders of Cloudera, early Facebook employee, famously said about 10, 12 years ago, "The best and greatest engineering minds of my generation are trying to figure out how to get people to click on ads." And this is a wonderful example of how to use data to change people's lives. So guys, congratulations, best of luck, really awesome example of applying technology to create an important societal outcome. Really appreciate your time on theCUBE. Thank you. >> Bye-bye. >> All right, and thanks for watching this segment of theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. Keep it right there for more deep dives. (upbeat music)

>>Hello and welcome to the power of and where H P E Aruba and Pensando are changing the game the way customers scale at the cloud and what's next in the evolution in switching everyone. I'm john ferrier with the Cuban. I'm here with Shane Corbyn, Director of Technical Product management. Pensando Williams show vice president Product management, Aruba HP Gentlemen, thank you for coming on and doing a deep dive and and going into the big news. So the first question I want to ask you guys is um, what do you guys see from a market customer perspective that kicked this project off? Amazing results over the past year or so. Where did it all come from? >>It's a great question, John So when we were doing our homework, there were actually three very clear customer challenges. First, security threats were largely spawned with from within the perimeter. In fact, four star highlights that 80% of threats originate within the internal network. Secondly, workloads are largely distributed, creating a ton of east west traffic and then lastly, network services such as firewalls load balancers. VPN aggregators are expensive. They're centralized and then ultimately result in service changing complexity. So everyone, >>so go ahead. Change. >>Yeah. Additionally, when we spoke to our customers after launching initially the distributed services platform, these compliance challenges clearly became apparent to us and while they saw the architectural value of adopting what the largest public cloud providers have done by putting a smart making each compute note to provide these state full services. Enterprise customers were still were struggling with the need to upgrade fleets and Brownfield servers and the associated per node cost of adding a spark nick to every compute node. Typically the traffic volumes for on a personal basis within an enterprise data center are significantly lower than cloud. Thus we saw an opportunity here to in conjunction with Aruba developed a new category of switching product um, to share the crossing capabilities of our unique intellectual property around our DPU across a rack of servers that Net Net delivers the same set of services through a new category of platform, enabling a distributed services architecture and ultimately addressing the compliance and uh, TCO generating huge TCO and ri for customers. >>You know, one of the things that we've been reporting on with you guys as well as the cloud scale, this is the volume of data and just the performance and scale I think the timing of the, of this partnership and the product development is right on point. You got the edge right around the corner more, more distributed nature of cloud operations, huge, huge change in the marketplace. So great timing on the origination story there. Great stuff. Tell me more about the platform itself. The details what's under the hood, the hardware. Os, what are the specs? >>Yeah, so we started with a very familiar premise, Ruba customers are already leveraging C X with an edge to cloud, common operating model and deploying Leaf and spy networks. Plus we're excited to introduce the industry's first distributed services switch where the first configuration has 48 25 gig ports with 100 gig uplinks running Aruba C X cloud native operating system. Pensando A six and software inside enabling layer four through seven staple services you want to elaborate on. >>Let me elaborate on that a little further. Um, you know, as we spoke, existing platforms and how customers were seeking to address these challenges were inherently limited by the diocese and that thus limited their scale and performance and ability in traditional switching platforms to deliver truly stable functions in in a switching platform. This was, you know, architecturally from the ground up. When we developed our DPU 1st and 2nd generation, we delivered it or we we we built it with staples services in in mind from the Gecko. We we leverage to clean state designed with RP four program with GPU, we evolved to our seven nanometer based DPU right now, which is essentially enabling software and silicon and this has generated a new level of performance scale flexibility and capability in terms of services this serves as the foundation for or 200 gig card where we're taking the largest cloud providers into production for. And the DPU itself is designed inherently to process state track state connections and state will flow is a very, very large scale without impacting performance. And in fact, the two of these deep you component service, their services foundation of the C X 10-K And this is how we enable states of functions in a switching platform. Functions like stable network network fire walling, stable segmentation, enhance programmable telemetry. Which we believe will bring a whole lot of value to our customers. And this is a, a platform that's inherently programmable from the ground up. We can we can build and and leverages platform to build new use cases around encryption, enabling state for load balancing, stable nash to name a few. But the key message here is this is this is a platform with the next generation of architecture is in mind is programmed but at all levels of the stack and that's what makes it fundamentally different than anything else. >>I want to just double click on that if you don't mind before we get to the competitive question because I think you brought up the state thing, I think this is worth calling out if you guys don't mind commenting more on this state issue because this is big cloud. Native developers right now want speed, they're shifting left at the Ci cd pipeline with program ability. So going down and having the program ability and having state is a really big deal. Can you guys just expand on that a little bit more and why it's important and how hard it really is to pull off. >>I I can start I guess. Well um it's very hard to pull off because of the sheer amount of connections you need to track when you're developing something like a state, full firewall or state from load balancer. A key component of that is managing the connections at very, very large scale and understanding what's happening with those connections at scale without impacting application performance. And this is fundamentally different. A traditional switching platform regardless of how it's deployed today in a six don't typically process and manage state like this. Memory resources within the shape aren't sufficient. Um the policy scale that you can implement on a platform aren't sufficient to address and fundamentally enable deployable fire walling or load balancing or other state services. >>That's exactly right. So the other kind of key point here is that if you think about the sophistication of different security threats, it does really require you to be able to look at the entire packet and more so be able to look at the entire flow and be able to log that history so that you can get much better heuristics around different anomalies. Security threats that are emerging today. >>That's a great great point. Thanks for bringing that extra extra point out, I would just add to this, we're reporting this all the time when silicon angle in the cube is that you know, the you know, the the automation wave that's coming with around data, you know, it's the center of data now, not date as soon as we heard earlier on with the presentation data drives automation having that enabled with state is a real big deal. So I think that's really worth calling out now. I got to ask the competition question, how is this different? I mean this is an evolution, I would say it's a revolution you guys are being humble um but how is this different from what customers can deploy today >>architecturally, if you take a look at it? So we've, we've spoken about the technology and fundamentally in the platform, what's unique in the architecture but foundational e when customers deploy stable services, they're typically deployed leveraging traditional big box appliances for east west or workload based agents which seek to implement stable security for each East west architectural, what we're enabling is staples services like fire walling, segmentation can scale with the fabric and are delivered at the optimal point for east west which is through the Leaf for access their of the network and we do this for any type of workload. Being deployed on a virtualized compute node being deployed on a containerized, our worker node being deployed on bare metal agnostic of topology. It can be in the access layer of a three tier design and a data center. It can be in the leaf layer of the excellent VPN based fabric. But the goal is an all centrally managed to a single point of orchestration control which William we'll talk about shortly. The goal of this is to to drive down the TCO of your data center as a whole by allowing you to retire legacy appliances that are deployed in in east west role, not utilized host based agents and thus save a whole lot of money. And we've modeled on the order of 60 to 70% in terms of savings in terms of the traditional data center pod design of 1000 compute nodes which will be publishing and as as we go forward, additional services as we mentioned like encryption, this platform has the capability to terminate up to 800 gigs of line, right encryption, I P sec VPN per platform state will not load balancing and this is all functionality will be adding to this existing platform because it's programmable as we mentioned from the ground up. >>What are some of the use cases lead and one of the top use case. What's the low hanging fruit? And where does this go? Service providers enterprise, what are the types of customers you guys see implementing? >>Yeah, that's what's really exciting about the C X 10,000 we actually see customer interest from all types of different markets, whether it be higher education service providers to financial services, basically all enterprises verticals with private cloud or edge data centers for example, could be a hospital, a big box retailer or Coehlo. Such as an equity. It's so it's really the 6 10,000 that creates a new switching category enabling staple services in that leaf node, right at the workload, unifying network and security automation policy management. Second, the C X 10,000 greatly improved security posture and eliminates the need for hair pinning east west traffic all the way back to the centralized plants. Lastly, a Shane highlighted there's a 70% Tco savings by eliminating that appliance brawl and ultimately collapsing the network security operations. >>I love the category creation vibe here. Love it. And obviously the technical and the cloud line is great. But how do the customers manage all this? Okay. You got a new category. I just put the box in, throw away some other one. I mean how does this all get down? How does the customers manage all this? >>Yeah. So we're looking to build on top of the ribbon fabric composer. It's another familiar sight for our customers which already provides for compute storage and network automation with a broad ecosystem integrations such as being where the sphere be center as with Nutanix prison And so aligned with the c. x. 10,000 at G. A. now the aruba fabric composer unifies security and policy orchestration and management with the ability to find firewall policies efficiently and provide that telemetry to collectors such a slump. >>So the customer environments right now involve a lot of multi vendor and new frameworks cloud native. How does this fit into the customer's existing environment? The ecosystem. How do they get that get going here? >>Yeah, great question. Um our customers can get going is we we built a flexible platform that can be deployed in either Greenfield or brownfield. Obviously it's a best of breed architecture for distributed services were building in conjunction with the ruble but if customers want to gradually integrate this into their existing environments and they're using other vendors, spines or course this can be inserted seamlessly as a leaf or an access access to your switch to deliver the exact same set of services within that architecture. So it plugs seamlessly in because it supports all the standard control playing protocols, VX, Lenny, VPN and traditional attitude three tier designs easily. Now for any enterprise solution deployment, it's critical that you build a holistic ecosystem around it. It's clear that this will get customer deployments and the ecosystem being diverse and rich is very, very important and as part of our integrations with the controller, we're building a broad suite of integrations across threat detection application dependency mapping, Semen sore develops infrastructure as code tools like ants, Poland to answer the entire form. Um, it's clear if you look at these categories of integrations, you know XDR or threat detection requires full telemetry from within the data center. It's been hard to accomplish to date because you typically need agents on, on your compute nodes to give you the visibility into what's going on or firewalls for east west flaws. Now our platform can natively provide full visibility in dolphins, East west in the data center and this can become the source of telemetry truth that these Ml XT or engines required to work. The other aspects of ecosystem are around application dependency mapping the single core challenge with deploying segmentation. East West is understanding the rules to put in place right first, is how do you insert the service uh service device in such a way that it won't add more complexity. We don't add any complexity because we're in line natively. How do we understand that allow you to build the rules are necessary to do segmentation. We integrate with tools like guard corps, we provide our flow logs a source of data and they can provide rural recommendations and policy recommendations for customers around. We're building integrations around steve and soar with tools like Splunk and elastic elastic search that will allow net hops and sec ops teams to visualize, train and manage the services delivered by the C X 10-K. And the other aspect of ecosystem from a security standpoint is clearly how do I get policy from these traditional appliances and enforce them on this next generation architecture that you've built that can enable state health services. So we're building integrations with tools like toughen analgesic third party sources of policy that we can ingest and enforcing the infrastructure allowing you to gradually migrate to this new architecture over time >>it's really a cloud native switch, you solve people's problems pain points but yet positioned for growth. I mean it sounds that's my takeaway. But I gotta ask you guys both what's the takeaway for the customers because it's not that simple for that. We have a complicated >>Environment. I think, I think it's really simple every 10 years or so. We see major evolutions in the data center in the switching environment. We do believe we've created a new category with the distributed services, distributed services, switch, delivering cloud scale distribute services where the local where the workloads were side greatly simplifying network security provisions and operations with the Yoruba fabric composer while improving security posture and the TCO. But that's not all folks. It's a journey. Right. >>Yeah, it's absolutely a journey. And this is the first step in in a long journey with a great partner like Aruba, there's other platforms, 100 or four gig hardware platforms we're looking at and then there's additional services that we can enable over time allowing customers to drive even more Tco value out of the platform and the architectural services like encryption for securing the cloud on ramp services like state for load balancing to deploy east west in the data center and you know, holistically that's that's the goal, deliver value for customers and we believe we have an architecture and a platform and this is the first step in a long journey. It's >>a great way. I just ask one final final question for both of you. As product leaders, you've got to be excited having a category creation product here in this market, this big wave. What's what's your thoughts? >>Yeah, exactly. Right. It doesn't happen that often. And so we're all in, it's it's exciting to be able to work with a great team like Sandu and chain here. And so we're really excited about this launch. >>Yeah, it's awesome. The team is great. It's a great partnership between and santo and Aruba and you know, we we look forward to delivering value for john customers. >>Thank you both for sharing under the hood and more details on the product. Thanks for coming on. >>Thank you. Okay, >>the next evolution of switching, I'm john furrier here with the power of An HP, Aruba and Pensando, changing the game the way customers scale up in the cloud and networking. Thanks for watching. Mhm.

>> Hello everyone. And thanks for joining us today. My name is Brent Biddulph, managing director retail, consumer goods here at Cloudera. Cloudera is very proud to be partnering with companies like 3Soft to provide data and analytic capabilities for over 200 retailers across the world and understanding why demand forecasting could be considered the heartbeat of retail. And what's at stake is really no mystery to most retailers. And really just a quick level set before handing this over to my good friend, Kamil at 3Soft. IDC, Gartner, many other analysts kind of summed up an average here that I thought would be important to share just to level set the importance of demand forecasting in retail, and what's at stake, meaning the combined business value for retailers leveraging AI and IOT. So this is above and beyond what demand forecasting has been in the past, is a $371 billion opportunity. And what's critically important to understand about demand forecasting is it directly impacts both the top line and the bottom line of retail. So how does it affect the top line? Retailers that leverage AI and IOT for demand forecasting are seeing average revenue increases of 2% and think of that as addressing the in stock or out of stock issue in retail and retail is become much more complex now, and that it's no longer just brick and mortar, of course, but it's fulfillment centers driven by e-commerce. So inventory is now having to be spread over multiple channels. Being able to leverage AI and IOT is driving 2% average revenue increases. Now, if you think about the size of most retailers or the average retailer that, on its face is worth millions of dollars of improvement for any individual retailer. On top of that is balancing your inventory, getting the right product in the right place, and having productive inventory. And that is the bottom line. So the average inventory reduction, leveraging AI and IOT as the analysts have found, and frankly, having spent time in this space myself in the past a 15% average inventory reduction is significant for retailers, not being overstocked on product in the wrong place at the wrong time. And it touches everything from replenishment to out-of-stocks, labor planning, and customer engagement. For purposes of today's conversation, we're going to focus on inventory and inventory optimization and reducing out-of-stocks. And of course, even small incremental improvements. I mentioned before in demand forecast accuracy have millions of dollars of direct business impact, especially when it comes to inventory optimization. Okay. So without further ado, I would like to now introduce Dr. Kamil Volker to share with you what his team has been up to, and some of the amazing things are driving at top retailers today. So over to you, Kamil. >> I'm happy to be here and I'm happy to speak to you about what we deliver to our customers, but let me first introduce 3Soft. We are a 100 person company based in Europe, in Southern Poland, and we, with 18 years of experience specialized in providing what we call a data driven business approach to our customers. Our roots are in the solutions in the services. We originally started as a software house. And on top of that, we build our solutions. We've been automation that you get the software for biggest enterprises in Poland, further, we understood the meaning of data and data management and how it can be translated into business profits. Adding artificial intelligence on top of that makes our solutions portfolio holistic, which enables us to realize very complex projects, which leverage all of those three pillars of our business. However, in the recent time, we also understood the services is something which only the best and biggest companies can afford at scale. And we believe that the future of retail demand forecasting is in the product solutions. So that's why we created Occubee, our AI platform for data driven retail that also covers this area that we talked about today. I'm personally proud to be responsible for our technology partnerships with Cloudera and Microsoft. It's a great pleasure to work with such great companies and to be able to deliver the solutions to our customers together based on a common trust and understanding of the business, which cumulates at customer success at the end. So why should we analyze data at retail? Why is it so important? It's kind of obvious that there is a lot of potential in the data per se, but also understanding the different areas where it can be used in retail is very important. We believe that thanks to using data, it's basically easier to derive the good decisions for the business based on the facts and not intuition anymore. Those four areas that we observed in retail, our online data analysis, that's the fastest growing sector, let's say for those data analytics services, which is of course based on the econ and online channels, availability to the customer. Pandemic only speeds up this process of engagement of the customers in that channel, of course, but traditional offline, let's say brick and mortar shops. They still play the biggest role for most of the retailers, especially from the FMCG sector. However, it's also very important to remember that there is plenty of business related questions that need to be answered from the headquarter perspective. So is it actually good idea to open a store in a certain place? Is it a good idea to optimize a stock in a certain producer? Is it a good idea to allocate the goods to online channel in specific way, those kinds of questions, they need to be answered in retail every day. And with that massive amount of factors coming into the equation, it's really not that easy to base only on the integration and expert knowledge. Of course, as Brent mentioned at the beginning, the supply chain and everything who's relates to that is also super important. We observe our customers to seek for the huge improvements in the revenue, just from that one single area as well. So let me present you a case study of one of our solutions, and that was the lever to a leading global grocery retailer. The project started with the challenge set of challenges that we had to conquer. And of course the most important was how to limit overstocks and out of stocks. That's like the holy grail in retail, of course, how to do it without flooding the stores with the goods. And in the same time, how to avoid empty shelves. From the perspective of the customer, it was obvious that we need to provide a very well, a very high quality of sales forecast to be able to ask for what will be the actual sales of the individual product in each store every day, considering huge role of the perishable goods in the specific grocery retailer, it was a huge challenge to provide a solution that was able to analyze and provide meaningful information about what's there in the sales data and the other factors we analyzed on daily basis at scale, however, our holistic approach implementing AI with data management background and these automation solutions all together created a platform that was able to significantly increase the sales for our customer just by minimizing out of stocks. In the same time, we managed to not overflood the stock, the shops with the goods, which actually decreased losses significantly, especially on the fresh fruit. Having said that, these results, of course translate into the increase in revenue, which can be calculated in hundreds of millions of dollars per year. So how the solution actually works? Well in its principle, it's quite simple. We just collect the data. We do it online, we put that in our data, like based on the cloud, through other technology, we implement our artificial intelligence models on top of it. And then based on the aggregated information, we create the forecast and we do it every day or every night for every single product in every single store. This information is sent to the warehouses and then the automated replenishment based on the forecast is on the way. The huge and most important aspect of that is the use of the good tools to do the right job. Having said that, you can be sure that there is too many information in this data. And there is actually two-minute forecast created every night than any expert could ever check. This means our solution needs to be very robust. It needs to provide information with high quality and high veracity. There is plenty of different business process, which is based on our forecast, which need to be delivered on time for every product in each individual shop. Observing the success of this project and having the huge market potential in mind, we decided to create our Occubee, which can be used by many retailers who don't want to create a dedicated software that will be solving this kind of problem. Occubee is our software service offering, which is enabling retailers to go data driven path management. We create Occubee with retailers for retailers, implementing artificial intelligence on top of data science models created by our experts. Having data analysis in place based on data management tools that we use, we've written first attitude. The uncertain times of pandemic clearly shows that it's very important to apply correction factors, which are sometimes required because we need to respond quickly to the changes in the sales characteristics. That's why Occubee is open box solution, which means that you basically can implement that in your organization, without changing the process internally. It's all about mapping your process into the system, not the other way around. The fast trends and products collection possibilities allow the retailers to react to any changes, which occur in the sales every day. Also, it's worth to mention that really it's not only FMCG and we believe that different use cases, which we observe in fashion, health and beauty, home and garden, pharmacies, and electronics, flavors of retail are also very meaningful. They also have one common thread. That's the growing importance of e-commerce. That's why we didn't want to leave that aside of Occubee. And we made everything we can to implement a solution, which covers all the needs. When you think about the factors that affect sales, there is actually huge variety of data that we can analyze. Of course, the transactional data that every dealer possesses, like sales data from sale from stores, from e-commerce channel, also averaging numbers from weeks, months, and years makes sense, but it's also worth to mention that using the right tool that allows you to collect that data from also internal and external sources makes perfect sense for retail. It's very hard to imagine a competitive retailer that is not analyzing the competitor's activity, changes in weather or information about some seasonal stores, which can be very important during the summer and other holidays, for example. But on the other hand, having this information in one place makes the actual benefit and environment for the customer. Demand forecasting seems to be like the most important and promising use case. We can talk about when I think about retail, but it's also the whole process of replenishment that can cover with different sets of machine learning models, and data management tools. We believe that analyzing data from different parts of the retail replenishment process can be achieved with implementing a data management solution based on Cloudera products and with adding some AI on top of it, it makes perfect sense to focus on not only demand forecasting, but also further use cases down the line. When it comes to the actual benefits from implementing solutions for demand management, we believe it's really important to analyze them holistically first it's of course, out of stock minimization, which can be provided by simply better size focus, but also reducing overstocks by better inventory management can be achieved by us in the same time. Having said that, we believe that analyzing data without any specific new equipment required in point of sales is the low hanging fruit that can be easily achieved in almost every industry, in almost every regular customer. >> Hey, thanks, Kamil. Having worked with retailers in this space for a couple of decades, myself, I was really impressed by a couple of things and they might've been understated, frankly, the results of course. I mean, as I kind of set up this session, you doubled the numbers on the statistics that the analysts found. So obviously in customers, you're working with... you're doubling average numbers that the industry overall is having, and most notably how the use of AI or Occubee has automated so many manual tasks of the past, like tour tuning, item profiles, adding new items, et cetera, and also how quickly it felt like, and this is my core question. Your team can cover or provide the solution to not only core center store, for example, in grocery, but you're covering fresh products. And frankly, there are solutions out on the market today that only focus on center store non-perishable departments. I was really impressed by the coverage that you're able to provide as well. So can you articulate kind of what it takes to get up and running and your overall process to roll out the solution? I feel like based on what you talked about and how you were approaching this in leveraging AI, that you're streamlining processes of legacy, demand, forecasting solutions that required more manual intervention, how quickly can you get people set up? And what is the overall process of like to get started with this software? >> Yeah, usually, it takes three to six months to onboard a new customer to that kind of solution. And frankly, it depends on the data that the customer has. Usually it's different for smaller, bigger companies, of course, but we believe that it's very important to start with a good foundation. The platform needs to be there, the platform that is able to basically analyze or process different types of data, structured, unstructured, internal, external, and so on. But when you have this platform set is all about starting ingesting data there. And usually for a smaller companies, it's easier to start with those, let's say, low hanging fruits. So the internal data, which is there, this data has the highest veracity. It's all really easy to start with, to work with them because everyone in the organization understands this data. For the bigger companies it might be important to ingest also kind of more unstructured data, some kind of external data that need to be acquired. So that may influence the length of the process. But we usually start with the customers with workshops. That's very important to understand the reasons because not every deal is the same. Of course, we believe that the success of our customers comes also due to the fact that we train those models, those AI models individually to the needs of our customers. >> Totally understand. And POS data, every retailer has right in, in one way shape or form. And it is the fundamental data point, whether it's e-comm or the brick and mortar data, every retailer has that data. So, that totally makes sense. But what you just described was months, there are legacy and other solutions out there, that this could be a year or longer process to roll out to the number of stores, for example, that you're scaling to. So that's highly impressive. And my guess is a lot of the barriers that have been knocked down with your solution are the fact that you're running this in the cloud. from a compute standpoint on Cloudera from a public cloud stamp point on Microsoft. So there's no IT intervention, if you will, or hurdles in preparation to get the database set up and all of the work. I would imagine that part of the time savings to getting started, would that be an accurate description? >> Yeah, absolutely. In the same time, this actually lowering the business risks because we see the same data and put that into the data lake, which is in the cloud. We did not interfere with the existing processes, which are processing this data in the combined. So we just use the same data. We just already in the company, we ask some external data if needed, but it's all aside of the current customers infrastructure. So this is also a huge gain, as you said. >> Right. And you're meeting customers where they are, right? So as I said, foundationally, every retailer POS data, if they want to add weather data or calendar event data, or, one incorporated course online data with offline data, you have a roadmap and the ability to do that. So it is a building block process. So getting started with core data as with POS online or offline is the foundational component, which obviously you're very good at. And then having that ability to then incorporate other data sets is critically important because that just improves demand forecast accuracy, right. By being able to pull in those, those other data sources, if you will. So Kamil, I just have one final question for you. There are plenty of... not plenty, but I mean, there's enough demand forecasting solutions out on the market today for retailers. One of the things that really caught my eye, especially being a former retailer and talking with retailers was the fact that you're promoting an open box solution. And that is a key challenge for a lot of retailers that have seen black box solutions come and go. And especially in this space where you really need direct input from the customer to continue to fine tune and improve forecast accuracy. Could you give just a little bit more of a description or response to your approach to open box versus black box? >> Yeah, of course. So, we've seen in the past the failures of the projects based on the black box approach, and we believe that this is not the way to go, especially with this kind of, let's say specialized services that we provide in meaning of understanding the customer's business first and then applying the solution, because what stands behind our concept in Occubee is the, basically your process in the organization as a retailer, they have been optimized for years already. That's where retailers put their focus for many years. We don't want to change that. We are not able to optimize it properly for sure as IT combined, we are able to provide you a tool which can then be used for mapping those very well optimized process and not to change them. That's our idea. And the open box means that in every process that you will map in the solution, you can then in real time monitor the execution of those processes and see what is the result of every step. That way, we create truly explainable experience for our customers, then can easily go for the whole process and see how the forecast was calculated. And what is the reason for a specific number to be there at the end of the day? >> I think that is invaluable. (indistinct) I really think that is a differentiator and what 3Soft is bringing to market. With that, thanks everyone for joining us today. Let's stay in touch. I want to make sure to leave Kamil's information here. So reach out to him directly, or feel free at any point in time obviously to reach out to me. Again, so glad everyone was able to join today, look forward to talking to you soon.

