>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path, >>Everybody. We're back in Las Vegas. The cube's coverage we're day one at UI Path forward. Five. Pascal Borne is here. He's an expert and bestselling author in the topic of AI and automation and the book Intelligent Automation. Welcome to the world of Hyper Automation, the first book on the topic. And of course, Ray Wong is back on the cube. He's the founder, chairman and principal analyst, Constellation Reese, also bestselling author of Everybody Wants To Rule the World. Guys, thanks so much for coming on The Cubes. Always a pleasure. Ray Pascal, First time on the Cube, I believe. >>Yes, thank you. Thanks for the invitation. Thank you. >>So what is artificial about artificial intelligence, >>For sure, not people. >>So, okay, so you guys are both speaking at the conference, Ray today. I think you're interviewing the co CEOs. What do you make of that? What's, what are you gonna, what are you gonna probe with these guys? Like, how they're gonna divide their divide and conquer, and why do you think the, the company Danielle in particular, decided to bring in Rob Sland? >>Well, you know what I mean, Like, you know, these companies are now at a different stage of growth, right? There's that early battle between RPA vendors. Now we're actually talking something different, right? We're talking about where does automation go? How do we get the decisioning? What's the next best action? That's gonna be the next step. And to take where UI path is today to somewhere else, You really want someone with that enterprise cred and experience the sales motions, the packages, the partnership capabilities, and who else better than Roblin? He, that's, he's done, he can do that in his sleep, but now he's gotta do that in a new space, taking whole category to another level. Now, Daniel on the other hand, right, I mean, he's the visionary founder. He put this thing from nothing to where he is today, right? I mean, at that point you want your founder thinking about the next set of ideas, right? So you get this interesting dynamic that we've seen for a while with co CEOs, those that are doing the operations, getting the stuff out the door, and then letting the founders get a chance to go back and rethink, take a look at the perspective, and hopefully get a chance to build the next idea or take the next idea back into the organization. >>Right? Very well said. Pascal, why did you write your book on intelligent automation and, and hyper automation, and what's changed since you've written that book? >>So, I, I wrote this book, An Intelligent Automation, two years ago. At that time, it was really a new topic. It was really about the key, the, the key, the key content of the, of the book is really about combining different technologies to automate the most complex end to end business processes in companies. And when I say capabilities, it's, we, we hear a lot about up here, especially here, robotic process automation. But up here alone, if you just trying to transform a company with only up here, you just fall short. Okay? A lot of those processes need more than execution. They need language, they need the capacity to view, to see, they need the capacity to understand and to, and to create insights. So by combining process automation with ai, natural language processing, computer vision, you give this capability to create impact by automating end to end processes in companies. >>I, I like the test, what I hear in the keynote with independent experts like yourself. So we're hearing that that intelligent automation or automation is a fundamental component of digital transformation. Is it? Or is it more sort of a back office sort of hidden in inside plumbing Ray? What do you think? >>Well, you start by understanding what's going on in the process phase. And that's where you see discover become very important in that keynote, right? And that's where process mining's playing a role. Then you gotta automate stuff. But when you get to operations, that's really where the change is going to happen, right? We actually think that, you know, when you're doing the digital transformation pieces, right? Analytics, automation and AI are coming together to create a concept we call decision velocity. You and I make a quick decision, boom, how long does it take to get out? Management committee could free forever, right? A week, two months, never. But if you're thinking about competing with the automation, right? These decisions are actually being done a hundred times per second by machine, even a thousand times per second. That asymmetry is really what people are facing at the moment. >>And the companies that are gonna be able to do that and start automating decisions are gonna be operating at another level. Back to what Pascal's book talking about, right? And there are four questions everyone has to ask you, like, when do you fully intelligently automate? And that happens right in the background when you augment the machine with a human. So we can find why did you make an exception? Why did you break a roll? Why didn't you follow this protocol so we can get it down to a higher level confidence? When do you augment the human with the machine so we can give you the information so you can act quickly. And the last one is, when do you wanna insert a human in the process? That's gonna be the biggest question. Order to cash, incident or resolution, Hire to retire, procure to pay. It doesn't matter. When do you want to put a human in the process? When do you want a man in the middle, person in the middle? And more importantly, when do you want insert friction? >>So Pascal, you wrote your book in the middle of the, the pandemic. Yes. And, and so, you know, pre pandemic digital transformation was kind of a buzzword. A lot of people gave it lip service, eh, not on my watch, I don't have to worry about that. But then it became sort of, you're not a digital business, you're out of business. So, so what have you seen as the catalyst for adoption of automation? Was it the, the pandemic? Was it sort of good runway before that? What's changed? You know, pre isolation, post isolation economy. >>You, you make me think about a joke. Who, who did your best digital transformation over the last years? The ceo, C H R O, the Covid. >>It's a big record ball, right? Yeah. >>Right. And that's exactly true. You know, before pandemic digital transformation was a competitive advantage. >>Companies that went into it had an opportunity to get a bit better than their, their competitors during the pandemic. Things have changed completely. Companies that were not digitalized and automated could not survive. And we've seen so many companies just burning out and, and, and those companies that have been able to capitalize on intelligent automation, digital transformations during the pandemic have been able not only to survive, but to, to thrive, to really create their place on the market. So that's, that has been a catalyst, definitely a catalyst for that. That explains the success of the book, basically. Yeah. >>Okay. Okay. >>So you're familiar with the concept of Stew the food, right? So Stew by definition is something that's delicious to eat. Stew isn't simply taking one of every ingredient from the pantry and throwing it in the pot and stirring it around. When we start talking about intelligent automation, artificial intelligence, augmented intelligence, it starts getting a bit overwhelming. My spy sense goes off and I start thinking, this sounds like mush. It doesn't sound like Stew. So I wanna hear from each of you, what is the methodical process that, that people need to go through when they're going through digital trans transmission, digital transformation, so that you get delicious stew instead of a mush that's just confused everything in your business. So you, Ray, you want, you want to, you wanna answer that first? >>Yeah. You know, I mean, we've been talking about digital transformation since 2010, right? And part of it was really getting the business model, right? What are you trying to achieve? Is that a new type of offering? Are you changing the way you monetize something? Are you taking existing process and applying it to a new set of technologies? And what do you wanna accomplish, right? Once you start there, then it becomes a whole lot of operational stuff. And it's more than st right? I mean, it, it could be like, well, I can't use those words there. But the point being is it could be a complete like, operational exercise. It could be a complete revenue exercise, it could be a regulatory exercise, it could be something about where you want to take growth into the next level. And each one of those processes, some of it is automation, right? There's a big component of it today. But most of it is really rethinking about what you want things to do, right? How do you actually make things to be successful, right? Do I reorganize a process? Do I insert a place to do monetization? Where do I put engagement in place? How do I collect data along the way so I can build better feedback loop? What can I do to build the business graph so that I have that knowledge for the future so I can go forward doing that so I can be successful. >>The Pascal should, should, should the directive be first ia, then ai? Or are these, are these things going to happen in parallel naturally? What's your position on that? Is it first, >>So it, so, >>So AI is part of IA because that's, it's, it's part of the big umbrella. And very often I got the question. So how do you differentiate AI in, I a, I like to say that AI is only the brain. So think of ai cuz I'm consider, I consider AI as machine learning, Okay? Think of AI in a, like a brain near jar that only can think, create, insight, learn, but doesn't do anything, doesn't have any arms, doesn't have any eyes, doesn't not have any mouth and ears can't talk, can't understand with ia, you, you give those capabilities to ai. You, you basically, you create a cap, the capability, technological capability that is able to do more than just thinking, learning and, and create insight, but also acting, speaking, understanding the environment, viewing it, interacting with it. So basically performing these, those end to end processes that are performed currently by people in companies. >>Yeah, we're gonna get to a point where we get to what we call a dynamic scenario generation. You're talking to me, you get excited, well, I changed the story because something else shows up, or you're talking to me and you're really upset. We're gonna have to actually ch, you know, address that issue right away. Well, we want the ability to have that sense and respond capability so that the next best action is served. So your data, your process, the journey, all the analytics on the top end, that's all gonna be served up and changed along the way. As we go from 2D journeys to 3D scenarios in the metaverse, if we think about what happens from a decentralized world to decentralized, and we think about what's happening from web two to web three, we're gonna make those types of shifts so that things are moving along. Everything's a choose your end venture journey. >>So I hope I remember this correctly from your book. You talked about disruption scenarios within industries and within companies. And I go back to the early days of, of our industry and East coast Prime, Wang, dg, they're all gone. And then, but, but you look at companies like Microsoft, you know, they were, they were able to, you know, get through that novel. Yeah. Ibm, you know, I call it survived. Intel is now going through their, you know, their challenge. So, so maybe it's inevitable, but how do you see the future in terms of disruption with an industry, Forget our industry for a second, all industry across, whether it's healthcare, financial services, manufacturing, automobiles, et cetera. How do you see the disruption scenario? I'm pretty sure you talked about this in your book, it's been a while since I read it, but I wonder if you could talk about that disruption scenario and, and the role that automation is going to play, either as the disruptor or as the protector of the incumbents. >>Let's take healthcare and auto as an example. Healthcare is a great example. If we think about what's going on, not enough nurses, massive shortage, right? What are we doing at the moment? We're setting five foot nine robots to do non-patient care. We're trying to capture enough information off, you know, patient analytics like this watch is gonna capture vitals from a going forward. We're doing a lot what we can do in the ambient level so that information and data is automatically captured and decisions are being rendered against that. Maybe you're gonna change your diet along the way, maybe you're gonna walk an extra 10 minutes. All those things are gonna be provided in that level of automation. Take the car business. It's not about selling cars. Tesla's a great example. We talk about this all the time. What Tesla's doing, they're basically gonna be an insurance company with all the data they have. They have better data than the insurance companies. They can do better underwriting, they've got better mapping information and insights they can actually suggest next best action do collision avoidance, right? Those are all the things that are actually happening today. And automation plays a big role, not just in the collection of that, that information insight, but also in the ability to make recommendations, to do predictions and to help you prevent things from going wrong. >>So, you know, it's interesting. It's like you talk about Tesla as the, the disrupting the insurance companies. It's almost like the over the top vendors have all the data relative to the telcos and mopped them up for lunch. Pascal, I wanna ask you, you know, the topic of future of work kind of was a bromide before, but, but now I feel like, you know, post pandemic, it, it actually has substance. How do you see the future of work? Can you even summarize what it's gonna look like? It's, it's, Or are we here? >>It's, yeah, it's, and definitely it's, it's more and more important topic currently. And you, you all heard about the great resignation and how employee experience is more and more important for companies according to have a business review. The companies that take care of their employee experience are four times more profitable that those that don't. So it's a, it's a, it's an issue for CEOs and, and shareholders. Now, how do we get there? How, how do we, how do we improve the, the quality of the employee experience, understanding the people, getting information from them, educating them. I'm talking about educating them on those new technologies and how they can benefit from those empowering them. And, and I think we've talked a lot about this, about the democratization local type of, of technologies that democratize the access to those technologies. Everyone can be empowered today to change their work, improve their work, and finally, incentivization. I think it's a very important point where companies that, yeah, I >>Give that. What's gonna be the key message of your talk tomorrow. Give us the bumper sticker, >>If you will. Oh, I'm gonna talk, It's a little bit different. I'm gonna talk for the IT community in this, in the context of the IT summit. And I'm gonna talk about the future of intelligent automation. So basically how new technologies will impact beyond what we see today, The future of work. >>Well, I always love having you on the cube, so articulate and, and and crisp. What's, what's exciting you these days, you know, in your world, I know you're traveling around a lot, but what's, what's hot? >>Yeah, I think one of the coolest thing that's going on right now is the fact that we're trying to figure out do we go to work or do we not go to work? Back to your other point, I mean, I don't know, work, work is, I mean, for me, work has been everywhere, right? And we're starting to figure out what that means. I think the second thing though is this notion around mission and purpose. And everyone's trying to figure out what does that mean for themselves? And that's really, I don't know if it's a great, great resignation. We call it great refactoring, right? Where you work, when you work, how we work, why you work, that's changing. But more importantly, the business models are changing. The monetization models are changing macro dynamics that are happening. Us versus China, G seven versus bricks, right? War on the dollar. All these things are happening around us at this moment and, and I think it's gonna really reshape us the way that we came out of the seventies into the eighties. >>Guys, always a pleasure having folks like yourself on, Thank you, Pascal. Been great to see you again. All right, Dave Nicholson, Dave Ante, keep it right there. Forward five from Las Vegas. You're watching the cue.

(upbeat music) >> Welcome back to theCUBE coverage of AWS re:Invent 2021. I'm John Furrier, your host for theCUBE. In this segment, we're going to be talking about Red Hat and the AWS evolving partnership. A great segment, really talking about how Hybrid and the Enterprise are evolving, certainly multicloud and the horizon. But a lot of benefits in the cloud, we've been covering on theCUBE and on SiliconANGLE with Red Hat for the past year. Very relevant. We've got Gunnar Hellekson, GM of Red Hat Enterprise Linux, And Joe Fernandes, VP and GM of the Hybrid Platforms, both of Red Hat. Gentlemen, thanks for coming on theCUBE. >> Yeah, thanks for having us. >> Thanks for having us John. >> So, you know, me, I'm a fan boy of Red Hat. So I always say, you guys made all the right investments, OpenShift, all these things that you guys made decisions years ago playing out beautifully. And I think, you know, with Amazon's re:Invent, you're seeing the themes all play out. Modern application stack, you're starting to see things at the top of the stack evolve, you've got 5G in the Edge, workloads being redefined and expanded on the cloud with Cloud Scale. So everything has been going down to Hybrid and Enterprise grade level discussions. This is in the Wheelhouse of Red Hat. So I want to congratulate you. But what's your reaction? What do you guys see this year at re:Invent? What's the top story? >> I can start. >> Who wants to start with first? >> Sure, I mean, clearly, AWS itself is huge. But as you mentioned, the world is Hybrid, right, so customers are running still in their data center, in the Amazon Public Cloud across multiple Public Clouds and out to the Edge and bring in more and more workloads. So it's not just the applications, analytics. It's AI, it's machine learning. And so, yeah, we can expect to see more discussion around that, more great examples of customer use cases. And as you mentioned, Red Hat has been right in the middle of this for some time John. >> You guys also had some success with the fully managed OpenShift service called ROSA, R-O-S-A, which is Red Hat OpenShift Service on AWS, another acronym, but really this is about what the customers are looking for. Can you take us through an update on OpenShift on AWS, because the combination of managed services in the cloud, refactoring applications, but working on-premises is a big deal. Take us through why that's so important. >> Yeah, so, we've had customers running OpenShift on AWS for a long time, right? So whether it's our software-based offerings where customers deploy OpenShift themselves, or our fully managed cloud service. We've had cloud services on AWS for over five years. What ROSA brings or Red Hat OpenShift on AWS is a jointly managed service, right? So we're working in partnership with Amazon, with AWS to make OpenShift available as a jointly-managed service offering. It's a native AWS service offering. You can get it right through the AWS console. You can leverage your AWS committed spend. But, most importantly, you know, it's something that we're working on together. Bringing new customers to the table for both Red Hat and AWS. And we're really excited about it because it's really helping customers accelerate their move to the public cloud and really helping them drive that Hybrid strategy that we talked about. >> Gunnar, you know what I want to get your thoughts on this, because one of the things that I love about this market right now is open-source continues to be amazing, continues to drive more value, and there's new migration of talent coming in. The numbers are just continuing to grow and grow. But the importance of Red Hat's history with AWS is pretty significant. I mean, Red Hat pioneered Open-source and it's been involved with AWS from the early days. Can you take us through a little bit of history for the folks that may not know Red Hat's partnership with AWS? >> Yeah. I mean, we've been collaborating with AWS since 2008. So for over a decade we've been working together, and what's made the partnership work is that we have a common interest in making sure that customers have a consistent approachable experience. Whether they're going on-premise or in the cloud. Nobody wants to have to go through an entire retraining and retooling exercise just to take advantage of all the great advantages of the cloud. And, so being able to use something like Red Hat Enterprise Linux as a consistent substrate on which you can build your application platforms is really attractive. So, that's where the partnership started. And since then we've had the ability to better integrate with native AWS services. And one thing I want to point out is that, a lot of these integrations are kind of technical. It's not just about technical consistency across these platforms, it's also about operational consistency and business concerns. And when you're moving into an Open Hybrid Cloud kind of a situation, that's what becomes important, right? You don't want to have two completely different tool sets on two completely different platforms. You want as much consistency as possible as you move from one to the other. And I think a lot of customers see value in that, both for the Red Hat Enterprise Linux side of the business, and also on the OpenShift side of the business. >> Well that's interesting. I'd love to get your both perspective on this whole Enterprise focus, because the Enterprise is, as you know, guys you've been there from the beginning, they have requirements. And there're sometimes, they're different by Enterprise. So as you see cloud, and I remember early days of Amazon, it's the 15th year of AWS, 10th year of re:Invent as a conference. I mean, that seems like a lifetime ago. But that's not, not too far ago where, you know, it was like, well, Amazon might not make it, its only for developers. Enterprisers do their own thing. Now it's like, it's all about the Enterprise. How are Enterprise customers evolving with you guys? Because they're all seeing the benefit of replatforming. But as they refactor, how has Red Hat evolved with that trend and how have you helped Amazon? >> Yeah, so as we mentioned, Enterprisers really across the globe are adopting a Hybrid Cloud Strategy. But, Hybrid actually isn't just about the infrastructure. So, its certainly the infrastructure where these Enterprisers are running these applications is increasingly becoming Hybrid as you move from data center to multiple public clouds and out to the Edge. But the Enterprisers application portfolios are also Hybrid, right? It's a Hybrid mix of very traditional monolithic and tier type applications. But also new cloud native services that have either been built from scratch, or as you mentioned, existing applications have been refactored. And then they're moving beyond the applications, as I mentioned to make better use of data. Also evolving their processes for how they build, deploy, and manage, leveraging, CI/CD and GitOps and so forth. So really for us it's, how do you help Enterprises bring all that together, right? Manage this Hybrid infrastructure that's supporting this Hybrid portfolio of applications that really help them evolve their processes. We've been working with Enterprises on these types of challenges for a long time. And we're now partnering with Amazon to do the same in terms of our joint product and service offerings. >> Talking about the RHEL evolution. I mean, because that's the bread and butter for Red Hat. It has been there for a long time. OpenShift again, making argument earlier, I mentioned the bets you guys made with Kubernetes, for instance, and it's all been made with all the right moves. So I love ROSA. You got me sold on that. RHEL though has been the tried and true steady workhorse. How has that evolved with workloads? >> Yeah, you know, it's interesting. I think when customers were at the stage, when they were wondering, if well, can I use AWS to solve my problem, or should I use AWS to solve my problem? Our focus was largely on kind of technical enablement. Can we keep up with the pace of new hardware that Amazon is rolling up? Can we ensure that consistency with the on-premise and off-premise? And I think now we're starting to shift focus into really differentiating RHEL on the AWS platform. Again, integrating natively with AWS services, making it easier to operate in AWS. And a good example of this is using tools like Red Hat Insights, which we announced, I guess, about a year ago. Which is now included in every Red Hat Enterprise Linux subscription. Using tools like Insights in order to give customers advice on maybe potential problems that are coming up, helping customer solve them. Can the customers identify problems before they happen? Helping them with performance problems. And again, having additional tools like that, additional cloud-based tools, makes RHEL as easy to use on the Cloud despite all the complexity of all the redeploying, refactoring, microservices, there is now a proliferation of infrastructure options, and to the extent that RHEL can be the thing that is consistent, solid, reliable, secure, just as customers are getting in, then we can make customer successful. >> You know, Joe, we talked about this last time we were chatting, I think Red Hat Summit or Ansible Fest, I forget which event it was, but we were talking about how modern application developers at the top of the stack just want to code. They want to write some code, and now they want the infrastructure's code, AKA DevOps, DevSecOps, but as this trend of moving up the stack continues to be a big theme at re:Invent, that requires automation. That requires a lot of stuff that happened under the covers. Red Hat is at the center of all this action from historical perspective, pre-existing Enterprises before Cloud now, during Cloud, and soon to be Cloud Scale, how do you see that evolving? Because how are customers shaping their architecture? Cause this is distributed computing in the cloud. It's essentially, we've seen this moving before, but now at such a scale where data, security, these are all new elements. How do you talk about that? >> Yeah, well, first of all, got to mention, Linux is a given right. Linux is going to be available in every environment, data center, Public Cloud, Edge. Linux combined with Linux containers and Kubernetes, that's the abstraction like abstracting the applications away from the infrastructure. And now it's all about how do you build on top of that to bring that automation that you mentioned. So, we're very focused on helping customers really build fully automated end to end deployment pipelines, so they can build their applications more efficiently. They can automate the continuous integration and deployment of those applications into whatever Cloud or Edge footprint they choose. And that they can promote across environments. Because again, it's not just about developing the applications, it's about moving them all the way through to production where their customers are relying on those services to do their work and so forth. And so that's what we're doing is, you know, obviously I think, Linux is a given, Linux, Containers, Kubernetes. Those decisions have been made and now it's a matter of how can we put that together with the automation that allows them to accelerate those deployments out to production so customers can take advantage of them? >> You know, Gunnar, we were joking in theCUBE. I was old enough to remember we used to install Linux on a server back in the day. Now a lot of these young developers never actually have to install the software and do some of those configurations 'cause it's all automated now. Again, the commoditization and automation trend, abstraction layers, some say, is a good thing. So how do you see the evolution of this DevOps movement with the partnership with AWS going forward? What types of things are you working on with Amazon Web Services and what kind of offerings can customers look forward to? >> Yeah, sure. So, I mean, it used to be that as you say, Linux was something that you managed with a mouse and keyboard. And I think it's been quite a few years since any significant amount of Linux has been managed with a mouse and a keyboard. A lot of it is scripts, automation tools, configuration management tools, things like this. And the investments we've made both in RHEL and in specifically RHEL on AWS is around enabling RHEL to be more manageable. And so, including things like something we call System Roles. So these are Ansible modules that kind of automate routine system's administration tasks. We've made investments in something called Image Builder. And so this is a tool that allows customers to kind of compose the operating system that they need, create a blueprint for it, and then kind of stamp out the same image, whether it's an ISO image, so you can install it on-premise or an AMI so we can deploy it in AWS. So again, the problem used to be helping customers package and manage dependencies and that kind of old world, three and a half-inch floppy disc kind of Linux problems. And now we've evolved towards making Linux easier to deploy and manage at a grand scale whether you're in AWS or whether you're On premise. >> Joe, take us through the Hybrid story. I know obviously success with OpenShifts Managed Service on AWS. What's the update there for you? What are customers expecting this re:Invent and what's the story for you guys? >> Yeah, so, you know, the OpenShift Managed Services business this is the fastest growing segment of our business. We're seeing lots of new customers. And again, bringing new customers, I think for both Red Hat and AWS through this service. So, we expected to hear from customers at re:Invent about what they're doing. Again, not only with OpenShift and our Red Hat solutions, but really with what they're building on top of those service offerings, of those solutions to sort of bring more value to their customers. To me, that's always the best part of re:Invent is really hearing from customers. And when we all start going there in person again, to actually be able to meet with them one-on-one, whether it's in person or virtual and so forth. So, looking forward to that. >> Well, great to have you guys on theCUBE. Congratulations on all success. The Enterprise continues to adopt more and more Cloud which benefits all the work you guys have done both on the RHEL side, and as you guys modernize with all these great services and managed services continues to be the center of all the action. Thanks for coming on. Appreciate it. >> Thanks John. >> Thank you. >> Okay, Red Hat's partnership with AWS evolving as Cloud scale Edge, all distributed computing, all happening at large scale. This is theCUBE with CUBE coverage of AWS re:Invent 2021. I'm John Furrier. Thanks for watching. (upbeat music)

>>Mhm. Mhm. >>We're here with the Cube covering Calm Vault Connections 21. We're gonna look at the data protection space and how cloud computing has advanced the way we think about backup recovery and protecting our most critical data. Ranga Rajagopalan, who is the vice president of products at Con vault and Stephen Orban, who's the General manager of AWS marketplace and control services gents. Welcome to the cube. Good to see you. >>Thank you. Always A pleasure to see you here >>steve. Thanks for having us. Very >>welcome, Stephen, let's start with you. Look the cloud has become a staple of digital infrastructure. I don't know where we'd be right now without being able to access enterprise services I. T. Services remotely. Um But specifically how our customers looking at backup and recovery in the cloud, is it a kind of a replacement for existing strategies? Is it another layer of protection? How are they thinking about that? >>Yeah. Great question. David again, thank thanks for having me. And I think you know, look if you look back to 15 years ago when the founders of AWS had the hypothesis that many enterprises governments and developers we're gonna want access to on demand pay as you go I. T. Resources in the cloud. Uh None of us would have been able to predict that it would have Matured and um you know become the staple that it has today over the last 15 years. But the reality is that a lot of these enterprise customers, many of whom have been doing their own IT infrastructure for the last 10, 20 or multiple decades do have to kind of figure out how they deal with the change management of moving to the cloud. And while a lot of our customers um will initially come to us because they're looking to save money or costs, almost all of them decided to stay and go big because of the speed at which they are able to innovate on behalf of their customers and when it comes to storage and backup, that just plays right into where they're headed. And there's a variety of different techniques that customers use, whether it be, you know, a lift and shift for a particular set of applications or a data center where they do very much. Look at how can they replace the backup and recovery that they have on premises in the cloud using solutions like, but we're partnering with console to do or completely reimagining their architecture for net new developments that they can really move quickly for their customers. Um and and completely developing something brand new, where it is really a, you know, a brand new replacement and innovation for for for what they've done in the past. >>Great, thank you, Stephen Rachael, I want to ask you about the d were digital. Look, if you're not a digital business today, you're basically out of business. So, my question to you is how have you seen customers change the way they think about data protection during what I call the forced March to digital over the last 18, 19 months or customers, you know, thinking about data protection differently today >>definitely Dave and and thank you for having me and steven. Pleasure to join you on this cube interview first going back to stevens comments can't agree more. Almost every business that we talked with today has a cloud first strategy, a cloud transformation mandate and you know, the reality is back to your digital comment. There are many different paths to the hybrid multi cloud and different customers. You know, there are different parts of the journey. So I still was saying most often customers at least in the data protection perspective start the conversation by thinking here have all these tips. Can I start using cloud as my air gap long term retention target and before they realized they start moving their workloads into the cloud and none of the backup and record yesterday's are going to change. So you need to continue protecting the clothes, which is where the cloud native data protection comes in and then they start innovating around er, can I use cloud as media sites so that you know, I don't need to meet in the other side. So this year is all around us. Cloud transformation is all around us and and the real essence of this partnership between AWS and calm vault is essentially to dr and simplify all the paths to the club regardless of whether you're going to use it as a storage started or you know, your production data center, all your dear disaster recovery site. >>Yeah, it really is about providing that optionality for customers. I talked to a lot of customers and said, hey, our business resilience strategy was really too focused on D. R. I've talked to all the customers at the other end of the spectrum said we don't even have a D. R. Strategy now, we're using the cloud for that. So it's really all over the map and you want that optionality. So steven and then go ahead. >>Please, ransomware plays a big role in many of these considerations that greatly. It's unfortunately not a question of whether you're going to be hit by ransomware, it's almost we can like, what do you do when you're hit by ransomware and the ability to use the clothes scaled immediately, bring up the resources, use the cloud backups has become a very popular choice simply because of the speed with which you can bring the business back to normal our patients. The agility and the power that cloud brings to the table. >>Yeah, ransomware is scary. You don't, you don't even need a high school diploma to be a ransomware ist you can just go on the dark web and by ransomware as a service and do bad things and hopefully you'll end up in jail. Uh Stephen we know about the success of the AWS marketplace, uh you guys are partnering here. I'm interested in how that partnership, you know, kind of where it started and how it's evolving. >>Yeah, happy to highlight on that. So, look when >>we when we started >>Aws or when the founders of aws started aws, as I said 15 years ago we we realized very early on that while we were going to be able to provide a number of tools for customers to have on demand access to compute storage, networking databases that many, particularly enterprise and government government customers still use a wide range of tools and solutions from hundreds, if not in some cases thousands of different partners. I mean I talked to enterprises who literally use thousands of of different vendors to help them deliver their solutions for their customers. So almost 10 years ago, we're almost at our 10 year anniversary for AWS marketplace, we launched the first substantiation of AWS marketplace which allowed builders and customers to find try buy and then deploy third party software solutions running on amazon machine instances also noticed as armies natively right in their AWS and cloud accounts to complement what they were doing in the cloud. And over the last nearly 10 years we've evolved quite a bit to the point where we support software and multiple different packaging types, whether it be amazon machine instances, containers, machine learning models and of course SAS and the rise of software as a service. So customers don't have to manage the software themselves. But we also support data products through the AWS Data exchange and professional services for customers who want to get services to help them integrate the software into their environments. And we now do that across a wide range of procurement options. So what used to be pay as you go amazon machine instances now includes multiple different ways to contract directly, customer can do that directly with the vendor with their channel partner or using kind of our public e commerce capabilities. And we're super excited, um, over the last couple of months we've been partnering with calm vault to get their industry leading backup and recovery solutions listed on AWS marketplace, which is available for our collective customers now. So not only do they have access to convulse awesome solutions to help them protect against ransomware as we talked about and to manage their backup and recovery environments, but they can find and deploy that directly in one click right into their AWS accounts and consolidate their building relationship right on the AWS and voice. And it's been awesome to work with with Rhonda and the product teams and convo to really, um, expose those capabilities where converts using a lot of different AWS services to provide a really great native experience for our collective customers as they migrate to the cloud. >>Yeah, the marketplace has been amazing. We've watched it evolve over the past decade and, and, and it's a, it's a key characteristic of everybody has a cloud today. We're a cloud to butt marketplaces unique uh, in that it's the power of the ecosystem versus the resources of one and Ringo. I wonder from, from your perspective, if you could talk about the partnership with AWS from your view and then specifically you've got some hard news, I wonder if you could talk about that as well. >>Absolute. So the partnership has been extended for more than 12 years. Right. So aws and Commonwealth have been bringing together solutions that help customers solve the data management challenges and everything that we've been doing has been driven by the customer demand that we seek. Right customers are moving their workloads in the cloud. They're finding new ways of deploying their workloads and protecting them. Um, you know, earlier we introduced cloud native integration with the EBS API which has driven almost 70% performance improvements in backup and restores. And when you look at huge customers like coca cola who have standardized on AWS um, combo. That is the scale that they want to operate in. You manage around 1 50,000 snapshots 1200 ec, two instances across six regions. But with just one resource dedicated for the data management strategy. Right? So that's where the real built in integration comes into play and we've been extending it to make use of the cloud efficiencies like our management and auto scale and so on. Another aspect is our commitment to a radically simple customer experience and that's, you know, I'm sure Stephen would agree it's a big month for at AWS as well. That's really together with the customer demand which brought us together to introduce com ball into the AWS marketplace exactly the way Stephen described it. Now the heart announcement is coming back up and recovery is available in native this marketplace. So the exact four steps that Stephen mentioned, find, try buy and deploy everything simplified through the marketplace So that our aws customers can start using far more back of software in less than 20 minutes. A 60 year trial version is included in the product through marketplace and you know, it's a single click buy, we use the cloud formation templates to deploy. So it becomes a super simple approach to protect the AWS workloads and we protect a lot of them. Starting from easy to rds dynamodb document DB um, you know, the containers, the list just keeps going on. So it becomes a very natural extension for our customers to make it super simple to start using convert data protection for the w >>well the con vault stack is very robust. You have extremely mature stack. I want, I'm curious as to how this sort of came about and it had to be customer driven. I'm sure where your customers saying, hey, we're moving to the cloud, we had a lot of workloads in the cloud, we're calm vault customer. That intersection between calm vault and AWS customers. So again, I presume this was customer driven. but maybe you can give us a little insight and add some color to that. >>Everything in this collaboration has been customer driven. We were earlier talking about the multiple paths to chlorine vapor example and still might probably add more color from his own experience at our jones. But I'll bring it to reference Parsons who's a civil engineering leader. They started with the cloud first mandate saying we need to start moving all our backups to the cloud but we have wanted that bad actors might find it easy to go and access the backups edible is um, Conwell came together with the security features and com well brought in its own authorization controls and now we have moved more than 14 petabytes of backup data into the club and it's so robust that not even the backup administrator and go and touch the backups without multiple levels of authorization. Right. So the customer needs, whether it is from a security perspective performance perspective or in this case from a simplicity perspective is really what is driving this. And and the need came exactly like that. There are many customers who have no standardized on it because they want to find everything through the AWS marketplace. They want to use their existing, you know, the AWS contracts and also bring data strategy as part of that so that that's the real um, driver behind this. Um, Stephen and I hope actually announced some of the customers that I actively started using it. You know, many notable customers have been behind this uh, innovation, don't even, I don't know, I wanted to add more to that. >>I would just, I would, I would just add Dave, you know, look if I look back before I joined a W S seven years ago, I was the C I O at dow jones and I was leading a a fairly big cloud migration there over a number of years. And one of the impetus is for us moving to the cloud in the first place was when Hurricane Sandy hit, we had a real disaster recovery scenario in one of our New Jersey data centers um, and we had to act pretty quickly convert was, was part of that solution. And I remember very clearly Even back then, back in 2013, they're being options available to help us accelerate are moved to the cloud and just to reiterate some of the stuff that Rhonda was talking about consoles, done a great job over the last more than a decade, taking features from things like EBS and S three and EC two and some of our networking capabilities and embedding them directly into their services so that customers are able to more quickly move their backup and recovery workloads to the cloud. So each and every one of those features was as a result of, I'm sure combo working backwards from their customer needs just as we do at >>AWS >>and we're super excited to take that to the next level to give customers the option to then also by that right on their AWS invoice on AWS marketplace. >>Yeah, I mean, we're gonna have to leave it there steven, you've mentioned several times the sort of the early days of back then we were talking about gigabytes and terabytes and now we're talking about petabytes and beyond. Guys. Thanks so much. I really appreciate your time and sharing the news with us. >>Dave. Thanks for having us. >>All right. Keep it right there more from combat connections. 21. You're watching the >>cube. Mm hmm.

>>Welcome back to HP discover 2021 My name is Dave Volonte and you're watching the cubes, virtual coverage of H. P. S. Big customer event. Of course, the virtual edition, we're gonna dig into transformations the role of technology in the role of senior technology leadership. Look, let's face it, H P. E. Has gone through a pretty dramatic transformation itself in the past few years. So it makes a great example in case study and with me is rashmi kumari who is the senior vice president and C. I. O. At HP rashmi welcome come on inside the cube. >>Dave Nice to be here. >>Well, it's been almost a year since Covid changed the world as we know it. How would you say the role of the CEO specifically and generally it has changed. I mean you got digital Zero Trust has gone from buzzword to >>mandate >>digital. Everybody was complacent about digital in many ways and now it's really accelerated remote work hybrid. How do you see it? >>Absolutely. As I said in the last discover that Covid has been the biggest reason to accelerate digital transformation in the company's I. C. C. I O. S role has changed tremendously in the last 15 months. It's no more just keep the operations running that's become a table stick. Our roles have become not only to create digital customer experience engaged with our customers in different ways, but also to transform the company operations from inside out to be able to give that digital experience from beginning to end off the customer engagement going forward. We have also become responsible for switching our strategies around the companies as the Covid. Covid hit in different parts of the world at different times and how companies structured their operations to go from one region to another. A global company like H. B had to look into its supply chain differently. Had to look into strategies to mitigate the risk that was created because of the supply chain disruptions as well as you go to taking care of our employees. How do you create this digital collaboration experience where teams can still come together and make the work happen for our end customers? How do we think about future employee engagement when people are not coming into these big buildings and offices and working together, But how to create the same level of collaboration coordination as well as delivery or faster uh goods and services which is enabled by technology going forward. So see I. O. And I. T. S. Role has gone from giving a different level of customer experience to a different level of employee experience as well as enabling day to day operations of the company's. Ceos have realized that digital is the way to go forward. It does not matter what industry you are in and now see a as have their seat at the table to define what the future of every company now, which is a technology company respective you are in oil and gas or mining or a technical product or a card or a mobility company. End of the day you have to act and behave like a technology company. >>So I want to ask you about that because you've you've been a Ceo and uh you know, leading technology provider now for the last three years and you've had previous roles and where you know non technical technology, you know, selling to I. T. Companies and as you point out those worlds are coming together, everybody is a technology company today. How do you think that changes the role of the C. I. O. Because it would always seem to me that there was a difference between A C. I. O. And a tech company. You know what I mean by that? And the C. I. O. It's sort of every other company is those two worlds converging. >>Absolutely. And it's interesting you pointed out that I have worked in many different industries from healthcare and pharma to entertainment to utilities. Um And now at a technology company end of the day um The issues that I. T. Deals with are pretty similar across the organization. What is different here is now my customers are people like me in other industries and I have a little bit of an advantage because just having the experience across various ecosystem. Even at H. B. Look I was fortunate um at H. B. Because of Antonio's leadership, we have topped out mandate to transform how we did business. And I talked about my next gen IT program in last year's cube interview. But at the same time while we were changing our customer partners experience from ordering to order processing to supply chain to finance. Uh We decided this pivot of becoming as a service company. And if you think about that pivot it's pretty common if it was a technology company or non technology company at HP. We were very used to selling a product and coming back three years later at the time of refresh of infrastructure or hardware. That's no more true for us now we are becoming as a service or a subscription company and I. T. Played a major role to enable that quote to cash experience. Which is very different than the traditional experience around how we stay connected with our customer, how we proactively understand their behavior. I always talk about this term. Um Digital exhaust which results into data which can result into better insight and you can not only Upsell cross l because now you have more data about your product usage, but first and the foremost give what your customer wants in a much better way because you can proactively understand their needs and wants because you are providing a digital product versus a physical product. So this is the change that most of the companies are now going through. If you look at Domino's transition, there are pills a sellers but they did better because they had better digital experience. If you look at Chipotle, these are food service companies I. K which is a furniture manufacturer across the board. We have helped our customers and industries to understand how to become a more digital provider. And and remember when uh hp says edge to cloud platform as a service edges the product, the customers who we deal with and how do we get that? Help them get their data to understand how the product is behaving and then get the information to cloud for further analysis. Um and understanding from the data that comes out of the products that gets up, >>I think you've been HP now think around three years and I've been watching of course for decades. Hp. Hp then HP is I feel like it's entering now the sort of third phase of its transformation, your phase one was okay, we gotta figure out how to deal or or operate as a separate companies. Okay. That took some time and then it was okay. Now how do we align our resources and you know, what are the waves that we're gonna ride? And how do we how do we take our human capital, our investments and what bets do we place and and all in on as a service. And now it's like okay how do we deliver on all those promises? So pretty massive transformations. You talked about edge to cloud as a service so you've got this huge pivot in your in your business. What's the technology strategy to support that transformation? >>Yeah that's a that's a great question. So as I mentioned first your second phase which was becoming a stand alone company was the next N. I. T. Program very broad and um S. Four and 60 related ecosystem application. We're even in the traditional business there was a realization that we were 100 20 billion company. We are 30 billion company. We need different types of technologies as well as more integrated across our product line across the globe. And um we I'm very happy to report that we are the last leg of next in I. T. Transformation where we have brought in new customer experience through low touch or not touch order pressing. A very strong as four capabilities. Where we are now able to run all global orders across all our hardware and services business together. And I'm happy to report that we have been able to successfully run through the transformation which a typical company of our size would take five or six years to do in around close to three years. But at the same time while we were building this foundation and the capabilities to be able to do other management, supply chain and data and analytics platforms. We also made the pivot to go to as a service now for as a service and subscription selling. It needs a very different quote to Kazakh cash experience for our customers and that's where we had to bring in um platforms like brim to do um subscription building, convergent charging and a whole different way to address. But we were lucky to have this transformation completed on which we could bolt on this new capability and we had the data and another X platform built which now these as a service products can also use to drive better insight into our customer behavior um as well as how they're using our product a real time for our operations teams. >>Well they say follow the money in the cube. We love to say follow the day to day is obviously a crucial component of competitive advantage business value. So you talk a little bit more about the role of data. I'm interested I'm interested in where I. T. Fits uh you know a lot of companies that have a Chief data officer or Ceo sometimes they're separate. Sometimes they they work you know for each other or Cdo works for C. I. O. How do you guys approach the whole data conversation? >>Yeah that's a that's a great question and has been top of the mind of a lot of C E O C I O S. Chief digital officers in many different companies. The way we have set it up here is do we do have a chief data officer and we do have a head of uh technology and platform and data within I. T. Look. The way I see is that I call the term data torture if we have multiple data lakes, if we have multiple data locations and the data is not coming together at one place at the first time that it comes out of the source system, we end up with data swamps and it's very difficult to drive insights. It's very difficult to have a single version of truth. So HP had two pronged approach. First one was as part of this next gen i. T. Transformation we embarked upon the journey first of all to define our customers and products in a very uniform way across the globe. It's called entity Master Data and Product Master Data Program. These were very very difficult program. We are now happy to report that we can understand the customer from code stage to servicing stage beginning to end across all our system. It's been a tough journey but it was a effort well spent at the same time while we were building this message capability, we also invest the time in our analytics platform because we are generating so much data now globally as one footprint. How do we link our data link to R. S. A. P. And Salesforce and all these systems where our customer data flows through and create analytics and insight from it from our customers or our operations team. At the same time, we also created a chief data officer role where the responsibility is really to drive business from understanding what decision making an analytics they need around product, around customer, around their usage, around their experience to be able to drive better alignment with our customers and products going forward. So this creates efficiencies in the organization. If you have a leader who is taking care of your platforms and data building single source of truth and you have a leader who is propagating this mature notion of handling data as enterprise data and driving that focus on understanding the metrics and the insight that the businesses need to drive better customer alignment. That's when we gain those efficiencies and behind the scenes, the chief data officer and the data leader within my organization worked very, very closely to understand each other needs sometimes out of the possible where do we need the data processing? Is it at the edge? Is it in the cloud? What's the best way to drive the technology and the platform forward? And they kind of rely on each other's knowledge and intelligence to give us give us superior results. And I have done data analytics in many different companies. This model works where you have focused on insight and analytics without because data without insight is of no value, but at the same time you need clean data. You need efficient, fast platforms to process that insight at the functional nonfunctional requirements that are business partners have and that's how we have established in here and we have seen many successes recently. As of now, >>I want to ask you a kind of a harder maybe it's not harder question. It's a weird question around single version of the truth because it's clearly a challenge for organizations and there's many applications workloads that require that single version of the truth. The operational systems, the transaction systems, the HR the salesforce. Clearly you have to have a single version of the truth. I feel like however we're on the cusp of a new era where business lines see an opportunity for whatever their own truth to work with a partner to create some kind of new data product. And it's early days in that. But I want to and maybe not the right question for HP. But I wonder if you see it with in your ecosystems where where it's it's yes, single version of truth is sort of one class of data and analytics gotta have that nail down data quality, everything else. But then there's this sort of artistic version of the data where business people need more freedom. They need more latitude to create. Are you seeing that? And maybe you can help me put that into context. >>Uh, that's a great question. David. I'm glad you asked it. So I think tom Davenport who is known in the data space talks about the offensive and the defensive use cases of leveraging data. I think the piece that you talked about where it's clean, it's pristine, it's quality. It's all that most of those offer the offensive use cases where you are improving company's operations incrementally because you have very clean that I have very good understanding of how my territories are doing, how my customers are doing how my products are doing. How am I meeting my sls or how my financials are looking? There's no room for failure in that area. The other area is though, which works on the same set of data. It's not a different set of data, but the need is more around finding needles in the haystack to come up with new needs, new ones and customers or new business models that we go with. The way we have done it is we do take this data take out what's not allowed for everybody to be seen and then what we call is a private space. But that's this entire data available to our business leader, not real time because the need is not as real time because they're doing more what we call this predictive analytics to be able to leverage the same data set and run their analytics. And we work very closely with business in its we educate them. We tell them how to leverage this data set and use it and gather their feedback to understand what they need in that space to continue to run with their with their analytics. I think as we talk about hindsight insight and foresight hindsight and insight happens more from this clean data lakes where you have authenticity, you have quality and then most of the foresight happens in a different space where the users have more leverage to use data in many different ways to drive analytics and insights which is not readily available. >>Thank you for that. That's interesting discussion. You know digital transformation. It's a journey and it's going to take many years. A lot of ways, not a lot of ways 2020 was a forced March to digital. If you weren't a digital business, you were out of business and you really didn't have much time to plan. So now organizations are stepping back saying, okay let's really lean into our strategy the journey and along the way there's gonna be blind spots, there's bumps in the road when you look out what are the potential disruptions that you see maybe in terms of how companies are currently approaching their digital transformations? That's a great question. >>Dave and I'm going to take a little bit more longer term view on this topic. Right in what's top of my mind um recently is the whole topic of E. S. G. Environmental, social and governance. Most of the companies have governance in place, right? Because they are either public companies or they're under some kind of uh scrutiny from different regulatory bodies or what not. Even if you're a startup, you need to do things with our customers and what not. It has been there for companies. It continues to be there. We the public companies are very good at making sure that we have the right compliance, right privacy, right governance in in in place. Now we'll talk about cyber security. I think that creates a whole new challenge in that governance space. However, we have the set up within our companies to be able to handle that challenge. Now, when we go to social, what happened last year was really important. And now as each and every company, we need to think about what are we doing from our perspective to play our part in that. And not only the bigger companies leaders at our level, I would say that Between last March and this year, I have hired more than 400 people during pandemic, which was all virtual, but me and my team have made sure that we are doing the right thing to drive inclusion and diversity, which is also very big objective for h P E. And Antonio himself has been very active in various round tables in us at the world Economic forum level and I think it's really important for companies to create that opportunity, remove that disparity that's there for the underserved communities. If we want to continue to be successful in this world too, create innovative products and services, we need to sell it to the broader cross section of populations and to be able to do that, we need to bring them in our fold and enable them to create that um, equal consumption capabilities across different sets of people. Hp has taken many initiatives and so are many companies. I feel like uh, The momentum that companies have now created around the topic of equality is very important. I'm also very excited to see that a lot of startups are now coming up to serve that 99% versus just the shiny ones, as you know, in the bay area to create better delivery methods of food or products. Right. The third piece, which is environmental, is extremely important as well as we have seen recently in many companies and where even the dollar or the economic value is flowing are around the companies which are serious about environmental HP recently published its living Progress report. We have been in the forefront of innovation to reduce carbon emissions, we help our customers, um, through those processes. Again, if we do, if our planet is on fire, none of us will exist, right. So we all have to do that every little part to be able to do better. And I'm happy to report, I myself as a person, solar panels, battery electric cars, whatever I can do, but I think something more needs to happen right where as an individual I need to pitch in, but maybe utilities will be so green in the future that I don't need to put panels on my roof, which again creates a different kind of uh waste going forward. So when you ask me about disruptions, I personally feel that successful company like ours have to have E. S. G. Top of their mind and think of products and services from that perspective, which creates equal opportunity for people, which creates better environment sustainability going forward. And, you know, our customers are investors are very interested in seeing what we are doing to be able to serve that cause uh for for bigger cross section of companies, and I'm most of the time very happy to share with my C I. O cohort around how are H. P E F s capabilities creates or feeds into the circular economy, how much e waste we have recycled or kept it off of landfills are green capabilities, How it reduces the evils going forward as well as our sustainability initiatives, which can help other, see IOS to be more um carbon neutral going forward as well. >>You know, that's a great answer, rashmi, thank you for that because I gotta tell you hear a lot of mumbo jumbo about E S G. But that was a very substantive, thoughtful response that I think, I think tech companies in particular are have to lead in our leading in this area. So I really appreciate that sentiment. I want to end with a very important topic which is cyber. It's obviously, you know, escalated in, in the news the last several months. It's always in the news, but You know, 10 or 15 years ago there was this mentality of failure equals fire. Now we realize, hey, they're gonna get in, it's how you handle it. Cyber has become a board level topic, you know? Years ago there was a lot of discussion, oh, you can't have the sec ops team working for the C. I. O. Because that's like the Fox watching the Henhouse, that's changed. Uh it's been a real awakening, a kind of a rude awakening. So the world is now more virtual, you've gotta secure physical uh assets. I mean, any knucklehead can now become a ransomware attack, er they can, they can, they can buy ransomware as a services in the dark, dark web. So that's something we've never seen before. You're seeing supply chains get hacked and self forming malware. I mean, it's a really scary time. So you've got these intellectual assets, it's a top priority for organizations. Are you seeing a convergence of the sea? So roll the C. I. O. Roll the line of business roles relative to sort of prior years in terms of driving security throughout organizations. >>This is a great question. And this was a big discussion at my public board meeting a couple of days ago. It's as as I talk about many topics, if you think digital, if you think data, if you think is you, it's no more one organizations, business, it's now everybody's responsibility. I saw a Wall Street Journal article a couple of days ago where Somebody has compared cyber to 9-11-type scenario that if it happens for a company, that's the level of impact you feel on your on your operations. So, you know, all models are going to change where C so reports to see IO at H P E. We are also into products or security and that's why I see. So is a peer of mine who I worked with very closely who also worked with product teams where we are saving our customers from a lot of pain in this space going forward. And H. B. E. Itself is investing enormous amount of efforts in time in coming out of products which are which are secured and are not vulnerable to these types of attacks. The way I see it is see So role has become extremely critical in every company and the big part of that role is to make people understand that cybersecurity is also everybody's responsibility. That's why in I. T. V. Propagate def sec ups. Um As we talk about it, we are very very careful about picking the right products and services. This is one area where companies cannot shy away from investing. You have to continuously looking at cyber security architecture, you have to continuously look at and understand where the gaps are and how do we switch our product or service that we use from the providers to make sure our companies stay secure The training, not only for individual employees around anti phishing or what does cybersecurity mean, but also to the executive committee and to the board around what cybersecurity means, what zero trust means, but at the same time doing drive ins, we did it for business continuity and disaster recovery. Before now at this time we do it for a ransomware attack and stay prepared as you mentioned. And we all say in tech community, it's always if not when no company can them their chest and say, oh, we are fully secured because something can happen going forward. But what is the readiness for something that can happen? It has to be handled at the same risk level as a pandemic or earthquake or a natural disaster. And assume that it's going to happen and how as a company we will behave when when something like this happen. So I'm here's believer in the framework of uh protect, detect, govern and respond um as these things happen. So we need to have exercises within the company to ensure that everybody is aware of the part that they play day today but at the same time when some event happen and making sure we do very periodic reviews of I. T. And cyber practices across the company. There is no more differentiation between I. T. And O. T. That was 10 years ago. I remember working with different industries where OT was totally out of reach of I. T. And guess what happened? Wanna cry and Petra and XP machines were still running your supply chains and they were not protected. So if it's a technology it needs to be protected. That's the mindset. People need to go with invest in education, training, um awareness of your employees, your management committee, your board and do frequent exercises to understand how to respond when something like this happen. See it's a big responsibility to protect our customer data, our customers operations and we all need to be responsible and accountable to be able to provide all our products and services to our customers when something unforeseen like this happens, >>Russian, very generous with your time. Thank you so much for coming back in the CUBA is great to have you again. >>Thank you. Dave was really nice chatting with you. Thanks >>for being with us for our ongoing coverage of HP discover 21 This is Dave Volonte, you're watching the virtual cube, the leader in digital tech coverage. Be right back. >>Mm hmm, mm.