>>Thank you and good morning or afternoon, everyone, depending on where you're coming to us from and welcome to today's breakout session, fast data, a retail industry business imperative. My name is Brent Bedell, global managing director of retail, consumer bids here at Cloudera and today's hosts joining today. Joining me today is our feature speaker Brian Hill course managing partner from RSR. We'll be sharing insights and implications from recently completed research across retailers of all sizes in vertical segments. At the end of today's session, I'll share a brief overview on what I personally learned from retailers and how Cloudera continues to support retail data analytic requirements, and specifically around streaming data, ingest analytics, automation for customers around the world. There really is the next step up in terms of what's happening with data analytics today. So let's get started. So I thought it'd be helpful to provide some background first on how Clare to Cloudera is supporting and retail industry leaders specifically how they're leveraging Cloudera for leading practice data analytics use cases primarily across four key business pillars. >>And these will be very familiar to, to those in the industry. Personalize interactions of course, plays heavily into e-commerce and marketing, whether that's developing customer profiles, understanding the OB omni-channel journey, moving into the merchandising line of business focused on localized promotional planning, forecasting demand, forecast accuracy, then into supply chain where inventory visibility is becoming more and more critical today, whether it's around fulfillment or just understanding where your stuff is from a customer perspective. And obviously in and outbound route optimization right now, as retailers are taking control of actual delivery, whether it's to a physical store location or to the consumer. And then finally, uh, which is pretty exciting to me as a former store operator, you know, what's happening with physical brick and mortar right now, especially for traditional retailers. Uh, the whole re-imagining of stores right now is on fire in a lot of focus because, you know, frankly, this is where fulfillment is happening. >>Um, this is where customers, you know, still 80% of revenue is driven through retail, through physical brick and mortar. So right now store operations is getting more focused and I would say it probably is had and decades. Uh, and a lot of has to do for us with IOT data and analytics in the new technologies that really help, uh, drive, uh, benefits for retailers from a brick and mortar standpoint. And then, and then finally, um, you know, to wrap up before handing off to Brian, um, as you'll see, you know, all of these, these lines of businesses are raw, really experiencing the need for speed, uh, you know, fast data. So we're, we're moving beyond just discovery analytics. You don't things that happened five, six years ago with big data, et cetera. And we're really moving into real time capabilities because that's really where the difference makers are. >>That's where the competitive differentiation as across all of these, uh, you know, lines of business and these four key pillars within retail, um, the dependency on fast data is, is evident. Um, and it's something that we all read, you know, you know, in terms of those that are students of the industry, if you will, um, you know, that we're all focused on in terms of bringing value to the individual, uh, lines of business, but more importantly to the overall enterprise. So without further ado, I, I really want to, uh, have Brian speak here as a, as a third party analyst. You know, he, he's close in touch with what's going on, retail talking to all the solution providers, all the key retailers about what's important, what's on their plate. What are they focusing on right now in terms of fast data and how that could potentially make a difference for them going forward? So, Brian, uh, off to you, >>Well, thanks, Brent. I appreciate the introduction. And I was thinking, as you were talking, what is fast data? Well, data is fast. It is fast data it's stuff that comes at you very quickly. When I think about the decision cycles in retail, they were, they were, they were time phased and there was a time when we could only make a decision perhaps once a month and then met once a week and then once a day, and then intraday fast data is data that's coming at you and something approaching real time. And we'll explain why that's important in just a second. But first I want to share with you just a little bit about RSR. We've been in business now for 14 years. And what we do is we studied the business use cases that drive the adoption of technology in retail. We come from the retail industry, I was a retail technologist, my entire working life. >>And so we started this company. So I'm, I have a built in bias, of course, and that is that the difference between the winners in the retail world and in fact, in the entire business world and everybody else is how they value the strategic importance of information, and really that's where the battle is being fought today. We'll talk a little bit about that. So anyway, uh, one other thing about RSR research, our research is free to the entire world. Um, we don't, we don't have a paywall. You have to get behind. All you have to do is sign into our website, uh, identify yourself and all of our research, including these two reports that we're showing on the screen now are available to you. And we'd love to hear your comments. So when we talk about data, there's a lot of business implications to what we're trying to do with fast data and as being driven by the real world. >>Uh, we saw a lot of evidence of that during the COVID pandemic in 2020, when people had to make many decisions very, very quickly, for example, a simple one. Uh, do I redirect my replenishments to store B because store a is impacted by the pandemic, those kinds of things. Uh, these two drawings are actually from a book that came out in 1997. It was a really important book for me personally is by a guy named Steven Hegel. And it was the name of the book was the adaptive enterprise. When you think about your business model, um, and you think about the retail business model, most of those businesses are what you see on the left. First of all, the mission of the business doesn't change much at all. It changes once in a generation or maybe once in a lifetime, um, but it it's established quite early. >>And then from that point on it's, uh, basically a wash rinse and repeat cycle. You do the things that you do over and over and over again, year in and year out season in and season out. And the most important piece of information that you have is the transaction data from the last cycle. So a Brent knows this from his experience as a, as a retailer, the baseline for next year's forecast is last year's performance. And this is transactional in nature. It's typically pulled from your ERP or from your best of breed solution set on the right is where the world is really going. And before we get into the details of this, I'll just use a real example. I'm I'm sure like, like me, you've watched the path of hurricanes as they go up to the Florida coast. And one of the things you might've noticed is that there's several different possible paths. >>These are models, and you'll hear a lot about models. When you talk to people in the AI world, these are models based on lots and lots of information that they're getting from Noah and from the oceanographic people and all those kinds of folks to understand the likely path of the hurricane, based on their analysis, the people who watch these things will choose the most likely paths and they will warn communities to lock down and do whatever they need to do. And then they see as the, as the real hurricane progresses, they will see if it's following that path, or if it's varying, it's going down a different path and based on that, they will adapt to a new model. And that is what I'm talking about here now that not everything is of course is life and death as, as a hurricane. But it's basically the same concept what's happening is you have your internal data that you've had since this, a command and control model that we've mentioned on the left, and you're taking an external data from the world around you, and you're using that to make snap decisions or quick decisions based on what you see, what's observable on the outside, back to my COVID example, um, when people were tracking the path of the pandemic through communities, they learn that customers or consumers would favor certain stores to pick up their, what they needed to get. >>So they would avoid some stores and they would favor other stores. And that would cause smart retailers to redirect the replenishments on very fast cycles to those stores where the consumers are most likely to be. They also did the same thing for employees. Uh, they wanted to know where they could get their employees to service these customers. How far away were they, were they in a community that was impacted or were they relatively safe? These are the decisions that were being made in real time based on the information that they were getting from the marketplace around them. So, first of all, there's a context for these decisions. There's a purpose and the bounds of the adaptive structure, and then there's a coordination of capabilities in real time. And that creates an internal feedback loop, but there's also an external feedback loop. This is more of an ecosystem view. >>And based on those two, those two inputs what's happening internally, what your performance is internally and how your community around you is reacting to what you're providing. You make adjustments as necessary. And this is the essence of the adaptive enterprise. Engineers might call this a sense and respond model. Um, and that's where retail is going. But what's essential to that is information and information, not just about the products that you sell or the stores that you sell it in, or the employees that you have on the sales floor or the number of market baskets you've completed in the day, but something much, much more. Um, if you will, a twin, a digital twin of the physical assets of your business, all of your physical assets, the people, the products, the customers, the buildings, the rolling stock, everything, everything. And if you can create a digital equivalent of a physical thing, you can then analyze it. >>And if you can analyze it, you can make decisions much, much more quickly. So this is what's happening with the predict pivot based on what you see, and then, because it's an intrinsically more complicated model to automate, decision-making where it makes sense to do so. That's pretty complicated. And I talk about new data. And as I said earlier, the old data is all transactional in nature. Mostly about sales. Retail has been a wash in sales data for as long as I can remember throw, they throw most of it away, but they do keep enough to create the forecast the next for the next business cycle. But there's all kinds of new information that they need to be thinking about. And a lot of this is from the outside world. And a lot of this is non-transactional nature. So let's just take a look at some of them, competitive information. >>Those are always interested in what the competitor is up to. What are they promoting? How well are they they doing, where are they? What kind of traffic are they generating sudden and stuff, significant changes in customer behaviors and sentiment COVID is a perfect example of something that would cause this consumers changing their behaviors very quickly. And we have the ability to, to observe this because in a great majority of cases, nowadays retailers have observed that customers start their, uh, shopping journey in the digital space. As a matter of fact, Google recently came out and said, 60%, 63% of all, all sales transactions begin in the digital domain. Even if many of them end up in the store. So we have the ability to observe changes in consumer behavior. What are they looking at? When are they looking at it? How long do they spend looking at it? >>What else are they looking at while they're, while they're doing that? What are the, what is the outcome of that market metrics? Certainly what's going on in the marketplace around you? A good idea. Example of this might be something related to a sporting event. If you've planned based on normal demand and for, for your store. And there's a big sporting event, like a football match or a baseball game, suddenly you're going to see a spike in demand. So understanding what's going on in the market is really important. Location, demographics and psychographics, demographics have always been important to retailers, but now we're talking about dynamic demographics, what customers, or what consumers are, are in your market, in something approaching real time, psychographics has more to do with their attitudes. What kind of folks are, are, are in them in a particular marketplace? What do they think about what do they favor? >>And all those kinds of interesting deep tales, real-time environmental and social incidents. Of course, I mentioned hurricanes. And so that's fairly, self-evident disruptive events, sporting events, et cetera. These are all real. And then we get the real time internet of things. These are, these are RFID sensors, beacons, video, et cetera. There's all kinds of stuff. And this is where, yeah, it's interesting. This is where the supply chain people will start talking about the difference, little twin to their physical world. If you can't say something, you can manage it. And retailers want to be able to manage things in real time. So IOT, along with it, the analytics and the data that's generated is really, really important for them going forward, community health. We've been talking a lot about that, the progression of the flu, et cetera, et cetera, uh, business schedules, commute patterns, school schedules, and whether these are all external data that are interesting to retailers and can help them to make better operational in something approaching real time. >>I mentioned the automation of decision making. This is a chart from Gardner, and I'd love to share with you. It's a really good one because it describes very simply what we're talking about. And it also describes where the inflection of new technology happens. If you look on the left there's data, we have lots and lots of data. We're getting more data all the time, retailers for a long time. Now, since certainly since the seventies or eighties have been using data to describe what happened, this is the retrospective analysis that we're all very familiar with, uh, data cubes and those kinds of things. And based on that, the human makes some decisions about what they're going to do going forward. Um, sometime in the not too distant past, this data was started to be used to make diagnostic decisions, not only what happened, but why did it happen? >>And me might think of this as, for example, if sales were depressed for a certain product, was it because we had another product on sale that day, that's a good example of fairly straightforward diagnostics. We then move forward to what we might think of as predictive analytics. And this was based on what happened in the past and why it happened in the past. This is what's likely to happen in the future. You might think of this as, for example, halo effect or, or the cannibalization effect of your category plans. If you're, if you happen to be a grocer and based on that, the human will make a decision as to what they need to do next then came along AI, and I don't want to oversell AI here. AI is a new way for us to examine lots and lots of data, particularly unstructured data AI. >>If I could simplify it to its maximum extent, it essentially is a data tool that allows you to see patterns in data, which might be interesting. It's very good at sifting through huge data sets of unstructured data and detecting statistically significant patterns. It gets deeper than that, of course, because it uses math instead of rules. So instead of an if then, or else a statement that we might've used with our structured data, we use the math to detect these patterns in unstructured data. And based on those, we can make some models. For example, uh, my guy in my, in my, uh, just turned 70 on my 70 year old man, I'm a white guy. I live in California. I have a certain income and a certain educational level. I'm likely to behave in this way based on a model that's pretty simplistic. But based on that, you can see that. >>And when another person who meets my psychographics, my demographics, my age group, my income level and all the rest, um, you, they might, they might be expected to make a certain action. And so this is where prescriptive really comes into play. Um, AI makes that possible. And then finally, when you start to think about moving closer to the customer on something, approaching a personalized level, a one-to-one level, you, you suddenly find yourself in this situation of having to make not thousands of decisions, but tens of millions of decisions. And that's when the automation of decision-making really gets to be pretty important. So this is all interesting stuff, and I don't want to oversell it. It's exciting. And it's new. It's just the latest turn of the technology screw. And it allows us to use this new data to basically automate decision-making in the business, in something approaching real time so that we can be much, much more responsive to real-time conditions in the marketplace. >>Very exciting. So I hope this is interesting. This is a piece of data from one of our recent pieces of research. Uh, this happens to be from a location analytics study. We just published last week and we asked retailers, what are the big challenges what's been going on in the last 12 months for them? And what's likely to be happening for them in the next few years. And it's just fascinating because it speaks to the need for faster decision-making there. The challenges in the last 12 months were all related to COVID. First of all, fulfilling growing online demand. This is a very, very real time issue that we all had to deal with. But the next one was keeping forecasts in sync with changing demand. And this is one of those areas where retailers are now finding themselves, needing to look at that exoticness for that external data that I mentioned to you last year, sales were not a good predictor of next year of sales. >>They needed to look at sentiment. They needed to look at the path of the disease. They needed to look at the availability of products, alternate sourcing, global political issues. All of these things get to be pretty important and they affect the forecast. And then finally managing a supply them the movement of the supply through the supply chain so that they could identify bottlenecks now, point to one of them, which we can all laugh at now because it's kind of funny. It wasn't funny at the time we ran out of toilet paper, toilet paper was a big problem. Now there is nothing quite as predictable as toilet paper, it's tied directly to the size of the population. And yet we ran out and the thing we didn't expect when the COVID pandemic hit was that people would panic. And when people panic, they do funny things. >>One of the things I do is buy up all the available toilet paper. I'm not quite sure why that happened. Um, but it did happen and it drained the supply chain. So retailers needed to be able to see that they needed to be able to find alternative sources. They needed to be able to do those kinds of things. This gets to the issue of visibility, real time data, fast data tomorrow's challenge. It's kind of interesting because one of the things that they've retailers put at the top of their list is improved inventory productivity. Uh, the reason that they are interested in this is because then we'll never spend as much money, anything as they will on inventory. And they want the inventory to be targeted to those places where it is most likely to be consumed and not to places where it's least likely to be consumed. >>So this is trying to solve the issue of getting the right product at the right place at the right time to the right consumer and retailers want to improve this because the dollars are just so big, but in this complex, fast moving world that we live in today, it's this requires something approaching real-time visibility. They want to be able to monitor the supply chain, the DCS and the warehouses. And they're picking capacity. We're talking about each of us, we're talking about each his level. Decision-making about what's flowing through the supply chain all the way from the, from the manufacturing doctor, the manufacturer through to consumption. There's two sides of the supply chain and retailers want to look at it, you'll hear retailers and, and people like me talk about the digital twin. This is where this really becomes important. And again, the digital twin is, is enabled by IOT and AI analytics. >>And finally they need to re to increase their profitability for online fulfillment. Uh, this is a huge issue, uh, for some grocers, the volume of online orders went from less than 10% to somewhere north of 40%. And retailers did in 2020, what they needed to do to fulfill those customer orders in the, in the year of the pandemic, that now the expectation that consumers have have been raised significantly. They now expect those, those features to be available to them all the time. And many people really liked them. Now retailers need to find out how to do it profitably. And one of the first things they need to do is they need to be able to observe the process so that they can find places to optimize. This is out of our recent research and I encourage you to read it. >>And when we think about the hard one wisdoms that retailers have come up with, we think about these things better visibility has led to better understanding, which increases their reaction time, which increases their profitability. So what are the opportunities? This is the first place that you'll see something that's very common. And in our research, we separate over performers, who we call retail winners from everybody else, average and under-performers, and we've noticed throughout the life of our company, that retail winners, don't just do all the same things that others do. They tend to do other things. And this shows up in this particular graph, this again is from the same study. So what are the opportunities to, to address these challenges? I mentioned to you in the last slide, first of all, strategic placement of inventory throughout the supply chain to better fulfill customer needs. This is all about being able to observe the supply chain, get the inventory into a position where it can be moved quickly to fast changing demand. >>And on the consumer side, a better understanding and reacting to unplanned events that can drive a dramatic change in customer behavior. Again, this is about studying the data, analyzing the data and reacting to the data that comes before the sales transaction. So this is observing the path to purchase observing things that are happening in the marketplace around the retailer, so that they can respond very quickly, a better understanding of the dramatic changes in customer preference and path to purchase. As they engage with us. One of the things we, all we all know about consumers now is that they are in control and the literally the entire planet is the assortment that's available to them. If they don't like the way they're interacting with you, they will drop you like a hot potato and go to somebody else. And what retailers fear justifiably is the default response to that is to just see if they can find it on Amazon. >>You don't want this to happen if you're a retailer. So we want to observe how we are interacting with consumers and how well we are meeting their needs, optimizing omni-channel order fulfillment to improve profitability. We've already mentioned this, uh, retailers did what they needed to do to offer new fulfillment options to consumers. Things like buy online pickup curbside, buy online pickup in store, buy online, pick up at a locker, a direct to consumer all of those things. Retailers offer those in 2020 because the consumers demand it and needed it. So when retailers are trying to do now is to understand how to do that profitably. And finally, this is important. It never goes away. Is the reduction of waste shrink within the supply chain? Um, I'm embarrassed to say that when I was a retail executive in the nineties, uh, we were no more certain of consumer demand than anybody else was, but we, we wanted to commit to very high service levels for some of our key county categories somewhere approaching 95%. >>And we found the best way to do that was to flood the supply chain with inventory. Uh, it sounds irresponsible now, but in those days, that was a sure-fire way to make sure that the customer had what she was looking for when she looked for it. You can't do that in today's world. Money is too tight and we can't have that, uh, inventory sitting around and move to the right places. Once we discovered what the right place is, we have to be able to predict, observe and respond in something much closer to your time. One of the next slide, um, the simple message here, again, a difference between winners and everybody else, the messages, if you can't see it, you can't manage it. And so we asked retailers to identify, to what extent an AI enabled supply chain can help their company address some issues. >>Look at the differences here. They're shocking identifying network bottlenecks. This is the toilet paper story I told you about over half of retail winners, uh, feel that that's very important. Only 19% of average and under performers, no surprise that their average and under-performers visibility into available to sell inventory anywhere within the enterprise, 58% of winners and only 32% of everybody else. And you can go on down the list, but you get the just retail winners, understand that they need to be able to see their assets and something approaching real time so that they can make the best decisions possible going forward in something approaching real time. This is the world that we live in today. And in order to do that, you need to be able to number one, see it. And number two, you need to be able to analyze it. And number three, you have to be able to make decisions based on what you saw, just some closing observations on. >>And I hope this was interesting for you. I love talking about this stuff. You can probably tell I'm very passionate about it, but the rapid pace of change in the world today is really underscoring the importance. For example, of location intelligence, as a key component of helping businesses to achieve sustainable growth, greater operational effectiveness and resilience, and ultimately your success. So this is really, really critical for retailers to understand and successfully evolving businesses need to accommodate these new consumer shopping behaviors and changes in how products are brought to the market. So that, and in order to do that, they need to be able to see people. They need to be able to see their assets, and they need to be able to see their processes in something approaching real time, and then they need to analyze it. And based on what they've uncovered, they need to be able to make strategic and operational decision making very quickly. This is the new world we live in. It's a real-time world. It's a, it's a sense and respond world and it's the way forward. So, Brent, I hope that was interesting for you. I really enjoyed talking about this, as I said, we'd love to hear a little bit more. >>Hey, Brian, that was excellent. You know, I always love me love hearing from RSR because you're so close to what retailers are talking about and the research that your company pulls together. Um, you know, one of the higher level research articles around, uh, fast data frankly, is the whole notion of IOT, right? And he does a lot of work in this space. Um, what I find fascinating based off the recent research is believe it or not, there's $1.2 trillion at stake in retail per year, between now and 2025. Now, how is that possible? Well, part of it is because the Kinsey captures not only traditional retail, but also QSRs and entertainment then use et cetera. That's considered all of retail, but it's a staggering number. And it really plays to the effect that real-time can have on individual enterprises. In this case, we're talking of course, about retail. >>So a staggering number. And if you think about it from streaming video to sensors, to beacons, RFID robotics, autonomous vehicles, retailers are testing today, even pizza delivery, you know, autonomous vehicle. Well, if you think about it, it shouldn't be that shocking. Um, but when they were looking at 12 different industries, retail became like the number three out of 12, and there's a lot of other big industries that will be leveraging IOT in the next four years. So, um, so retailers in the past have been traditionally a little stodgy about their spend in data and analytics. Um, I think retailers in general have got the religion that this is what it's going to take to compete in today's world, especially in a global economy. And in IOT really is the next frontier, which is kind of the definition of fast data. Um, so I, I just wanted to share just a few examples or exemplars of, of retailers that are leveraging Cloudera technology today. >>So now, so now the paid for advertisement at the end of this, right? So, so, you know, so what bringing to market here. So, you know, across all retail, uh, verticals, you know, if we look at, you know, for example, a well-known global mass virtual retailer, you know, they're leveraging Cloudera data flow, which is our solution to move data from point to point in wicked fast space. So it's open source technology that was originally developed by the NSA. So, um, it is best to class movement of data from an ingest standpoint, but we're also able to help the roundtrip. So we'll pull the sensor data off all the refrigeration units for this particular retailer. They'll hit it up against the product lifecycle table. They'll understand, you know, temperature fluctuations of 10, 20 degrees based on, you know, fresh food products that are in the store, what adjustments might need to be made because frankly store operators, they'll never know refrigeration don't know if a cooler goes down and they'll have to react quickly, but they won't know that 10, 20 degree temperature changes have happened overnight. >>So this particular customer leverages father a data flow understand temperature, fluctuations the impact on the product life cycle and the round trip communication back to the individual department manager, let's say a produce department manager, deli manager, meat manager, Hey, you had, you know, a 20 degree drop in temperature. We suggest you lower the price on these products that we know are in that cooler, um, for the next couple of days by 20%. So you don't have to worry, tell me about freshness issues and or potential shrink. So, you know, the grocery with fresh product, if you don't sell it, you smell it, you throw it away. It's lost to the bottom line. So, you know, critically important and, you know, tremendous ROI opportunity that we're helping to enable there, uh, from a, a leading global drugstore retailer. So this is more about data processing and, you know, we're excited to, you know, the recent partnership with the Vidia. >>So fast data, isn't always at the edge of IOT. It's also about workloads. And in retail, if you are processing your customer profiles or segmentation like intra day, you will ever achieve personalization. You will never achieve one-on-one communications with readers killers or with customers. And why is that? Because customers in many cases are touching your brand several times a week. So taking you a week or longer to process your segmentation schemes, you've already lost and you'll never achieve personalization in frack. In fact, you may offend customers by offering. You might push out based on what they just bought yesterday. You had no idea of it. So, you know, that's what we're really excited about. Uh, again, with, with the computation speed, then the video brings to, to Cloudera, we're already doing this today already, you know, been providing levels, exponential speed and processing data. But when the video brings to the party is course GPU's right, which is another exponential improvement, uh, to processing workloads like demand forecast, customer profiles. >>These things need to happen behind the scenes in the back office, much faster than retailers have been doing in the past. Um, that's just the world we all live in today. And then finally, um, you know, proximity marketing standpoint, or just from an in-store operation standpoint, you know, retailers are leveraging Cloudera today, not only data flow, but also of course our compute and storage platform and ML, et cetera, uh, to understand what's happening in store. It's almost like the metrics that we used to look at in the past in terms of conversion and traffic, all those metrics are now moving into the physical world. If you can leverage computer vision in streaming video, to understand how customers are traversing your store, how much time they're standing in front of the display, how much time they're standing in checkout line. Um, you can now start to understand how to better merchandise the store, um, where the hotspots are, how to in real time improve your customer service. >>And from a proximity marketing standpoint, understand how to engage with the customer right at the moment of truth, right? When they're right there, um, in front of a particular department or category, you know, of course leveraging mobile devices. So that's the world of fast data in retail and just kind of a summary in just a few examples of how folks are leveraging Cloudera today. Um, you know, from an overall platform standpoint, of course, father as an enterprise data platform, right? So, you know, we're, we're helping to the entire data life cycle. So we're not a data warehouse. Um, we're much more than that. So we have solutions to ingest data from the edge from IOT leading practice solutions to bring it in. We also have experiences to help, you know, leverage the analytic capabilities of, uh, data engineering, data science, um, analytics and reporting. Uh, we're not, uh, you know, we're not, we're not encroaching upon the legacy solutions that many retailers have today. >>We're providing a platform, this open source that helps weave all of this mess together that existed retail today from legacy systems because no retailer, frankly, is going to rip and replace a lot of stuff that they have today. Right. And the other thing that Cloudera brings to market is this whole notion of on-prem hybrid cloud and multi-cloud right. So our whole, our whole culture has been built around open source technology as the company that provides most of the source code to the Apache network around all these open source technologies. Um, we're kind of religious about open source and lack of vendor lock-in, uh, maybe to our fault. Uh, but as a company, we pull that together from a data platform standpoint. So it's not a rip and replace situation. It's like helping to connect legacy systems, data and analytics, um, you know, weaving that whole story together to be able to solve this whole data life cycle from beginning to end. >>And then finally, you know, just, you know, I want to thank everyone for joining today's session. I hope you found it informative. I can't say Brian killed course enough. Um, you know, he's my trusted friend in terms of what's going on in the industry. He has much broader reach of course, uh, in talking to a lot of our partners in, in, in, in other, uh, technology companies out there as well. But I really appreciate everyone joining the session and Brian, I'm going to kind of leave it open to you to, you know, any closing comments that you might have based on, you know, what we're talking about today in terms of fast data and retail. >>First of all, thank you, Brent. Um, and this is an exciting time to be in this industry. Um, and I'll just leave it with this. The reason that we are talking about these things is because we can, the technology has advanced remarkably in the last five years. Some of this data has been out there for a lot longer than that in it, frankly wasn't even usable. Um, but what we're really talking about is increasing the cycle time for decisions, making them go faster and faster so that we can respond to consumer expectations and delight them in ways that that make us a trusted provider of their life, their lifestyle needs. So this is really a good time to be a retailer, a real great time to be servicing the retail technology community. And I'm glad to be a part of it. And I was glad to be working with you. So thank you, Brian. >>Yeah, of course, Brian, and one of the exciting things for me to not being in the industry, as long as I have and being a former retailer is it's really exciting for me to see retailers actually spending money on data and it for a change, right? They've all kind of come to this final pinnacle of this is what it's going to take to compete. Um, you know, you know, and I talked to, you know, a lot of colleagues, even, even salespeople within Cloudera, I like, oh, retail, very stodgy, you know, slow to move. That's not the case anymore. Um, you know, religion is everyone's, everyone gets the religion of data and analytics and the value of that. And what's exciting for me to see as all this infusion of immense talent within the industry years ago, Brian, I mean, you know, retailers are like, you know, pulling people from some of the, you know, the greatest, uh, tech companies out there, right? From a data science data engineering standpoint, application developers, um, retail is really getting this legs right now in terms of, you know, go to market and in the leverage of data and analytics, which to me is very exciting. Well, >>You're right. I mean, I, I became a CIO around the time that, uh, point of sale and data warehouses were starting to happen data cubes and all those kinds of things. And I never thought I would see a change that dramatic, uh, as the industry experience back in those days, 19 89, 19 90, this changed doors that, but the good news is again, as the technology is capable, uh, it's, it's, we're talking about making technology and information available to, to retail decision-makers that consumers carry around in their pocket purses and pockets is there right now today. Um, so the, the, the question is, are you going to utilize it to win or are you going to get beaten? That's really what it boils down to. Yeah, >>For sure. Uh, Hey, thanks everyone. We'll wrap up. I know we ran a little bit long, but, uh, appreciate, uh, everyone, uh, hanging in there with us. We hope you enjoyed the session. The archive contact information is right there on the screen. Feel free to reach out to either Brian and I. You can go to cloudera.com. Uh, we even have, you know, joint sponsored papers with RSR. You can download there as well as eBooks and other assets that are available if you're interested. So thanks again, everyone for joining and really appreciate you taking the time. >>Hello everyone. And thanks for joining us today. My name is Brent Bedell, managing director retail, consumer goods here at Cloudera. Cloudera is very proud to be partnering with companies like three soft to provide data and analytic capabilities for over 200 retailers across the world and understanding why demand forecasting could be considered the heartbeat of retail. And what's at stake is really no mystery to most, to most retailers. And really just a quick level set before handing this over to my good friend, uh, Camille three soft, um, you know, IDC Gartner. Um, many other analysts have kind of summed up an average, uh, here that I thought would be important to share just to level set the importance of demand forecasting or retail. And what's at stake. I mean the combined business value for retailers leveraging AI and IOT. So this is above and beyond. What demand forecasting has been in the past is a $371 billion opportunity. >>And what's critically important to understand about demand forecasting. Is it directly impacts both the top line and the bottom line of retail. So how does it affect the top line retailers that leverage AI and IOT for demand forecasting are seeing average revenue increases of 2% and think of that as addressing the in stock or out of stock issue in retail and retail is become much more complex now, and that is no longer just brick and mortar, of course, but it's fulfillment centers driven by e-commerce. So inventory is now having to be spread over multiple channels. Being able to leverage AI and IOT is driving 2% average revenue increases. Now, if you think about the size of most retailers or the average retailer that on its face is worth millions of dollars of improvement for any individual retailer on top of that is balancing your inventory, getting the right product in the right place and having productive inventory. >>And that is the bottom line. So the average inventory reduction, leveraging AI and IOT as the analyst have found, and frankly, having spent time in this space myself in the past a 15% average inventory reduction is significant for retailers not being overstocked on product in the wrong place at the wrong time. And it touches everything from replenishment to out-of-stocks labor planning and customer engagement for purposes of today's conversation. We're going to focus on inventory and inventory optimization and reducing out-of-stocks. And of course, even small incremental improvements. I mentioned before in demand forecast accuracy have millions of dollars of direct business impact, especially when it comes to inventory optimization. Okay. So without further ado, I would like to now introduce Dr. Camille Volker to share with you what his team has been up to. And some of the amazing things that are driving at top retailers today. So over to you, Camille, >>Uh, I'm happy to be here and I'm happy to speak to you, uh, about, uh, what we, uh, deliver to our customers. But let me first, uh, introduce three soft. We are a 100 person company based in Europe, in Southern Poland. Uh, and we, uh, with 18 years of experience specialized in providing what we call a data driven business approach, uh, to our customers, our roots are in the solutions in the services. We originally started as a software house. And on top of that, we build our solutions. We've been automation that you get the software for biggest enterprises in Poland, further, we understood the meaning of data and, and data management and how it can be translated into business profits. Adding artificial intelligence on top of that, um, makes our solutions portfolio holistic, which enables us to realize very complex projects, which, uh, leverage all of those three pillars of our business. However, in the recent time, we also understood that services is something which only the best and biggest companies can afford at scale. And we believe that the future of retail, uh, demon forecasting is in the product solutions. So that's why we created occupy our AI platform for data driven retail. That also covers this area that we talked about today. >>I'm personally proud to be responsible for our technology partnerships with other on Microsoft. Uh, it's a great pleasure to work with such great companies and to be able to, uh, delivered a solution store customers together based on the common trust and understanding of the business, uh, which cumulates at customer success at the end. So why, why should you analyze data at retail? Why is it so important? Um, it's kind of obvious that there is a lot of potential in the data per se, but also understanding the different areas where it can be used in retail is very important. We believe that thanks to using data, it's basically easier to the right, uh, the good decisions for the business based on the facts and not intuition anymore. Those four areas that we observe in retail, uh, our online data analysis, that's the fastest growing sector, let's say for those, for those data analytics services, um, which is of course based on the econ and, uh, online channels, uh, availability to the customer. >>Pandemic only speeds up this process of engagement of the customers in that channel, of course, but traditional offline, um, let's say brick and mortar shops. Uh, they still play the biggest role for most of the retailers, especially from the FMCG sector. However, it's also very important to remember that there is plenty of business, uh, related questions that meet that need to be answered from the headquarter perspective. So is it actually, um, good idea to open a store in a certain place? Is it a good idea to optimize a stock with Saturday in producer? Is it a good idea to allocate the goods to online channel in specific way, those kinds of questions they are, they need to be answered in retail every day. And with that massive amount of factors coming into that question, it's really not, not that easy to base, only on the intuition and expert knowledge, of course, uh, as Brent mentioned at the beginning, the supply chain and everything who's relates to that is also super important. We observe our customers to seek for the huge improvements in the revenue, just from that one single area as well. Okay. >>So let me present you a case study of one of our solutions, and that was the lever to a leading global grocery retailer. Uh, the project started with the challenge set of challenges that we had to conquer. And of course the most important was how to limit overstocks and out of stocks. Uh, that's like the holy grail in of course, uh, how to do it without flooding the stores with the goods and in the same time, how to avoid empty shelves, um, from the perspective of the customer, it was obvious that we need to provide a very well, um, a very high quality of sales forecast to be able to ask for, uh, what will be the actual sales of the individual product in each store, uh, every day, um, considering huge role of the perishable goods in the specific grocery retailer, it was a huge challenge, uh, to provide a solution that was able to analyze and provide meaningful information about what's there in the sales data and the other factors we analyzed on daily basis at scale, however, uh, our holistic approach implementing AI with data management, uh, background, and these automation solutions all together created a platform that was able to significantly increase, uh, the sales for our customer just by minimizing out of stocks. >>In the same time we managed to not overflow the stock, the shops with the goods, which actually decreased losses significantly, especially on the fresh fruit. >>Having said that this results of course translate into the increase in revenue, which can be calculated in hundreds of millions of dollars per year. So how the solution actually works well in its principle, it's quite simple. We just collect the data. We do it online. We put that in our data lake, based on the cloud, there are technology, we implement our artificial intelligence models on top of it. And then based on the aggregated information, we create the forecast and we do it every day or every night for every single product in every single store. This information is sent to the warehouses and then the automated replenishment based on the forecast is on the way the huge and most important aspect of that is the use of the good tools to do the right job. Uh, having said that you can be sure that there is too many information in this data, and there is actually two-minute forecast created every night that any expert could ever check. >>This means our solution needs to be, uh, very robust. It needs to provide information with high quality and high porosity. There is plenty of different business process, which is on our forecast, which need to be delivered on time for every product in each individual shop observing the success of this project and having the huge market potential in mind, we decided to create our QB, which can be used by many retailers who don't want to create a dedicated software for that. We'll be solving this kind of problem. Occupy is, uh, our software service offering, which is enabling retailers to go data driven path management. >>We create occupant with retailers, for retailers, uh, implementing artificial intelligence, uh, on top of data science models created by our experts, uh, having data, data analysis in place based on data management tools that we use we've written first, um, attitude. The uncertain times of pandemic clearly shows that it's very important to apply correction factors, which are sometimes required because we need to respond quickly to the changes in the sales characteristics. That's why occupy B is open box solution, which means that you basically can implement that in your organization. We have without changing the process internally, it's all about mapping your process into this into the system, not the other way around the fast trends and products, collection possibilities allow the retailers to react to any changes, which are pure in the sales every day. >>Also, it's worth to mention that really it's not only FMCG. And we believe that different use cases, which we observed in fashion health and beauty, common garden pharmacies and electronics, flavors of retail are also very meaningful. They also have one common thread. That's the growing importance of e-commerce. That's why we didn't want to leave that aside of occupant. And we made everything we can to implement a solution, which covers all of the needs. When you think about the factors that affect sales, there is actually huge variety of data and that we can analyze, of course, the transactional data that every dealer possesses like sales data from sale from, from e-commerce channel also, uh, averaging numbers from weeks, months, and years makes sense, but it's also worth to mention that using the right tool that allows you to collect that data from also internal and external sources makes perfect sense for retail. Uh, it's very hard to imagine a competitive retailer that is not analyzing the competitor's activity, uh, changes in weather or information about some seasonal stores, which can be very important during the summer during the holidays, for example. Uh, but on the other hand, um, having that information in one place makes the actual benefit and environment for the customer. >>Okay. Demon forecasting seems to be like the most important and promising use case. We can talk about when I think about retail, but it's also their whole process of replenishment that can cover with different sets of machine learning models. And they done management tools. We believe that analyzing data from different parts of the retail, uh, replenishment process, uh, can be achieved with implementing a data management solution based on caldera products and with adding some AI on top of it, it makes perfect sense to focus on not only demand forecasting, but also further use cases down the line when it comes to the actual benefits from implementing solutions for demand management, we believe it's really important to analyze them holistically. First is of course, out of stocks, memorization, which can be provided by simply better sales focus, but also reducing overstocks by better inventory management can be achieved in, in the same time. Having said that we believe that analyzing data without any specific new equipment required in point of sales is the low hanging fruit that can be easily achieved in almost every industry in almost every regular customer. >>Hey, thanks, Camille, having worked with retailers in this space for a couple of decades, myself, I was really impressed by a couple of things and they might've been understated, frankly. Um, the results of course, I mean, you, you know, as I kind of set up this session, you doubled the numbers on the statistics that the analysts found. So obviously in customers you're working with, um, you know, you're, you're doubling average numbers that the industry is having and, and most notably how the use of AI or occupy has automated so many manual tasks of the past, like tour tuning, item profiles, adding new items, et cetera. Uh, and also how quickly it felt like, and this is my, my core question. Your team can cover, um, or, or provide the solution to, to not only core center store, for example, in grocery, but you're covering fresh products. >>And frankly, there are, there are solutions out on the market today that only focus on center store non-perishable department. So I was really impressed by the coverage that you're able to provide as well. So can you articulate kind of what it takes to get up and running and your overall process to roll out the solution? I feel like based on what you talked about, um, and how you were approaching this in leveraging AI, um, that you're, you're streamlining processes of legacy demand, forecasting solutions that required more manual intervention, um, how quickly can you get people set up and what is the overall process like to get started with soft? >>Yeah, it's usually it takes three to six months, uh, to onboard a new customer to that kind of solution. And frankly it depends on the data that the customer, uh, has. Uh, usually it's different, uh, for smaller, bigger companies, of course. Uh, but we believe that it's very important to start with a good foundation. The platform needs to be there, the platform that is able to, uh, basically analyze or process different types of data, structured, unstructured, internal, external, and so on. But when you have this platform set, it's all about starting ingesting data there. And usually for a smaller companies, it's easier to start with those, let's say, low hanging fruits. So the internal data, which is there, this data has the highest veracity is already easy to start with, to work with them because everyone in the organization understands this data for the bigger companies. It might be important to ingest also kind of more unstructured data, some kind of external data that need to be acquired. So that may, that may influence the length of the process. But we usually start with the customers. We have, uh, workshops. That's very important to understand their business because not every deal is the same. Of course, we believe that the success of our customers comes also due to the fact that we train those models, those AI models individually to the needs of our >>Totally understand and POS data, every retailer has right in, in one way shape or form. And it is the fundamental, uh, data point, whether it's e-comm or the brick and mortar data, uh, every retailer has that data. So that, that totally makes sense. But what you just described was bunts. Um, there are, there are legacy and other solutions out there that this could be a, a year or longer process to roll out to the number of stores, for example, that you're scaling to. So that's highly impressive. And my guess is a lot of the barriers that have been knocked down with your solution are the fact that you're running this in the cloud, um, you know, on, from a compute standpoint on Cloudera from a public cloud stamp point on Microsoft. So there's, there's no, it intervention, if you will, or hurdles in preparation to get the database set up and in all of the work, I would imagine that part of the time-savings to getting started, would that be an accurate description? >>Yeah, absolutely. Uh, in the same time, this actually lowering the business risks, because we simply take data and put that into the data lake, which is in the cloud. We do not interfere with the existing processes, which are processing this data in the combined. So we just use the same data. We just already in the company, we ask some external data if needed, but it's all aside of the current customers infrastructure. So this is also a huge gain, as you said, right? >>And you're meeting customers where they are. Right. So, as I said, foundationally, every retailer POS data, if they want to add weather data or calendar event data or, you know, want incorporate a course online data with offline data. Um, you have a roadmap and the ability to do that. So it is a building block process. So getting started with, for data, uh, as, as with POS online or offline is the foundational component, which obviously you're very good at. Um, and then having that ability to then incorporate other data sets is critically important because that just improves demand, forecast accuracy, right. By being able to pull in those, those other data sources, if you will. So Camille, I just have one final question for you. Um, you know, there, there are plenty of not plenty, but I mean, there's enough demand forecasting solutions out on the market today for retailers. One of the things that really caught my eye, especially being a former retailer and talking with retailers was the fact that you're, you're promoting an open box solution. And that is a key challenge for a lot of retailers that have, have seen black box solutions come and go. Um, and especially in this space where you really need direct input from the, to continue to fine tune and improve forecast accuracy. Could you give just a little bit more of a description or response to your approach to open box versus black box? >>Yeah, of course. So, you know, we've seen in the past the failures of the projects, um, based on the black box approach, uh, and we believe that this is not the way to go, especially with this kind of, uh, let's say, uh, specialized services that we provide in meaning of understanding the customer's business first and then applying the solution, because what stands behind our concept in occupy is the, basically your process in the organization as a retailer, they have been optimized for years already. That's where retailers put their, uh, focus for many years. We don't want to change that. We are not able to optimize it properly. For sure as it combined, we are able to provide you a tool which can then be used for mapping those very well optimized process and not to change them. That's our idea. And the open box means that in every process that you will map in the solution, you can then in real time monitor the execution of those processes and see what is the result of every step. That way we create truly explainable experience for our customers, then okay, then can easily go for the whole process and see how the forecast, uh, was calculated. And what is the reason for a specific number to be there at the end of the day? >>I think that is, um, invaluable. Um, can be, I really think that is a differentiator and what three soft is bringing to market with that. Thanks. Thanks everyone for joining us today, let's stay in touch. I want to make sure to leave, uh, uh, Camille's information here. Uh, so reach out to him directly or feel free at any, any point in time, obviously to reach out to me, um, again, so glad everyone was able to join today, look forward to talking to you soon.