>>Welcome to this cube conversation that is a part of the AWS startup showcase. I'm lisa martin I've got with me now the ceo of amazon john Vitaly john welcome to the cube >>lisa. It's a pleasure to be here. Nice to see you. >>Likewise give our audience in a real liaison and what it is that you guys do specifically in pharma and life sciences. >>Well, you can find that in our, the name of the company is on uh, we think of us as leading uh, customers to the horizon of AI and pharmaceutical, biological manufacturing. And uh, we're all about helping our customers take The step into Pharma 40 and really realized the value of leveraging, machine learning and artificial intelligence in the manufacturing process so they can get higher yields and predictability and ultimately better outcomes for their patients. >>Is your technology built on AWS? >>Absolutely. From the ground up. We leverage, yeah, we leveraged as much as we can from AWS innovation and, you know, a few years ago, when our founders envisioned the future of manufacturing in this industry and where it needs to go first thought was go with a leader to build the solutions and of course A W. S. Is by far the largest provider of this type of technology. And we're happy to say that we're helping and partnering with A W. S. Two to advance the science of artificial intelligence in life sciences. And uh it's just a natural fit for us to continue to leverage the platform on behalf of our customers. >>I like that. The Ai horizon. Excellent. So talk to me a little bit about, you know, the last year has been presented many challenges and also opportunities for people in every industry. I'm just wondering what are some of the changes that we've seen? Farm and life sciences companies have become household names for example, but talk to me about some of the the key initiatives in smart manufacturing and what pharma companies require. >>Well sure, you know farmer companies and biotech companies like look into the lessons from other industries where ai has been widely adopted. If you look at uh manufacturing and other industries has been widely adopted for a number of years. Tesla is a great example of how to use A. I. And robotics and and data science uh to advance uh the efficiency of manufacturing globally. Uh that's exactly what we're trying to achieve here in in life sciences. So um you know, a lot of the leading innovators in this space have been working in their labs with data science teams to you know find new ways to collect data uh to cleanse that data, make it data that's useful across the enterprise. Um but they haven't really tackled, you know, continuous processing in manufacturing yet. There are a number of leaders that are mapping out strategies and they've begun to go down this path. Um But most are really looking at how first to bring the data together in a way that it could be democratized and anonymous in some cases and used across the enterprise. Uh There's a model that we've adopted in terms of our product strategy and how we engage customers and that's the uh the the pharmaceutical maturity model which was developed by the bio forum. This maturity models is a great way for companies and vendors alike innovators to look at how to help Advance their capabilities from one level to the next. And so we help customers understand where they are in that journey and we look for the areas where they can get traction more quickly. They can see value sooner and therefore the adoption would would be accelerating across across their their sites. And in different ways of use. >>Is that maturity model? That farm of maturity model? Is it is it built on or based on digital transformation? >>Absolutely. It's all about digital transformation. And so the model really begins with pre digital and you'd be amazed to find I think the the amount of Excel spreadsheets that are still used in manufacturing today and that would be what we would consider to be pretty much pre digital because that data is not accessible. It's only used by the operator or the user. So it's really about getting from that level to uh breaking down data silos and bringing that data together and harmonizing the data and making it useful. The next level would be about the connected plant actually connecting machines and data lakes um to begin to get more value and find find more ways to improve the processes. And then you move up to using advanced analytics and AI and then ultimately have an enterprise wide adaptive manufacturing capabilities, which is really the ultimate vision, ultimate goal. Every manufacturer has. >>One of the things that we've been talking about for the last 14 plus months or so is really the acceleration in cloud adoption, digital transformation as really a survival mechanism that many industries undertook. And we saw all of us go remote or many of us and be dependent on cloud based collaboration tools. For example, I'm curious in the pharmaceutical industry again, as I said, you know, we we know that the big three and for household names that many of us have been following for the last 14 months or so. What have you seen in terms of acceleration? Informal companies going all right, we need to figure out where we are in this maturity model. We need to be able to accelerate, you know, drug discovery, be able to get access to data. Has that accelerated in the Covid era? >>Covid has been the great catalyst of all time for this industry. Ah and I think it was a wake up call for a lot of, a lot of people in the industry to recognize that uh, just because we have the highest quality standards and we have highest level of compliance requirements and um, we ultimately all think about efficacy and patient safety as our goal to achieve the highest levels of quality. Everyone agrees with that. What the realization was is that we do not have the capacity in any, any geography or with any company, um, to meet the demands that we're seeing today demands to get product to market the demand to get the supply chain right and make it work for manufacturing. The, uh, the uh, The opportunity to partner to get there was, you know, you can see that by the way companies came together to partner for COVID-19 vaccine manufacturing production. And so, um, it was a wake up call that it's time to get over the kind of cultural barriers, risk aversion and really come together to coalesce around a a smart manufacturing strategy that has to be combined with a G XP or good manufacturing compliance standards. And that has to be designed in to the technology and manufacturing processes Together. That's Pharma 4.0, >>got it. Thank you. Let's dig in more to that GSP compliance. And you guys, we talk about that in different industries. The X being, you know, X for X type of industry, talk to me about the compliance regulations and your G XP AI platform and how you guys built on top of amazon, help customers evolve their maturity and facilitate complaints. >>Absolutely. So as I alluded to earlier, one of the biggest challenges is just getting the data together in a place that you can actually manage it. And because there's so many legacy systems and on predominantly on prem technologies and use today, cloud is starting to gain a lot more traction, but it's been limited to uh kind of tier two and tier three data. Uh so now we're seeing uh you know, the recognition that uh just having a data link isn't enough. And so uh we have to overcome, you know, the biggest barrier is really a version to change and change management is really a huge part of any customer being successful. And I think with a W S and us, we were working together to help customers customers understand the type of change management that's required. It's not enough to say, well, we're going to apply the old techniques and processes and use new technology. It just doesn't work that way. If you're adding people uh, and scaling up people just to do validation, worked on a brand new platform, like AWS offers, like we offer on top of AWS, you just won't get three return on investment, you won't get the outcomes and results you're targeting. Uh you have to really have a full strategy in place. Um but you can, and start in small ways, you can start to get traction with use cases that might not have the a huge impact that you're looking for, but it's a way to get started. And uh, the AWS platform is, you know, a great way to look at um, a strategy to scale manufacturing not just in one site but across multiple sites because it's really a data management strategy uh for us using US components uh to build our data collection technology was the starting point. So how do you bring this day together and make it easy and with low overhead and begin to use Ai at the point of collection? So we built our technology with AWS components to do that it's called we call them be data feeders and those are agents that go out and collect that data and bring it together. We also because of the way at AWS innovated around data management we can use a multitude of components to continue to build capabilities on top of what we have today. So we're excited to partner to follow the AWS Roadmap but also continue to add value to what A. W. S. Does today for customers. >>Right? Seems very symbiotic but also your gives you the platform gives you the agility and flexibility that you need to turn things on a dime. I like how you said Covid was a catalyst. I've been saying that for a year now there are things that it has catalyzed for the good and one of those that we've seen repeatedly is that the need for real time data access in many industries like life sciences and pharma is no longer a nice to have but it's incredibly challenging to get real time access to high quality data. Be able to run analytics on that you know, identify where the supply chain in the manufacturing process. For example things can be optimized. Give me an example or some examples of some of the use cases that you guys are working with customers on. I imagine things like that to process optimization, anomaly detection. But what are some of those key use cases in which you really excel? >>Well, it all starts with with what we can do around predictions. There's a lot of data science work being done today, understand variability and how to reduce deviations and how to get more um of predictions to know what is expected to happen. Uh But a lot of that doesn't get applied to the processes. It's not applied as a change the process because that requires revalidation of that entire process. Our platform brings huge value to customers and partners because we do the qualification and validation on the platform in real time. And so that eliminates the needs to go back out and deploy people and uh track and re document uh and re validate what's going on in the process. So that that just takes a huge uh responsibility in some cases liabilities off off of the operators and uh the folks analyzing the data. So that's that's really to get to real time. You have to think carefully about how to apply apply ai because a I was developed in a scientific way but you also have to apply it in a scientific way to to these critical processes in manufacturing. And so that's that's only done uh on a platform, you can't do it on a kind of a stand alone basis. You have to leverage a platform because you're analysing changes to the data and to the code being used to collect and analyze the data that all has to be documented. And that's that's done by our capabilities are using to audit or create audit trails uh to any changes that are happening in the process. And so that's a critical critical process monitoring capability. That is almost impossible to do manually. Uh Some some would say it's impossible to do manually. Uh so uh the the ability to to qualify algorithms to validate in real time enables real time manufacturing and there's a F. D A. Uh I would I would say mandate but guidance called continuous process verification cPV that they will be coming out with additional guidance on that this year. That's really there to uh tell tell manufacturers that they should be getting to real time capabilities. They should be driving their investments and and types of deployments to get to real time manufacturing. That's the only way you can predict deviations and predict anomalies and deal with them in the process and track it. >>So give me give me a snapshot of a customer or two that you've worked with in the last year as they were rapidly evolving and adjusting to the changes going on. How did you help some of these customers extract more value from their pharma manufacturing processes, understand what it is that they need to do to embrace A. I. And get to that real time. >>Absolutely. So, you know, most of our customers are facing the challenge and dilemma that just adding more people and more resources and even upgrading existing technologies or adding more data scientist has a limit. They've reached the limit of improvement that they can make to these processes in the output in manufacturing. So the next natural step would be to say, okay, what science can I apply here and what technology is available To really get to that next one or two improvement in the processes. And it's really critical to look at um you know, not just one use case, but how can I address multiple problems using the same technology? So bringing multi variant uh multi variable excuse me. Um analysis capabilities um is is something that's done in every other industry um but it has not been applied here in terms of changing how manufacturing works today. We can do that, we can we can do multi variable analysis in real time, we can predict what will happen. We can actually alert the operator to make changes to the process based on uh a number of predictions of what will happen in a batch or series of matches in manufacturing. We also bring unstructured data into those calculations that wasn't possible before cloud technology came along and before a I was deployed. Um So now we can look at environmental inputs, we can look at um upstream data that can be used for improving um you know, the yield on batches. So the you know, the main um focus today is you know, how do I get, reduce my risk around asset management? How can I improve visibility into the supply chain? How can I reduce deviations in these processes? How can I get more yield? How can I optimize the yield uh in any given batch uh to improve uh you know, the entire process but also reduce costs in each step of the way. Uh So uh the good news is that when you apply our technology and our know how uh there's an immediate positive impact. There's a customer, we're working with very large customer where we walked in and they said we have this problem, we've reached a certain level of optimization and yield. We can't seem to get it to go any higher. and within six weeks we had a solution in place and we are saving them tens of millions of dollars in material loss just in that once one step in the process that's worth hundreds of millions of dollars in terms of finished product. Uh and if you apply that across multiple lines and across multiple manufacturing sites for that customer, we're talking hundreds of millions of dollars of savings, um >>significant impact, significant business impact that your customers I saw on the website, you know, R. O. I. And was at six when I get this right. I had it here somewhere um quite quickly. But the key thing there is that these organizations actually are really moving their business forward. You just gave some great examples of how you can do that. And just kind of a phase one of the project. Let me ask you this in in a post Covid world, assuming we'll get there hopefully soon. Where is in your opinion? Um Ai and ml for pharma companies, is it going to be something that is is for those that adopt it and adopt all the change management needed to do that? Is it going to be kind of the factor in deciding the winners and the losers of tomorrow? Okay, >>well, I don't want to lay down predictions like that, but I would, what I would say is uh all of thought leaders out there have have openly shared and privately shared that this is exactly where the industry has to go to meet the demands. Not just of ramping up COVID-19 vaccine production on a global basis, which we have to do. It's also dealing with how do we how do we uh scale up for personalized medicine, which requires small, small batch manufacturing? How do we turn over lines of manufacturing more efficiently to get more drugs to market more different types of drugs to market, how to contract manufacturers deal with all these pressures, um, and still serve their customers and innovate. Uh, there's also the rise of generics there, you know, that's bringing on cost pressures for big pharma particularly. And so these are all moving the industry in the right direction to respond to these on an individual basis. Would would definitely require the use of Ai and Ml But when you bring it all together, there's a huge huge of push for finding and finding breakthroughs to increase capacity and quality at the same time. >>Yeah, tremendous opportunity. My last question for you, john is a bit more on the personal side. I know you're a serial entrepreneur. What drew you to a zon when you have the opportunity? I can only imagine based on some of the things that you've said. But what was it that you said? This is my next great >>opportunity. That's a great question because I asked myself that question, uh so having been in the industry for for a long time, having been with very innovative companies my whole career, uh I knew that uh manufacturing had fallen behind even further in terms of innovating using the latest cloud technologies and ai in particular, I knew that from running another company uh that focused on the use of predictive analytics. And so uh given all the vectors coming together, the market pressure that's happening on the technology, absolutely. Being a maturity level that we could we could make these things a reality for customers in the size of the challenge. And market opportunity was just overwhelming. It was it was enough to make me jump in with both feet. So I'm very happy uh to be leading such a great team and amazing, amazing talent at amazon and super excited about our partnership with a W. S and where that's going and solving very, very complex and very critical, uh, challenges that our customers are facing together as partners. >>Absolutely. Well, john, thank you for joining me today and talking to us about who is on is what you're doing, particularly in pharma and life sciences, smart manufacturing and what you're enabling in a covid catalysis sort of way. We appreciate you joining us here today. >>This has been a pleasure. Thanks for having me. >>Likewise for john Vitaly, I'm lisa martin, you're watching the cube.

>>what? Hello, I'm john free with the cube. I want to welcome Conrad Feldman, the founder and Ceo of Kwan cast here to kick off the quan cast industry summit on the demise of third party cookies. The events called the cookie conundrum, a recipe for success. The changing advertising landscape, super relevant conversation just now. More than ever. Conrad welcome to your own program kicking this off. Thanks for holding this event. It's a pleasure. Great to chat with you today. So a big fan been following your company since the founding of it. Been analytics is always the prize of any data driven company. Media. Anything's all data driven now. Um, talk about the open internet because now more than ever it's under siege. As I, as I mentioned in my open, um, we've been seeing the democratization, a new trend of decentralization. We're starting to see um, you know, everyone's present online now, Clay Shirky wrote a book called, here comes everyone in 2005. Well everyone's here. Right? So you know, we're here, it's gonna be more open. But yet people are looking at as close right now. You're seeing the big players, um, or in the data. What's your vision of this open internet? >>Well, an open internet exists for everyone. And if you think about the evolution of the internet, when the internet was created for the first time really in history, anyone that had access to the internet could publish the content, whatever they were interested in and could find an audience. And of course that's grown to where we are today, where five billion people around the world are able to engage in all sorts of content, whether that's entertainment or education, news, movies. What's perhaps not so widely understood is that most of that content is paid for by advertising and there's a lot of systems that support advertising on the open Internet and some of those are under siege today certainly. >>And what's the big pressure point? Is it just more control the data? Is it just that these walled gardens are wanting to, you know, suck the audience in there? Is that monetization driving it? What's where's the friction? >>Well, the challenges is sort of the accumulation of power into a really small number of now giant corporations who have actually reduced a lot of the friction that marketers have in spending their money effectively. And it means that those companies are capturing a disproportionate spend of the ad budgets that fund digital content. So the problem is if more of the money goes to them, less of its going to independent content creators. It's actually getting harder for independent voices to emerge and be heard. And so that's the real challenges. That has more power consolidates into just a limited number of tech giants. The funding path for the open Internet becomes constrained and there'll be less choice for consumers without having to pay for subscriptions. >>Everyone knows the more data you have the better and certainly, but the centralized power when the trend is going the other way, the consensus is everyone wants to be decentralized more truth, more trust all this is being talked about on the heels of the google's news around, you know, getting rid of third party cookies and others have followed suit. Um, what does this mean? I mean, this cookies have been the major vehicle for tracking and getting that kind of data. What is gonna be replaced with what is this all about? And can you share with us what the future will look like? >>Sure, Well, just as advertising funds the open Internet is advertising technology that supports that advertising spend. It supports sort of the business of advertising that funds the open Internet. And within all of that technology is the need for different systems to be able to align around um the identification of for example, a consumer, Have they been to this site before? Have they seen an ad before? So there's all of these different systems that might be used for advertising for measurement, for attribution, for creating personalization. And historically they've relied upon the third party cookie as the mechanism for synchronization. Well, the third party cookie has been in decline for some time. It's already mostly gone from actually apple safari browser, but google's chrome has so much control over how people access the internet. And so it was when Google announced that chrome was going to deprecate the third party cookie, that it really sort of focus the minds of the industry in terms of finding alternative ways to tailor content and ultimately to just simply measure the effectiveness of advertising. And so there's an enormous amount of um innovation taking place right now to find alternative solutions. >>You know, some are saying that the free open internet was pretty much killed when, you know, the big comes like facebook and google started bringing all this data and kind of pulls all sucks all the auction in the room, so to speak. What's this mean with cookies now getting, getting rid of um, by google has an impact publishers because is it helpful? I mean hurtful. I mean, where's the where is that, what the publisher impact? >>Well, I don't think anyone really knows right now. So first of all, cookies weren't necessarily a very good solution to the sort of the challenge of maintaining state and understanding those sorts of the delivery of advertising and so on. It's just the one that's commonly used, I think for different publishers it may mean different things. But many publishers need to be able to demonstrate the value and the effectiveness of the advertising solutions that they deliver. So they'll be innovating in terms of how they use their first party data. They'll be continuing to use contextual solutions that have long been used to create advertising relevant, relevant. I think the big question of course is how we're going to measure it that any of this is effective at all because everyone relies upon measuring advertising effectiveness to justify capturing those budgets in the first place. >>You know, you mentioned contextual come up a lot also in the other interviews we've done with the folks in the around the internet around this topic of machine learning is a big 12 What is the impact of this with the modernization of the solution? You mentioned cookies? Okay cookies, old technology. But the mechanisms in this ecosystem around it or not, it funds the open internet. What is that modern solution that goes that next level? Is it contextual metadata? Is that shared systems? What's the it's the modernization of that. >>It's all of those and and more. There's no there's no single solution to replace the third party cookie. There'll be a combination of solutions. Part of that will be alternative identity mechanisms. So you know, you will start to see more registration wars to access content so that you have what's called a deterministic identify there will be statistical models so called probabilistic models, contextual has always been important. It will become more important and it will be combined with we use contextual combining natural language processing with machine learning models to really understand the detailed context of different pages across the internet. You'll also see the use of first party data and there are discussions about shared data services as well. I think there's gonna be a whole set of different innovations that will need to inter operate and it's going to be an evolutionary process as people get used to using these different systems to satisfy the different stages of the media fulfillment cycle from research and planning to activation to measurement. >>You know, you put up walled gardens. I want to just touch on the on on this kind of concept of walled gardens and and and and compare and contrast that with the demand for community, open internet has always fostered a community vibe. You see network effects mostly in distinct user communities or subnets of sub networks. If you will kind of walled gardens became that kind of group get together but then became more of a media solution to make the user is the product, as they say, facebook's a great example, right? People talk about facebook and from that misinformation abuse walled garden is not the best thing happening right now in the world, but yet is there any other other choice? That's how they're going to make money? But yet everyone wants trust, truth community. Are they usually exclusive? How do you see this evolving, what's your take? >>Well, I think the open internet is a, is a forum where anyone can have their voice, uh, put their voice out there and have it discovered and it's in that regard, it's a it's a force for good look. I think there are there are challenges, obviously in terms of some of the some of the optimization that takes place with inside the walled gardens, which is, is sort of optimized to drive engagement can have some unintended consequences. Um obviously that's something that's, that's broadly being discussed today and the impact on society, but sort of more at a more pointed level, it's just the absorption of advertising dollars. There's a finite amount of money from advertisers. It's estimated to be $400 billion this year in digital advertising. So it's a huge amount of money in terms of funding the open Internet, which sounds great except for its increasingly concentrated in a tiny number of companies. And so, you know, our job at Quan cast as champions of the free and open Internet is to help direct money effectively to publishers across the open internet and give advertisers a reliable, repeatable way of accessing the audiences that they care about in the environment they care about and delivering advertising results. >>It's a publisher, we care a lot about what our audience wants and try to serve them and listen to them. If we could get the data, we want that data and then also broker in the monetization with advertisers, who might want to reach that audience in whatever way. So this brings up the question of, you know, automation and role of data. You know, this is a huge thing to having that data closed loop, if you will for for publishers. But yet most publishers are small, some niche. And even as they can become super large, they don't have all the data and more, the more data, the better the machine learning. So what's the answer to this as it goes forward? How do we get there? What's the dots that that we need to connect to get that future state? >>So I think it takes it takes companies working together effectively. I think a really important part of it is, is a more direct conversation with consumers. We've seen that change beginning to happen over the past few years with the introduction of regulations that require clear communication to consumers about the data that's captured. And y and I think that creates an opportunity to explain to your audience is the way in which content is funded. So I think that consumer that consumer conversation will be part of the collective solution. >>You know, I want to as we wind down this kickoff segment, get your thoughts and vision around um, the evolution of the internet and you guys have done some great work at quan Cast is well documented, but everyone used to talk about traffic by traffic, then it became cost of acquisitions. PPC search. This is either mechanisms that people have been using for a long, long time, then you know, your connections but audience is about traffic, audience traffic. If this if my family is online, doesn't it become about networks and the people. So I want to get your thoughts and your vision because if community is going to be more important than people agree that it is and things are gonna be decentralized, more openness, more voices to be heard. You need to dress ability. The formation of networks and groups become super important. What's your vision on that? >>So my vision is to create relevance and utility for consumers. I think that's one of the things that's often forgotten is that when we make advertising more relevant and useful for consumers, it automatically fulfils the objectives that publishers and marketers have, everyone wins when advertising is more relevant. And our vision is to make advertising relevant across the entire open internet so that that ad supported model can continue to flourish and that five billion and hopefully many more billions in the future, people around the world have access to high quality, diverse content. >>If someone asked you Conrad, what is quant cast doing to make the open internet viable now that cookies are going away? What's the answer? >>So well, the cookie pieces is a central piece of it in terms of finding solutions that will enable sort of planning activation and measurement post cookies and we have a lot of innovation going on. There were also working with a range of industry bodies and our and our partners to build solutions for this. What we're really trying to do is to make buying the open internet as straightforward for marketers as it is today and buying the walled gardens. The reason the walled gardens capture so much money is they made it really easy for marketers to get results, marketers would like to be able to spend their money across all of the diverse publishes the open internet. You know, our job at Comcast is to make it just as easy to effectively spend money in funding the content that they really care about in reaching the audiences that they want. >>Great stuff. Great Mission. Conrad, thanks for coming on. Conrad Feldmann founder and Ceo here at the cookie conundrum recipe for success event, Quant Cast Industry summit on the demise of third party cookies. Thank you. Conrad appreciate it. Thank you. Yeah, I'm john ferrier, stay with us for more on the industry event around the middle cookies. Mhm Yeah, yeah, thank you. Mhm. Welcome back to the Qantas industry summit on the demise of third party cookies, the cookie conundrum, a recipe for success. I'm john furrier host of the cube, the changing landscape of advertising is here and shit Gupta, founder of you of digital is joining us chief. Thanks for coming on this segment. Really appreciate, I know you're busy, you've got two young kids as well as providing education to the digital industry, you got some kids to take care of and train them to. So welcome to the cube conversation here as part of the program. >>Yeah, thanks for having me excited to be here. >>So the office of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big 34 tech players dominate the marketplace so clearly in a major inflection point and we've seen this movie before Web mobile revolution which was basically a reply platform NG of capabilities. But now we're in an error of re factoring the industry, not re platt forming a complete changing over of the value proposition. So a lot at stake here as this open web, open internet, global internet evolves. What are your, what's your take on this, this industry proposals out there that are talking to this specific cookie issue? What does it mean? And what proposals are out there? >>Yeah, so, you know, I I really view the identity proposals and kind of to to kind of groups, two separate groups. So on one side you have what the walled gardens are doing and really that's being led by google. Right, so google um you know, introduce something called the privacy sandbox when they announced that they would be deprecating third party cookies uh as part of the privacy sandbox, they've had a number of proposals unfortunately, or you know, however you want to say they're all bird themed for some reason, I don't know why. Um but the one, the bird theme proposal that they've chosen to move forward with is called flock, which stands for Federated learning of cohorts. And essentially what it all boils down to is google is moving forward with cohort