momentum is gathering [Music] business is evolving more and more quickly moving through one transformation to the next because change never stops it only accelerates this is a world that demands a new kind of compute deployed from edge to core to cloud compute that can outpace the rapidly changing needs of businesses large and small unlocking new insights turning data into outcomes empowering new experiences compute that can scale up or scale down with minimum investment and effort guided by years of expertise protected by 360-degree security served up as a service to let it control own and manage massive workloads that weren't there yesterday and might not be there tomorrow this is the compute power that will drive progress giving your business what you need to be ready for what's next this is the compute power of hpe delivering your foundation for digital transformation welcome to accelerating next thank you so much for joining us today we have a great program we're going to talk tech with experts we'll be diving into the changing economics of our industry and how to think about the next phase of your digital transformation now very importantly we're also going to talk about how to optimize workloads from edge to exascale with full security and automation all coming to you as a service and with me to kick things off is neil mcdonald who's the gm of compute at hpe neil always a pleasure great to have you on it's great to see you dave now of course when we spoke a year ago you know we had hoped by this time we'd be face to face but you know here we are again you know this pandemic it's obviously affected businesses and people in in so many ways that we could never have imagined but in the reality is in reality tech companies have literally saved the day let's start off how is hpe contributing to helping your customers navigate through things that are so rapidly shifting in the marketplace well dave it's nice to be speaking to you again and i look forward to being able to do this in person some point the pandemic has really accelerated the need for transformation in businesses of all sizes more than three-quarters of cios report that the crisis has forced them to accelerate their strategic agendas organizations that were already transforming or having to transform faster and organizations that weren't on that journey yet are having to rapidly develop and execute a plan to adapt to this new reality our customers are on this journey and they need a partner for not just the compute technology but also the expertise and economics that they need for that digital transformation and for us this is all about unmatched optimization for workloads from the edge to the enterprise to exascale with 360 degree security and the intelligent automation all available in that as a service experience well you know as you well know it's a challenge to manage through any transformation let alone having to set up remote workers overnight securing them resetting budget priorities what are some of the barriers that you see customers are working hard to overcome simply per the organizations that we talk with are challenged in three areas they need the financial capacity to actually execute a transformation they need the access to the resource and the expertise needed to successfully deliver on a transformation and they have to find the way to match their investments with the revenues for the new services that they're putting in place to service their customers in this environment you know we have a data partner called etr enterprise technology research and the spending data that we see from them is it's quite dramatic i mean last year we saw a contraction of roughly five percent of in terms of i.t spending budgets etc and this year we're seeing a pretty significant rebound maybe a six to seven percent growth range is the prediction the challenge we see is organizations have to they've got to iterate on that i call it the forced march to digital transformation and yet they also have to balance their investments for example at the corporate headquarters which have kind of been neglected is there any help in sight for the customers that are trying to reduce their spend and also take advantage of their investment capacity i think you're right many businesses are understandably reluctant to loosen the purse strings right now given all of the uncertainty and often a digital transformation is viewed as a massive upfront investment that will pay off in the long term and that can be a real challenge in an environment like this but it doesn't need to be we work through hpe financial services to help our customers create the investment capacity to accelerate the transformation often by leveraging assets they already have and helping them monetize them in order to free up the capacity to accelerate what's next for their infrastructure and for their business so can we drill into that i wonder if we could add some specifics i mean how do you ensure a successful outcome what are you really paying attention to as those sort of markers for success well when you think about the journey that an organization is going through it's tough to be able to run the business and transform at the same time and one of the constraints is having the people with enough bandwidth and enough expertise to be able to do both so we're addressing that in two ways for our customers one is by helping them confidently deploy new solutions which we have engineered leveraging decades of expertise and experience in engineering to deliver those workload optimized portfolios that take the risk and the complexity out of assembling some of these solutions and give them a pre-packaged validated supported solution intact that simplifies that work for them but in other cases we can enhance our customers bandwidth by bringing them hpe point next experts with all of the capabilities we have to help them plan deliver and support these i.t projects and transformations organizations can get on a faster track of modernization getting greater insight and control as they do it we're a trusted partner to get the most for a business that's on this journey in making these critical compute investments to underpin the transformations and whether that's planning to optimizing to safe retirement at the end of life we can bring that expertise to bayer to help amplify what our customers already have in-house and help them accelerate and succeed in executing these transformations thank you for that neil so let's talk about some of the other changes that customers are seeing and the cloud has obviously forced customers and their suppliers to really rethink how technology is packaged how it's consumed how it's priced i mean there's no doubt in that to take green lake it's obviously a leading example of a pay as pay-as-you-scale infrastructure model and it could be applied on-prem or hybrid can you maybe give us a sense as to where you are today with green lake well it's really exciting you know from our first pay-as-you-go offering back in 2006 15 years ago to the introduction of green lake hpe has really been paving the way on consumption-based services through innovation and partnership to help meet the exact needs of our customers hpe green lake provides an experience that's the best of both worlds a simple pay-per-use technology model with the risk management of data that's under our customers direct control and it lets customers shift to everything as a service in order to free up capital and avoid that upfront expense that we talked about they can do this anywhere at any scale or any size and really hpe green lake is the cloud that comes to you like that so we've touched a little bit on how customers can maybe overcome some of the barriers to transformation what about the nature of transformations themselves i mean historically there was a lot of lip service paid to digital and and there's a lot of complacency frankly but you know that covered wrecking ball meme that so well describes that if you're not a digital business essentially you're going to be out of business so neil as things have evolved how is hpe addressed the new requirements well the new requirements are really about what customers are trying to achieve and four very common themes that we see are enabling the productivity of a remote workforce that was never really part of the plan for many organizations being able to develop and deliver new apps and services in order to service customers in a different way or drive new revenue streams being able to get insights from data so that in these tough times they can optimize their business more thoroughly and then finally think about the efficiency of an agile hybrid private cloud infrastructure especially one that now has to integrate the edge and we're really thrilled to be helping our customers accelerate all of these and more with hpe compute i want to double click on that remote workforce productivity i mean again the surveys that we see 46 percent of the cios say that productivity improved with the whole work from home remote work trend and on average those improvements were in the four percent range which is absolutely enormous i mean when you think about that how does hpe specifically you know help here what do you guys do well every organization in the world has had to adapt to a different style of working and with more remote workers than they had before and for many organizations that's going to become the new normal even post pandemic many it shops are not well equipped for the infrastructure to provide that experience because if all your workers are remote the resiliency of that infrastructure the latencies of that infrastructure the reliability of are all incredibly important so we provide comprehensive solutions expertise and as a service options that support that remote work through virtual desktop infrastructure or vdi so that our customers can support that new normal of virtual engagements online everything across industries wherever they are and that's just one example of many of the workload optimized solutions that we're providing for our customers is about taking out the guesswork and the uncertainty in delivering on these changes that they have to deploy as part of their transformation and we can deliver that range of workload optimized solutions across all of these different use cases because of our broad range of innovation in compute platforms that span from the ruggedized edge to the data center all the way up to exascale and hpc i mean that's key if you're trying to affect the digital transformation and you don't have to fine-tune you know be basically build your own optimized solutions if i can buy that rather than having to build it and rely on your r d you know that's key what else is hpe doing you know to deliver things new apps new services you know your microservices containers the whole developer trend what's going on there well that's really key because organizations are all seeking to evolve their mix of business and bring new services and new capabilities new ways to reach their customers new way to reach their employees new ways to interact in their ecosystem all digitally and that means app development and many organizations of course are embracing container technology to do that today so with the hpe container platform our customers can realize that agility and efficiency that comes with containerization and use it to provide insights to their data more and more that data of course is being machine generated or generated at the edge or the near edge and it can be a real challenge to manage that data holistically and not have silos and islands an hpe esmerald data fabric speeds the agility and access to data with a unified platform that can span across the data centers multiple clouds and even the edge and that enables data analytics that can create insights powering a data-driven production-oriented cloud-enabled analytics and ai available anytime anywhere in any scale and it's really exciting to see the kind of impact that that can have in helping businesses optimize their operations in these challenging times you got to go where the data is and the data is distributed it's decentralized so i i i like the esmerel of vision and execution there so that all sounds good but with digital transformation you get you're going to see more compute in in hybrid's deployments you mentioned edge so the surface area it's like the universe it's it's ever-expanding you mentioned you know remote work and work from home before so i'm curious where are you investing your resources from a cyber security perspective what can we count on from hpe there well you can count on continued leadership from hpe as the world's most secure industry standard server portfolio we provide an enhanced and holistic 360 degree view to security that begins in the manufacturing supply chain and concludes with a safeguarded end-of-life decommissioning and of course we've long set the bar for security with our work on silicon root of trust and we're extending that to the application tier but in addition to the security customers that are building this modern hybrid are private cloud including the integration of the edge need other elements too they need an intelligent software-defined control plane so that they can automate their compute fleets from all the way at the edge to the core and while scale and automation enable efficiency all private cloud infrastructures are competing with web scale economics and that's why we're democratizing web scale technologies like pinsando to bring web scale economics and web scale architecture to the private cloud our partners are so important in helping us serve our customers needs yeah i mean hp has really upped its ecosystem game since the the middle of last decade when when you guys reorganized it you became like even more partner friendly so maybe give us a preview of what's coming next in that regard from today's event well dave we're really excited to have hp's ceo antonio neri speaking with pat gelsinger from intel and later lisa sue from amd and later i'll have the chance to catch up with john chambers the founder and ceo of jc2 ventures to discuss the state of the market today yeah i'm jealous you guys had some good interviews coming up neil thanks so much for joining us today on the virtual cube you've really shared a lot of great insight how hpe is partnering with customers it's it's always great to catch up with you hopefully we can do so face to face you know sooner rather than later well i look forward to that and uh you know no doubt our world has changed and we're here to help our customers and partners with the technology the expertise and the economics they need for these digital transformations and we're going to bring them unmatched workload optimization from the edge to exascale with that 360 degree security with the intelligent automation and we're going to deliver it all as an as a service experience we're really excited to be helping our customers accelerate what's next for their businesses and it's been really great talking with you today about that dave thanks for having me you're very welcome it's been super neal and i actually you know i had the opportunity to speak with some of your customers about their digital transformation and the role of that hpe plays there so let's dive right in we're here on the cube covering hpe accelerating next and with me is rule siestermans who is the head of it at the netherlands cancer institute also known as nki welcome rule thank you very much great to be here hey what can you tell us about the netherlands cancer institute maybe you could talk about your core principles and and also if you could weave in your specific areas of expertise yeah maybe first introduction to the netherlands institute um we are one of the top 10 comprehensive cancers in the world and what we do is we combine a hospital for treating patients with cancer and a recent institute under one roof so discoveries we do we find within the research we can easily bring them back to the clinic and vis-a-versa so we have about 750 researchers and about 3 000 other employees doctors nurses and and my role is to uh to facilitate them at their best with it got it so i mean everybody talks about digital digital transformation to us it all comes down to data so i'm curious how you collect and take advantage of medical data specifically to support nki's goals maybe some of the challenges that your organization faces with the amount of data the speed of data coming in just you know the the complexities of data how do you handle that yeah it's uh it's it's it's challenge and uh yeah what we we have we have a really a large amount of data so we produce uh terabytes a day and we we have stored now more than one petabyte on data at this moment and yeah it's uh the challenge is to to reuse the data optimal for research and to share it with other institutions so that needs to have a flexible infrastructure for that so a fast really fast network uh big data storage environment but the real challenge is not not so much the i.t bus is more the quality of the data so we have a lot of medical systems all producing those data and how do we combine them and and yeah get the data fair so findable accessible interoperable and reusable uh for research uh purposes so i think that's the main challenge the quality of the data yeah very common themes that we hear from from other customers i wonder if you could paint a picture of your environment and maybe you can share where hpe solutions fit in what what value they bring to your organization's mission yeah i think it brings a lot of flexibility so what we did with hpe is that we we developed a software-defined data center and then a virtual workplace for our researchers and doctors and that's based on the hpe infrastructure and what we wanted to build is something that expect the needs of doctors and nurses but also the researchers and the two kind of different blood groups blood groups and with different needs so uh but we wanted to create one infrastructure because we wanted to make the connection between the hospital and the research that's that's more important so um hpe helped helped us not only with the the infrastructure itself but also designing the whole architecture of it and for example what we did is we we bought a lot of hardware and and and the hardware is really uh doing his his job between nine till five uh dennis everything is working within everyone is working within the institution but all the other time in evening and and nights hours and also the redundant environment we have for the for our healthcare uh that doesn't do nothing of much more or less uh in in those uh dark hours so what we created together with nvidia and hpe and vmware is that we we call it video by day compute by night so we reuse those those servers and those gpu capacity for computational research jobs within the research that's you mentioned flexibility for this genius and and so we're talking you said you know a lot of hard ways they're probably proliant i think synergy aruba networking is in there how are you using this environment actually the question really is when you think about nki's digital transformation i mean is this sort of the fundamental platform that you're using is it a maybe you could describe that yeah it's it's the fundamental platform to to to work on and and and what we see is that we have we have now everything in place for it but the real challenge is is the next steps we are in so we have a a software defined data center we are cloud ready so the next steps is to to make the connection to the cloud to to give more automation to our researchers so they don't have to wait a couple of weeks for it to do it but they can do it themselves with a couple of clicks so i think the basic is we are really flexible and we have a lot of opportunities for automation for example but the next step is uh to create that business value uh really for for our uh employees that's a great story and a very important mission really fascinating stuff thanks for sharing this with our audience today really appreciate your time thank you very much okay this is dave vellante with thecube stay right there for more great content you're watching accelerating next from hpe i'm really glad to have you with us today john i know you stepped out of vacation so thanks very much for joining us neil it's great to be joining you from hawaii and i love the partnership with hpe and the way you're reinventing an industry well you've always excelled john at catching market transitions and there are so many transitions and paradigm shifts happening in the market and tech specifically right now as you see companies rush to accelerate their transformation what do you see as the keys to success well i i think you're seeing actually an acceleration following the covet challenges that all of us faced and i wasn't sure that would happen it's probably at three times the paces before there was a discussion point about how quickly the companies need to go digital uh that's no longer a discussion point almost all companies are moving with tremendous feed on digital and it's the ability as the cloud moves to the edge with compute and security uh at the edge and how you deliver these services to where the majority of applications uh reside are going to determine i think the future of the next generation company leadership and it's the area that neil we're working together on in many many ways so i think it's about innovation it's about the cloud moving to the edge and an architectural play with silicon to speed up that innovation yes we certainly see our customers of all sizes trying to accelerate what's next and get that digital transformation moving even faster as a result of the environment that we're all living in and we're finding that workload focus is really key uh customers in all kinds of different scales are having to adapt and support the remote workforces with vdi and as you say john they're having to deal with the deployment of workloads at the edge with so much data getting generated at the edge and being acted upon at the edge the analytics and the infrastructure to manage that as these processes get digitized and automated is is so important for so many workflows we really believe that the choice of infrastructure partner that underpins those transformations really matters a partner that can help create the financial capacity that can help optimize your environments and enable our customers to focus on supporting their business are all super key to success and you mentioned that in the last year there's been a lot of rapid course correction for all of us a demand for velocity and the ability to deploy resources at scale is more and more needed maybe more than ever what are you hearing customers looking for as they're rolling out their digital transformation efforts well i think they're being realistic that they're going to have to move a lot faster than before and they're also realistic on core versus context they're they're their core capability is not the technology of themselves it's how to deploy it and they're we're looking for partners that can help bring them there together but that can also innovate and very often the leaders who might have been a leader in a prior generation may not be on this next move hence the opportunity for hpe and startups like vinsano to work together as the cloud moves the edge and perhaps really balance or even challenge some of the big big incumbents in this category as well as partners uniquely with our joint customers on how do we achieve their business goals tell me a little bit more about how you move from this being a technology positioning for hpe to literally helping your customers achieve their outcomes they want and and how are you changing hpe in that way well i think when you consider these transformations the infrastructure that you choose to underpin it is incredibly critical our customers need a software-defined management plan that enables them to automate so much of their infrastructure they need to be able to take faster action where the data is and to do all of this in a cloud-like experience where they can deliver their infrastructure as code anywhere from exascale through the enterprise data center to the edge and really critically they have to be able to do this securely which becomes an ever increasing challenge and doing it at the right economics relative to their alternatives and part of the right economics of course includes adopting the best practices from web scale architectures and bringing them to the heart of the enterprise and in our partnership with pensando we're working to enable these new ideas of web scale architecture and fleet management for the enterprise at scale you know what is fun is hpe has an unusual talent from the very beginning in silicon valley of working together with others and creating a win-win innovation approach if you watch what your team has been able to do and i want to say this for everybody listening you work with startups better than any other company i've seen in terms of how you do win win together and pinsando is just the example of that uh this startup which by the way is the ninth time i have done with this team a new generation of products and we're designing that together with hpe in terms of as the cloud moves to the edge how do we get the leverage out of that and produce the results for your customers on this to give the audience appeal for it you're talking with pensano alone in terms of the efficiency versus an amazon amazon web services of an order of magnitude i'm not talking 100 greater i'm talking 10x greater and things from throughput number of connections you do the jitter capability etc and it talks how two companies uniquely who believe in innovation and trust each other and have very similar cultures can work uniquely together on it how do you bring that to life with an hpe how do you get your company to really say let's harvest the advantages of your ecosystem in your advantages of startups well as you say more and more companies are faced with these challenges of hitting the right economics for the infrastructure and we see many enterprises of various sizes trying to come to terms with infrastructures that look a lot more like a service provider that require that software-defined management plane and the automation to deploy at scale and with the work we're doing with pinsando the benefits that we bring in terms of the observability and the telemetry and the encryption and the distributed network functions but also a security architecture that enables that efficiency on the individual nodes is just so key to building a competitive architecture moving forwards for an on-prem private cloud or internal service provider operation and we're really excited about the work we've done to bring that technology across our portfolio and bring that to our customers so that they can achieve those kind of economics and capabilities and go focus on their own transformations rather than building and running the infrastructure themselves artisanally and having to deal with integrating all of that great technology themselves makes tremendous sense you know neil you and i work on a board together et cetera i've watched your summarization skills and i always like to ask the question after you do a quick summary like this what are the three or four takeaways we would like for the audience to get out of our conversation well that's a great question thanks john we believe that customers need a trusted partner to work through these digital transformations that are facing them and confront the challenge of the time that the covet crisis has taken away as you said up front every organization is having to transform and transform more quickly and more digitally and working with a trusted partner with the expertise that only comes from decades of experience is a key enabler for that a partner with the ability to create the financial capacity to transform the workload expertise to get more from the infrastructure and optimize the environment so that you can focus on your own business a partner that can deliver the systems and the security and the automation that makes it easily deployable and manageable anywhere you need them at any scale whether the edge the enterprise data center or all the way up to exascale in high performance computing and can do that all as a service as we can at hpe through hpe green lake enabling our customers most critical workloads it's critical that all of that is underpinned by an ai powered digitally enabled service experience so that our customers can get on with their transformation and running their business instead of dealing with their infrastructure and really only hpe can provide this combination of capabilities and we're excited and committed to helping our customers accelerate what's next for their businesses neil it's fun i i love being your partner and your wingman our values and cultures are so similar thanks for letting me be a part of this discussion today thanks for being with us john it was great having you here oh it's friends for life okay now we're going to dig into the world of video which accounts for most of the data that we store and requires a lot of intense processing capabilities to stream here with me is jim brickmeyer who's the chief marketing and product officer at vlasics jim good to see you good to see you as well so tell us a little bit more about velocity what's your role in this tv streaming world and maybe maybe talk about your ideal customer sure sure so um we're leading provider of carrier great video solutions video streaming solutions and advertising uh technology to service providers around the globe so we primarily sell software-based solutions to uh cable telco wireless providers and broadcasters that are interested in launching their own um video streaming services to consumers yeah so this is this big time you know we're not talking about mom and pop you know a little video outfit but but maybe you can help us understand that and just the sheer scale of of the tv streaming that you're doing maybe relate it to you know the overall internet usage how much traffic are we talking about here yeah sure so uh yeah so our our customers tend to be some of the largest um network service providers around the globe uh and if you look at the uh the video traffic um with respect to the total amount of traffic that that goes through the internet video traffic accounts for about 90 of the total amount of data that uh that traverses the internet so video is uh is a pretty big component of um of how people when they look at internet technologies they look at video streaming technologies uh you know this is where we we focus our energy is in carrying that traffic as efficiently as possible and trying to make sure that from a consumer standpoint we're all consumers of video and uh make sure that the consumer experience is a high quality experience that you don't experience any glitches and that that ultimately if people are paying for that content that they're getting the value that they pay for their for their money uh in their entertainment experience i think people sometimes take it for granted it's like it's like we we all forget about dial up right those days are long gone but the early days of video was so jittery and restarting and and the thing too is that you know when you think about the pandemic and the boom in streaming that that hit you know we all sort of experienced that but the service levels were pretty good i mean how much how much did the pandemic affect traffic what kind of increases did you see and how did that that impact your business yeah sure so uh you know obviously while it was uh tragic to have a pandemic and have people locked down what we found was that when people returned to their homes what they did was they turned on their their television they watched on on their mobile devices and we saw a substantial increase in the amount of video streaming traffic um over service provider networks so what we saw was on the order of 30 to 50 percent increase in the amount of data that was traversing those networks so from a uh you know from an operator's standpoint a lot more traffic a lot more challenging to to go ahead and carry that traffic a lot of work also on our behalf and trying to help operators prepare because we could actually see geographically as the lockdowns happened [Music] certain areas locked down first and we saw that increase so we were able to help operators as as all the lockdowns happened around the world we could help them prepare for that increase in traffic i mean i was joking about dial-up performance again in the early days of the internet if your website got fifty percent more traffic you know suddenly you were you your site was coming down so so that says to me jim that architecturally you guys were prepared for that type of scale so maybe you could paint a picture tell us a little bit about the solutions you're using and how you differentiate yourself in your market to handle that type of scale sure yeah so we so we uh we really are focused on what we call carrier grade solutions which are designed for that massive amount of scale um so we really look at it you know at a very granular level when you look um at the software and and performance capabilities of the software what we're trying to do is get as many streams as possible out of each individual piece of hardware infrastructure so that we can um we can optimize first of all maximize the uh the efficiency of that device make sure that the costs are very low but one of the other challenges is as you get to millions and millions of streams and that's what we're delivering on a daily basis is millions and millions of video streams that you have to be able to scale those platforms out um in an effective in a cost effective way and to make sure that it's highly resilient as well so we don't we don't ever want a consumer to have a circumstance where a network glitch or a server issue or something along those lines causes some sort of uh glitch in their video and so there's a lot of work that we do in the software to make sure that it's a very very seamless uh stream and that we're always delivering at the very highest uh possible bit rate for consumers so that if you've got that giant 4k tv that we're able to present a very high resolution picture uh to those devices and what's the infrastructure look like underneath you you're using hpe solutions where do they fit in yeah that's right yeah so we uh we've had a long-standing partnership with hpe um and we work very closely with them to try to identify the specific types of hardware that are ideal for the the type of applications that we run so we run video streaming applications and video advertising applications targeted kinds of video advertising technologies and when you look at some of these applications they have different types of requirements in some cases it's uh throughput where we're taking a lot of data in and streaming a lot of data out in other cases it's storage where we have to have very high density high performance storage systems in other cases it's i gotta have really high capacity storage but the performance does not need to be quite as uh as high from an io perspective and so we work very closely with hpe on trying to find exactly the right box for the right application and then beyond that also talking with our customers to understand there are different maintenance considerations associated with different types of hardware so we tend to focus on as much as possible if we're going to place servers deep at the edge of the network we will make everything um maintenance free or as maintenance free as we can make it by putting very high performance solid state storage into those servers so that uh we we don't have to physically send people to those sites to uh to do any kind of maintenance so it's a it's a very cooperative relationship that we have with hpe to try to define those boxes great thank you for that so last question um maybe what the future looks like i love watching on my mobile device headphones in no distractions i'm getting better recommendations how do you see the future of tv streaming yeah so i i think the future of tv streaming is going to be a lot more personal right so uh this is what you're starting to see through all of the services that are out there is that most of the video service providers whether they're online providers or they're your traditional kinds of paid tv operators is that they're really focused on the consumer and trying to figure out what is of value to you personally in the past it used to be that services were one size fits all and um and so everybody watched the same program right at the same time and now that's uh that's we have this technology that allows us to deliver different types of content to people on different screens at different times and to advertise to those individuals and to cater to their individual preferences and so using that information that we have about how people watch and and what people's interests are we can create a much more engaging and compelling uh entertainment experience on all of those screens and um and ultimately provide more value to consumers awesome story jim thanks so much for keeping us helping us just keep entertained during the pandemic i really appreciate your time sure thanks all right keep it right there everybody you're watching hpes accelerating next first of all pat congratulations on your new role as intel ceo how are you approaching your new role and what are your top priorities over your first few months thanks antonio for having me it's great to be here with you all today to celebrate the launch of your gen 10 plus portfolio and the long history that our two companies share in deep collaboration to deliver amazing technology to our customers together you know what an exciting time it is to be in this industry technology has never been more important for humanity than it is today everything is becoming digital and driven by what i call the four key superpowers the cloud connectivity artificial intelligence and the intelligent edge they are super powers because each expands the impact of the others and together they are reshaping every aspect of our lives and work in this landscape of rapid digital disruption intel's technology and leadership products are more critical than ever and we are laser focused on bringing to bear the depth and breadth of software silicon and platforms packaging and process with at scale manufacturing to help you and our customers capitalize on these opportunities and fuel their next generation innovations i am incredibly excited about continuing the next chapter of a long partnership between our two companies the acceleration of the edge has been significant over the past year with this next wave of digital transformation we expect growth in the distributed edge and age build out what are you seeing on this front like you said antonio the growth of edge computing and build out is the next key transition in the market telecommunications service providers want to harness the potential of 5g to deliver new services across multiple locations in real time as we start building solutions that will be prevalent in a 5g digital environment we will need a scalable flexible and programmable network some use cases are the massive scale iot solutions more robust consumer devices and solutions ar vr remote health care autonomous robotics and manufacturing environments and ubiquitous smart city solutions intel and hp are partnering to meet this new wave head on for 5g build out and the rise of the distributed enterprise this build out will enable even more growth as businesses can explore how to deliver new experiences and unlock new insights from the new data creation beyond the four walls of traditional data centers and public cloud providers network operators need to significantly increase capacity and throughput without dramatically growing their capital footprint their ability to achieve this is built upon a virtualization foundation an area of intel expertise for example we've collaborated with verizon for many years and they are leading the industry and virtualizing their entire network from the core the edge a massive redesign effort this requires advancements in silicon and power management they expect intel to deliver the new capabilities in our roadmap so ecosystem partners can continue to provide innovative and efficient products with this optimization for hybrid we can jointly provide a strong foundation to take on the growth of data-centric workloads for data analytics and ai to build and deploy models faster to accelerate insights that will deliver additional transformation for organizations of all types the network transformation journey isn't easy we are continuing to unleash the capabilities of 5g and the power of the intelligent edge yeah the combination of the 5g built out and the massive new growth of data at the edge are the key drivers for the age of insight these new market drivers offer incredible new opportunities for our customers i am excited about recent launch of our new gen 10 plus portfolio with intel together we are laser focused on delivering joint innovation for customers that stretches from the edge to x scale how do you see new solutions that this helping our customers solve the toughest challenges today i talked earlier about the superpowers that are driving the rapid acceleration of digital transformation first the proliferation of the hybrid cloud is delivering new levels of efficiency and scale and the growth of the cloud is democratizing high-performance computing opening new frontiers of knowledge and discovery next we see ai and machine learning increasingly infused into every application from the edge to the network to the cloud to create dramatically better insights and the rapid adoption of 5g as i talked about already is fueling new use cases that demand lower latencies and higher bandwidth this in turn is pushing computing to the edge closer to where the data is created and consumed the confluence of these trends is leading to the biggest and fastest build out of computing in human history to keep pace with this rapid digital transformation we recognize that infrastructure has to be built with the flexibility to support a broad set of workloads and that's why over the last several years intel has built an unmatched portfolio to deliver every component of intelligent silicon our customers need to move store and process data from the cpus to fpgas from memory to ssds from ethernet to switch silicon to silicon photonics and software our 3rd gen intel xeon scalable processors and our data centric portfolio deliver new core performance and higher bandwidth providing our customers the capabilities they need to power these critical workloads and we love seeing all the unique ways customers like hpe leverage our technology and solution offerings to create opportunities and solve their most pressing challenges from cloud gaming to blood flow to brain scans to financial market security the opportunities are endless with flexible performance i am proud of the amazing innovation we are bringing to support our customers especially as they respond to new data-centric workloads like ai and analytics that are critical to digital transformation these new requirements create a need for compute that's warlord optimized for performance security ease of use and the economics of business now more than ever compute matters it is the foundation for this next wave of digital transformation by pairing our compute with our software and capabilities from hp green lake we can support our customers as they modernize their apps and data quickly they seamlessly and securely scale them anywhere at any size from edge to x scale but thank you for joining us for accelerating next today i know our audience appreciated hearing your perspective on the market and how we're partnering together to support their digital transformation journey i am incredibly excited about what lies ahead for hp and intel thank you thank you antonio great to be with you today we just compressed about a decade of online commerce progress into about 13 or 14 months so now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like and with me is alan jensen who's the chief information officer and senior vice president of the sawing group hello alan how are you fine thank you good to see you hey look you know when i look at the 100 year history plus of your company i mean it's marked by transformations and some of them are quite dramatic so you're denmark's largest retailer i wonder if you could share a little bit more about the company its history and and how it continues to improve the customer experience well at the same time keeping costs under control so vital in your business yeah yeah the company founded uh approximately 100 years ago with a department store in in oahu's in in denmark and i think in the 60s we founded the first supermarket in in denmark with the self-service and combined textile and food in in the same store and in beginning 70s we founded the first hyper market in in denmark and then the this calendar came from germany early in in 1980 and we started a discount chain and so we are actually building department store in hyber market info in in supermarket and in in the discount sector and today we are more than 1 500 stores in in three different countries in in denmark poland and germany and especially for the danish market we have a approximately 38 markets here and and is the the leader we have over the last 10 years developed further into online first in non-food and now uh in in food with home delivery with click and collect and we have done some magnetism acquisition in in the convenience with mailbox solutions to our customers and we have today also some restaurant burger chain and and we are running the starbuck in denmark so i can you can see a full plate of different opportunities for our customer in especially denmark it's an awesome story and of course the founder's name is still on the masthead what a great legacy now of course the pandemic is is it's forced many changes quite dramatic including the the behaviors of retail customers maybe you could talk a little bit about how your digital transformation at the sawing group prepared you for this shift in in consumption patterns and any other challenges that that you faced yeah i think uh luckily as for some of the you can say the core it solution in in 19 we just roll out using our computers via direct access so you can work from anywhere whether you are traveling from home and so on we introduced a new agile scrum delivery model and and we just finalized the rolling out teams in in in january february 20 and that was some very strong thing for suddenly moving all our employees from from office to to home and and more or less overnight we succeed uh continuing our work and and for it we have not missed any deadline or task for the business in in 2020 so i think that was pretty awesome to to see and for the business of course the pandemic changed a lot as the change in customer behavior more or less overnight with plus 50 80 on the online solution forced us to do some different priorities so we were looking at the food home delivery uh and and originally expected to start rolling out in in 2022 uh but took a fast decision in april last year to to launch immediately and and we have been developing that uh over the last eight months and has been live for the last three months now in the market so so you can say the pandemic really front loaded some of our strategic actions for for two to three years uh yeah that was very exciting what's that uh saying luck is the byproduct of great planning and preparation so let's talk about when you're in a company with some strong financial situation that you can move immediately with investment when you take such decision then then it's really thrilling yeah right awesome um two-part question talk about how you leverage data to support the solid groups mission and you know drive value for customers and maybe you could talk about some of the challenges you face with just the amount of data the speed of data et cetera yeah i said data is everything when you are in retail as a retailer's detail as you need to monitor your operation down to each store eats department and and if you can say we have challenge that that is that data is just growing rapidly as a year by year it's growing more and more because you are able to be more detailed you're able to capture more data and for a company like ours we need to be updated every morning as a our fully updated sales for all unit department single sku selling in in the stores is updated 3 o'clock in the night and send out to all top management and and our managers all over the company it's actually 8 000 reports going out before six o'clock every day in the morning we have introduced a loyalty program and and you are capturing a lot of data on on customer behavior what is their preferred offers what is their preferred time in the week for buying different things and all these data is now used to to personalize our offers to our cost of value customers so we can be exactly hitting the best time and and convert it to sales data is also now used for what we call intelligent price reductions as a so instead of just reducing prices with 50 if it's uh close to running out of date now the system automatically calculate whether a store has just enough to to finish with full price before end of day or actually have much too much and and need to maybe reduce by 80 before as being able to sell so so these automated [Music] solutions built on data is bringing efficiency into our operation wow you make it sound easy these are non-trivial items so congratulations on that i wonder if we could close hpe was kind enough to introduce us tell us a little bit about the infrastructure the solutions you're using how they differentiate you in the market and i'm interested in you know why hpe what distinguishes them why the choice there yeah as a when when you look out a lot is looking at moving data to the cloud but we we still believe that uh due to performance due to the availability uh more or less on demand we we still don't see the cloud uh strong enough for for for selling group uh capturing all our data we have been quite successfully having one data truth across the whole con company and and having one just one single bi solution and having that huge amount of data i think we have uh one of the 10 largest sub business warehouses in global and but on the other hand we also want to be agile and want to to scale when needed so getting close to a cloud solution we saw it be a green lake as a solution getting close to the cloud but still being on-prem and could deliver uh what we need to to have a fast performance on on data but still in a high quality and and still very secure for us to run great thank you for that and thank alan thanks so much for your for your time really appreciate your your insights and your congratulations on the progress and best of luck in the future thank you all right keep it right there we have tons more content coming you're watching accelerating next from hpe [Music] welcome lisa and thank you for being here with us today antonio it's wonderful to be here with you as always and congratulations on your launch very very exciting for you well thank you lisa and we love this partnership and especially our friendship which has been very special for me for the many many years that we have worked together but i wanted to have a conversation with you today and obviously digital transformation is a key topic so we know the next wave of digital transformation is here being driven by massive amounts of data an increasingly distributed world and a new set of data intensive workloads so how do you see world optimization playing a role in addressing these new requirements yeah no absolutely antonio and i think you know if you look at the depth of our partnership over the last you know four or five years it's really about bringing the best to our customers and you know the truth is we're in this compute mega cycle right now so it's amazing you know when i know when you talk to customers when we talk to customers they all need to do more and and frankly compute is becoming quite specialized so whether you're talking about large enterprises or you're talking about research institutions trying to get to the next phase of uh compute so that workload optimization that we're able to do with our processors your system design and then you know working closely with our software partners is really the next wave of this this compute cycle so thanks lisa you talk about mega cycle so i want to make sure we take a moment to celebrate the launch of our new generation 10 plus compute products with the latest announcement hp now has the broadest amd server portfolio in the industry spanning from the edge to exascale how important is this partnership and the portfolio for our customers well um antonio i'm so excited first of all congratulations on your 19 world records uh with uh milan and gen 10 plus it really is building on you know sort of our you know this is our third generation of partnership with epic and you know you are with me right at the very beginning actually uh if you recall you joined us in austin for our first launch of epic you know four years ago and i think what we've