level learning and understanding of users in the future after third party cookies, unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting tracking purposes. And so that's on one side of the equation, it's what google is doing with flock and privacy sandbox now on the other side is, you know, things like unified I. D. Two point or the work that I. D five is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, unified I. D. Two point oh comes to mind because it's the one that's probably got the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it and unified, I need to point out again is user level. So it's it's basically taking data that's authenticated data from users across various websites you know that are logging in and taking those authenticated users to create some kind of identity map. And so if you think about those two work streams right, you've got the walled gardens and or you know, google with flock on one side and then you've got unified I. D. Two point oh and other I. D. Frameworks for the open internet. On the other side, you've got these two very differing type of approaches to identity in the future. Again on the google side it's cohort level, it's going to be built into chrome. Um The idea is that you can pretty much do a lot of the things that we do with advertising today, but now you're just doing it at a group level so that you're protecting privacy, whereas on the other side of the open internet you're still getting down to the user level. Um And that's pretty powerful. But the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw is under five of all website traffic is authenticated. So really if you if you simplify things you boil it all down, you have kind of these two very differing approaches. >>I guess the question it really comes down to what alternatives are out there for cookies and which ones do you think will be more successful? Because I think, you know, the consensus is at least from my reporting, in my view, is that the world agrees. Let's make it open, Which one is going to be better. >>Yeah, that's a great question, john So as I mentioned, right, we have we have to kind of work streams here, we've got the walled garden work streams, work stream being led by google and their work around flock, and then we've got the open internet, right? Let's say unified I. D to kind of represents that. I personally don't believe that there is a right answer or an endgame here. I don't think that one of them wins over the other, frankly, I think that, you know, first of all, you have those two frameworks, neither of them are perfect, they're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution. Right? So they're saying, hey, we use, you know, an open I. D. Framework in this way to get down to the user level and use that authenticated data and that's important. But we don't have all the scale. So now we go to google and we go to flock to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce, right? We have some of our own data, we have some of our own partnerships, we're gonna bring that in and layer it on top. Right? And so really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both. With a little extra something on top. I think that's that's what we're starting to see out of a lot of companies in the space. And I think that's frankly where we're headed. >>What do you think the industry will evolve to, in your opinion? Because I think this is gonna, you can't ignore the big guys on this because these programmatic you mentioned also the data is there. But what do you think the market will evolve to with this, with this conundrum? >>So, so I think john where we're headed? You know, I think we're right now we're having this existential existential crisis, right? About identity in this industry, because our world is being turned upside down, all the mechanisms that we've used for years and years are being thrown out the window and we're being told they were gonna have new mechanisms, Right? So cookies are going away device ids are going away and now we got to come up with new things and so the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Like everyone's always talking about identity right now, where do I think this is going if I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today. Right? Forget about all the changes. Just think about it now and maybe a few years before today, Identity for marketers in my opinion has been a little bit of a checkbox activity. Right? It's been hey, um, okay, uh, you know ad tech company or a media company, do you have an identity solution? Okay. Tell me a little bit more about it. Okay, Sounds good. That sounds good. Now can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business? And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know. Yes, You have it. Okay, great. Let's move on, type of thing. Right. And so that, that's, that's kind of where we've been now, all of a sudden The cookies are going away, the device ids are going away. And so the world is turning upside down in this crisis of how are we going to keep doing what we were doing for the last 10 years in the future. So everyone's talking about it and we're trying to re engineer right? The mechanisms now if I was to look into the crystal ball right 2 3 years from now where I think we're headed is not much is going to change. And what I mean by that john is um uh I think that marketers will still go to companies and say do you have an ID solution? Okay tell me more about it. Okay uh Let me understand a little bit better. Okay you do it this way. Sounds good. Now the ways in which companies are going to do it will be different right now. It's flock and unified I. D. And this and that right. The ways the mechanisms will be a little bit different but the end state right? Like the actual way in which we operate as an industry and kind of like the view of the landscape in my opinion will be very simple or very similar, right? Because marketers will still view it as a tell me you have an ID solution. Make me feel good about it. Help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment where we do have to talk about and figure out what we're going to do in the future. My just my viewpoint is that the future will actually not look all that different than the present. >>And I'll say the user base is the audience. Their their data behind it helps create new experiences, machine learning and Ai are going to create those and we have the data you have the sharing it or using it as we're finding shit Gupta great insight dropping some nice gems here. Founder of you of Digital and also the Adjunct professor of Programmatic advertising at Levi School of Business and santa Clara University professor. Thank you for coming dropping the gems here and insight. Thank you. >>Thanks a lot for having me john really appreciate >>it. Thanks for watching. The cooking 100 is the cube host Jon ferrier me. Thanks for watching. Mhm. Yeah. Mhm. Hello welcome back to the cookie conundrum recipe for success and industry conference and summit from Guanacaste on the demise of third party cookies. Got a great industry panel here to break it down chris Gunther Senior Vice president Global Head of programmatic at news corp chris thanks for coming on Zal in Managing Director Solutions at Z axis and Summer Simpson. Vice president Product at quan cast stellar panel. Looking forward to this conversation. Uh thanks for coming on and chatting about the cookie conundrum. Thank you for having us. So chris we'll start with you at news corp obviously a major publisher deprecation of third party cookies affects everyone. You guys have a ton of traffic, ton of audience across multiple formats. Um, tell us about the impact to you guys and the reliance he has had on them. And what are you gonna do to prepare for this next level change? >>Sure. I mean, I think like everyone in this industry there's uh a significant reliance and I think it's something that a lot of talk about audience targeting but obviously that reliance on third party cookies pervasive across the whole at tech ecosystem Martek stack. And so you know, we have to think about how that impact vendor vendors, we work with what it means in terms of use cases across marketing, across advertising, across site experience. So, you know, without a doubt, it it's it's significant, but you know, we look at it as listen, it's disruptive, uh, disruption and change is always a little scary. Um, but overall it's a, it's a long overdue reset. I mean, I think that, you know, our perspective is that the cookies, as we all know was it was a crutch, right sort of a technology being used in way it shouldn't. Um, and so as we look at what's going to happen presumably after Jan 2022 then it's, it's a good way to kind of fix on some bad practices practices that lead to data leakage, um, practice or devalue for our perspective, some of the, you know, we offered as as publishers and I think that this is a key thing is that we're not just looking to as we look at the post gender world, not just kind of recreating the prior world because the prior world was flawed or I guess you could say the current world since it hasn't changed yet. But the current world is flawed. Let's not just not, you know, let's not just replicate that. Let's make sure that, you know, third party cookie goes away. Other work around like fingerprinting and things like that. You know, also go away so philosophically, that's where our heads at. And so as we look at how we are preparing, you know, you look at what are the core building blocks of preparing for this world. Obviously one of the key ones is privacy compliance. Like how do we treat our users with consent? Yeah, obviously. Are we um aligned with the regulatory environments? Yeah. In some ways we're not looking just a Jan 2022, but Jan 23 where there's gonna be the majority of our audiences we covered by regulation. And so I think from regulation up to data gathering to data activation, all built around an internal identifier that we've developed that allows us to have a consistent look at our users whether they're logged in or obviously anonymous. So it's really looking across all those components across all our sites and in all in a privacy compliant way. So a lot of work to be done, a lot of work in progress. But we're >>excited about what's going on. I like how you framed at Old world or next gen kind of the current situation kind of flawed. And as you think about programmatic, the concept is mind blowing and what needs to be done. So we'll come back to that because I think that original content view is certainly relevant, a huge investment and you've got great content and audience consuming it from a major media standpoint. Get your perspective on the impact because you've got clients who want to get their their message out in front of the audience at the right time, at the right place and the right context. Right, So your privacy, you got consent, all these things kind of boiling up. How do you help clients prepare? Because now they can go direct to the consumer. Everyone, everyone has a megaphone, now, everyone's, everyone's here, everyone's connected. So how are you impacted by this new notion? >>You know, if if the cookie list future was a tic tac, dance will be dancing right now, and at least into the next year, um this has been top of mind for us and our clients for quite some time, but I think as each day passes, the picture becomes clearer and more in focus. Uh the end of the third party cookie does not mean the end of programmatic. Um so clients work with us in transforming their investments into real business outcomes based on our expertise and based on our tech. So we continue to be in a great position to lead to educate, to partner and to grow with them. Um, along this uh cookie list future, the impact will be all encompassing in changing the ways we do things now and also accelerating the things that we've already been building on. So we take it from the top planning will have a huge impact because it's gonna start becoming more strategic around real business outcomes. Uh where Omni channel, So clients want to drive outcomes, drew multiple touch points of a consumer's journey, whether it has programmatic, whether it has uh cookie free environment, like connected tv, digital home audio, gaming and so forth. So we're going to see more of these strategic holistic plans. Creative will have a lot of impact. It will start becoming more important with creative testing. Creative insights. You know, creative in itself is cookie list. So there will be more focused on how to drive uh brand dialogue to connect to consumers with less targeting. With less cookies, with the cohesiveness of holistic planning. Creative can align through multiple channels and lastly, the role of a. I will become increasingly important. You know, we've always looked to build our tech our products to complement new and existing technology as well as the client's own data and text back to deliver these outcomes for them. And ai in its core it's just taking input data uh and having an output of your desired outcome. So input data could be dSP data beyond cookies such as browser such as location, such as contextual or publisher taking clients first party data, first party crm data like store visitation, sales, site activity. Um and using that to optimize in real time regardless of what vendor or what channel we're on. Um So as we're learning more about this cookie list dance, we're helping our clients on the steps of it and also introducing our own moves. >>That's awesome. Data is going to be a key value proposition, connecting in with content real time. Great stuff. Somewhere with your background in journalism and you're the tech VP of product at quan cast. You have the keys to the kingdom over there. It's interesting Journalism is about truth and good content original content. But now you have a data challenge problem opportunity on both sides, brands and publishers coming together. It's a data problem in a way it's a it's a tech stack, not so much just getting the right as to show up at the right place the right time. It's really bigger than that now. What's your take on this? >>Um you know, >>so first >>I think that consumers already sort of like except that there is a reasonable value exchange for their data in order to access free content. Right? And that's that's a critical piece for us to all kind of like understand over the past. Hi guys, probably two years since even even before the G. D. P. R. We've been doing a ton of discovery with customers, both publishers and marketers. Um and so you know, we've kind of known this, this cookie going away thing has been coming. Um And you know, Google's announcement just kind of confirmed it and it's been, it's been really, really interesting since Google's announcement, how the conversations have changed with with our customers and other folks that we talked to. And I've almost gone from being like a product manager to a therapist because there's such an emotional response. Um you know, from the marketing perspective, there's real fear there. There's like, oh my God, how you know, it's not just about, you know, delivering ads, it's about how do I control frequency? How do I, how do I measure, you know, success? Because the technology has has grown so much over the years to really give marketers the ability to deliver personalized advertising, good content, right. The consumers um and be able to monitor it and control it so that it's not too too intrusive on the publisher perspective side, we see slightly different response. It's more of a yes, right. You know, we're taking back control and we're going to stop the data leakage, we're going to get the value back for our inventory. Um and that both things are a good thing, but if it's, if it's not managed, it's going to be like ships passing in the night, right? In terms of um of, you know, they're there, them coming together, right, and that's the critical pieces that they have to come together. They have to get closer, you got to cut out a lot of that loom escape in the middle so that they can talk to each other and understand what's the value exchange happening between marketers and publishers and how do we do that without cookies? >>It's a fascinating, I love love your insight there. I think it's so relevant and it's got broader implications because, you know, if you look at how data's impact, some of these big structural changes and re factoring of industries, look at cyber security, you know, no one wants to share their data, but now if they share they get more insight, more machine learning, benefit more ai benefit. So now we have the sharing notion, but that goes against counter the big guys that want to wall garden, they want to hoard all the data and and control that to provide their own personalization. So you have this confluence of, hey, I want to hoard the data and then now I want to share the data. So so christmas summer you're in the, in the wheelhouse, you got original content and there's other providers out there. So is there the sharing model coming with privacy and these kinds of services? Is the open, come back again? How do you guys see this uh confluence of open versus walled gardens, because you need the data to make machine learning good. >>So I'll start uh start off, I mean, listen, I think you have to give credit to the walled gardens have created, I think as we look as publishers, what are we offering to our clients, what are we offering to the buy side? We need to be compelling. We shouldn't just be uh yeah, actually as journalists, I think that there is a case of the importance of funding journalism. Um but ultimately we need to make sure we're meeting the KPI is and the business needs of the buy side. And I think around that it is the sort of three core pillars that its ease of access, its scope of of activation and targeting and finally measurable results. So as I think is us as an individual publishers, so we have, we have multiple publications. So we do have scale. But then in partnership with other publishers perhaps to organizations like pre bid, you know, I think we can, you know, we're trying to address that and I think we can offer something that's compelling um, and transparent in terms of what these results are. But obviously, you know, I want to make sure it's clear transparent terms of results, but obviously where there's privacy in terms of the data and I think the form, you know, I think we've all heard a lot like data clean rooms, a lot of them out there flogging those wears. I think there's something valuable but you know, I think it's the right who is sort of the right partner or partners um and ultimately who allows us to get as close as possible to the buy side. And so that we can share that data for targeting, share it for perhaps for measurement, but obviously all in a privacy compliant >>way summer, what's your take on this? Because you talk about the future of the open internet democratization, the network effect that we're seeing in Vire al Itty and across multiple on the on the channels. Is that pointed out what's happening? That's the distribution now. So um that's almost an open garden model. So it's like um yeah, >>yeah, it's it's um you know, back in the day, you know, um knight ridder who was who was the first group that I that I worked for, um you know, each of those individual properties, um we're not hugely valuable on their own from a digital perspective, but together as a unit, they became valuable, right, and got scale for advertisers. Now we're in a place where, you know, I kind of think that each of those big networks are going to have to come together and work together to compare in size to the, to the world gardens. Um, and yeah, this is something that we've talked about before and an open garden. Um, I think that's the, that's the definitely the right route to take. And I and I agree with chris it's, it's about publishers getting as close to the market. Is it possible working with the tech companies that enable them to do that and doing so in a very privacy centric >>way. So how do we bring the brands and agencies together to get ready for third party cookies? Because there is a therapist moment here of it's gonna be okay. The parachute will open. The future is not gonna be as as grim. Um, it's a real opportunity. But if managed properly, what's your take on this is just more first party data strategy and what's your assessment of this? >>So we collaborated right now with ball grants on how did this still very complex cookie list future. Um, you know what's going to happen in the future? 2, 6 steps that we can take right now and market should take. Um, The first step is to gather intel on what's working on your current campaign, analyzing the data sets across cookie free environment. So you can translate those tactics eventually when the cookies do go away. So we have to look at things like temperature or time analysis. We could look at log level data. We could look at site analytics data. We can look at brand measurement tools and how creative really impacts the campaign success. The second thing we can look at is geo targeting strategies. The geo target strategy has been uh underrated because the granularity and geo data could go down all the way to the local level, even beyond zip code. So for example the census black data and this is especially important for CPG brands. So we're working closely with the client teams to understand not only the online data but the offline data and how we can utilize that in the future. Uh We want to optimize investments around uh markets that are working so strong markets and then test and underperforming markets. The third thing we can look at is contextual. So contextual by itself is cookie free. Uh We could build on small scale usage to test and learn various keywords and content categories based sets. Working closely with partners to find ways to leverage their data to mimic audiences that you are trying to target right now with cookies. Um the 4th 1 is publisher data or publisher targeting. So working with your publishers that you have strong relationships with who can curate similar audiences using their own first party data and conducting RFs to understand the scale and reach against your audience and their future role maps. So work with your top publishers based on historical data to try to recreate your best strategies. The 15 and I think this is very important is first party data, you know, that's going to matter more than ever. In the calculus future brands will need to think about how to access and developed the first party data starting with the consumers seeing a value in exchange for the information. It's a gold mine and understanding of consumer, their intent, the journey um and you need a really great data science team to extract insights out of that data, which will be crucial. So partner with strategic onboarding vendors and vet their ability to accept first party data into a cleaner environment for targeting for modeling for insight. And lastly, the six thing that we can do is begin to inform prospect prospecting by dedicating test budget to start gaining learnings about cookie list 11 place that we can start and it is under invested right now is Safari and Firefox. They have been calculus for quite some time so you can start here and begin testing here. Uh work with your data scientist team to understand the right mix is to to target and start exploring other channels outside of um just programmatic cookies like CTV digital, out of home radio gaming and so forth. So those are the six steps that we're taking right now with our clients to uh prepare and plan for the cookie list future. >>So chris let's go back to you. What's the solution here? Is there one, is there multiple solutions? What's the future look like for a cookie was future? >>Uh I think the one certain answers, they're definitely not just one solution. Um as we all know right now there there seems to be endless solutions, a lot of ideas out there, proposals with the W three C uh work happening within other industry bodies uh you know private companies solutions being offered and you know, it's a little bit of it's enough to make everyone's head spin and to try to track it to understand and understand the impact. And as a publisher were obviously a lot of people are knocking on our door. Uh they're saying, hey our solution is one that is going to bring in lots of money, you know, the all the buy side is going to use it. This is the one like I ma call to spend um, and so expect here and so far is that none of these solutions are I think everyone is still testing and learning no one on the buy side from our, from our knowledge is really committed to one or a few. It's all about a testing stage. I think that, you know, putting aside all that noise, I think what matters the most to us as publisher is actually something summer mentioned before. It's about control. You know, if we're going to work with a again, outside of our sort of, you know, internal identifier work that we're doing is we're going to work with an outside party or outside approach doesn't give us control as a publisher to ensure that it is, we control the data from our users. There isn't that data leakage, it's probably compliant. What information gets shared out there. What is it, what's released within within the bid stream? Uh If it is something that's attached to a somewhat declared user registered user that if that then is not somehow amplified or leverage off on another site in a way that is leveraging bit stream data or fingerprinting and going against. I think that the spirit of what we're trying to do in a post third party cookie world so that those controls are critical and I think they have those controls, his publisher, we have collectively be disciplined in what solutions that we we test out and what we eventually adopt. But even when the adoption point arrives, uh definitely it will not be one. There will be multiple because it's just too many use cases to address >>great, great insight there from, from you guys, news corp summer. Let's get back to you. I want to get your thoughts. You've been in many waves of innovation ups and downs were on a new one. Now we talked about the open internet democratization. Journalism is under a lot of pressure now, but there's now a wave of quality people really leaning in towards fighting misinformation, understanding truth and community and date is at the heart of it. What do you see as the new future for journalists, reward journalism is our ways their path forward. >>So there's uh, there's what I hope is going to happen. Um, and then I'm just gonna ignore what could write. Um, you know, there's there's a trend in market right now, a number of fronts, right? So there are marketers who are leaning into wanting to spend their marketing dollars with quality journalists, focusing on bipac owned and operated, really leaning into into supporting those businesses that have been uh, those publishers that have been ignored for years. I really hope that this trend continues. Um We are leaning into into helping um, marketers curate that supply right? And really, uh, you know, speak with their dollars about the things that that they support. Um, and uh, and and value right in market. So I'm hoping that that trend continues and it's not just sort of like a marketing blip. Um, but we will do everything possible to kind of like encourage that behavior and and give people the information they need to find, you know, truly high quality journalism. >>That's awesome chris Summer. Thanks for coming on and sharing your insight on this panel on the cookie list future. Before we go, just quick summary each of you. If you don't mind just giving a quick sound bite or bumper sticker of what we can expect. If you had to throw a prediction For what's going to happen in the next 24 months Chris We'll start with you. >>Uh it's gonna be quite a ride. I think that's an understatement. Um I think that there, I wouldn't be surprised if if google delays the change to the chrome by a couple of months and and may give the industry some much needed time, but no one knows. I guess. I guess I'm not except for someone somewhere deep within chrome. So I think we all have to operate in a way that changes to happen, changes to happen quickly and it's gonna cover across all facets of the industry, all facets of from advertising, marketing. So just be >>prepared. >>Yeah, along the same lines, be prepared, nobody knows what's going to happen in the future. Uh You know, while dancing in this together. Uh I think um for us it's um planning and preparing and also building on what we've already been working on. Um So omni channel ai um creative and I think clients will uh lean more into those different channels, >>awesome. So we'll pick us home, last word. >>I think we're in the throwing spaghetti against the wall stage. Right, so this is a time of discovery of leaning in trying everything out, Learning and iterating as fast as we possibly >>can. Awesome. And I love the cat in the background over your shoulder. Can't stop staring at your wonderful cat. Thanks for coming on chris, Thanks for coming on. This awesome panel industry breakdown of the cookie conundrum. The recipe for success data ai open. Uh The future is here, it's coming, it's coming fast. I'm john fryer with the cube. Thanks for watching. Mhm. Yeah. Mhm. Mhm. Welcome back to the Quant Cast industry summit on the demise of third party cookies. The cookie conundrum, a recipe for success. We're here peter day. The cto of quad cast and crew T cop car, head of product marketing quad cast. Thanks for coming on talking about the changing advertising landscape. >>Thanks for having us. Thank you for having >>us. So we've been hearing this story out to the big players. Want to keep the data, make that centralized control, all the leverage and then you've got the other end. You got the open internet that still wants to be free and valuable for everyone. Uh what's what are you guys doing to solve this problem? Because cookies go away? What's going to happen there? How do people track things you guys are in this business first question? What is quan cast strategies to adapt to third party cookies going away? What's gonna be, what's gonna be the answer? >>Yeah. So uh very rightly said, john the mission, the Qantas mission is the champion of free and open internet. Uh And with that in mind, our approach to this world without third party cookies is really grounded in three fundamental things. Uh First as industry standards, we think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind, we've been participating >>with I. A. B. >>Tech lab, we've been part of their project Triarc. Uh same thing with pre bid, who's kind of trying to figure out the pipes of identity. Di di di di di pipes of uh of the future. Um And then also is W three C, which is the World Wide Web Consortium. Um And our engineers and our engineering team are participating in their weekly meetings trying to figure out what's happening with the browsers and keeping up with the progress they're on things such as google's block. Um The second uh sort of thing is interoperability, as you've mentioned, there are lots of different uh I. D. Solutions that are emerging. You have you I. D. Two point oh, you have live RAM, you have google's flock. Uh And there will be more, there are more and they will continue to be more. Uh We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. Uh The reason really is to meet our customers where they are at today. Our customers use multiple different data management platforms, the mps. Um and that's why we support multiple of those. Um This is not going to be much different than that. We have to meet our customers where we are, where they are at. And then finally, of course, which is at the very heart of who contrast is innovation. Uh As you can imagine being able to take all of these multiple signals in including the I. D. S. And the cohorts, but also others like contextual first party um consent is becoming more and more important. Um And then there are many other signals, like time, language geo location. So all of these signals can help us understand user behavior intent and interests um in absence of 3rd party cookies. However, uh there's there's something to note about this. They're very raw, their complex, they're messy all of these different signals. Um They are changing all the time, they're real time. Um And there's incomplete information isolation. Just one of these signals cannot help you build a true and complete picture. So what you really need is a technology like AI and machine learning to really bring all of these signals together, combine them statistically and get an understanding of user behavior intent and interests and then act on it, be it in terms of providing audience insights um or responding to bid requests and and so on and so forth. So those are sort of the three um fundamentals that our approach is grounded in which is industry standards, interoperability and and innovation. Uh and you know, you have peter here, who is who is the expert So you can dive much deeper into >>it. Is T. T. O. You've got to tell us how is this going to actually work? What are you guys doing from a technology standpoint to help with data driven advertising in a third party cookie list world? >>Well, we've been um This is not a shock, you know, I think anyone who's been close to his space has known that the 3rd Party Cookie has been um uh reducing inequality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really google chrome making a, making the changes that they're gonna be making. So we've been investing in the space for many years. Um and we've had to make a number of hugely diverse investment. So one of them is in how as a marketer, how do I tell if my marketing still working in the world without >>computers? The >>majority of marketers completely reliant on third party cookies today to tell them if they're if they're marketing is working or not. And so we've had to invest heavily and statistical techniques which are closer to kind of economic trick models that markets are used to things like out of home advertising, It's going to establishing whether they're advertising is working or not in a digital environment actually, >>just as >>often, you know, as is often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement has often mistaken precision for accuracy. And there's a real opportunity to kind of see the wood for the trees if you like. And start to come with better methods of measuring the affections of advertising without third party cookies. And in fact to make countless other investments in areas like contextual modeling and and targeting that third party cookies and and uh, connecting directly to publishers rather than going through this kind of bloom escape that's gonna tied together third party cookies. So if I was to enumerate all the investments we've made, I think we'll be here till midnight but we have to make a number of vestments over a number of years and that level investments only increasing at the moment. >>Peter on that contextual. Can you just double click on that and tell us more? >>Yeah, I mean contextual is unfortunately these things, this is really poorly defined. It can mean everything from a publisher saying, hey, trust us, this dissipated about CVS to what's possible now and has only really been possible the last couple of years, which is to build >>statistical >>models of the entire internet based on the content that people are actually consumed. And this type of technology requires massive data processing capabilities. It's able to take advantage of the latest innovations in there is like natural language processing and really gives um computers are kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize, organized the Internet in terms of the types of content of pages. So this type of technology has only been possible the last two years and we've been using contextual signals since our inception, it's always been massively predictive in terms of audience behaviours, in terms of where advertising is likely to work. And so we've been very fortunate to keep the investment going um and take advantage of many of these innovations that have happened in academia and in kind of uh in adjacent areas >>on the ai machine learning aspect, that seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and ai factoring into your platform? >>I think it's, it's how we've always operated right from our interception when we started as a measurement company, the way that we were giving our customers at the time, we were just publishers, just the publisher side of our business insights into who their audience was, were, was using machine learning techniques. And that's never really changed. The foundation of our platform has always been, has always been machine learning from from before. It was cool. A lot of our kind of, a lot of our core teams have backgrounds in machine learning phds in statistics and machine learning and and that really drives our our decision making. I mean, data is only useful if you can make sense of it and if you can organize it and if you can take action on it and to do that at this kind of scout scale, it's absolutely necessary to use machine learning technology. >>So you mentioned contextual also, you know, in advertising, everyone knows in that world that you've got the contextual behavioural dynamics, the behavior that's kind of generally everyone's believing is happening. The consensus is undeniable is that people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't wanna get walled into a walled garden, nobody wants to be in the world, are they want to be free to pop around and visit sites is more horizontal scalability than ever before. Yet, the bigger players are becoming walled garden, vertical platforms. So with future of ai the experience is going to come from this data. So the behavior is out there. How do you get that contextual relevance and provide the horizontal scale that users expect? >>Yeah, I think it's I think it's a really good point and we're definitely this kind of tipping point. We think, in the broader industry, I think, you know, every published right, we're really blessed to work with the biggest publishers in the world, all the way through to my mom's vlog, right? So we get to hear the perspectives of publishers at every scale. I think they consistently tell us the same thing, which is they want to more directly connected consumers, they don't wanna be tied into these walled gardens, which dictate how they must present their content and in some cases what content they're allowed to >>present. >>Um and so our job as a company is to really provide level >>the playing field a little bit, >>provide them the same capabilities they're only used to in the walled gardens, but let's give them more choice in terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively by making their audiences in their environments discoverable by marketers measurable by marketers and connect them as directly as possible to make that kind of ad funded economic model as effective in the open Internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet as it is in social media. It should be as effective for them to reach people in the environment is really high quality content as it is on facebook. And so we invest a lot of a lot of our R and D dollars in making that true. We're now live with the Comcast platform, which does exactly that. And as third party cookies go away, it only um only kind of exaggerated or kind of further emphasizes the need for direct connections between brands and publishers. And so we just wanna build the technology that helps make that true and gives the kind of technology to these marketers and publishers to connect and to deliver great experiences without relying on these kind of walled >>gardens. Yeah, the Director Director, Consumer Director audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for for that's happening in this new world? How do you ingest the content and just this consent uh signaling? >>Uh we were really fortunate to have an amazing, amazing R and D. Team and, you know, we've had to do all sorts to make this, you need to realize our vision. This has meant things like, you know, we have crawlers which scan the entire internet at this point, extract the content of the pages and kind of make sense of it and organize it uh, and organize it for publishers so they can understand how their audiences overlap with potential competitors or collaborators. But more importantly, organize it for marketers. So you can understand what kind of high impact opportunities are there for them there. So, you know, we've had to we've had to build a lot of technology. We've had to build analytics engines, which can get answers back in seconds so that marketers and publishers can kind of interact with their own data and make sense of it and present it in a way that's compelling and help them drive their strategy as well as their execution. We've had to invest in areas like consent management because we believe that a free and open internet is absolutely reliant on trust and therefore we spend a lot of our time thinking about how do we make it easy for end users to understand who has access to their data and easy for end users to be able to opt out. And uh and as a result of that, we've now got the world's most widely adopted adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. Were fortunate enough to have had a large enough R and D budget over the last four or five years, make a number investments, everything from consent and identity through context, your signals through the measurement technologies, which really bring advertisers >>and Publishers places together great insight. Last word for you is what's the what's the customer view here as you bring these new capabilities of the platform, uh what's what are you guys seeing as the highlight uh from a platform perspective? >>So the initial response that we've seen from our customers has been very encouraging, both on the publisher side as well as the marketer side. Um I think, you know, one of the things we hear quite a lot is uh you guys are at least putting forth a solution, an actual solution for us to test Peter mentioned measurement, that really is where we started because you cannot optimize what you cannot measure. Um so that that is where his team has started and we have some measurement very, very uh initial capabilities still in alpha, but they are available in the platform for marketers to test out today. Um so the initial response has been very encouraging. People want to engage with us um of course our, you know, our fundamental value proposition, which is that the Qantas platform was never built to be reliant on on third party data. These stale segments like we operate, we've always operated on real time live data. Um The second thing is, is our premium publisher relationships. We have had the privilege of working like Peter said with some of the um biggest publishers, but we also have a very wide footprint. We have first party tags across um over 100 million plus web and mobile destinations. Um and you know, as you must have heard like that sort of first party footprint is going to come in really handy in a world without third party cookies, we are encouraging all of our customers, publishers and marketers to grow their first party data. Um and so that that's something that's a strong point that customers love about us and and lean into it quite a bit. Um So yeah, the initial response has been great. Of course it doesn't hurt that we've made all these are in the investments. We can talk about consent. Um, and you know, I often say that consent, it sounds simple, but it isn't, there's a lot of technology involved, but there's lots of uh legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, very good response. Initially >>democratization. Everyone's a publisher. Everyone's a media company. They have to think about being a platform. You guys provide that. So I congratulate Peter. Thanks for dropping the gems there. Shruti, thanks for sharing the product highlights. Thanks for, for your time. Thank you. Okay, this is the quan cast industry summit on the demise of third party cookies. And what's next? The cookie conundrum. The recipe for success with Kwan Cast. I'm john free with the cube. Thanks for watching. Mm

>>from around the globe. It's the >>cube presenting >>active de que intelligent automation for data quality brought to you by Iota Ho >>Welcome to the sixth episode of the I. O. Tahoe data automation series. On the cube. We're gonna start off with a segment on how to accelerate the adoption of snowflake with Glenn Grossman, who is the enterprise account executive from Snowflake and yusef khan, the head of data services from Iota. Gentlemen welcome. >>Good afternoon. Good morning, Good evening. Dave. >>Good to see you. Dave. Good to see you. >>Okay glenn uh let's start with you. I mean the Cube hosted the snowflake data cloud summit in November and we heard from customers and going from love the tagline zero to snowflake, you know, 90 minutes very quickly. And of course you want to make it simple and attractive for enterprises to move data and analytics into the snowflake platform but help us understand once the data is there, how is snowflake helping to achieve savings compared to the data lake? >>Absolutely. dave. It's a great question, you know, it starts off first with the notion and uh kind of, we coined it in the industry or t shirt size pricing. You know, you don't necessarily always need the performance of a high end sports car when you're just trying to go get some groceries and drive down the street 20 mph. The t shirt pricing really aligns to, depending on what your operational workload is to support the business and the value that you need from that business? Not every day. Do you need data? Every second of the moment? Might be once a day, once a week through that t shirt size price and we can align for the performance according to the environmental needs of the business. What those drivers are the key performance indicators to drive that insight to make better decisions, It allows us to control that cost. So to my point, not always do you need the performance of a Ferrari? Maybe you need the performance and gas mileage of the Honda Civic if you would just get and deliver the value of the business but knowing that you have that entire performance landscape at a moments notice and that's really what what allows us to hold and get away from. How much is it going to cost me in a data lake type of environment? >>Got it. Thank you for that yussef. Where does Io Tahoe fit into this equation? I mean what's, what's, what's unique about the approach that you're taking towards this notion of mobilizing data on snowflake? >>Well, Dave in the first instance we profile the data itself at the data level, so not just at the level of metadata and we do that wherever that data lives. So it could be structured data could be semi structured data could be unstructured data and that data could be on premise. It could be in the cloud or it could be on some kind of SAAS platform. And so we profile this data at the source system that is feeding snowflake within snowflake itself within the end applications and the reports that the snowflake environment is serving. So what we've done here is take our machine learning discovery technology and make snowflake itself the repository for knowledge and insights on data. And this is pretty unique. Uh automation in the form of our P. A. Is being applied to the data both before after and within snowflake. And so the ultimate outcome is that business users can have a much greater degree of confidence that the data they're using can be trusted. Um The other thing we do uh which is unique is employee data R. P. A. To proactively detect and recommend fixes the data quality so that removes the manual time and effort and cost it takes to fix those data quality issues. Uh If they're left unchecked and untouched >>so that's key to things their trust, nobody's gonna use the data. It's not trusted. But also context. If you think about it, we've contextualized are operational systems but not our analytic system. So there's a big step forward glen. I wonder if you can tell us how customers are managing data quality when they migrate to snowflake because there's a lot of baggage in in traditional data warehouses and data lakes and and data hubs. Maybe you can talk about why this is a challenge for customers. And like for instance can you proactively address some of those challenges that customers face >>that we certainly can. They have. You know, data quality. Legacy data sources are always inherent with D. Q. Issues whether it's been master data management and data stewardship programs over the last really almost two decades right now, you do have systemic data issues. You have siloed data, you have information operational, data stores data marks. It became a hodgepodge when organizations are starting their journey to migrate to the cloud. One of the things that were first doing is that inspection of data um you know first and foremost even looking to retire legacy data sources that aren't even used across the enterprise but because they were part of the systemic long running operational on premise technology, it stayed there when we start to look at data pipelines as we onboard a customer. You know we want to do that era. We want to do QA and quality assurance so that we can, And our ultimate goal eliminate the garbage in garbage out scenarios that we've been plagued with really over the last 40, 50 years of just data in general. So we have to take an inspection where traditionally it was E. T. L. Now in the world of snowflake, it's really lt we're extracting were loading or inspecting them. We're transforming out to the business so that these routines could be done once and again give great business value back to making decisions around the data instead of spending all this long time. Always re architect ng the data pipeline to serve the business. >>Got it. Thank you. Glenda yourself of course. Snowflakes renowned for customers. Tell me all the time. It's so easy. It's so easy to spin up a data warehouse. It helps with my security. Again it simplifies everything but so you know, getting started is one thing but then adoption is also a key. So I'm interested in the role that that I owe. Tahoe plays in accelerating adoption for new customers. >>Absolutely. David. I mean as Ben said, you know every every migration to Snowflake is going to have a business case. Um uh and that is going to be uh partly about reducing spending legacy I. T. Servers, storage licenses, support all those good things um that see I want to be able to turn off entirely ultimately. And what Ayatollah does is help discover all the legacy undocumented silos that have been built up, as Glenn says on the data estate across a period of time, build intelligence around those silos and help reduce those legacy costs sooner by accelerating that that whole process. Because obviously the quicker that I. T. Um and Cdos can turn off legacy data sources the more funding and resources going to be available to them to manage the new uh Snowflake based data estate on the cloud. And so turning off the old building, the new go hand in hand to make sure those those numbers stack up the program is delivered uh and the benefits are delivered. And so what we're doing here with a Tahoe is improving the customers are y by accelerating their ability to adopt Snowflake. >>Great. And I mean we're talking a lot about data quality here but in a lot of ways that's table stakes like I said, if you don't trust the data, nobody's going to use it. And glenn, I mean I look at Snowflake and I see obviously the ease of use the simplicity you guys are nailing that the data sharing capabilities I think are really exciting because you know everybody talks about sharing data but then we talked about data as an asset, Everyone so high I to hold it. And so sharing is is something that I see as a paradigm shift and you guys are enabling that. So one of the things beyond data quality that are notable that customers are excited about that, maybe you're excited about >>David, I think you just cleared it out. It's it's this massive data sharing play part of the data cloud platform. Uh you know, just as of last year we had a little over about 100 people, 100 vendors in our data marketplace. That number today is well over 450 it is all about democratizing and sharing data in a world that is no longer held back by FTp s and C. S. V. S and then the organization having to take that data and ingested into their systems. You're a snowflake customer. want to subscribe to an S and P data sources an example, go subscribe it to it. It's in your account there was no data engineering, there was no physical lift of data and that becomes the most important thing when we talk about getting broader insights, data quality. Well, the data has already been inspected from your vendor is just available in your account. It's obviously a very simplistic thing to describe behind the scenes is what our founders have created to make it very, very easy for us to democratize not only internal with private sharing of data, but this notion of marketplace ensuring across your customers um marketplace is certainly on the type of all of my customers minds and probably some other areas that might have heard out of a recent cloud summit is the introduction of snow park and being able to do where all this data is going towards us. Am I in an ale, you know, along with our partners at Io Tahoe and R. P. A. Automation is what do we do with all this data? How do we put the algorithms and targets now? We'll be able to run in the future R and python scripts and java libraries directly inside Snowflake, which allows you to even accelerate even faster, Which people found traditionally when we started off eight years ago just as a data warehousing platform. >>Yeah, I think we're on the cusp of just a new way of thinking about data. I mean obviously simplicity is a starting point but but data by its very nature is decentralized. You talk about democratizing data. I like this idea of the global mesh. I mean it's very powerful concept and again it's early days but you know, keep part of this is is automation and trust, yussef you've worked with Snowflake and you're bringing active D. Q. To the market what our customers telling you so far? >>Well David the feedback so far has been great. Which is brilliant. So I mean firstly there's a point about speed and acceleration. Um So that's the speed to incite really. So where you have inherent data quality issues uh whether that's with data that was on premise and being brought into snowflake or on snowflake itself, we're able to show the customer results and help them understand their data quality better Within Day one which is which is a fantastic acceleration. I'm related to that. There's the cost and effort to get that insight is it's a massive productivity gain versus where you're seeing customers who've been struggling sometimes too remediate legacy data and legacy decisions that they've made over the past couple of decades, so that that cost and effort is much lower than it would otherwise have been. Um 3rdly, there's confidence and trust, so you can see Cdos and see IOS got demonstrable results that they've been able to improve data quality across a whole bunch of use cases for business users in marketing and customer services, for commercial teams, for financial teams. So there's that very quick kind of growth in confidence and credibility as the projects get moving. And then finally, I mean really all the use cases for the snowflake depend on data quality, really whether it's data science, uh and and the kind of snow park applications that Glenn has talked about, all those use cases work better when we're able to accelerate the ri for our joint customers by very quickly pushing out these data quality um insights. Um And I think one of the one of the things that the snowflake have recognized is that in order for C. I. O. Is to really adopt enterprise wide, um It's also as well as the great technology with Snowflake offers, it's about cleaning up that legacy data state, freeing up the budget for CIA to spend it on the new modern day to a state that lets them mobilise their data with snowflake. >>So you're seeing the Senate progression. We're simplifying the the the analytics from a tech perspective. You bring in Federated governance which which brings more trust. Then then you bring in the automation of the data quality piece which is fundamental. And now you can really start to, as you guys are saying, democratized and scale uh and share data. Very powerful guys. Thanks so much for coming on the program. Really appreciate your time. >>Thank you. I appreciate as well. Yeah.

>>from >>Around the globe. It's the cube with digital coverage of IBM think 2021 brought to you by IBM. >>Welcome back to the cubes ongoing coverage of IBM Think 2021 virtual cube, you know, the pandemic has caused us to really rethink this this whole concept of operational resilience and we're gonna dig into that and talk about the importance of constructing a holistic resilience plan and get the perspective of some really great domain experts. Alan Downs is the vice president, global Cloud security and resiliency services at IBM and he's joined by MS Michelle what? Weston who is the director of cloud security and resiliency offerings at IBM folks. Welcome to the cube. Thanks for coming on. >>Thank you. >>Now before we get into it, I said IBM but I want to ask you, alan about an announcement you made last month about Kendrell new spin out from IBM. What can you tell us? >>Very excited about the name? I think there's a lot of meaning in the name centered around new growth and censored around partnership and relationship. So if you look at the name that was announced I think it really does typify what we set out to be as a trusted partner in the industry. All born around new growth centered around strong partnership and relationship. So very pleased and excited and look forward to the opportunity we have going forward. >>Yeah congratulations on that. Had some clarity martin schroder. New ceo Cubillan. Great executive love it. So good luck. Um Alan let me stay with you for a second. I mean operational resilience it means different things to different people and we know from speaking with C. IOS in our community during the pandemic. It doesn't just mean disaster recovery. In fact a lot of C. I. O. Said that their business continuing strategy were too focused on on D. R. Ellen. What does operational resilience mean from your perspective? >>So I'll answer it this way. Operational resiliency risk is defined as the quantifiable steps that any client needs to take in order to respond, recover from an unplanned outage. It sits squarely within operational risk. And if you think about it, operational risk is the kind of non financial element of risk. And defined within that category, operational resiliency risk is trying to identify those steps both pre active and reactive that a client needs to consider that they would have to take in the event of an unplanned disruption or an unplanned outage that would impact their ability to serve their clients or to serve their organization. That's how I define operational resiliency risk. >>Great and I wonder Michelle if you can add to that but I think you know I sometimes say that the pandemic was like a forced march to digital and part of that was business resilience. But You know, where do we go from here? You know, we had 14 months shoved into our face and now we have some time to think about. So how should clients think about evolving their strategies in this regard? >>Yeah, Well, certainly with respect to what was called Newco now, Kendrell, um our approach has been advisory led. Uh we will help clients along this journey. Uh, one thing that I'd like to point out in one of the journeys that we've been taking over the last couple of years is it really is about security and resiliency together. If you think of that planning and how to mitigate your operational risk, the security and resiliency go hand in hand through the same people within the organization that are planning for that and worried about it. And so we had already started about three years ago to pull the two together and to have a unified value proposition for clients around security and resiliency, both being advisory lead, doing everything for a client from project based to the digital consumption world which we know clients live in today to a fully managed service all around security and resiliency together. >>Yeah, so I mean it's really important topic. I mean you heard Chair Powell last month. He was he was on 60 minutes saying well yeah worried about inflation, were way more worried about security. So so alan you know, were let's say you're in the virtual, you know, conference room with the board of directors. What's that conversation like? Uh where does it start? >>I think there is a huge concern right now with regard to security and obviously resiliency as well. But if you just think about what we've all been through and what's transpired in the last 12 months, the what we call the threat landscape has broadened significantly and therefore clients have had to go through a rapid transformation not just by moving employees to home base, but also their clients having a much higher expectation in terms of access to systems, access to transactions which are all digital. So you referred to it earlier. But the transformation, our clients have had to go on driving a higher dependence on those systems that enable them to serve their clients digitally and enable them to allow the employees to work remotely in this period has increased the dependencies that they have across the environment that are running many of the critical business processes. So the discussion in the boardroom is very much are we secure? Are we safe? How do we know how safe and secure and resilient should we be? And based on that fact about how safe and secure should we be? Where are we today as an organization? And I think these are the questions that are at the boardroom is basically from a resiliency security perspective, where should we be that supports our strategy vision and our client expectation? And then the second question is very much where are we today? How do we know that we are secure? How do we know that we can recover from any unplanned or unforeseen disruption to our environments? >>So Michelle, I mean I just mentioned the threat surface is expanding and we're just getting started, everybody's like crazy about five G leaning in the edge Iot and that's just uh this could be orders of magnitude by the end of the decade compared to where it is today. So how do you think about the key steps that organizations should should take to ensure operational resilience, you know, not only today, but also putting in a road map. >>Yeah, yeah. And and one thing that we do know from our clients is those that have actually planned for resiliency and security at the forefront. They tend to do that more effectively and more efficiently. Um It's much better to do that than to try to do that after an outage. You certainly learn a lot. Um but that's not the experience that you want to go through. You want to have that planning and strategy in the forefront. As Alan said in terms of the threat vector, the pandemic brought that on as well. We saw surgeons Of cyberattacks, opportunistic attacks. Um you know, we saw the best of people in the pandemic as well as the worst in people. Some of those attacks were on agencies that we're trying to recover. We're trying to treat the public with respect to the COVID-19 pandemic. So none of us can let our guard down here. I think we can anticipate that that's only going to increase. And with the emergence of these new technologies like cloud, we know that there's been such a massive benefit to clients. In fact those that were cloud enabled to sustain their businesses during the pandemic full stop. But with that comes a lot more complexity. Those threat vectors increase five G. I expect to be the same. So again, resilience and security have never been more relevant. More important, we see a lot of our clients putting budget there and those that plan for it with a strategic mindset and understand that whatever they have today may be good enough, but in the future they're going to have to invest and continue to evolve that strategy. Are those that have done the best. >>Yeah, the bolt on strategy doesn't doesn't really work that well, but and I wonder if you think about when we talk to CSOS for example, and you ask them what's your biggest challenge? They'll say things like lack of talent. We got too many tools. It's just as we're on the hamsters on wheels. So I would think that's, you know, unfortunately for some, but it's good for your, your business. That's that's a dynamic that you can help with. I mean you're a services organization, you got deep expertise in this. So I wonder if you could, could talk a little bit about that, that lack of talent, that skills gap and how you guys address that. >>I think this is really the fit for managed services providers like Kendrell, um, certainly with some of our largest clients, if we look at Peta as an example, that notion of phone a friend is really important when it starts to go down and you're not sure what you're gonna do next. You want the expertise, you want to be able to phone someone and you want to be able to rely on them to help you recover your most critical data. One of the things clients have also been asking us for is a vaulted capability, almost like the safe deposit box for your data and your critical applications. Being able to put them somewhere and then in the event of needing to recover, um, you certainly could call someone to help you do exactly that >>Ellen. I wonder if you can address this. I mean, I like IBM I was I'm a customer. I trust IBM. What's your relationship? Are you still gonna, you know, be able to allow me to tap the pieces that that I like and maybe you guys can be more agile in some respects, maybe you can talk about that a little bit. >>She has Sure, Dave and many of our clients, we have a long history with a very positive experience of delivering, you know, market leading and high high quality of services and product the relationship continue. So we will remain very close to IBM and we will continue to work with many of IBM's customers as will IBM work with our customers going forward. So the relationship, I believe whilst a different dynamic will continue and I believe engenders an opportunity for growth and you know, we mentioned earlier the very name signifies the fact that it's new growth and I do think that that partnership will continue and we'll continue together to deliver the type of service, the quality of products and services that our clients have, you know, enjoyed from IBM over the last number of years, >>Michelle my, one of my takeaway from your earlier comments as you guys are hands on consultative in nature. Um, and I think about the comment I made about a lot of Ceo said we were way too d our focus. But when I think about d are a lot of times it was a checkbox to the board. Hey, we got it. But it was last time you tested it. Well, we don't test it because it's too risky to test. You know, we, we do fail over, but we don't fail back because it's just too risky. Can I stress test, you know, my environment, we, at the point now where technology and expertise will allow us to do that is that part of what you bring to the table? >>It is exactly exactly what we bring to the table. So from a first of all, from a compliance and regulatory perspective, you no longer have that option. A lot of the auditors are asking you to demonstrate your d our plan. We have technology and I think we've talked about this before about the automation that we have in our portfolio with resiliency orchestration that allows you to see the risk in your environment on a day to day basis. Proactively manage it. I tried to recover this, there's a there's a failure and then you're able to proactively address it. I also give the example from a resiliency orchestration perspective in this very powerful software automation that we have for D. R. We've had clients that have come in scheduled A. D. R. Test, it was to be all day they've ordered in lunch And the D. R. test fail over failed back took 22 minutes and lunch was canceled. >>I love >>it. Very powerful and very powerful with an auditor. >>That's awesome. Okay guys, we've got to leave it there. Really great to get the update. Best of luck to you and congratulations. Thanks for coming on. >>Thank you so much >>and thank you for watching. This is Dave Volonte for the cubes continuous coverage of IBM think 2021 right back. >>Mhm.