created now is just an incredible portfolio that really does go across um you know all of the uh you know the verticals that are required we've always talked about how do we customize and make things easier for our customers to use together and so i'm very excited about your portfolio very excited about our partnership and more importantly what we can do for our joint customers it's amazing to see 19 world records i think i'm really proud of the work our joint team do every generation raising the bar and that's where you know we we think we have a shared goal of ensuring that customers get the solution the services they need any way they want it and one way we are addressing that need is by offering what we call as a service delivered to hp green lake so let me ask a question what feedback are you hearing from your customers with respect to choice meaning consuming as a service these new solutions yeah now great point i think first of all you know hpe green lake is very very impressive so you know congratulations um to uh to really having that solution and i think we're hearing the same thing from customers and you know the truth is the compute infrastructure is getting more complex and everyone wants to be able to deploy sort of the right compute at the right price point um you know in in terms of also accelerating time to deployment with the right security with the right quality and i think these as a service offerings are going to become more and more important um as we go forward in the compute uh you know capabilities and you know green lake is a leadership product offering and we're very very you know pleased and and honored to be part of it yeah we feel uh lisa we are ahead of the competition and um you know you think about some of our competitors now coming with their own offerings but i think the ability to drive joint innovation is what really differentiate us and that's why we we value the partnership and what we have been doing together on giving the customers choice finally you know i know you and i are both incredibly excited about the joint work we're doing with the us department of energy the oak ridge national laboratory we think about large data sets and you know and the complexity of the analytics we're running but we both are going to deliver the world's first exascale system which is remarkable to me so what this milestone means to you and what type of impact do you think it will make yes antonio i think our work with oak ridge national labs and hpe is just really pushing the envelope on what can be done with computing and if you think about the science that we're going to be able to enable with the first exascale machine i would say there's a tremendous amount of innovation that has already gone in to the machine and we're so excited about delivering it together with hpe and you know we also think uh that the super computing technology that we're developing you know at this broad scale will end up being very very important for um you know enterprise compute as well and so it's really an opportunity to kind of take that bleeding edge and really deploy it over the next few years so super excited about it i think you know you and i have a lot to do over the uh the next few months here but it's an example of the great partnership and and how much we're able to do when we put our teams together um to really create that innovation i couldn't agree more i mean this is uh an incredible milestone for for us for our industry and honestly for the country in many ways and we have many many people working 24x7 to deliver against this mission and it's going to change the future of compute no question about it and then honestly put it to work where we need it the most to advance life science to find cures to improve the way people live and work but lisa thank you again for joining us today and thank you more most importantly for the incredible partnership and and the friendship i really enjoy working with you and your team and together i think we can change this industry once again so thanks for your time today thank you so much antonio and congratulations again to you and the entire hpe team for just a fantastic portfolio launch thank you okay well some pretty big hitters in those keynotes right actually i have to say those are some of my favorite cube alums and i'll add these are some of the execs that are stepping up to change not only our industry but also society and that's pretty cool and of course it's always good to hear from the practitioners the customer discussions have been great so far today now the accelerating next event continues as we move to a round table discussion with krista satrathwaite who's the vice president and gm of hpe core compute and krista is going to share more details on how hpe plans to help customers move ahead with adopting modern workloads as part of their digital transformations krista will be joined by hpe subject matter experts chris idler who's the vp and gm of the element and mark nickerson director of solutions product management as they share customer stories and advice on how to turn strategy into action and realize results within your business thank you for joining us for accelerate next event i hope you're enjoying it so far i know you've heard about the industry challenges the i.t trends hpe strategy from leaders in the industry and so today what we want to do is focus on going deep on workload solutions so in the most important workload solutions the ones we always get asked about and so today we want to share with you some best practices some examples of how we've helped other customers and how we can help you all right with that i'd like to start our panel now and introduce chris idler who's the vice president and general manager of the element chris has extensive uh solution expertise he's led hpe solution engineering programs in the past welcome chris and mark nickerson who is the director of product management and his team is responsible for solution offerings making sure we have the right solutions for our customers welcome guys thanks for joining me thanks for having us krista yeah so i'd like to start off with one of the big ones the ones that we get asked about all the time what we've been all been experienced in the last year remote work remote education and all the challenges that go along with that so let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environment uh so i i really think that there's a couple of things that have stood out for me when we're talking with customers about vdi first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why but what it really uncovered was how little planning had gone into this space around a couple of key dynamics one is scale it's one thing to say i'm going to enable vdi for a part of my workforce in a pre-pandemic environment where the office was still the the central hub of activity for work uh it's a completely different scale when you think about okay i'm going to have 50 60 80 maybe 100 of my workforce now distributed around the globe um whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning uh whether that's uh in the area of things like uh formula one racing where we had uh the desire to still have events going on but the need for a lot more social distancing not as many people able to be trackside but still needing to have that real-time experience this really manifested in a lot of ways and scale was something that i think a lot of customers hadn't put as much thought into initially the other area is around planning for experience a lot of times the vdi experience was planned out with very specific workloads or very specific applications in mind and when you take it to a more broad-based environment if we're going to support multiple functions multiple lines of business there hasn't been as much planning or investigation that's gone into the application side and so thinking about how graphically intense some applications are one customer that comes to mind would be tyler isd who did a fairly large roll out pre-pandemic and as part of their big modernization effort what they uncovered was even just changes in standard windows applications had become so much more graphically intense with windows 10 with the latest updates with programs like adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than than they had counted on so in addition to planning for scale you also need to have that visibility into what are the actual applications that are going to be used by these remote users how graphically intense those might be what's the login experience going to be as well as the operating experience and so really planning through that experience side as well as the scale and the number of users uh is is kind of really two of the biggest most important things that i've seen yeah mark i'll i'll just jump in real quick i think you you covered that pretty comprehensively there and and it was well done the couple of observations i've made one is just that um vdi suddenly become like mission critical for sales it's the front line you know for schools it's the classroom you know that this isn't a cost cutting measure or a optimization nit measure anymore this is about running the business in a way it's a digital transformation one aspect of about a thousand aspects of what does it mean to completely change how your business does and i think what that translates to is that there's no margin for error right you really need to deploy this in a way that that performs that understands what you're trying to use it for that gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be whether it's a racetrack classroom or on the other end of a conference call or a boardroom right so what we do in in the engineering side of things when it comes to vdi or really understand what's a tech worker what's a knowledge worker what's a power worker what's a gp really going to look like what's time of day look like you know who's using it in the morning who's using it in the evening when do you power up when do you power down does the system behave does it just have the it works function and what our clients can can get from hpe is um you know a worldwide set of experiences that we can apply to making sure that the solution delivers on its promises so we're seeing the same thing you are krista you know we see it all the time on vdi and on the way businesses are changing the way they do business yeah and it's funny because when i talk to customers you know one of the things i heard that was a good tip is to roll it out to small groups first so you could really get a good sense of what the experience is before you roll it out to a lot of other people and then the expertise it's not like every other workload that people have done before so if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way okay one of the other things we've been talking a lot about today is digital transformation and moving to the edge so now i'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time i'll start with chris all right hey thanks okay so you know it's funny when it comes to edge because um the edge is different for for every customer in every client and every single client that i've ever spoken to of hp's has an edge somewhere you know whether just like we were talking about the classroom might be the edge but but i think the industry when we're talking about edge is talking about you know the internet of things if you remember that term from not to not too long ago you know and and the fact that everything's getting connected and how do we turn that into um into telemetry and and i think mark's going to be able to talk through a couple of examples of clients that we have in things like racing and automotive but what we're learning about edge is it's not just how do you make the edge work it's how do you integrate the edge into what you're already doing and nobody's just the edge right and and so if it's if it's um ai mldl there's that's one way you want to use the edge if it's a customer experience point of service it's another you know there's yet another way to use the edge so it turns out that having a broad set of expertise like hpe does to be able to understand the different workloads that you're trying to tie together including the ones that are running at the at the edge often it involves really making sure you understand the data pipeline you know what information is at the edge how does it flow to the data center how does it flow and then which data center uh which private cloud which public cloud are you using i think those are the areas where where we really sort of shine is that we we understand the interconnectedness of these things and so for example red bull and i know you're going to talk about that in a minute mark um uh the racing company you know for them the the edge is the racetrack and and you know milliseconds or partial seconds winning and losing races but then there's also an edge of um workers that are doing the design for for the cars and how do they get quick access so um we have a broad variety of infrastructure form factors and compute form factors to help with the edge and this is another real advantage we have is that we we know how to put the right piece of equipment with the right software we also have great containerized software with our esmeral container platform so we're really becoming um a perfect platform for hosting edge-centric workloads and applications and data processing yeah it's uh all the way down to things like our superdome flex in the background if you have some really really really big data that needs to be processed and of course our workhorse proliance that can be configured to support almost every um combination of workload you have so i know you started with edge krista but but and we're and we nail the edge with those different form factors but let's make sure you know if you're listening to this this show right now um make sure you you don't isolate the edge and make sure they integrate it with um with the rest of your operation mark you know what did i miss yeah to that point chris i mean and this kind of actually ties the two things together that we've been talking about here but the edge uh has become more critical as we have seen more work moving to the edge as where we do work changes and evolves and the edge has also become that much more closer because it has to be that much more connected um to your point uh talking about where that edge exists that edge can be a lot of different places but the one commonality really is that the edge is is an area where work still needs to get accomplished it can't just be a collection point and then everything gets shipped back to a data center or back to some some other area for the work it's where the work actually needs to get done whether that's edge work in a use case like vdi or whether that's edge work in the case of doing real-time analytics you mentioned red bull racing i'll i'll bring that up i mean you talk about uh an area where time is of the essence everything about that sport comes down to time you're talking about wins and losses that are measured as you said in milliseconds and that applies not just to how performance is happening on the track but how you're able to adapt and modify the needs of the car uh adapt to the evolving conditions on the track itself and so when you talk about putting together a solution for an edge like that you're right it can't just be here's a product that's going to allow us to collect data ship it back someplace else and and wait for it to be processed in a couple of days you have to have the ability to analyze that in real time when we pull together a solution involving our compute products our storage products our networking products when we're able to deliver that full package solution at the edge what you see are results like a 50 decrease in processing time to make real-time analytic decisions about configurations for the car and adapting to to real-time uh test and track conditions yeah really great point there um and i really love the example of edge and racing because i mean that is where it all every millisecond counts um and so important to process that at the edge now switching gears just a little bit let's talk a little bit about some examples of how we've helped customers when it comes to business agility and optimizing their workload for maximum outcome for business agility let's talk about some things that we've done to help customers with that mark yeah give it a shot so when we when we think about business agility what you're really talking about is the ability to to implement on the fly to be able to scale up to scale down the ability to adapt to real time changing situations and i think the last year has been has been an excellent example of exactly how so many businesses have been forced to do that i think one of the areas that that i think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds if you take a look at the need that customers have to to be able to migrate workloads and migrate data between public cloud environments app development environments that may be hosted on-site or maybe in the cloud the ability to move out of development and into production and having the agility to then scale those application rollouts up having the ability to have some of that some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers all right well i we could keep going on and on but i'll stop it there uh thank you so much uh chris and mark this has been a great discussion thanks for sharing how we helped other customers and some tips and advice for approaching these workloads i thank you all for joining us and remind you to look at the on-demand sessions if you want to double click a little bit more into what we've been covering all day today you can learn a lot more in those sessions and i thank you for your time thanks for tuning in today many thanks to krista chris and mark we really appreciate you joining today to share how hpe is partnering to facilitate new workload adoption of course with your customers on their path to digital transformation now to round out our accelerating next event today we have a series of on-demand sessions available so you can explore more details around every step of that digital transformation from building a solid infrastructure strategy identifying the right compute and software to rounding out your solutions with management and financial support so please navigate to the agenda at the top of the page to take a look at what's available i just want to close by saying that despite the rush to digital during the pandemic most businesses they haven't completed their digital transformations far from it 2020 was more like a forced march than a planful strategy but now you have some time you've adjusted to this new abnormal and we hope the resources that you find at accelerating next will help you on your journey best of luck to you and be well [Music] [Applause] [Music] 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(upbeat music) >> We just compressed about a decade of online commerce progress into about 13 or 14 months. So now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like. And with me is Alan Jensen who is the chief information officer and senior vice president of the Salling Group. Hello, Alan, how are you? >> Fine, thank you. >> Good to see you. Look, you know, when I look at the hundred year history plus of your company, I mean, it's a marked by transformations and some of them are quite dramatic. So you're Denmark's largest retailer. I wonder if you could share a little bit more about the company its history and how it continues to improve the customer experience while at the same time keeping costs under control so vital in your business. >> Yeah, the company founded approximately 100 year ago with a department store in Denmark. And I think in the 60s we founded the first supermarket in Denmark with the self-service and combined textile and food in the same store. And in the beginning 70s, we found that the first hypermarket in Denmark and then the discounter came from Germany early in 1980 and we started a discount chain. And so we are actually building department store in hypermarket in supermarket, and in the discount sector. And today we are more than 1,500 stores in three different countries in Denmark, Poland, and Germany. And especially for the Danish market we have a approximately 38% market share and it is the leader. We have over the last 10 years developed further into online first in non-food and now in food with home delivery with Clayton Calais. And we have done some acquisition in the convenience with me box solutions to our customers. And we have today also some restaurant burger chain and we are running the Starbucks in Denmark. So you can see a full plate of different opportunities for our customer in especially Denmark. >> It's an awesome story. And of course the founder's name is still on the masthead. What a great legacy. Now, of course the pandemic has forced many changes quite dramatic including the behaviors of retail customers. Maybe you could talk a little bit about how your digital transformation at the Salling Group prepared you for this shift in consumption patterns and any other challenges that you faced. >> I think luckily as for some of the you can say the coati solution in 19 we just roll out using our computers. We are direct access, so you can work from anywhere whether you are traveling from home and so on. We introduced a new age from delivery model and we just finalized the rolling out teams in January, February 20. And that was some very strong thing for suddenly moving all our employees from office to home and more or less overnight we succeed continuing our work and for IT We have not missed any deadline or task for the business in 2020. So I think that was a pretty awesome to see. And for the business, of course the pandemic changed a lot as the change in customer behavior, more or less overnight with plus 50, 80% on the online solution forced us to do some different priorities as we were looking at food home delivery and originally expected to start rolling out in 2022 but took a fast decision in April last year to launch immediately. And we have been developing that over the last eight months and has been live for the last three months now in the market. So you can say the pandemic really front-loaded some of our strategic actions for two to three years. >> What's that saying? Luck is the by-product of great planning and preparation. So let's talk about... what happened? >> And when you are in a company with some strong financial situation that you can move immediately with investment when you take such a decision, then it's really failing yeah. >> Right, awesome. Two-part question. Talk about how you leverage data to support the Solent group's mission and you know drive value for customers. And maybe you could talk about some of the challenges you face with just the amount of data, the speed of data, et cetera. >> Yeah, I said data is everything when you are in retail, as retail is detail as you need to monitor your operation down to each store each department. And if you can say, we have challenged that data is just growing rapidly as a year by year it's growing more and more because you're able to be more detailed, you're able to capture more data. And for a company like ours we need to be updated every morning as our fully updated sales for all unit department single skew selling in the stores is updated three o'clock in the night and send out to all top management and our managers all over the company. It's actually 8,000 reports going out before six o'clock every day in the morning. We have introduced a loyalty program and we are capturing a lot of data on customer behavior. What is their preferred of us? What is their preferred time in the week for buying different things. And all these data is now used to personalize our offers to our value customers. So we can be exactly hitting the best time and convert it to sales. Data is also now used for what we call intelligent price reductions so instead of just reducing prices with 50% if it's a close to running out of date now the system automatically calculate whether a store has just enough to finish with full price before end of day, or actually have too much and need to maybe reduce by 80% before. So being able to sell. So these automated solutions build on data is bringing efficiency into our operation. >> Wow, you make it sound easy. These are non-trivial items. So congratulations on that. I wonder if we could close HPE was kind enough to introduce us, tell us a little bit about the infrastructure of the solutions you're using how they differentiate you in the market. And I'm interested in you know why HPE what distinguishes them, why they choose there. >> When you look out a lot is looking at moving data to the cloud, but we still believe that due to performance, due to the availability, more or less on demand, we still don't see the cloud strong enough for Salling Group capturing all our data. We have been quite successfully having one data truth across the whole company and having one just one single BI solution and having that huge amount of data. I think we have one of the 10 largest sub business warehouses global. And on the other hand we also want to be agile and want to scale when needed. So getting close to a cloud solution, we saw it be GreenLake as a solution, getting close to the cloud but still being on-prem and could deliver what we need to have fast performance on data, but still in a high quality and still very secure for us to run. >> Great, thank you for that. Alan thanks so much for your time really appreciate your insights and congratulations on the progress and best of luck in the future. >> Thank you. >> All right, keep it right there. We have tons more content coming. You're watching Accelerating Next from HPE. (upbeat music)

(upbeat music) >> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online brought to you by Amazon Web Services. >> Welcome back to theCUBE's coverage of AWS Public Sector Summit Online. I'm John Furrier, your host of theCUBE. I wish we could be there in person, but we're doing remote because of the COVID and the pandemic. We've got a great guest, Paul Grist. Worldwide Public Sector, Head of Education International for AWS. Paul, thank you for coming on remotely. >> Great to be here, John. >> There's a lot of disruption in the education space this year with universities and schools still uncertain about what the future will look like. What are some of the biggest trends you're seeing? >> John, what we've seen is the rapid adoption of technology and the growth of flexible online learning, learning that can take place anytime, anywhere. What we've seen is universities, national education systems, and schools rapidly migrating systems and content to the cloud, spinning up new applications. And we've seen companies that provide technology and content and platforms, the ed techs and publishers of the world, increasing their capacity, increasing their capability to deliver new applications to education. >> What is some of this research that you're finding out there? >> Yeah. You know, a time of much change and things happening very, very fast. We responded fast to the changes, John. Got a load of customer conversations together, looking at speeches by educationalists who were responding to the changes at some of the online events that spun up very quickly at places like the University of Buckingham, ASU, JSV, Inside Higher Education, places like Blackboard World. And really just talked to those leaders about their responses to the change, what kinds of things they were doing, and brought that together into the research. It's underpinned by some in-depth research and insights from education reports and articles too. >> Thanks Paul, really appreciate it. Having that research is critical. I know you guys do a lot of work on that. I know you got some news, take a quick plug for the new research that's coming out. You guys just put out today, just take a minute to quickly explain what it's about and how to find it. >> We're publishing today some new research that shows the seven key emerging trends in this new world of education. Check it out on the AWS website. Two key trends, flexible learning and the new world of employability. >> So you guys got a lot of data. It's great with Amazon, got a lot of customers. Good to see you guys getting that research. The question I have for you Paul is, what amount of the research shows really the COVID situation? Because there's before COVID, there's kind of during, and then there's going to be a post-COVID mode. Was that prior research in place with COVID or after COVID? Can you share kind of the update on the relevance of your research? >> Yeah, I think the sector has changed. The sector has gone through the fastest change it's ever gone through. And undoubtedly most of the issues, most of the challenges and opportunities in the sector, predate the pandemic. But what we've seen is COVID accelerate many of the challenges and the opportunities, but also bring new opportunities. >> Yeah, one of the things we've seen with education is the disruption, and the forcing function with COVID. There's a problem, we all know what it is. It's important, there's consequences for those. And you can quantify the disruption with real business value and certainly student impact. There's been downsides with remote education. More teacher-parent involvement and students having to deal with isolation, less social interaction. How do you guys see that? Or what is Amazon doing to solve these problems? Can you talk about that? >> Yeah. I think you know, education is very much a people business. And what we've been trying to do is partner with organizations to ensure that the people are kept at the center of the business. So working with organizations such as LS, sorry, Los Angeles United School District in the US to spin up a call center to allow students to contact their tutors. And parents to interact with tutors, to get questions answered. >> So one of the challenges these academic institutions are facing is speed, it's pace of change. What's going on with competition? How are they competing? How are universities and colleges staying relevant? Obviously there's a financial crisis involved. There's also the actual delivery aspect of it. More and more mergers. You're starting to see ecosystem changes. Can you talk about what's going on in the educational ecosystem? >> Yeah I mean, educational institutions are being forced to rethink their business models. It's an international marketplace in higher education. It's been a growing marketplace for many, many years. That suddenly stopped overnight, so every university has had to rethink about where their revenues are coming from, where the students are coming from. There's been some surprises too. I mean in the UK, actually international enrollments are up post-COVID because one of the strange side effects of COVID is without being able to travel, there's actually a cost saving for students. And so we've seen universities in the UK benefit from students who want to study, perhaps travel and the cost of study was too high previously. Now being able to study remotely. It's an unexpected and unintended consequence. But it kind of shows how there are opportunities for all organizations during this time. >> Many countries had to cancel exams altogether this year, which has been a big, huge problem. I mean people are outraged and people want to learn. It's been, you know, the silver lining in all this is that you have the internet (laughs). You have the cloud. I want to get your thoughts. How are universities and schools dealing with this challenge? Because you have a multi-sided marketplace. You've got the institutions, you've got the students, you got the educators, they all have to be successful. How are universities dealing with this challenge? >> Yeah I think, you know, teaching and learning has been online for 20, 30 years. And I think a lot of organizations have adopted online teaching and learning. But I think assessment is the one big area of education that remains to be made available at scale at low cost. So most assessment is still a pen-and-paper-based. There's big trust and identity issues. And what we're seeing through this COVID change is organizations really getting to grip with both of those issues. So, having the confidence to put assessment online, to make it available at scale, and then also having the confidence to tackle trust and identity questions. So who is taking the exam, where are they sitting? Can we be sure that it's actually that person taking that exam? So you know, the rise of things like proctoring technologies giving organizations the opportunity to assess remotely. >> How has this crisis affected research at academic institutions? Because certainly we know that if you need a lab or something, certainly we're seeing students need to be physically in person. But with remote and all those changes going on with the scale and the pace of change, how has research at academic institutions been impacted? >> Yeah I mean, research has always been a really collaborative activity, but we've seen that collaboration increase. It's had to increase. Researchers have had to go remote. Many of them work in labs. They haven't been able to do that. They've needed to spin up applications and new technologies in the cloud to continue working. But what we're seeing is governments taking an increased interest in the research being applicable, making sure that it leads to innovation which is meaningful. Getting much more involved and insisting that the research is made available now. And of course there's no place that that's clearer than in health research and trying to find a cure for COVID. And then secondly, we're seeing that research is becoming much more collaborative not just across institutions but also countries. So one of the great projects we're involved in at the moment is with the University of Adelaide who are collaborating with researchers from the Breeding and Acclimatization Institute in Poland on a project to study the increase in crop yield of wheat. >> One of the things that's coming out of this, whether it's research or students is open online courses, virtual capabilities. But a concept called stackable learning. Can you explain what that is? >> Yeah. We're in a global marketplace in education and there's increased competition between universities and education providers to make new types of certificates and online badges available. We know that employers are looking for ever more agile methods of scaling and upskilling. And stackable learning is a concept that's been around for a couple of decades now, where learning is broken down into smaller chunks, put together in a more personalized way from a number of different providers. Spun up very, very quickly to respond to need and then delivered to students. We're seeing some of the big providers like edX and Coursera who, again have been around for over a decade become really prominent in the provision of some of these stackable credentials. Their systems run on the cloud. They're easy to access, in many, many cases they're free. We're seeing an increasing number of employers and education institutions adopt and embed these types of delivery systems into their curriculum. >> Totally a fan of stackable learning, it's called the Lego model, whatever I call it. But also online brings the nonlinear progressions. The role of data is super important. So I'm very bullish on education being disrupted by cloud providers and new apps. So you know, I wanted to call that out because I think it's super important. Let me get to a really important piece that it has to be addressed, and I want to get your thoughts on. Cyber security. Okay, cyber attacks and privacy of students are two areas that are super important for institutions to address. What's your reaction to that? >> Yeah, I mean the use of more technology becomes, you know again, a target for cyber attack and unfortunately it's an increasing phenomenon. Simply put, every organization needs to put security first. Needs to operate as a security-first organization. They need to adopt technologies, people and processes that can protect their investments. And work with data management vendors, cloud vendors who've got the compliances and the common privacy and security frameworks such as GDPR in place to make sure that they provide secure services. AWS's security offerings include auditing, login and identity management, data encryption capabilities that offer more transparency and control, to allow institutions protect student data. >> Super important, thanks for sharing. Finally, what's the steps institutions can take to close the digital divide because now some people are taking gap years. Research is changing. People might not even have PCs or internet connections. There's still, this exposes the haves and have nots. What steps can institutions take to do their part? >> Yeah, digital learning is here to stay, John. We've learned that many learners do not have access to technology necessary for online learning. Whether those are devices or a reliable internet connection. But again, you know governments, states, educational authorities have all turned their attention to these issues over the last few months. And we're seeing organizations partner with technology providers that can provide internet connections. Partners in AWS, such as Kajeet who've installed hotspot devices on buses to deploy in areas with no connectivity. You know whether that's a place like Denver, Colorado or whether it's a place, you know, in Nigeria in Africa, remote connection remains a problem everywhere. And we're seeing everybody addressing that issue now. >> Paul, great to have you on theCUBE and sharing your insights on what's going on in international education. Final question for you. In your own words, why is this year at the AWS Public Sector Summit Online important? What's the most important story that people should walk away in this educational industry? >> The most important story, John, is it's a time of incredible change but also incredible opportunity. And we're seeing organizations who have wanted to change, who've wanted to deliver more to their students, who want to deliver a greater experience, who want to access more students and have much greater reach. Now with the appetite to do that. re:Invent is a great opportunity to work with AWS, to understand what's going on with our partners, with our customers. And look at some of the common solutions for the challenges that they're looking to solve. >> Paul Grist, thank you for coming on theCUBE. Really appreciate it. Worldwide Head of Education for International AWS. Thank you for sharing. >> Thanks John, great to be here. >> Okay, this is theCUBE's coverage of AWS Public Sector Online Summit. Remote, virtual, this is theCUBE virtual. I'm John Furrier, your host. Thanks for watching. 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>> From around the globe, it's theCUBE, with digital coverage of VMworld 2020, brought to you by the VMworld and its ecosystem partners. >> I'm Stu Miniman, and welcome back to theCUBES coverage of VMworld 2020, our 11th year doing this show, of course, the global virtual event. And what do we love talking about on theCUBE? We love talking to customers. It is a user conference, of course, so really happy to welcome to the program. From the University of Pisa, the Chief Technology Officer Maurizio Davini and joining him is Thierry Pellegrini, one of our theCUBE alumni. He's the vice president of worldwide, I'm sorry, Workload Solutions and HPC with Dell Technologies. Thierry, thank you so much for joining us. >> Thanks too. >> Thanks to you. >> Alright, so let, let's start. The University of Pisa, obviously, you know, everyone knows Pisa, one of the, you know, famous city iconic out there. I know, you know, we all know things in Europe are a little bit longer when you talk about, you know, some of the venerable institutions here in the United States, yeah. It's a, you know, it's a couple of hundred years, you know, how they're using technology and everything. I have to imagine the University of Pisa has a long storied history. So just, if you could start before we dig into all the tech, give us our audience a little bit, you know, if they were looking up on Wikipedia, what's the history of the university? >> So University of Pisa is one of the oldest in the world because there has been founded in 1343 by a pope. We were authorized to do a university teaching by a pope during the latest Middle Ages. So it's really one of the, is not the oldest of course, but the one of the oldest in the world. It has a long history, but as never stopped innovating. So anything in Pisa has always been good for innovating. So either for the teaching or now for the technology applied to a remote teaching or a calculation or scientific computing, So never stop innovating, never try to leverage new technologies and new kind of approach to science and teaching. >> You know, one of your historical teachers Galileo, you know, taught at the university. So, you know, phenomenal history help us understand, you know, you're the CTO there. What does that encompass? How, you know, how many students, you know, are there certain areas of research that are done today before we kind of get into the, you know, the specific use case today? >> So consider that the University of Pisa is a campus in the sense that the university faculties are spread all over the town. Medieval like Pisa poses a lot of problems from the infrastructural point of view. So, we have bought a lot in the past to try to adapt the Medieval town to the latest technologies advancement. Now, we have 50,000 students and consider that Pisa is a general partners university. So, we cover science, like we cover letters in engineering, medicine, and so on. So, during the, the latest 20 years, the university has done a lot of effort to build an infrastructure that was able to develop and deploy the latest technologies for the students. So for example, we have a private fiber network covering all the town, 65 kilometers of a dark fiber that belongs to the university, four data centers, one big and three little center connected today at 200 gigabit ethernet. We have a big data center, big for an Italian University, of course, and not Poland and U.S. university, where is, but also hold infrastructure for the enterprise services and the scientific computing. >> Yep, Maurizio, it's great that you've had that technology foundation. I have to imagine the global pandemic COVID-19 had an impact. What's it been? You know, how's the university dealing with things like work from home and then, you know, Thierry would love your commentary too. >> You know, we, of course we were not ready. So we were eaten by the pandemic and we have to adapt our service software to transform from imperson to remote services. So we did a lot of work, but we are able, thanks to the technology that we have chosen to serve almost a 100% of our curriculum studies program. We did a lot of work in the past to move to virtualization, to enable our users to work for remote, either for a workstation or DC or remote laboratories or remote calculation. So virtualization has designed in the past our services. And of course when we were eaten by the pandemic, we were almost ready to transform our service from in person to remote. >> Yeah, I think it's, it's true, like Maurizio said, nobody really was preparing for this pandemic. And even for, for Dell Technologies, it was an interesting transition. And as you can probably realize a lot of the way that we connect with customers is in person. And we've had to transition over to modes or digitally connecting with customers. We've also spent a lot of our energy trying to help the community HPC and AI community fight the COVID pandemic. We've made some of our own clusters that we use in our HPC and AI innovation center here in Austin available to genomic research or other companies that are fighting the the virus. And it's been an interesting transition. I can't believe that it's already been over six months now, but we've found a new normal. >> Detailed, let's get in specifically to how you're partnering with Dell. You've got a strong background in the HPC space, working with supercomputers. What is it that you're turning to Dell in their ecosystem to help the university with? >> So we are, we have a long history in HPC. Of course, like you can imagine not to the biggest HPC like is done in the U.S. so in the biggest supercomputer center in Europe. We have several system for doing HPC. Traditionally, HPC that are based on a Dell Technologies offer. We typically host all kind of technology's best, but now it's available, of course not in a big scale but in a small, medium scale that we are offering to our researcher, student. We have a strong relationship with Dell Technologies developing together solution to leverage the latest technologies, to the scientific computing, and this has a lot during the research that has been done during this pandemic. >> Yeah, and it's true. I mean, Maurizio is humble, but every time we have new technologies that are to be evaluated, of course we spend time evaluating in our labs, but we make it a point to share that technology with Maurizio and the team at the University of Pisa, That's how we find some of the better usage models for customers, help tuning some configurations, whether it's on the processor side, the GPU side, the storage and the interconnect. And then the topic of today, of course, with our partners at VMware, we've had some really great advancements Maurizio and the team are what we call a center of excellence. We have a few of them across the world where we have a unique relationship sharing technology and collaborating on advancement. And recently Maurizio and the team have even become one of the VMware certified centers. So it's a great marriage for this new world where virtual is becoming the norm. >> But well, Thierry, you and I had a conversation to talk earlier in the year when VMware was really geering their full kind of GPU suite and, you know, big topic in the keynote, you know, Jensen, the CEO of Nvidia was up on stage. VMware was talking a lot about AI solutions and how this is going to help. So help us bring us in you work with a lot of the customers theory. What is it that this enables for them and how to, you know, Dell and VMware bring, bring those solutions to bear? >> Yes, absolutely. It's one statistic I'll start with. Can you believe that only on average, 15 to 20% of GPU are fully utilized? So, when you think about the amount of technology that's are at our fingertips and especially in a world today where we need that technology to advance research and scientistic discoveries. Wouldn't it be fantastic to utilize those GPU's to the best of our ability? And it's not just GPU's , I think the industry has in the IT world, leverage virtualization to get to the maximum recycles for CPU's and storage and networking. Now you're bringing the GPU in the fold and you have a perfect utilization and also flexibility across all those resources. So what we've seen is that convergence between the IT world that was highly virtualized, and then this highly optimized world of HPC and AI because of the resources out there and researchers, but also data scientists and company want to be able to run their day to day activities on that infrastructure. But then when they have a big surge need for research or a data science use that same environment and then seamlessly move things around workload wise. >> Yeah, okay I do believe your stat. You know, the joke we always have is, you know, anybody from a networking background, there's no such thing as eliminating a bottleneck, you just move it. And if you talk about utilization, we've been playing the shell game for my entire career of, let's try to optimize one thing and then, oh, there's something else that we're not doing. So,you know, so important. Retail, I want to hear from your standpoint, you know, virtualization and HPC, you know, AI type of uses there. What value does this bring to you and, you know, and key learnings you've had in your organization? >> So, we as a university are a big users of the VMware technologies starting from the traditional enterprise workload and VPI. We started from there in the sense that we have an installation quite significant. But also almost all the services that the university gives to our internal users, either personnel or staff or students. At a certain point that we decided to try to understand the, if a VMware virtualization would be good also for scientific computing. Why? Because at the end of the day, their request that we have from our internal users is flexibility. Flexibility in the sense of be fast in deploying, be fast to reconfiguring, try to have the latest beats on the software side, especially on the AI research. At the end of the day we designed a VMware solution like you, I can say like a whiteboard. We have a whiteboard, and we are able to design a new solution of this whiteboard and to deploy as fast as possible. Okay, what we face as IT is not a request of the maximum performance. Our researchers ask us for flexibility then, and want to be able to have the maximum possible flexibility in configuring the systems. How can I say I, we can deploy as more test cluster on the visual infrastructure in minutes or we can use GPU inside the infrastructure tests, of test of new algorithm for deep learning. And we can use faster storage inside the virtualization to see how certain algorithm would vary with our internal developer can leverage the latest, the beat in storage like NVME, MVMS or so. And this is why at the certain point, we decided to try visualization as a base for HPC and scientific computing, and we are happy. >> Yeah, I think Maurizio described it it's flexibility. And of course, if you think optimal performance, you're looking at the bare medal, but in this day and age, as I stated at the beginning, there's so much technology, so much infrastructure available that flexibility at times trump the raw performance. So, when you have two different research departments, two different portions, two different parts of the company looking for an environment. No two environments are going to be exactly the same. So you have to be flexible in how you aggregate the different components of the infrastructure. And then think about today it's actually fantastic. Maurizio was sharing with me earlier this year, that at some point, as we all know, there was a lot down. You could really get into a data center and move different cables around or reconfigure servers to have the right ratio of memory, to CPU, to storage, to accelerators, and having been at the forefront of this enablement has really benefited University of Pisa and given them that flexibility that they really need. >> Wonderful, well, Maurizio my understanding, I believe you're giving a presentation as part of the activities this week. Give us a final glimpses to, you know, what you want your peers to be taking away from what you've done? >> What we have done that is something that is very simple in the sense that we adapt some open source software to our infrastructure in order to enable our system managers and users to deploy HPC and AI solution fastly and in an easy way to our VMware infrastructure. We started doing a sort of POC. We designed the test infrastructure early this year and then we go fastly to production because we had about the results. And so this is what we present in the sense that you can have a lot of way to deploy Vitola HPC, Barto. We went for a simple and open source solution. Also, thanks to our friends of Dell Technologies in some parts that enabled us to do the works and now to go in production. And that's theory told before you talked to has a lot during the pandemic due to the effect that stay at home >> Wonderful, Thierry, I'll let you have the final word. What things are you drawing customers to, to really dig in? Obviously there's a cost savings, or are there any other things that this unlocks for them? >> Yeah, I mean, cost savings. We talked about flexibility. We talked about utilization. You don't want to have a lot of infrastructure sitting there and just waiting for a job to come in once every two months. And then there's also the world we live in, and we all live our life here through a video conference, or at times through the interface of our phone and being able to have this web based interaction with a lot of infrastructure. And at times the best infrastructure in the world, makes things simpler, easier, and hopefully bring science at the finger tip of data scientists without having to worry about knowing every single detail on how to build up that infrastructure. And with the help of the University of Pisa, one of our centers of excellence in Europe, we've been innovating and everything that's been accomplished for, you know at Pisa can be accomplished by our customers and our partners around the world. >> Thierry, Maurizio, thank you much for so much for sharing and congratulations on all I know you've done building up that COE. >> Thanks to you. >> Thank you. >> Stay with us, lots more covered from VMworld 2020. I'm Stu Miniman as always. Thank you for watching the theCUBE. 