>>from >>Around the globe. It's the cube with digital coverage of IBM think 2021 brought to you by IBM. Welcome to the cubes coverage of IBM Think 2021. I'm your host lisa martin today. Have a new guest new to the cube moderate Tabla, the director of strategic partnerships for enterprise application services is joining me moderate. It's nice to have you on the program. >>Thank you lisa. Very excited to be here and hello everyone. >>So different this year. Again Virtual like last year we're going to talk about digital transformation and we saw this huge acceleration in 2020. The massive adoption of SAS applications. We want to talk though about IBM managed services for S AP applications. So before we get into that I'd love for you to be able to describe what your role is to our audience. >>Absolutely lisa. So good day everyone. I've been with IBM for over 23 years and my current role, I run the strategic alliances for IBM basically in the E. R. P. Space S. A. P. Being our primary strategic partner, I have a global team of architects and we basically look at market requirements. Talk to a lot of customers, talk to our business partner S. A. P. Obviously um you know, try to help them would come up with a solution. Well the transformation journey to the cloud and hopefully today, you know, we'll elaborate a little bit more on the exact work that we do in this space. So very happy to be here. Thank you. >>Sure. So we're going to dissect the IBM s. A. P. Relationship. I think you even worked at S. A. P. Before your 23 year tenure at IBM. So we'll get to some of that as well. But help us understand customers have so much choice each day. There is more and more interest why should a customer choose IBM as their strategic partner for this digital transformation journey. >>Well really, IBM has been in this essay p business for many, many decades. As you know Um we have many many certified people in S. A. P. close to 40,000 people actually globally. Um And we can help the clients in various aspects of their journey. So you know the typical cloud journey has four different aspects to it. Um You need the advice so you need basically systems integration services to help customers actually define the scope on, you know what they actually want to either upgrade, bring it to current as well as you know what workloads they want to move to the cloud. We can help customers with our Systems integration services called the Global Business Business Services in IBM we can help them with their entire planning, we can help them with the actual move to the cloud. So IBM offers a whole different variety of services for migration or not only to see ASAP workloads. I mean ASAP typically ends up being the heart of the workloads that any of the major customers run but surrounding SCP, there's a lot of other applications so we can help plan that entire journey for advice and then move it as well as in the interim. You know, there's also another step which can be some customers. They need to build net new and you know upgrade their applications to the latest technologies so we can help them with that. And then once the building move is over, obviously customers need help with the actual steady state run state environment and that's where this key service that we have managed services for SCP applications helps them. So our certifications with S. A. P. And the fact that we have consultants that are certified and all these different aspects of the journey can really help your clients. The other part, I would say that IBM is really a hybrid cloud provider. So obviously we have our cloud service, the IBM cloud, but we can offer this service meeting the customer where they need to be. So we are a client centric service, so if the customer has a choice of AWS or Azure, uh we can meet them left. So this is how, you know, we can really help our customers with our expertise. I know the data point to note that, you know, 70 80 of the enterprise customers still have not moved their workloads to the cloud. So this is a space, especially with Covid, as you've seen what's happened, you know, customers now are really, really looking to accelerate the journey because it's become a necessity, It's no longer something that our Ceo and C I O can push to the right, right, this is something they have to act now. So I began with all these various services, you know, specifically good in the S A. P area. Um, and given that we've been managing these production workloads for a lot of these enterprise customers on our cloud services for many, many years, we have the experience, we can truly help them with their journey >>And as you said, that's so critical of these days. One of the things that I think we learned in 2020 is is there was no time like the present, it really became such a massive shift that for business survival, those that weren't digitized definitely were in some hot water. Talk to me. So you talked about the IBM s, a P relationship being longstanding, Can you talk to me about the different aspects of the alliance and how that helps you guys to meet customers where they are? >>Sure. Um so s. a. p. and idea, we've been strategic partners for over 46 years. That's a long time. The partnership obviously has evolved over the years and I'll talk about you know a few of the different aspects where we've been partners um you know, the alliance initially obviously started, you know, IBM is in multiple businesses as you know, we have our one of the largest systems integrators in the world from a global business services point of view as well as one of the largest application planet services providers. So that's uh you know part of the alliance then we have our server groups, the power systems that IBM has. So that's another dimension of the alliance where um you know 5 6000 plus ASAP clients even today are still running um there? S a the applications on the power systems, whether it's on premise or also in some of the cloud deployment models. Historically we also had obviously the Database DB two alliance, but now with the S. A. P. S moved to Hannah um that's kind of a little bit of a mute point. Obviously it still exists, but most of the clients are now obviously being encouraged really to adopt S. A. P. S latest S four hana from the services standpoint. The other facet, you know, is really around the cloud services. So that's really our topic today right. Um in the cloud services area we have alliances with S. A. P very very strong alliances that have existed for you know, almost a decade now. Um as I said we've been managing the production workloads for very very large customers in many different industries, their entire supply chains. HR financial systems are running on IBM either in the old traditional hosting models um or also in our cloud models for the past 10 plus years. Right as IBM has evolved, so we have made sure that we do a whole different types of certifications with S. A. P. To stay current. Um many of these certifications are done either you know every two years, some are done every year. And if anyone checks, you know, the S. A. P. Service marketplace website which is owned by S. A. P. You can see IBM listed in all these different angles as a certified provider. There isn't another provider that can claim this breath in terms of certifications that IBM has done and that's why customers can benefit either from one or two of these services that IBMS provides or obviously a combination is a single vendor if the customer needs. So, you know, we have the sex, we have the credibility, we have decades of, you know, Delivery excellence in these areas, servicing these clients. Lots of the Fortune, 100 customers actually are running. Um there? S a p workloads on the IBM systems, whether in traditional hosting or in a hybrid cloud deployment. Some cases were actually providing services for customers that run their SCP workloads on premise. So we cater to that, you know, sets of clients as well and then of course others that are purely on our cloud. Um IBM cloud as well as hyper scholars. Yeah, so long >>list of certifications, that seems to be one of the biggest differentiators that you talked about me a little bit about how things have evolved over the last 12 to 18 months. in terms of how is IBMS focus changed for hybrid cloud with S. A. P. >>Yeah, so the focus changed if you know, you know, until last year we will call the cloud and cognitive company. Um This year of course the whole company has changed and we're going through a major transformation at the moment. We are the hybrid cloud company now. And that that name change means a lot. It means a lot in the sense that it gives choices to the customer, that's what the whole mission is all about. We want to make sure that customers are consuming IBM services and the IBM wants to meet them where they want to be. So there's you know, flexibility of choices in terms of hybrid, another cloud deployment model. So most customers in the S. A. P. Area, you know, they're looking for either just a pure private cloud deployment or they're looking for public cloud deployment or a combination and some are because, you know, there? S A. P. S. Footprint sizes are so large. Think about the multinational global companies, you know, and then they operate in so many different regions of the world and their data sizes of their databases are so large. Perhaps, you know, the public cloud really isn't a good fit yet. These customers are looking to move some sort of their workloads to the cloud. So that's where this hybrid cloud helps them. Because customers, you know, 90 plus percent of the clients today are really not choosing one hyper Scaler as their deployment option. They're really looking at multiple. So because they're running their workloads not just ASAP, but everything else, you know, SCP always brings along a whole bunch of other applications like tax applications and other interfaces, homegrown applications analytics that the customers are using. So if you want to take advantage of the true hybrid cloud and the benefits of all the various um, deployments and hyper scale is available in that region. Really, the hybrid cloud strategy from IBM is a perfect fit because we give them choices of deployment. We're not saying that you have to deploy an IBM cloud. Um, we're saying you can deploy either on premise VWs as your idea of cloud. Really what makes sense? You know, best sense for the types of war clothes that the customer is looking at. So that's how the strategy for IBM has completely changed to meet the clients, you know, for what they're actually looking for. Talk to me a >>little bit about the go to market so I B M and S A P longstanding decades old relationship, A lot of certifications that you talked about. We're talking about business critical Applications, you mentioned supply chain a minute ago and I can't help but think it how supply chain has been affected in the last year. What is the good market approach with respect to providing consultation services to help customers determine? Should we migrate to what Hyper Scaler and how and when? >>Yeah, so we can help them with that? Um, so hyper hyper scale is obviously, you know, IBM has been listed for example, as the leader in Gartner 2020 and you know, there's lots of other stats that show them that IBM is a leader in application services, in consulting services, application management services as well as managed services. So these are all different, Right? And you can see us being listed as a leader either it's in Gartner or I. D. C. Or Horse or Wave. And for many reasons and you know, IBM actually has one series of pinnacle awards from S. A. P. Over the U. S. How this helps the clients really determined is that, you know, IBM obviously does a lot of studies externally. We have internal as well as external facing views of comparatives of the various hyper scholars, um you know, including Aws, Azure, G. C. P. And so on. So when a customer comes to us for asking for advice, um, and so on, we basically look at our own intellectual properties, all the analysis that has been done. And more importantly, we look at the full scope of services that the customer wants is doing. What sort of a business are there in. We have industry experts, there's E. R. P. Strategy, um, folks within IBM. So, you know, they go after a certain industry and when they, let's say, you know, they've gone after the oil and gas industry, for example, they will look at multiple customers in that particular space. So based on their experiences, we can actually define the right road map for the client to be able to help them to move their work clothes to this hybrid cloud strategy that I just mentioned. Right? So that's how we can help them because we have the expertise in that industry as well. >>And I'm curious moderate in the last year with so much flux and rapidly changing market conditions, Did you >>see any >>one or two industries in particular really leading the charge here and coming to IBM. S. A. P. For help on this transformation journey which has been accelerated by a couple of years. >>Suddenly the retail industry for sure, right. I mean in spite of the crisis, I think the retail industry did pretty well, right? Because people still have to buy stuff. Of course, the whole buying behavior change. No question. Um You and I don't know about two days of, but for me, you know, I was never a major online shopper. Oh yeah. You know, I just about everything. Um previously it used to be select things here and there, but now it's totally changed, right? So that industry certainly has accelerated. No question. We've had a lot of those coming. The other industries that I've seen. The change in the last 12, 18 months is really, for example, you know, the banking industry and so on. Um IBM basically, you know, launched a lot of services in the financial services sector for this reason. Um So those are of course transforming very fast to keep up with the market. Um and I'm sure there's others, right? But these are the two that come to mind. Yeah, >>two that have been most affected and needed to pivot so quickly. In addition to health care. Let me ask you one final question here. Before we wrap. Talk to me about the advantages of using the PMC partner managed cloud s a P license resale model. The advantages of using that and the benefits. >>Sure. Um so we, you know, so far our discussion was really focused around, you know, the various service capabilities that IBM has in terms of our capabilities for helping clients with hyper scholars and hybrid cloud. We also need to spend a little bit of time talking about the operations model. Right? So when they're running their production workloads on IBM PMC is yet another dimension. So what PMC partner managed cloud is really some very limited partnerships that s A P does And the IBM is the lead on that one in this base. What ASAP allows is the partner, which in this case is IBM to resell the ASAP software license to a customer. So IBM has the rights globally to resell the license and why is that beneficial to the client? Because now, um, IBM can actually turn around the S. A. P license and have the customer pay us in a SAS model. So it basically is now an apex model where the customer is basically paying, you know, a monthly fee as an example, so there's no upfront cost to the client and they basically pay IBM and IBM PS ASAP. So IBM is kind of holding the risk if you will on behalf of the customer, it gives customers more choices, more flexibilities, better pricing approach. So if the customer wants as an example to buy everything the full package, including systems implementation services, deployment models with choices on a cloud, whether it's IBM cloud or others as well as the license itself. IBM has this end to end capability today. We've been selling it to several clients for a few years in several geography is right. So that's the advantage behind it. >>Excellent. Thanks for breaking that down moderate and joining me today talking about what's new with I B M and S A P, the opportunities for customers to accelerate their digital transformation. We appreciate you stopping by. >>Thank you very much, lisa truly enjoyed it. Thank you. >>Good. Me too. For moderate Tabla. I'm lisa martin. You're watching the cubes coverage of IBM think 2021. >>Mm.

>>Okay, >>welcome to Accelerating next. Thank you so much for joining us today. We have a great program. We're gonna talk tech with experts, will 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 excess scale with full security and automation all coming to you as a service. And with me to kick things off as Neil Mcdonald, who's the GM of compute at HP NEAL. Always a pleasure. Great to have you on. >>It's great to see you dad >>now, of course, when we spoke a year ago, we had hoped by this time we'd be face to face. But here we are again, you know, this pandemic, It's obviously affected businesses and people in so many ways that we could never have imagined. But the reality is in reality, tech companies have literally saved the day. Let's start off, how is HPV contributing to helping your customers navigate through things that are so rapidly shifting in the marketplace, >>although it's nice to be speaking to you again and I look forward to being able to do this in person. At some >>point. The >>pandemic has really accelerated the need for transformation and businesses of all sizes. More than three quarters of C. I. O. S. Report that the crisis has forced them to accelerate their strategic agendas, organizations that were ready 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 computer 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 extra scale With 360° 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, re setting budget priorities. What are some of the barriers that you see customers are working hard to overcome? >>Simply put the organizations that we talk with our 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 E. T. R. 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 5% of in terms of I. T. Spending budgets etcetera. And this year we're seeing a pretty significant rebound. Maybe a 67% growth ranges is the prediction. The challenge we see his organizations have to they 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 that the corporate headquarters which have kind of been neglected. Is there any help in sight for the customers that are trying to reduce their spending 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 uh, we work through HP 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 the business. >>So can we drill into that? I would wonder if you 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 prepackaged validated supported solution intact that simplifies that work for them. But in other cases we can enhance our customers bandwidth by bringing them HP 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 computer investments to underpin the transformations and whether that's planning to optimizing to save for retirement at the end of life. We can bring that expertise to bear to help amplify what our customers already have in house and help them accelerate and succeed in executing these transformations. >>Thank you for that. Let's let's talk about some of the other changes that customers see him in the cloud is 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. So take Green Lake, it's obviously leading example of a 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 now from our first pay, as you go offering back in 2006, 15 years ago to the introduction of Green Lake. HBs really been paving the way on consumption-based services through innovation and partnership to help meet the exact needs of our customers. Hp Green Lake provides an experience, is the best of both worlds. A simple paper 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 HP Greenlee because 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 covid wrecking ball meme that so well describes that if you're not a digital business, essentially you're gonna be out of business. So, you know, those things have evolved, how is HPV 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 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 HP computer. >>I want to double click on that remote workforce productivity. I mean again the surveys that we see, 46 of the ceo say that productivity improved with the whole work from home remote work trend. And on average those improvements were in the four range which is absolutely enormous. I mean when you think about that how does HP specifically 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 I. T. 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 latency is 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 V. D. I. 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 exa scale in 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, basically build your own optimized solutions if I can buy that rather than having to build it and rely on your R and D. You know, that's key. What else is HP doing? You know, to deliver new apps, new services, you 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 that development and many organizations of course are embracing container technology to do that today. So with the HP container platform, our customers can realize that agility and efficiency that comes with container ization and use it to provide insight to their data more and more on that data of course is being machine generated or generated the edge or the near edge. And it can be a real challenge to manage that data holistically and not of silos and islands at H. P. S. Moral 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 and at 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 gotta go where the data is and the data is distributed. It's decentralized. I I like the liberal vision and execution there so that all sounds good. But with digital transformation you're gonna see more compute in hybrid deployments. You mentioned edge. So the surface area, it's like the universe its its 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 H P. E there >>Or you can count on continued leadership from hp as the world's most secure industry standard server portfolio. We provide an enhanced and holistic 360° 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 Khyber or private cloud, including the integration of the Edge need other elements to 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 Pensando 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 H. P. Is really up to its ecosystem game since the middle of last decade when when you guys reorganized and it became even more partner friendly. So maybe give us a preview of what's coming next in that regard from today's event. >>Well, they were really excited to have HP. Ceo, Antonio Neri speaking with Pat Gelsinger's from Intel and later lisa su from A. M. D. And later I'll have the chance to catch up with john Chambers, the founder and Ceo of J. C. Two ventures to discuss the state of the market today. >>Yeah, I'm jealous. You got, yeah, that's a good interviews coming up, NEal, thanks so much for joining us today on the virtual cube. You've really shared a lot of great insight how HP is is partner 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. >>I look forward to that. And 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 exa scale with that 360° security with the intelligent automation. And we're gonna 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 day. Thanks for having me >>very welcome. It's been super Neil 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 HPV plays there. So let's dive right in. >>Yeah. Mm.

>>okay. >>Just about a year ago, governments around the world forced shutdowns of their respective economies. We've never seen anything like it. Central banks took immediate action and effective monetary policy like none we've ever seen before. They dropped interest rates to near zero, injected a huge amount of cash into the system, and they fueled this liquidity boom to support those individuals and businesses that were in greatest need. Banks were overwhelmed with the volume of paperwork, for instance, small business P, P P loans and other things. Home buying boomed as mortgage rates hit all time lows for several weeks in the spring, it was complete chaos, but the tech industry stepped up and accommodated work from home. Cloud infrastructure was spun up instantly as access to data centers was really restricted, and Saas companies became a fundamental staple of not only keeping the lights on but helping customers thrive in the face of a pandemic. Automation became a >>mandate >>as humans, they couldn't possibly keep up with the tidal wave of demand, a document overload that was hitting the system. Now, one of the companies that was there to help financial firms in particular, get through the knothole was Oculus, a company that focuses on intelligent automation to deploy the power of machines to allow humans to focus on what they do best. Hello, everyone. And welcome to this cube conversation. My name is Dave Volonte, and we're profiling the most interesting SAS startups that are reimagining how we work. And with me is Sam Bobbly, the co founder and CEO of Oculus. Sam, welcome to the Cube. First time. >>Hey, Dave. Thanks so much for having me excited to have the conversation. >>Yeah, me too. So, listen, I know you've told the story of a zillion times, but I want a community here. How and why did you start the company >>for sure. So when I was in college, I was having a conversation with my dad. Uh, he was telling me about a meeting he just had with his elder law attorney. And the other law attorney was complaining about having to review hundreds or thousands of pages of financial documents for every long term care Medicaid application. When you apply for Medicaid coverage to enter a nursing home, you're required to submit 60 months of financials along with your application. And traditionally the elder law attorney or a nursing home would review those documents literally page by page, line by line to find high value transactions, transfers and other financial trends. And when I heard about this, it just it didn't make sense to me. I said, You know why? In this day and age isn't there? Why isn't there a technology solution that can ingest the documents and spit out a digital report replacing the cumbersome manual page by page review? So it really just started as a research project, trying to learn more about optical character recognition, which is the technology of transforming images into text. And, you know, as we kind of kicked around different products in the market, we we realized that there was an opportunity to build a unique platform that could ingest documents of any format quality and produce perfectly accurate results. And that was the genesis behind what ultimately became Oculus. >>You were a young man at this time. How old were you at that time? >>I was 22 when we started >>so fearless. And, uh, now my friend Eddie Mitchell started a company about 20 years ago. We hacked together a >>Dell >>system and this camera. It was all about the modern operating room in the future, and he showed it to a doctor and and it was just a prototype, she said. How much? He said 10 grand. She wrote a check right there. You have a similar story? How did you see the company? >>So we we we do have a pretty similar experience. You know, Our our concept was we want to get perfect results the customer every time. So if a customer sends us a clean bank statement from Chase or a blurry cell phone image with someone's thumb in the picture from a community bank in Maine, and it's rotated sideways or upside down like we want to give consistent, perfectly active results every single time. And you know, our our view was to completely solve the business problem. So the very first version of the software that we built, we had a rudimentary machine process to extract 60 or 70% of the data, and then we had a little tool built on the back end, where literally, me, myself and some of our early employees would clean up the data output, make sure it's perfect and then return When we couldn't submit, we'd returned to the customer accurate data that could be used at the time for for a Medicaid decision. And what happened is, while we were in our beta period, customers fell in love with the product. They felt it was magical and really just superior from an accuracy standpoint to anything they had ever tested before. And And one of our beta testers said to us, uh, where do I submit credit card information? So at that time, I turned to my colleagues and I said, I think we're ready to I think we're ready. Start charging for this thing and and roll it out for prime time. >>When I was researching the company, I learned that you leveraged. At least some of the idea came from the capture, and I never knew this, But the capture that we all hate came from Google where they write, they had at one point you could maybe you still can. You can go online. You can read books and have to It's just scanned. You can't even read the stuff half the time. So they were putting the capture in front of us, quite brilliant to try to solve for those those those white spaces that they didn't know. So So how did you learn from that? Was there an A P I that you could plug into Google's data set, or did you do your own? What was that? How did that all work? >>The the concept of humans in the loop is super powerful, right? So when we first started, we recognize that OCR and machine data capture couldn't do the job completely. OCR, generally speaking, can process financial documents with roughly 80 to 85% accuracy plus or minus machines, particularly struggled with semi structured and unstructured documents where the format is unpredictable as well as lower quality images. So pretty early on, we recognized that we needed human intervention in the process in order to achieve perfect accuracy every single time, and also to create training data to constantly teach our machine learning models to get smarter and drive additional automation. So, as I mentioned, the very first version was myself and other employees verifying the data on our own. But as we started thinking about how to scale this up and, you know, take on millions and millions of documents, we needed to, uh, you know, learn how to better parallelized task and really build the system for for efficiency and for scanning. So we we we learned about the Google Books Initiative and their ability to leverage capture technology and a distributed workforce to verify pieces of information that their systems couldn't automatically read from books. And we took a lot of those learnings into building our human in the loop infrastructure. And, you know, a way to think about our our product is it's the marriage of machines and humans that makes us unique. As much of the heavy lifting as we can do with machines we do. But whatever we can't do automatically, we slice into smaller tasks and intelligently route those tasks to humans to perform verification. We then layer in algorithmic checks to make sure our humans did the review correctly. The customer gets perfect results, and that same perfect output is used in a feedback loop to train our machine learning models to get smarter and smarter, which dynamically improves the product on an ongoing basis. And, you know, the folks at Google were we're onto this pretty early with the capture technology, and we were following in their footsteps with our own unique take on it, but specifically applying it to financial documents. >>I mean on the Cube. We know a lot about this because we were looking at transcriptions of video all the time, and it just keeps getting better and better and better in our systems. Get smarter and smarter, smarter. So we're sort of closing that gap between what humans can can do and machines can't. And I would expect that you're seeing the same thing. I mean, you think there's always going to be kind of humans in the loop in terms of the quality or is that gap going to be, you know, six nines in the, you know, near near term. >>I think it's gonna take a while to get rid of all the edge cases. You know, you mentioned the PPB program like we've been on the back end processing P p P loans for some of the leading players, like Cross River Bank, blue Vine, Square Capital and others. And you know, what we've seen during the ppb process is just a a wide variety of different documents and inputs, Uh, and a lot of difficult to read documents that are, you know, very challenging to automate. So I think we will, you know, incrementally continue to automate more and more of the process. But the value of having humans plus machines is much more powerful than just having machines alone or just having humans alone. And as it relates to the end customer, our our goal is to do as much of the mundane work as possible to free our customer up to do the more cerebral analysis. So in a lending context and and for the record, you know, our our biggest market opportunity is in the limbic space. Despite the fact that we started with medicating attorneys, we quickly pivoted and realized that our technology was super valuable to to lenders to help them automate the underwriting process. And our our thesis is, if we can take out all of the necessary evils like document review and allow underwriters to focus on the actual analysis of financial health, it's a win win win and creates a really fantastic, complementary relationship between us and our customers. >>Yes, I want to ask you about the pivot to financial services. You said you started well, you have the inspiration from elder law because Jimmy McGill. Okay. Saul Goodman breaking bad. You got started. An elder law. But then you made the pivot to financial services. Really pretty early on. You had really good, great product market fit, but you kind of went for it. I get early twenties. You know, you didn't have a big family at the time. I didn't have a lot of a lot of risks. So you went for it, right? But talk about that pivot because a lot of companies wouldn't do that. They get comfortable and just, you know, stay where they're at. But you made that >>call. It was a big risk, for sure. I mean, look, the product was working. We launched the paid version of our product in 2016. Pretty quickly were onboarding dozens of accountants and attorneys, you know, doing Medicaid work. Um, in mid to late 2016, we got introduced to a large small business lender in New York City called strategic funding Source. They've since renamed them their company Capital as the current name, but we met with the CEO and the head of product and showed them a demo of the technology. And they said, You know, quote unquote, we've been looking for this for years. We've been looking for something exactly like this for years, and we said back to them about how many pages of financial documents to review every single month. They pointed out to a bullpen of dozens of people sitting there tearing through bank statements, page by page, line by line. And they said, You know, it's hundreds of thousands. My eyes almost fell out of my head. I couldn't believe the volume, and it was much bigger than what the, you know, single accountants or attorneys were doing. Uh, so we made the strategic decision to pivot at that time and focus on