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>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome to the Cube's coverage of HP Discover 2020 Virtual Experience. I'm Lisa Martin, and I'm pleased to be joined by two guests from HP longtime partner Tech Data. We have calling Blair the vice president of sales and marketing of I. O. T. And Data Solutions and David Smith, H P E Pre Sales Field Solutions are common. And David, Welcome to the Cube. Thanks, Lisa. Great to see. So let's start with the calling. HP and Technical have been partners for over 40 years, but tell our audience a little bit about tech data before we get into the specifics of what you're doing and some of the cool I o. T. Stuff with HP. I >>think that the Tech data is a Fortune 100 distributor. We continued to evolved to be a solutions aggregator in these next generation technology businesses. As you've mentioned, we've been serving the I T distribution markets globally for for 40 plus years, and we're now moving into next generation technologies like Wild Analytics, I O. T and Security bubble Lifecycle Management services. But to be able todo position ourselves with our customer base and the needs of their clients have. So I'm excited to be here today to talk a little bit about what we're doing in I, O. T. And Analytics with David on the HPC side >>and in addition to the 40 plus years of partnership calling that you mentioned that Detected and HP have you've got over 200 plus hp. Resource is David, you're one of those guys in the field. Talk to us about some of the things that you're working on with Channel Partners Table David to enable them, especially during such crazy times of living and now >>absolutely, absolutely so. What we can do is we can provide strong sales and technical enablement if your team, for example, wants to better understand how to position HP portfolio if they require assistance and architect ing a secure performance i o t. Solution. We can help ensure that you're technical team is fully capable of having that conversation, and it's one that they're able to have of confidence, weaken validate the proposed HP solutions with the customers, technical requirements and proposed use case. We can even exist on a customer calls, if it would, would benefit our partner to kind of extend out to that. We also have a a a deep technical bench that Colin can speak to in the OT space toe lean on as well. For so solution is that kind of span into the space beyond where HP typically operates, which would be edge, compute computing and network. Sic security. >>Excellent call and tell me a little bit about Tech Data's investments in I o. T. When did this start? What are you guys doing today? >>Sure, we started in the cloud space. First tackle this opportunity in data center modernization and hybrid cloud. That was about seven years ago. Shortly thereafter we started investing very materially in the security cyber security space. And then we follow that with Data Analytics and then the Internet of things. Now we've been in those spaces with our long term partners for some time. But now that we're seeing this movement to the intelligent edge and a real focus on business outcomes and specialization, we've kind of tracked with the market, and we feel like we've invested a little bit ahead of where the channel is in terms of supporting our ecosystem of partners in this space. >>So the intelligent edge has been growing for quite some time. Poland in the very unique times that we're living in in 2020 how are you seeing that intelligent edge expand even more? And what are some of the pressing opportunities that tech data and HPC i O T solutions together can address? >>So a couple. So the first is a Xai mentioned earlier just data center modernization. And so, in the middle of code 19 and perhaps postcode 19 we're going to see a lot of clients that are really focused on monetizing the things that they've got. But doing so to drive business outcomes. We believe that increasingly, the predominance of use cases and compute and analytics is going to move to the edge. And HP has got a great portfolio for not just on premise high performance computing but also hybrid cloud computing. And then when we get into the edge with edge line and networking with Aruba and devices that need to be a digitized and sense arised, it's a really great partnership. And then what we're able to do also, Lisa, is we've been investing in vertical markets since 2000 and seven, and I've been a long the ride with that team, most all of that way. So we've got deep specialization and healthcare and industrial manufacturing, retail and then public sector. And then the last thing we've kind of turned on here recently just last month is a strategic partnership in the smarter cities space. So we're able to leverage a lot of those vertical market capabilities. Couple that with our HP organization and really drive specialized repeatable solutions in these vertical markets, where we believe increasingly, customers are going to be more interested in a repeatable solutions that can drive quick proof of value proof of concepts with minimal viable what kinds of products. And that's that's kind of the apartment today with RHB Organization and the HP Corporation >>David. Let's double click into some of those of vertical markets that Colin mentioned some of the things that pop into minor healthcare manufacturing. As we know, supply chains have been very challenged during covered. Give us an insight into what you're hearing from channel partners now virtually, but what are some of the things that are pressing importance? >>So from a pressing and important to Collins exact point, and your exact point as well is really it's all about the edge computing space now from a product perspective Azaz Colin had mentioned earlier. HP has their edge line converged systems, which is kind of taking the functionality of OT and edge T Excuse me of OT and I t and combine it into a single edge processing compute solution. You kind of couple that with the ability to configure components such as Tesla GP, use in specific excellent offerings to offer an aid and things like realtime, video processing and analytics. Uh, and a perfect example of this is, ah so for dissing and covert space. If if I need to be able to analyze a group of people to ensure they're staying as far apart as possible or, you know within self distant guidelines, that is where kind of the real time that's like an aspect of things can be taken advantage of same things with with the leveraging cameras where you could actually take temperature detection as as well, so it's really kind of best to think of Edge Lines Solutions is data center computing at the edge kind of transition into the Aruba space. Uh Rubio says offerings aid in the island Security is such a clear pass device inside, which allows for device discovery of network and monitoring of wired and wireless devices. There's also Aruba asset tracking and real time location of solutions, and that's particularly important in the healthcare space as well. If I have a lot of high value assets, things like wheelchairs, things like ventilation devices, where these things low located within my facilities and how can I keep keep track of them? They also, and by that I mean HP. They also kind of leveraging expanse ecosystem of partners. As an example, they leverage thing works allow their i o t solutions as well, when you kind of tying it all together with HP Point. Next to the end, customers provided with comprehensive loyalty solution. >>So, Colin, how ready? Our channel partners and the end user customers to rapidly pivot and start either deploying more technologies at the edge to be able to deliver some of the capabilities that David talked about in terms of analytics and sensors for social distancing. How ready are the channel partners and customers to be able to understand, adopt and execute this technology. >>So I think on the understanding side, I think the partners are there. We've been talking about digital transformation in the channel for a couple of years now, and I think what's happened through the 19 Pandemic is that it's been a real spotlight on the need for those business outcomes to to solve for very specific problems. And that's one of the values that we serve in the channel. So we've got a solution offering that we call our solution factory. And what we do really says is we leverage a process to look outside the industry. At Gartner, Magic Quadrant Solutions forced a Wave G two crowd. You know, top leaders, visionaries and understand What are those solutions that are in demand in these vertical markets that we talked about? And then we do a lot of work with David and his team internally in the HP organization to be able to do that and then build out that reference architectures so that we know that there's a solution that drives a bill of materials and a reference architecture that's going to work that clients are going to need and then we can do it quickly. You know, Tech data. Everything's about being bold, acting now getting scale. And we've got a large ecosystem partners that already have great relationships. So we pride ourselves on being able to identify what are those solutions that we can take to our partners that they can quickly take to their end users where you know we've We've kind of developed out what we think the 70 or 80% of that solution is going to look like. And then we drive point next and other services capabilities to be able to complete that last mile, if you will, of some of the customization. So we're helping them. For those who aren't ready, we're helping them. For those who already have very specific use cases and a practice that they drive with repeatable solutions were coming alongside them and understanding. What can we do? Using a practice builder approach, which is our consultative approach to understand where our partners are going in the market, who their clients are, what skill sets do they have? What supplier affinities do they want to drive? What brand marketing or demand generation support do they need? And that's where we can take some of these solutions, bring them to bear and engage in that consultative engagement to accelerate being ready as, as you rightly say, >>so tech. It has a lot of partners. You in general. You also have a lot of partners in the i o T space calling What? How do you from a marketing hat perspective? How do you describe the differentiation that Tech data and HP ease Iot solutions delivered to the channel to the end user? >>A couple of different things? I think that's that's differentiation. And that's one of the things that we strive for in the channel is to be specialized and to be competitively differentiated. And so the first part, I say to all of my team, Lisa, is you know, whether it's our solution consultants or our technical consultants, our solutions to the developers or the software development team that works my organization. Our goal is to be specialized in such a way that we're having relevant value added conversations not only our channel partners, but also end users of our partners want to bring us into those conversations, and many do. The next is really education and enablement as you would expect. And so there's a lot of things that are specialized in our technical. We drive education certification programs, roadshows, seminars, one of the things that we're seeing a lot of interest now. Lisa is for a digital marketing, and we're driving. Some really need offerings around digital marketing platforms that not only educate our partners but also allow our partners to bring their end users and tour some of this some of these technologies. So whether it's at our Clearwater office, where we've got an I. O T. Solution center, that we we take our partners and their clients through or we're using our facilities Teoh to do executive briefings and ideation as a service that, you know, kind of understanding the art of the possible. With both our resellers and their clients work, we're using our solution. Our solution catalogs that we've built an interactive pdf that allows our partners to understand over 50 solutions that we've got and then be able to identify. Where would they like to bring in David and his team and then my consultants to do that, that deep planning on business development, uh, that we talked about a little bit earlier. >>So the engagement right now is maybe even more important than it has been in a while because it's all hands off and virtual David. Talk to me about some of the engagement and the enablement piece that call and talked about. How are you able to really keep a channel partner and their end user customers engaged and interested in what you're able to deliver through this from New Virtual World? >>That's a great, great question. And we work in conjunction with our marketing teams to make sure that as new technologies and quite in I O. T space as well as within the HP East base as well that that our channel partners are educated and aware that these solutions exist. I know for a fact that for the majority of them you kind of get this consistent bombardment of new technology. But being able to actually have someone go out and explain it and then being able to correspondingly position it's use case and it's functionality and why it would provide value for your end customer is one of the benefits of tech data ads to kind of build upon that previous statement. The fact that We have such a huge portfolio of partners, so you kind of have HP and the edge compute space. But we have so many different partners in the OT space where it's really just a phone call, an email, a Skype message, a way to have that conversation around interoperability and then provide those responses back to our partners. >>Excellent. One more question before we go. Colin for you, A lot of partners. Why HP fry Mt. >>So a couple of reasons? One of the one of the biggest reasons as HP is just a great partner. And so when you look at evaluating I. O. T solutions that tend to be pretty comprehensive in many cases, Lisa it takes 10 or 12 partners to complete a really i o t solution and address that use case that that's in the field. And so when you have a partner like HP who's investing in these programs, investing in demand generation, investing in the spectrum of technology, whether it's hybrid Cloud Data Center, compute storage or your edge devices and Iot gateways, then to be able to contextualize those into what we call market ready solutions in each one of these vertical markets where there's references and there's use cases. And there were coupling education that specific rest of solutions. You know HP can do all of those things, and that's very important. Because in this new world, no one can go it alone anymore. It takes it takes partnerships, and we're all better together. And HP really does embrace that philosophy. And they've been a great partner for us in the Iot space. >>Excellent. Well, Colin and David, thank you so much for joining me today on the Cube Tech data. H p e i o t better together. Thank you so much. It's been a pleasure talking with you. >>Thank you. >>Thank you. Lisa. >>And four Collet and David. I am Lisa Martin. You're watching the Cube's virtual coverage of HP Discover 2020. Thanks for watching. Yeah, yeah, yeah, yeah.

>> Live from Orlando, Florida. It's the Cube. Covering Microsoft Ignite. Brought to you by Cohesity and the Cube's ecosystem partners. >> Welcome back, everyone, to the Cube's live coverage of the Microsoft Ignite here in Orlando. I'm your host Rebecca Night. Co-hosting today with Stu Miniman. We're joined by Calvin Roland. He is the SBP of Business Development at F5. Thanks so much for coming on the Cube. >> Lovely to be here. >> So set the scene for our viewers. What is F5? What are you about? You're based in Seattle. What do you do? >> Based in Seattle. Founded in 1996. Went public in 1999. We were known as the load balancer back then. We were the grandfathers that created that market space. We evolved it to an application centric focus, so now known as an application delivery control, or ADC, market and we're the leader in that space. >> You were $107 million in sales in 2001. Today $2 billion plus company. >> A little bit of growth. Been quite a ride. But we're not satisfied. We're looking to double that and more through the course of the next few years. >> So Calvin, like I said I've got a networking background, so obviously watch the ADC market. I might have been a little bit further down in the layer one through three stuff, but watched layers four through seven. I actually forgot that you guys are based in Seattle. There's been a little bit of activity over the last ten or fifteen years. Maybe you can explain how cloud's been impacting your space. (Inaudible) virtualized and all the Cloud guys are just going to eat your business alive? >> So I'm glad you asked that, actually. So a lot of people have said, gosh, the public cloud. Isn't that a problem for you? Is that going to be a head win at best for you guys? And the answer is well, if we don't continue to innovate the way we have since 1996, well, then yes, of course that's going to be a problem for us. But it's actually also a tremendous opportunity for us, and let me tell you why. So in the past, we were a physical product deployed in a data center. It had a floor. It had a roof. It had air conditioning. We put our product in a rack. And you had to buy all of the services in that box, if you will, and so then even as servers and data centers virtualized and we had virtual editions of our product, big IPEV, you still had to buy every feature that was in the product. But now with the advent of the cloud, we have an opportunity now to dis-aggregate those services and then re-aggregate them in any number of ways that are bespoke or specific for a given implementation construct, so the cloud puts us in a position to get in front of more application workloads, to get to more customers. Different personas like DevOps and ApDev, that we would not have been able to get in front of. So it puts us in a position to deliver on this vision we have, which is supplying applications and services for every application anywhere. >> Well Calvin, it's interesting. There's another Seattle-based company posting a 30,000 (inaudible). Microsoft has been going through their own digital transformation. >> Correct. >> We think about Windows on the PC, Windows on the server. Well, we've talked a lot about Windows 2019 and things like that, but Microsoft's gone through a digital transformation and it sounds like F5's going through a lot of those. Maybe help connect the dots as to the Microsoft ecosystem, how F5 plays into that. >> Okay, sure. Well, we have a long history of going to market together. It's a coincidence, but it doesn't hurt, that we're across Lake Washington from one another. F5 in Seattle, Microsoft in Redmond. But back in the early 2000s, Microsoft and F5 started working together saying hey, server constructs have moved to a three tier architecture being accessed through a web browser. There is a traffic management requirement to make sure that these applications, these servers, are always available, running fast, and then more secure than what it would otherwise be. We should be working with one another to make sure that we have best practice implementation guidance for our customers. And we focus on the enterprise, obviously. So it started there. And as the world started to evolve, server virtualization, data center virtualization, and now the cloud, we've continued to work hand in hand. And so now, regardless of whether or not you're deploying Azure Stack on prem, enabling a private cloud, and it's probably an and statement, it's not an or statement. deploying applications in Azure, you get the same experience as a result of that collaborative posture. >> So working hand in hand for digital transformation, you talked about the best practices. What have you learned? What emerged? What patterns? What behaviors that you have learned that you could also extend to other companies >> Okay, so beautiful thing about the cloud, about digital transformation, is there is now something that can satisfy that insatiable appetite in the marketplace for more and more applications. More complex architectures, as well. The good news: the technology is there. The economy makes sense. But that introduces complexity, right? That can actually be a gating factor for the enjoyment of that digital transformation. So, a best practice is implementing consistent methodologies for application and security services for the apps that you are standing up in this multi-cloud architecture. By having consistent methodologies you actually give yourself an opportunity to continue that pace of innovation. So the beauty is you're deploying more applications than ever before, more capability, more productivity. You're also increasing the opportunity for things to fail. You're also increasing your exposure footprint, if you will. 53% of cyber attacks are focused on the application, for example. Having consistent methodologies for ensuring that you have an appropriate security posture is something that obviously is a table stake. So F5 has been focusing on that as we go forward. >> Calvin, one of the things we look at is it's not just where things live but a lot of times, how do I take advantage of what the new platform can offer. You talked about in the cloud I can choose what features I'd need. As customers that are building new applications, whether that's micro services, containerized server (inaudible) or the like, what opportunities are there for F5 to get in there more. I don't know if it's new features or the like but, yeah. >> Sure, so the thing that we need to do is, speaking a little philosophically, is we need to meet customers where and when and how they want to be met and with what they want to be met with. I can flip it around and say the same thing for the applications. In this new application capital economy that we have, the application decides where it should be deployed, right? And so we need to do the technology and business model, they both go in hand in hand, innovation to ensure that we do just that. Meet the work load where and when and how it wants to be met and with the features and functionality that it needs to be met with. And so we have iterated our product roadmap portfolios, so we still have our physical big IP product, we still have the VE virtual edition of the product, we now have a cloud specific version, cloud edition. We are developing and will be available in our FY19 a DevOps CICD-focused version of the product. We have a SAS offering that is development being incubated as we speak. So we are looking to attack all of those vectors, so at the moment of ideation and instrumentation and orchestration we can be there to make sure that those personas know that they can take advantage of the application and security services that we provide. >> Calvin I want to have you take us one level deeper on securities. So obviously, critically important. Something we've been talking a lot about trust with Microsoft and how does security play into the product line from F5? >> It has for some time. We're just now shining a brighter light on it. >> Right. >> Because we were the indoor and outdoor for the majority of data centers, I'm dating myself by saying data center, for applications in the past our customers have said, hey, you're providing layer four through seven application services for us. This is an obvious place for you to supply security services like a web application firewall, access services, DDOS services, et cetera. And so we have done that and we've become a leader, for example, in the web application firewall, WAF, space. And so you'll continue to see us now focus on stand-alone security offerings that take advantage of that footprint that we've established in the marketplace, with this multi-cloud construct in mind. >> So you've painted this picture of a landscape. A multi-cloud world. Customers have so much choice. They're also struggling to keep up with the pace of innovation. I'm curious how you at F5 keep up with the pace of innovation and then also how you help customers do the same. >> No problem. It's easy. I'd like to say that we're better at it than everybody else, but we're in the pool swimming as fast as we can with everybody else. I used this phrase before. The market has this insatiable appetite for more and more applications. Now the good news is, well, the bad news is there is not commensurately more human capital to satisfy that insatiable appetite. No different for us. Luckily, technology and the economy for that technology has put us in a position to have a prayer, if you will. So CICD technology, obviously the agility that the cloud brings to us, the notion of being able to spread the tent that is DevOps to envelope the NetOps profession in a way that we now have coined this phrase SuperNetOps. So we've given the traditional NetOps profession the opportunity to partner more effectively with the DevOps persona that is driving a lot of this innovation to say, hey, as you're instrumenting these applications you need to make sure that you're thinking about these layer seven services, be they traffic management or security focused from day zero. And we can help you do so. So there's that on the implementation side and over on the development side, I mean we're just hiring like crazy and changing our methodologies like crazy, as well, just like everybody else. >> So I want to ask you about the hiring. At this point in time so many tech leaders really struggle with finding talent with the right kinds of skills and also the right kind of mindset because it is actually the people that drive the innovation. >> Right. >> So how do you recruit, and how do you retain the talent to make sure that they are there to make F5 the successful organization you want it to be? >> Are you going to make me put on my amateur Chief HR Officer hat? It's a challenge for us just like it is everybody else. Now we're lucky. We're in cloud city. We fell backwards to being in the most amazing spot on this rock that's hurtling through space. And so we benefit from the proximity to us being cloud central, if you will. And so almost through osmosis, we've picked up the ability to have that cloud shining on us to attract talent. But we have to diversify our R&D strategy as well. And so we're not just hiring in Seattle. We're not just hiring in San Jose. We're not just hiring in Spokane and Lowell, Tel Aviv. We have, like many others, we've stood up an F5 innovation center in India as well, for us to help us continue to drive that velocity of hiring for tech talent. We're going to continue to make investments in the R&D centers that we have stateside and in Israel and also in Warsaw, Poland, but for us to be able to continue to drive the R&D for the growth aspirations that we have we're hiring in India, as well. >> Calvin, this is actually the first time we've had the Cube at this event. We've done lots of industry events. The infrastructure side, the operating system side, the server side, the cloud and the like. You've had a large partnership with Microsoft for years, so, maybe help for people that haven't come, give them a little bit about what they're missing by not being at Microsoft Ignite. What kind of the vibe is that you get from customers at the show, meetings you're having, people you're talking to. >> Sure. Well I benefit from getting to be at a Ignite and InVision as well. The business focus sister event, if you will. But specifically to Ignite, all I could say is if you could turn the cameras around you would be able to see the energy that is taking place here. I actually feel like I'm shouting a little bit so hopefully I'm not bursting the ear drum of the listeners right now because it's loud in here. There's a lot of energy. There's a tremendous number of technology companies here, just like F5, that see an opportunity to be drivers of digital transformation. So people are curious about some of the challenges that we've talked about. And you're not here? Well then you've missed an opportunity. >> Anything that you would differentiate Microsoft and its ecosystem in this show? And the Invision, too. The business side compared to some of the other shows of the world? We go to- (crosstalk) >> It's breadth and depth. So either you get a very focused, very deep technology subject that you drill in on at an event like this. Or you get wide and shallow. And what I'd say about here is because of the decades, really, of enterprise focus and innovation and forward thinking of Microsoft, you get the breadth but you also get the depth as well. >> And actually you're the first guest we've actually had that mentioned the sister event. Maybe give us a little bit of color of what goes on there. >> So, I'll over-simplify it. The planners of the events are going to cringe. But I guess the simple differentiation is tech focus at Ignite. Business focus at Invision, if you will. So a lot of business leaders there that are being spoken to with the language that they need to be spoken to with. Helping them understand the breadth and depth of the technology that's happening here at Ignite but translating it into business transformation. So here we're focused a little bit more on technology innovation over at Invision, I don't even know if I'm pointing at the right direction, business model innovation. >> So if F5 were to have its own conference, its own Ignite-like event, what would you want to communicate about the vision and the strategy and the product services that F5 provides? >> So I've touched on it so I'll just reiterate it. We are excited about the phenomenon that is multi-cloud implementation constructs, digital transformation. We're excited about being a driver for that phenomenon. Enabling it to happen at a pace that it otherwise would not be able to happen in. And so the innovation that we're doing from a technology perspective, the product portfolio that I described, big IP, VE, cloud edition, Big IQ, our management and orchestration platform, our CICD-focused cloud specific implementation, our SAS, our managed service offering that is Silver Line. All of that technology and innovation we're tremendously excited about along with business model innovation. Licensing models like enterprise license agreements, subscription, et cetera. All of this puts us in a position within the Venn diagram that is digital transformation to actually achieve that nirvana which is providing application services for every application, anywhere. And so if you come to our event that's what you're going to learn about. >> But actually F5 Agility was in our backyard in Boston. >> Oh, man! >> You just missed it. You just missed it. Yes. >> Excellent, excellent. Well we'll be there next time. >> I'm counting on it. Don't say it if you don't mean it. >> Great. Well Calvin, thank you so much for coming on the show. It was a real pleasure having you here. >> It was a pleasure being here. Thank you. >> I'm Rebecca Night for Stu Miniman. We will have more from Microsoft Ignite in the Cube's live coverage in just a little bit.