FINTECH. Lenders continue to tailor the product and build additional features for the fintech lending space. And and, you know, lending in general had the perfect mix of short sale cycle and high average customer value that allowed a company like ours to scale and ramp our revenue quite quite quickly. Um, and then the other thing that happened is kind of as we were getting deeper and deeper into the space, the fintech space as a whole started growing massive. So we we kind of had the perfect storm of product market fit, plus the market growing that allowed us to really ramp significantly grow revenue. And, uh, you know, despite the fact that it was the risk it was, it was totally right. Decision to to focus the business on financial services >>much bigger Tam. And you could subjectively measure it by the size of the stack of papers. Um, how how does this relate to our p A. As you know, the R p. A hot space. You probably get this question a lot, and it sounds like there are some similarities with software bots. What's the similarity? What's the difference? >>Good question. It's It's totally a synergistic offering, right? So rrp a companies like UI path and automation anywhere they typically provide a horizontal toolkit to allow you know, banks and lenders to automate much of the mundane work like, for example, collecting information from emails or doing onboarding for a new employee. Or, you know, different types of tasks that a manual worker would have done but could be automated with relatively simple code. Um, what happens in our p a. Workflows is they get hung up on tasks that can't be completely automated. So, for example, a robot might be, uh, trying to complete an intend lending flow. But when a bank statement is submitted as part of that flow, the robot can't parse it. So what they do instead, is they routed to an underwriter who performs a manual analysis, keys information into a back office system that the bank is using and that information then gets handed back to a robot and continues the automation flow. What we do is we plug the gaps that used to be manual so a robot can pass US documents like bank statements or pay stubs or tax stops. We run our unique human in the loop process. We return structure Jason output directly to a robot, and it continues into the, you know, to the next step of the flow. And, you know, in in summary, the combination of robotic process automation and human in the loop, which is what we're doing, creates true and and automated flows rather than R P. A mite by itself might get you 80% of the way there. >>So do you have, like, software integrations or partnerships with those companies. How are you integrating with them? >>We do. We have software integrations with both UI path and automation anywhere in our core fintech lending business. R P A isn't as prevalent, but we are now expanding beyond fintech lenders into mortgage lending and traditional banks. And we're also expanding use cases, right? Like historically small business lending was the core of our business. More recently, we've moved into consumer auto mortgage, additional asset classes. And as we've gotten deeper with financial institutions, we've seen even more opportunity to partner and coexist with broader r p a player's >>Yeah, great. I mean, I was just staring at their s one. I guess it was came up Monday. Half over half a billion dollars in a are are they're actually cash flow positive as you iPad. So we're going to see we're going to see them hit the public market shortly. Um, hang on, folks. Uh, now it's okay. So this is you sell a sas, right? A SAS service. Even though there's that human in the loop, that's all part of the service. How do you How do you price? >>So usage based model. So we we kind of try to model are themselves nerve. A massive company is super powerful. We apply that same concept document processing, so it's a usage based model. Customers will pay us either per application per document or per page, and if they want to subscribe for, you know, one document per month or millions of documents per month, it's up to them. And we're able to flex up and flex down to meet the supply and demand. Um and that that concept that scalability and flexibility was particularly powerful in the P P P program, right? P P. P. Was kind of a very unique situation in the sense that lenders weren't able to predict the amount of loans they needed to process in normal lending. A small business lender can tell you Hey, we expect to get roughly 10,000 applications in the month of April with P P p. They could tell us, Hey, we're going to send out 200,000 marketing emails and we expect 30% of people might reply, but we really don't have any idea, right? So what happened is the big banks ended up hiring without exaggeration. Thousands of temporary employees to come in and review documents and kind of scrambled to do this in a work from home setting during the pandemic. Whereas Cross River, they took a technology first approach. They implemented our A P I in the back end, and it enabled them to instantly scale up their resources. And the result of that is Cross River ended up becoming a top three pp, a top three p p. P lender nationally, outperforming many of the big banks with a super efficient and fast document review process. Because we were able to help them on the back end with the automation. >>That's awesome. I love the pricing model you mentioned. You mentioned Amazon. Is that the cloud you use or >>we do Our Our product is hosted in AWS and we, you know, take a lot of learnings from them from a business model and and positioning point of view. >>Yeah, and and I'm thrilled to hear you say I mean, I think a lot of forward thinking startups are doing the consumption model. I mean, you certainly see that with companies like snowflake and data dog and stripe. I mean, I think that that SAS model of okay, we're gonna lock you into a one year, two year, three year term. Sorry if if you get acquired, you're stuck with some, you know, stranded licenses. That's your problem. I think that, you know, you really thought that out. Well, um, you mentioned you're sort of expanding your your your total available market now, looking at at new markets, what are some of the big trends that you want to ride over the coming decade as you scale your company? >>The biggest one for us is mortgage automation. You know, the kind of the one of fintech small business and consumer loans were optimized, and we went from a place where, uh, you know, you would deal with a loan officer and have an in person transaction to modern day. You can get a loan from small business. If you're a small business, you can get a loan from PayPal online effectively instantly. If you're a consumer, you can get a loan from Sofia or lending club super smooth digital experience and really revolutionized the way that you know, the market thinks about financial products. I think the next wave of that is mortgage, and that's what we're focused on. Uh, you know, mortgage is a massive market in the sense of thousands of lenders. The average application contains a couple 100 pages worth of financial documents, and the pain points of the back end of the mortgage process were really accentuated. During covid, right refi Valium went way up and mortgage lenders were forced to process that volume in a work from home setting. So what happened is mortgage lenders were struggling with the concept of sending personally identifiable financial information to underwriters who aren't working in an office there, working at home and, you know, kids running around a million things going on. And it's just more difficult to manage than ever before. Um, and you know, as as the the volume kind of normalized debate and mortgage lenders thought about their own future of automation, I think there was just clear recognition across the board that these these mortgage lenders needed to learn from some of the fintech and really focus on automating the back office peace and you know, to your point earlier about business model, what we think about is translating cost that used to be a fixed cost and turning them into a variable costs So now, instead of worrying about having to match supply and demand and hire or fire people, depending on the volume that's coming in on any given month, a mortgage lender can instantly flex up, reflects down and have a super fast, accurate process to handle the darks. Um, and you know, we're seeing just awesome traction in the market with that with the mortgage space and we're excited to push >>forward there. That's great. Thank you. I mean you, Sam. You describe the chaos that work from home. The financial industry is very overly officious. If you know it's very security conscious. How do you handle security? Maybe you could comment on that. How you think about that? >>Sure. I mean, we we take a compliance first approach. We built the product from the ground up with compliance in mind, knowing that we were selling into financial institutions. We have a sock to type one and type two certification, which is, you know, an industry standard. All of our our verification happens with the Oculus employees. So there's no third parties involved in our process whatsoever. Um and then lastly, But perhaps most importantly, our product in and of itself is innately, um, you know, innately drives compliance. So every data point that we process from a financial document, we not only return the data, we return an exact bounding box coordinates of where that data field appeared on the original source so that that audit trail lives with the loan throughout its life cycle. What we saw prior to Oculus is a mortgage would go through an underwriting process. They make a decision, and then that loan might be sold downstream and a diligence firm as to come in. And they don't have the resources to review all the loans. So they review 15% of the loan tape and then they say, you know, they give a rating and what we do is we proactively tackle that by creating a a perfect audit trail upon origination that can live with the loan throughout its life cycle and that that process and that traceability has been super valuable to our mortgage and banking partners. >>So you can ensure the providence there. So let me end just by talking about the company a little bit. So you incubated you nailed the product market fit the and you pivoted and re nailed the product market fit. And like a lot of companies in your position, I would imagine you saw your growth come from just having a great product. You know, initially, word gets around, but then you got a scale. Uh, maybe you could talk a little bit about how how you did that. How you're doing that. You know where your hiring how you're hiring, what your philosophy is on on scaling. >>Sure. Look, I think the key for us is just surrounding ourselves with the right people. You know, the right mentors, advisors and investors to help us really take the business to the next level. Uh, you know, we had no pride of authorship. We're building this and recognize that there are a lot of people out there who have been there, done that and can really guide us and show us the way. I know you had interviewed Marc Roberge on on the show previously. Formerly the C r. O of hubspot. Mark was someone that we you know, we we read his book and had taken sales advice from him from an early age. And over the over time, we got him a little bit more familiar with the company. And and ultimately, Mark and his partner, J Po at Stage two Capital ended up investing in Oculus and really helping us understand how to build the right go to market engine. Um, as the company got bigger, we took on investments from really reputable firms in the financial services space. So our largest investors are okay, H C F T fintech collective and and QED investors. Uh, you know, QED was was founded by Nigel Morris, who is the co founder of Capital One. They backed Sophia and Prosper and a lot of big fintech lenders and, you know, bringing the collective expertise from the fintech sector as well as you know, from a sales and go to market strategy. Point of view created the right mix of ingredients for us to to really ramp up significantly. Uh, we had an awesome run over the years. We were pretty recently recognized by magazine as the number one fastest growing fintech company. And, you know, as the momentum is increased and the market conditions have been very favorable to us, we we just want to double down and expand. Mortgage is the biggest area of opportunity for us. And what we're seeking from a hiring perspective is, you know, go to market sales account executive type resources on the mortgage side as well as you know, deeper products expertise both on the mortgage side as well as with machine learning our product. Because we have the human in the loop piece, we create massive amounts of training data on a daily basis. So it's a, I think, a really exciting place for cutting edge machine learning developers to come and and innovate. >>What can you share with our audience about, you know, your company, any metrics and whatever you're comfortable with, how much money you've raised on my head count? If you want to get some companies comfortable giving a r r others on. But what what do you What can you share with us? >>Sure. Um, you know, we we've raised about 50 million in venture capital. We have grown from one to north of 20 million in revenue in the in the last three years. So particularly since you know, 2017, 2018 is what we really started to see. The growth take off, uh, company size. We have about 800 to 900 employees globally. Now we have about 200 corporate employees who perform the, you know, the the day to day functions of Oculus. And then we have a long tail of about 600 or so verifiers who perform data verification and quality control work again, Speaking to the human in the loop piece of the bottle. Uh, we're, you know, we're focused on expanding beyond the fintech customer base, where we serve customers like plaid PayPal lending club so fi square, etcetera into the mortgage space and ultimately into the traditional banking space where you know, the problems, frankly, are extremely similar. Just on a much larger scale. >>San Bobbly. Congratulations on all the success. You You've got a great road ahead. I really appreciate you coming on the Cube, >>Dave. Thanks so much. It's been a great chat. Look forward to keeping in touch. >>Alright, Did our pleasure. Thank you for watching everybody. This is Dave Volonte for the Cube. We'll see you next time

>>Welcome to this IBM Watson health client conversation here. We're probing the dynamics of the relationship between IBM and its clients. And we're looking back, we're going to explore the present. We're going to discuss the future state of healthcare. My name is Dave Volante from the Cuban with me are Robert Stell horn. Who's associate director, H E O R at sukha, otherwise known as pharmaceuticals, America and Rena Felton. Who's with of course, IBM Watson health. Welcome folks. Great to have you. Hi, so like strong relationships, as we know, they're the foundation of any partnership. And of course over the past year, we've had to rely on both personal and professional relationships to get us through some of the most challenging times, if not the most challenging times of our lives. So let me start with you, Robert, how has the partnership with IBM helped you in 2020? >>I think it was just a continuation of the excellent relationship we have with Rena and IBM. Um, starting in March, we had really a shift to an all remote, uh, workplace environment. And I think that constant communication with Rina and IBM helped that situation because she kept us up to date with, uh, additional products and offerings. And basically we came up with some additional solutions towards the end of the year. So we're gonna watch >>Pick it up from here. Let's go, let's go a little bit deeper and maybe you can talk about some of the things that you've done with Robert and his team and, and maybe some of the accomplishments that you're most proud of in 2020. >>No, absolutely. And I have to kind of echo what you first said about the foundation and our partnerships being the foundation, um, of our past present and future. So I do want to take the opportunity to thank Rob again for joining us today. It is, um, I know, you know, with his kids home and remote learning, um, it's a lot, uh, to, to ask in addition to, you know, your day to day work. So, so thank you, Rob. Um, I guess the question that I have for you is what would be the greatest accomplishment, um, that Watseka and IBM Watson had in 2020? >>I would say it was the addition of the linked claims EMR data, the LDCD product that we were able to license in-house, uh, thanks to your attention and to show the advantages and the strengths of that data. We are able to license that in to our, uh, set up assets we have internally. And what that's gonna allow us to do is really find out more information about the patients. Uh, we're existing users of the Mark IBM, uh, market scan data. Um, this is going to allow us to tie into those same patients and find out more about them. Um, in particular, uh, a lot of our products are in the mental health space and a lot about standing questions we have are why are the patients getting different products? And with the notes are available in that link data. We're going to now be able to tap into more information about what is happening with the patient. >>Okay. Can I ask a question on that? Um, if you guys don't mind, I mean, you know, when you, when you hear about, you know, uh, EMR, uh, in the early days, it was a lot about meaningful use and getting paid. It sounds like you guys are taking it much deeper and as a, as a, you know, as an individual, right, you're, you're really happy to hear that this information is now going to be used to really improve, uh, healthcare is, do I have that right? Is that, you know, kind of the nature of where you guys are headed? >>Well, I think ultimately it's the, the, the, the main goal is to help the patients and provide the products that can really, um, help them in their daily lives. So, um, really with this data, now, we're going to be able to tap into more of the why, um, exist in claims data. We cannot really get that information, why VC information, about what diagnoses they incurred during their treatment history. And we also can see, uh, different prescriptions that are given to them, but now we're going to be able to tie that together and get more understanding to really see more focused treatment pattern for them. >>So, Reno, w w you sit down with Rob, do you have like a, sort of a planning session for 2021? Why don't you sort of bring us up to, uh, to what your thinking is there and how you guys are working together this year? >>Yeah, no, absolutely. Um, actually, before we get to that, I wanted to kind of add onto what Rob was saying as well. It's interesting given, you know, the pandemic in 2020 and what the LCD data is going to do, um, to really be able to look back. And as Rob mentioned, looking specifically at mental health, the ability to look back and start looking at the patients and what it's really done to our community and what it's really done to our country, um, and looking at patients, you know, looking back at, at sort of their, their patient journey and where we are today. Um, but Rob and I talk all the time, we talk all the time, we probably talk three or four times a day sometimes. So I would say, um, we, we text, uh, we do talk and have a lot of our strategic, um, sessions, uh, our outlook for 2021 and what the data strategy is for Otsuka. Um, in addition, additional data assets to acquire from IBM, as well as how can we sort of leverage brander IBM, um, assets like our red hat, our OpenShift, our cloud-based solutions. So, you know, Rob and I are constantly talking and we are, um, looking for new ways to bring in new solutions into Otsuka. Um, and you know, yeah, we, we, we talk a lot. What do you think, Rob? >>I think we have an excellent partnership. Uh, basically, um, I think their relationship there is excellent. Um, we have excellent communication and, you know, I find when there's situations where I may be a bind Reno's is able to help out instantly. Um, so it's, it's really a two way street and it's an excellent partnership. >>I wonder if I could double click on that. I mean, relative to maybe some of your, I mean, I'm sure you have lots of relationships with lots of different companies, but, but what makes it excellent specifically with regard to IBM? Is there, is there anything unique Rob, that stands out to you? >>It would be the follow-up, um, really, it's not just about, uh, delivering the data and say, okay, here you have your, your product work with it in basically the, the, the vendor disappears, it's the constant followup to make sure that it's being used in any way they can help and provide more information to really extract the full value out of it. >>So I'm gonna forget to ask you guys, maybe each of you, you know, both personally and professionally, I feel like, you know, 20, 20 never ended it just sort of blended in, uh, and, and, but some things have changed. We all talk about, geez, what's going to be permanent. How have you each been affected? Um, how has it helped you position for, for what's coming in in the years ahead, maybe Reena, you could start and then pick it up with, with Rob. >>Oh man. Um, you know, 2020 was definitely challenging and I think it was really challenging given the circumstances and in my position where I'm very much used to meeting with our customers and having lunch and really just kind of walking down the hallways and bumping into familiar faces and really seeing, you know, how we can provide value with our solutions. And so, you know, that was all stripped in 2020. Uh, so it's been, it's been quite challenging. I will say, working with Rob, working with some of my other customers, um, I've had, uh, I've had to learn the resilience and to be a little bit more relentless with phone calls and follow ups and, and being more agile in my communications with the customers and what their needs are, and be flexible with calendars because there's again, remote learning and, and, um, and the like, so I think, you know, positioned for 2021 really well. Um, I am excited to hopefully get back out there and start visiting our customers. But if not, I certainly learned a lot and just, um, the follow-up and again, the relentless phone calls and calling and checking up on our customers, even if it's just to say, hi, see how everyone's doing a mental check sometimes. So I think that's, that's become, um, you know, what 2020 was, and, and hopefully, you know, what, 2021 will be better and, uh, kind of continue on that, that relentless path. >>What do you think, Rob? Hi, how are you doing? >>I would echo a lot of Rina's thoughts and the fact of, yeah, definitely miss the in-person interaction. In fact, I will say that I remember the last time I was physically in the office that Scott, it was to meet with Rina. So I distinctively remember that they remember the date was March, I believe, March 9th. So it just shows how this year as has been sort of a blur, but at the same time, you remember certain milestones. And I think it's because of that relationship, um, we've developed with IBM that I can remember those distinctive milestones and events that took place. >>So Rob, I probably should have asked you upfront, maybe tell us a little bit about Alaska, uh, maybe, maybe give us the sort of quick soundbite on where you guys are mostly focused. Sure. >>Oh, it's guys, uh, a Japanese pharmaceutical company. The focus is in mental health and nephrology, really the two main business areas. Um, my role at guys to do the internal research and data analytics within the health economics and outcomes research group. Um, currently we are transitioned to a, uh, name, which is global value and real world evidence. Um, fact that transition is already happened. Um, so we're going to have more of a global presence going forward. Um, but my role is really to, uh, do the internal research across all the brands within the company. >>So, so Rena, I wonder this, thank you for that, Robert. I wonder if you could think, thinking about what you know about Scott and your relationship with Robin, your knowledge of, of the industry. Uh, there's so much that IBM can bring to the table. Rob was talking about data earlier, talking about EMR, you were talking about, you know, red hat and cloud and this big portfolio you have. So I wonder if you could sort of start a conversation for our audience just around how you guys see all those assets that you have and all the knowledge, all that data. How do you see the partnership evolving in the future to affect, uh, the industry and the, in the future of healthcare? >>Well, I would love to see, um, the entire, uh, uh, platform, um, shift to, to the IBM cloud, um, and certainly, you know, leverage the cloud pack and analytics that, that we have to offer, um, baby steps most definitely. Um, but I do think that there is, uh, the opportunity to really move, um, and transform the business into something a lot more than, than what it is. >>Rob has the pandemic effected sort of how you think about, um, you know, remote services and cloud services and the, like, were you already on the path headed there? Did accelerate things, have you, you know, have you not had time because things have been so busy or maybe you could comment? >>Yeah, I think it's really a combination. And so I think you hit on a, a fair point there, just the time, uh, aspect. Um, it's definitely been a challenge and your, um, I have two children and remote learning has definitely been a challenge from that perspective. So time has definitely been, uh, on the short side. Um, I do see that there are going to in the future be more and more users of the data. So I think that shift to a potential cloud environment is where things are headed. >>So we, I have a bunch more questions, but I want to step back for a second and see if there's anything that you'd like to ask Rob before I go onto my next section. Okay. So I wonder if you could think about, um, maybe both of you, the, the, when you think back on, on 2020 and all the, you know, what's transpired, what, what transitions did you guys have to make? Uh, maybe as a team together IBM and Alaska. Um, and, and, and what do you see as sort of permanent or semi-permanent is work from home? We're gonna going to continue at a higher rate, uh, are there new practice? I mean, I know just today I made an online appointment it's for a remote visit with my doctor, which never could have happened before the pandemic. Right. But are there things specific to your business and your relationship that you see as a transition that could be permanent or semi-permanent? >>Well, I, I think it's there, there's definitely a shift that's happened that will is here to stay, but I don't know if it's full, it's going to be a combination in the future. I think that in-person interactions, especially what Rena mentioned about having that face-to-face interaction is still going to be one things are in the right place and safe they're going to happen again. But I think the ability to show that work can happen in a virtual or a full remote workplace, that's going to just allow that to continue and really give the flex of people. The flexibility I know for myself, flexibility is key. Like I mentioned, with two small children, um, that, that, that becomes such a valuable addition to your work, your life and your work life in general, that I think that's here to stay. >>Okay. Um, so let me ask you this, uh, w one of the themes of this event is relentless re-invention. So what I'm hearing from you Rob, is that it kind of a hybrid model going forward, if you will, uh, maybe the option to work from home, but that face to face interaction, especially when you're creating things like you are in the pharmaceutical business and the deep R and D that collaborative aspect, you know, you, it's harder when you're, when, when, when you're remote. Um, but maybe you could talk about, you know, some of those key areas that you're, you're going to be focused on in 2021 and, and really where you would look for IBM to help. >>I think in 2021, the team I'm part of it, part of is, is growing. So I think there's going to be additional demand for internal research, uh, uh, capabilities for analysis done within the company. So I think I'm going to be looking to Rena to, uh, see what new data offerings are available and all what new products are going to be available. But beyond that, um, I think it's the potential that, you know, there's so much, uh, projects, um, that are going to be coming to the table. We may need to outsource some of that projects and IBM could be potentially be a partner there to do some of the analysis on to help out there. >>Anything you'd add. >>Uh, no, I think that, that sounds good. >>How would you grade IBM and your relationship with IBM Rob? >>Well, I have to be nice to Rina cause she's been very nice to me. I would say an a, an a plus >>My kids, I got kids in college. Several, they get A's, I'm happy. Oh, that's good. You know, you should be proud. So, congratulations. Um, anything else Reno, you give you, I'll give you a last word here before we wrap, >>You know, 2020 was, was a challenging. And, you know, we talked a little bit about, you know, what time in 2020, you know, Rob and I have always had a really good relationship. I think 2020, we got closer, um, with just both professionally and really diving in to key business challenges that they have, and really working with him to understand what the customer needs are and how we can help, not only from, you know, an HR perspective, but also how can we help Otsuka, um, as a company in, in totality. So, you know, we've been able to do that, but personally, I would say that I really appreciated the relationship. I mean, we can go from talking about work to talking about children, to talking about family, um, all in the same five minute conversation or 10 minute conversation, sometimes our conversation. So, you know, thank you, Rob 2020 was definitely super challenging. >>I know for you on so many levels. Um, but I have to say you've been really great at just showing up every time picked up the phone, asked questions. If I needed something I can call you, I knew you were going to pick up, I had an offering and be like, do you have 10 minutes? Can I share this with you? And you would pick up the phone, no problem, and entertain a call or set up a call with all your internal colleagues. And I, I appreciate that so much. And, you know, I appreciate our relationship. I appreciate the business and I, I do hope that we can continue on in 2021, we will continue on in 2021. Uh, but, um, but yeah, I thank you so much. >>Rain has been extremely helpful. I don't want to thank you for all the help. Um, just to add to that one point there, you know, we have, uh, also another product, which I forgot to mention that we licensed in from IBM, it's the treatment pathways, um, tool, which is an online tool. Um, and we have users throughout the globe. So there's been times where I've needed a new user added very quickly for someone in the home office in Japan. And Rena has been extremely helpful in getting things done quickly and very proactively. >>Well, guys, it's really clear that the depth of your relationship I'm interested that you actually got closer in 2020. Uh, the fact that you communicate, you know, several times a day is I think Testament to that relationship. Uh, I'm really pleased to hear what you're doing and the potential with the EMR data for patient outcomes. Uh, as I say in the early days, I used to hear all about how well you have to do that to get paid. And it's really great to see a partnership that's, that's really focused on, on, on patient health and, and changing our lives. So, and mental health is such an important area that for so many years was so misunderstood and the, and the data that we now have, and of course, IBM's heritage and data is key. Uh, the relationship and the follow-up and also the flexibility is, is something I think we all learned in 2020, we have to, we've kind of redefined, you know, resilience in our organizations and, uh, glad to see you guys are growing. Congratulations on the relationship. And thanks so much for spending some time with me. >>Thank you. Thank you, Dave. Thank you, Raina >>For watching this client conversation with IBM Watson health.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Welcome to the Cube. Virtual. This is our coverage of aws reinvent 2020. Specialized programming for worldwide public sector. I'm Lisa Martin. Got a couple of guests here from No. Veta, please welcome Steven Adelman, principal computer scientists, and Kevin Healed, vice president of Information Exploitation. Gentlemen, welcome to the Cube. >>Thank you. >>Thank you for having us. >>Alright, guys. So? So, Kevin, we're going to start with you. Give our audience an introduction to Nevada. What do you What do you guys do? Who are you? How do you play in the public sector Government space, >>right? Yeah. Thank you, Lisa. Eso, Nevada Nevada is a technology services company focused on government solutions. So primarily national security solutions. Eso think customers such as Doody, the intelligence community, FBI, law enforcement and things like that about 13 1300 employees worldwide, primarily in our in our field. Clear resource is, um, that really focused on cloud for solutions for our customers. So solving the tough mission challenges our customers have, so that could be in technology solutions such as Data Analytics A I M L i O T. Secure Workloads, full spectrum cyber Cobb video processing. Really anything that's a high end technology solution or something we do for the government. We have been a privilege. We have. It's a privilege to be a partner with AWS for for some time now. In fact, I think the first reinvent we may have been to Stephen was six years ago. Five years ago, two >>1012 or 13 >>s So we've we've we've been around for a while, really kind of enjoying it and certainly sad that we're missing an in person reinvent this year, but looking forward to doing it virtually so, we're actually advanced your partner with AWS with a machine learning and government competency. Andi really kind of thio pump the m l side of that. That was one of our first companies with compasses with AWS and led by a center of excellence that I have in my division that really focuses on machine learning and how we applied for the Michigan. And so, um, really, we focus on protecting the nation and protecting our activities in the country >>and on behalf of the country. We thank you, Steven. Give me a little bit of information from a double click perspective as computer scientists. What are some of the key challenges that no, that helps its customers to solve. And how do you do that with a W s? >>Yeah, Thank you. So really as, ah, company, that is is data first. So our initial love and and still are kind of strongest competency is in applying solutions to large data sets. And as you can imagine, uh, the bigger the data set them or compute you need the the more resource is you need and the flexibility from those resource is is truly important, which led us very early, as especially in the government space and public sector space to be in early. A doctor of cloud resource is because of the fact that, you know, rather than standing up a 200 node cluster at at many millions of dollars, we could we could spend up a W s resource is process a big data set, and then and then get the answers an analyst or on operator needed and then spin down. Those resource is when When when that kind of compute wasn't needed. And that is really, uh, kind of informed how we do our work Azaz Nevadans that that cloud infrastructure and now pushing into the edge compute space. Still kind of keeping those cloud best practices in play to get access to more data. That the two, the two biggest, I think revolutions that we've seen with regards to using data to inform business processes and missions has been that that cloud resource that allows us to do so much with so less and so much more flexibly and then the idea of cheap compute making it to the edge and the ability to apply sensors thio places where you know it would been a would have been, you know, operational cost prohibitive to do that and then, ironically, those air to things that aren't necessarily data analytics or machine learning focused but man, did they make it easier to collect that data and process that data and then get the answers back out. So that really has has has kind of, uh, shaped a lot of the way Nevada has grown as a company and how we serve our customers. >>So coming back over to you lets. One of the things that we've been talking about almost all year is just the acceleration in digital transformation and how much faster organizations, private sector, public sector need to innovate to stay relevant, to stay competitive. How do you are you working with government customers to help them innovate so quickly? >>You know, we're very fortunate that a set of customers that focuses actually innovation it's focuses. I rad on. Do you know we can't do the cool things we do without those customer relationships that really encourage us to, um, to try new things out and, quite frankly, fail quickly when we need Thio. And so, by establishing that relationship, what we've been able to do is to blend agile development. Actual acquisition with government requirements process, right? If if you know the typical stereotype of government work is it's this very stovepiped hard core acquisition process, right? And so we have been fortunate to instead try quick win kind of projects. And so one of the biggest things we do is partner with our government customers and try to find it difficult, um, challenged to solve over 6 to 12 month time, right? So instead of making this long four or five year acquisition cycles like show me, right. How can we solve this problem? And then we partner with the mission partner show success in six months show that we can do it with a smaller part of money, and then as we're able to actually make that happen, it expands in something bigger, broader, and then we kind of bringing together a coalition of the willing, if you will in the government and saying, Okay, are there other stakeholders to care about this problem, bring them on, bring their problems and bringing together? You know, we can't do that with some of the passionate people we have, like Stevens. A perfect example. When we talk about a car in the projects we're doing here, Stevens passion for this technology partner with our customers having these challenges and try to enhance what they're doing is a powerful combination. And then the last thing that we're able to is a company is we actually spend a decent amount of our own dollar dollars on I rad S O. R and D that we fund ourselves. And so, while finding those problems and spending government dollars in doing that. We also have spent our own dollars on machine learning Coyote sensor next Gen five g and things like that and how those compartment together partner together to go back to the government. >>Yeah, yeah, So I would even say, You know, there's this. There's a conventional wisdom that government is slow in plotting and a little bit behind commercial best practices. But there are There are pockets in growing pockets across the government, Um, where they're really they're really jumping ahead of, ah, lot of processes and getting in front of this curve and actually are quite innovative. And and because they kind of started off from behind, they could jump over a lot of kind of middle ground legacy technologies. And they're really innovating. As Kevin said with With With the card platform, we're partnering with um P E O Digital in the Air Force in South C, D. M and Air Force security forces as that kind of trifecta of stakeholders who all want toe kind of saw a mission problem and wanted to move forward quickly and leave the legacy behind and and really take a quantum leap forward. And if anything, they're they're driving us Thio, Innovate Mawr Thio Introduce more of those kind of modern back practices on bond. Nevada as a company loves to find those spots in the government sector where we've got those great partners who love what we're doing. And it's this great feedback loop where, um, where we can solve hard technical problems but then see them deployed to some really important and really cool and impactful missions. And we tend to recruit that that set that kind of nexus of people who want to both solve a really difficult problem but want to see it executed in a really impactful way as well. I mean, that really grates a great bond for us, and and I'm really excited to say that that a lot of the government it is really taking a move forward in this this this realm. And I think it's it's just good for our country and good for the missions that they support. >>Absolutely. And it's also surprising because, as you both said, you know, there is this expectation that government processes or lengthy, you know, laborious, um, not able to be turned around quickly. But as Kevin, you just said, you know helping customers. Government agencies get impact within 6 to 12 months versus 4 to 5 years. So you talked about Picard? Interesting name. Kevin. Tell me a little bit more about that technology and what it is that you guys deliver. That's unique. >>Well, honestly, it's probably best to start with Stephen. I can give you the high level. This is Stevens vision. I have to give him credit for that. And I will say way have lots of fun. Acronym. So it isn't Actually, it isn't backward. Um, right. Stephen doesn't actually stand for something. >>It stands for Platform for Integrated, a C three and Responsive for defense on >>Guy. You know >>that the Star Trek theme is the leg up from the last set of programs I had, >>which were >>my little ponies. So >>Oh, wow. That's a definite stuff in a different direction. Like >>it? Part of the great thing about working in the government is you get to name things, cool things, so but t get to your question eso So Picard really sprung out of this idea that I had a few years ago that the world but for our spaces, the Department of defense and the federal government was going to see a massive influx of the desire to consume sensors from from areas of responsibility, from installations and, frankly, from battlefields. Um, but they were gonna have to do it. In a way, um, uh, that presented some real challenges that you couldn't just kind of throw compute editor, throw traditional I t processes at it. You know, we have legacy sensors that are 40 years old sitting on installations. You know, old program, a logical controllers or facilities control systems that were written in cobalt in the seventies, right in the world are not even I, p based, most of them bond. Then on the other end of the spectrum, you have seven figure sensors that air, you know, throwing out megabits of second of data that are mounted to the back of jeeps. Right, That that air bouncing through the desert today. But we'll be bouncing through the jungle tomorrow, and you have to find all of those kind of in combined all of those together, um, and kind of create a cohesive data center for data set set for you know, the mission for, um, you know what we call a user to find common operating picture for a person. Thio kind of combine all of those different resource is and make it work for them. And so we found a great partner with security forces. Um, they realized that they wanted Thio to make a quantum leap forward. They had this idea that the next defender So there are there, like a military police outfit that the next defender was going to be a data driven defender and they were gonna have to win the information war war as much as they had to kind of dominate physical space. And they immediately got what we were trying to achieve, and it was just just great synergy. And then we've piled on some other elements, and we're really moving that platform forward to to kind of take every little bit of information we can get from the areas of responsibility and get it into a you know, your modern Data Lake, where they can extract information from all that data. >>Kevin, as the VP of information exploitation, that's a very interesting title. How are you helping government organizations to win the war on information? Leverage that information to make a big impact fast. >>Yeah. I mean, I think a lot of it is is that we try to break down the barriers between systems on data so that we can actually enable that data to fuse together to find and get insights into it. You know, as ML and I have become trendy topics, you know, they're very data hungry operations. And I think what Steven has done with the card and his team is really we want to be able to make those sensors seamless from a plug and play perspective that Aiken plug in a new sensor. It's a standards based, uh, interface that sends that data back so that we can and take it back to the user to find Operation Picture and make some decisions based off of that data. Um, you know, what's more is that data could even refused with more than the data that Stevens collecting off the sensors. It could be commercial data, other government data and I think is Davis. As Stephen said earlier, you have to get it back. And as long as you've gotten back in Labour's share with some of our mission partners, then you can do amazing things with it. And, you know, Stephen, I know you have some pretty cool ideas and what we're gonna do on the edge, right? How do we do some of this work of the edge where a sensor doesn't allow us to pull out that data back? >>Yeah, and and Thio follow on to what you were kind of referring to with regards to thio handling heterogeneous data from different sensors. Um, one of the main things that our government customers and we have seen is that there are a lot of historically there are a lot of vertical solutions where you know, the sensor, the platform, and then the data Laker kind of all part of this proprietary stack. And we quickly realized that that just doesn't work. And so one of the major thrust of that card platform was to make sure that we had ah, platform by which we could consume data through adapters from essentially any sensor speaking. Any protocol with any style data object, Whether that was an industry standard or a proprietary protocol, we could quickly interested and bring it into our Data lake. And then to pile on to what Kevin was talking about with compute. Right? So you have, uh, like, almost like a mass locks hierarchy of needs when it comes to cyber data or thio this coyote data or kind of unified data, Um, you know, you wanna turn it into basic information, alerts alarms, then you want to do reporting on it, or analytics or some some higher level workflow function. And then finally, you probably want to perform some analytics or some trending or sort of anomaly detection on it. And and that gets more computational e intensive each step of the way. And so you gotta You gotta build a platform that allows you to to both take some of that high level compute down to the edge, but also then bring some of that data up into the clouds where you could do that processing, and you have to have kind of fun jubilate e between that and so that hard platform allows you to kind of bring GP use and high processing units down to the edge and and make that work. Um, but then also and then as maybe even a first passive to rule out some of the most you know, some of the boring gated in the video Analytics platform. We call it Blue Sky and Blue Ocean. Right, so you're recording lots of video. That's not that interesting. How do you filter that out? So you're only sending the information The interesting video up eso You're not wasting bandwidth on stuff that just doesn't matter on DSO. It's It's a lot of kind of tuning these knobs and having a flexible enough platform that you could bring Compute down when you need it. And you could bring data up to compute on Big Cloud while you need it, and just kind of finding a way to tune that that that really does. I mean it. You know, that's a lot of words about how you do that. But what that comes to is flexible hardware and being able to apply those dev ops and C I. C D platform characteristics to that edge hardware and having a unified platform that allows you to kind of orchestrate your applications in your services all the way up and down your stack, from micro controllers to a big cloud instant creation. >>You make it sound so easy. Steven Kevin. Let's wrap it up with you in terms of like making impacts and going forward. We know the edge has exploded, even mawr, during this very interesting year. And that's going to be something that's probably going to stay, um, stay as a permanent impact or effect. What are some of the things that we can expect in 2021 in terms of how you're able to help government organizations capitalize on that, find things faster, make impact faster? >>Yeah. I mean, I think the cool thing we're seeing is that there's a lot more commoditization of sensors. There's a lot more censored information. And so let's use lighters. Example. We you know, things were getting cheaper, and so we can all of a sudden doom or or more things at the edge, and we ever would have expected. Right when you know Steven's team is integrating camera data and fence data from 40 years ago, you know, it's just saying on off it's not do anything fancy. But now we you know, you know, Stephen, I camera whether Metro you gave him before was, but the cost of light are has dropped so significantly that we can now then deploy that we can actually roll it out there and not being locked in their proprietary, uh, system. Um, so I see that being very powerful, you know? Also, I can see where you start having sensors interact with each other, right? So one sensor finds one thing and then a good example that we've started thio experiment with. And I think Steve, you could touch on it is using triggering a sensor, triggers a drone to actually investigate what's going on and then therefore, hybrid video back and then automatically can investigate instead of having to deploy a defender to actually see what happened at that. At that end, Points dio e don't know. There's it's amore detail you can provide there. >>Yeah, No. So exactly that Kevin. So So the power of the sensor is is something something old that that gives you very uninteresting Data like a one or a zero on on or off can detect something very specific and then do something kind of high speed, like task a drone to give you a visual assessment and then run object detection or facial recognition on, you know, do object detection to find a person and do facial recognition on that person to find out if that's a patrol walking through a field or a bad guy trying Thio invade your space. Um and so it's really the confluence and the gestalt of all of these sensors in the analytics working together, Um, that really creates the power from very simple, simple delivery. I think, um, there's this, You know, this idea that you know, ah 100 bytes of data is not that important. But when you put a million sensors giving you 100 bytes of data, you can truly find something extremely powerful. And then when you kind of and you make those interactions sing, um, it's amazing. Tow us the productivity that we can produce and the kind of fidelity of response that we can give thio actors in the space whether that's a defender trying to defend the base or a maintenance person trying thio proactively replace the fan or clean the fan on an H vac system. So So you know, you know, there isn't a fire at a base or for, uh, interesting enough. One of the things that we we've been able to achieve is we've taken maintenance data for helicopter engines and And we've been able to proactively say, Hey, you need to You need to take care of this part of the helicopter engine. Um and it saves money. It saves downtimes. It keeps the birds in the air. And it's a relatively simple algorithm that we were able to achieve. And we were able to do that with the maintenance people, bring them along in this endeavor and create analytics that they understood and could trust on DSO. I think that's really the power of this base. >>Tremendous power. I wish we had more time to to dig into it. Guys, thank you so much for sharing. Not just your insights, what nobody is doing but your passion for what you're doing and how you're making such an impact. Your passion is definitely palpable. Steven. Kevin, Thank you for joining me today. >>Thank you >>for my guests. I'm Lisa Martin. You're watching the Cube? Virtual. Yeah,

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Welcome to the cubes coverage of AWS reinvent 2020. The digital version I'm Lisa Martin and I have a couple of Cuba alumni joining me from Wien. We've got Danny Allen. It's C T O and S VP of product strategy And Dave Russell, VP of Enterprise Strategy, is here as well. Danny and a Welcome back to the Cube. >>Hi, Lisa. Great to be here. >>Hey, Lisa. Great to be here. Love talking with this audience >>It and thankfully, because of technologies like this in the zoom, were still able to engage with that audience, even though we would all be gearing up to be Go spending five days in Vegas with what 47,000 of our closest friends across, you know, and walking a lot. But I wanted Thio. Danny, start with you and you guys had them on virtually this summer. That's an event known for its energy. Talk to me about some of the things that you guys announced there. And how are your customers doing with this rapid change toe? work from home and this massive amount of uncertainty. >>Well, certainly no one would have predicted this the beginning of the year. There has been such transformation. There was a statement made earlier this year that we've gone through two years of transformation in just two months, and I would say that is definitely true. If you look both internally and bean our workforce, we have 4400 employees all of a sudden, 3000 of them that had been going into the office or working from home. And that is true of our customer base as well. There's a lot of remote, uh, remote employ, mental remote working, and so that has. You would think it would have impact on the digital systems. But what it's done is it's accelerated the transformation that organizations were going through, and that's been good in a number of different aspects. One certainly cloud adoption of clouds picked up things like Microsoft teams and collaboration software is certainly picked up, so it's certainly been a challenging year on many fronts. But on the on the other hand, it's also been very beneficial for us as well. >>Yeah, I've talked to so many folks in the last few months. There's silver linings everywhere. There's opportunity everywhere. But give our audience standing an overview of who them is, what you do and how you help customers secure their data. >>Sure, so VM has been in the backup businesses. What I'll say We started right around when virtualization was taking off a little before AWS and you see two left computing services on DWI would do back up a virtual environments. You know, over the last decade, we have grown into a $1 billion company doing backup solutions that enable cloud data management. What do you mean by that? Is we do backup of all kinds of different infrastructures, from virtual to cloud based Assad's based to physical systems, You name it. And then when we ingest that data, what we do is we begin to manage it. So an example of this is we have 400,000 customers, they're going back up on premises. And one of the things that we've seen this year is this massive push of that backup data into S three into the public cloud and s. So this is something that we help our customers with as they go through this transformation. >>And so you've got a team for a ws Cloud native solution. Talk to me a little bit about that. And how does that allow business is to get that centralized view of virtual physical SAS applications? >>Yeah, I think it all starts with architecture er and fundamentally beams, architectures. ER is based upon having a portable data format that self describing. So what >>does >>that mean? That means it reduces the friction from moving data that might have been born on premises to later being Stan Shih ated in, say, the AWS cloud. Or you can also imagine now new workloads being born in the cloud, especially towards the middle and end of this year. A lot of us we couldn't get into our data center. We had to do everything remotely. So we had to try to keep those lights on operationally. But we also had to begin to lift and shift and accelerate your point about silver linings. You know, if there is a silver lining, the very prepared really benefited. And I think those that were maybe a little more laggards they caught up pretty quickly. >>Well, that's good to hear stick big sticking with you. I'd love to get your perspectives on I t challenges in the last nine months in particular, what things have changed, what remains the same. And where is back up as a priority for the the I T folks and really the business folks, too? >>Yeah, I almost want to start with that last piece. Where? Where's backup? So back up? Obviously well understood as a concept, it's well funded. I mean, almost everybody in their right mind has a backup product, especially for critical data. But yet that all sounds very much the same. What's very, very different, though? Where are those workloads? Where do they need to be going forward? What are the service level agreements? Meaning that access times required for those workloads? And while we're arguably transitioning from certain types of applications to new applications, the vast majority of us are dead in the middle of that. So we've got to be able to embrace the new while also anchoring back to the past. >>Yeah, I'm not so easily sudden, done professionally or personally, Danny, I'd love to get your perspective on how your customer conversations have changed. You know, we're executives like you, both of you are so used to getting on planes and flying around and being able Thio, engage with your customers, especially events like Vermont, and reinvent What's the change been like? And from a business perspective, are you having more conversations at that business? Little as the end of the day. If you can't recover the data, that's the whole point, right? >>Yeah, it is. I would say the conversations really have four sentiments to them. The first is always starts with the pandemic and the impact of the pandemic on the business. The second from there is it talks about resource. We talked about resource management. That's resource management, both from a cost perspective. Customers trying to shift the costs from Capex models typically on premises into Op X cloud consumption models and also resource management as well. There's the shift from customers who are used to doing business one way, and they're trying to shift the resources to make it effective in a new and better way. I'd say the third conversation actually pivots from there to things like security and governance. One of the interesting things this year we've seen a lot of is ransomware and malware and attacks, especially because the attack surface has increased with people working from home. There is more opportunity for organizations to be challenged, and then, lastly, always pivots where it ends up his digital transformation. How do I get from where I used to be to where I want to be? >>Yeah, the ransomware increase has been quite substantial. I've seen a number of big. Of course you never want to be. The brand garment was head Carnival Cruise Line. I think canon cameras as well and you're talking about you know you're right, Danny. The attacks are toe surfaces, expanding. Um, you know, with unprotected cloud databases. I think that was the Facebook Tic Tac Instagram pack. And so it's and also is getting more personal, which we have more people from home, more distractions. And that's a big challenge that organizations need to be prepared for, because, really, it's not a matter of are we going to get a hit? But it's It's when, and we need to make sure that we have that resiliency. They've talked to us about how them enables customers toe have that resiliency. >>Yeah, you know, it's a multilayered approach like you know, any good defensive mechanism. It's not one thing it's trying to do all of the right things in advance, meaning passwords and perimeter security and, ideally, virtual private networks. But to your point, some of those things can fail, especially as we're all working remotely, and there's more dependence on now. Suddenly, perhaps not so. I t sophisticated people, too. Now do the right things on a daily basis and your point about how personal is getting. If we're all getting emails about, click on this for helpful information on the pandemic, you know there's the likelihood of this goes up. So in addition to try and do good things ahead of time, we've got some early warning detection capabilities. We can alert that something looks suspicious or a novelist, and bare bears out better investigation to confirm that. But ultimately, the couple of things that we do, they're very interesting and unique to beam are we can lock down copy of the backup data so that even internal employees, even somewhat at Amazon, can't go. If it's marked immutable and destroy it, remove it, alter it in any way before it's due to be modified or deleted, erased in any way. But one of the ones I'm most excited about is we can actually recover from an old backup and now introduce updated virus signatures to ensure we don't reintroduced Day zero threats into production environment. >>Is it across all workloads, physical virtual things like, you know, Microsoft or 65 slack talked about those collaboration tools that immune ability, >>so immune ability. We're expanding out into multiple platforms today. We've got it on on premises object storage through a variety of different partners. Actually, a couple dozen different partners now, and we have something very unique with AWS s three object lock that we you can really lock down that data and ensure that can't be compromised. >>That's excellent, Danny, over to you in terms of cloud adoption, you both talked about this acceleration of digital business transformation that we've all seen. I think everyone has whiplash from that and that this adoption of cloud has increased. We've seen a lot of that is being a facilitator like, are you working with clients who are sort of, you know, maybe Dave at that point you talked about in the beginning, like kind of on that on that. Bring in the beginning and we've got to transform. We've got to go to the cloud. How do you kind of help? Maybe facilitate their adoption of public health services like AWS with the technologies that the off first? >>Yeah, I'd say it's really two things everyone wants to say, Hey, we're disrupting the market. We're changing everything about the world around us. You should come with us. Being actually is a very different approach to this one is we provide stability through the disruption around you. So as your business is changing and evolving and you're going through digital transformation, we can give you the stability through that and not only the stability through that change, but we can help in that change. And what I mean by that is if you have a customer who's been on premises and running the workloads on premises for a long while, and maybe they've been sending their backups and deaths three and flagging that impute ability. But maybe now they want to actually migrate the workloads into E. C to weaken. Do that. It's a It's a three step three clicks and workflow to hit a button and say send it up into Easy to. And then once it's in AWS, we can protect the workload when it's there. So we don't just give the stability in this changing environment around us. But we actually help customers go through that transformation and help them move the workloads to the most appropriate business location for them. >>And how does that Danny contending with you from a cost optimization perspective? Of course, we always talk about cost as a factor. Um, I'm going to the cloud. How does that a facilitator of, like, being able to move some of those workloads like attitude that you talked about? Is that a facilitator of cost optimization? Lower tco? I would imagine at some point Yes, >>Yes, it is. So I have this saying the cloud is not a charity right there later in margin, and often people don't understand necessarily what it's going to cost them. So one of the fundamental things that we've had in being back up for a W s since the very beginning since version one is we give cost forecasting and it's not just a rudimentary cost forecasting. We look at the storage we looked compute. We looked at the networking. We look at what all of the different factors that go into a policy, and we will tell them in advance what it's going to cost. That way you don't end up in a position where you're paying a lot more than you expected to pay. And so giving that transparency, giving the the visibility into what the costs of the cloud migration and adoption are going to be is a critical motivator for customers actually to use our software. >>Awesome. And Dave, I'm curious if we look at some of the things trends wise that have gone on, what are you seeing? I t folks in terms of work from home, the remote workers, but I am imagine they're getting their hands on this. But do you expect that a good amount of certain types of folks from industries won't go back into the office because I ts realizing, like more cost optimization? Zor Hey, we don't need to be on site because we can leverage cloud capabilities. >>Yeah, I think it works, actually, in both directions least, I think we'll see employees continue to work remotely, so the notion of skyscrapers being filled with tens of thousands of people, you know, knowledge workers, as they were once called back in the day. That may not come to pass at least any time soon. But conversely to your point everybody getting back into the data center, you know, from a business perspective, the vast majorities of CEO so they don't wanna be in the real estate business. They don't wanna be in the brick and mortar and the power cooling the facilities business. So >>that was >>a trend that was already directionally happening. And just as an accelerant, I think 2000 and 20 and probably 2021 at least the first half just continues that trend. >>Yeah, Silicon Valley is a bit lonely. The freeways there certainly emptier, which is one thing. But it is. It's one of those things that you think you could be now granted folks that worked from home regardless of the functions they were in before. It's not the same. I think we all know that it's not the same working from home during a pandemic when there's just so much more going on. But at the same time, I think businesses are realizing where they can actually get more cost optimization. Since you point not wanting to manage real estate, big data centers, things like that, that may be a ah, positive spin on what this situation has demonstrated. Daddy Last question to you. I always loved it to hear about successful customers. Talk to me about one of your favorite reference customers that really just articulates beams value, especially in this time of helping customers with so many pivots. >>Well, the whole concept of digital transformation is clearly coming to the forefront with the pandemic. And so one of my favorite customers, for example, ducks unlimited up in Canada. They have i ot sensors where they're collecting data about about climate information. They put it into a repository and they keep it for 60 years. Why 60 years? Because who knows? Over the next 60 years, when these sensors in the data they're collecting may be able to solve problems like climate change. But if you >>look at it >>a broader sense, take that same concept of collection of data. I think we're in a fantastic period right now where things like Callum medicine. Um, in the past, >>it was >>kind of in a slow roll remote education and training was on kind of a slow roll. Climate change. Slow roll. Um, but now the pandemics accelerating. Ah, lot of that. Another customer, Royal Dutch Shell, for example. Traditionally in the oil and petrochemical industry, their now taking the data that they have, they're going through this transformation faster than ever before and saying, How do I move to sustainable energy? And so a lot of people look at 2020 and say, I want how does this year? Or, you know, this is not the transformation I want. I actually take the reverse of that. The customers that we have right now are taking the data sets that they have, and they're actually optimizing for a more sustainable future, a better future for us and for our Children. And I think that's a fantastic thing, and being obviously helps in that transformation. >>That's excellent. And I agree with you, Danny, you know, the necessity is the mother of invention. And sometimes when all of these challenges air exposed, it's hard right away to see what are the what are the positives right? What are the opportunities? But from a business perspective is you guys were talking about the beginning of our segment, you know, in the beginning was keeping the lights on. Well, now we've got to get from keeping the lights on, too. Surviving to pivoting well to thriving. So that hopefully 2021 this is good as everybody hopes it's going to be. Right, Dave? >>Yeah, absolutely. It's all data driven and you're right. We have to move from keep the lights up on going the operational aspect to growing the business in new ways and ideally transforming the business in new ways. And you can see we hit on digital transformation a number of times. Why? Because its data driven, Why do we intercept that with being well? Because if it's important to you, it's probably backed up and held for long term safekeeping. So we want to be able to better leverage the data like Danny mentioned with Ducks Unlimited. >>And of course, as we know, data volumes are only growing. So next time you're on day, you have to play us out with one of your guitars. Deal >>definitely, definitely will. >>Excellent for Dave Russell and Danny Allen. I'm Lisa Martin. Guys, thank you so much for joining. You're watching the Cube