>>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 Ignite 22, brought to you by Palo Alto Networks. >>Welcome back everyone. We're so glad that you're still with us. It's the Cube Live at the MGM Grand. This is our second day of coverage of Palo Alto Networks Ignite. This is takeaways from Ignite 22. Lisa Martin here with two really smart guys, Dave Valante. Dave, we're joined by one of our cube alumni, a friend, a friend of the, we say friend of the Cube. >>Yeah, otc. A friend of the Cube >>Karala joined us. Guys, it's great to have you here. It's been an exciting show. A lot of cybersecurity is one of my favorite topics to talk about. But I'd love to get some of the big takeaways from both of you. Dave, we'll start with you. >>A breathing room from two weeks ago. Yeah, that was, that was really pleasant. You know, I mean, I know was, yes, you sat in the analyst program, interested in what your takeaways were from there. But, you know, coming into this, we wrote a piece, Palo Alto's Gold Standard, what they need to do to, to keep that, that status. And we hear it a lot about consolidation. That's their big theme now, which is timely, right? Cause people wanna save money, they wanna do more with less. But I'm really interested in hearing zeus's thoughts on how that's playing in the market. How customers, how easy is it to just say, oh, hey, I'm gonna consolidate. I wanna get into that a little bit with you, how well the strategy's working. We're gonna get into some of the m and a activity and really bring your perspectives to the table. Well, >>It's, it's not easy. I mean, people have been calling for the consolidation of security for decades, and it's, it's, they're the first company that's actually made it happen. Right? And, and I think this is what we're seeing here is the culmination of this long term strategy, this company trying to build more of a platform. And they, you know, they, they came out as a firewall vendor. And I think it's safe to say they're more than firewall today. That's only about two thirds of their revenue now. So down from 80% a few years ago. And when I think of what Palo Alto has become, they're really a data company. Now, if you look at, you know, unit 42 in Cortex, the, the, the Cortex Data Lake, they've done an excellent job of taking telemetry from their products and from the acquisitions they have, right? And bringing that together into one big data lake. >>And then they're able to use that to, to do faster threat notification, forensics, things like that. And so I think the old model of security of create signatures for known threats, it's safe to say it never really worked and it wasn't ever gonna work. You had too many day zero exploits and things. The only way to fight security today is with a AI and ML based analytics. And they have, they're the gold standard. I think the one thing about your post that I would add the gold standard from a data standpoint, and that's given them this competitive advantage to go out and become a platform for a security. Which, like I said, the people have tried to do that for years. And the first one that's actually done it, well, >>We've heard this from some of the startups, like Lacework will say, oh, we treat security as a data problem. Of course there's a startup, Palo Alto's got, you know, whatever, 10, 15 years of, of, of history. But one of the things I wanted to explore with you coming into this was the notion of can you be best of breed and develop a suite? And we, we've been hearing a consistent answer to that question, which is, and, and do you need to, and the answer is, well, best of breed in security requires that full spectrum, that full view. So here's my question to you. So, okay, let's take Esty win relatively new for these guys, right? Yeah. Okay. And >>And one of the few products are not top two, top three in, right? Exactly. >>Yeah. So that's why I want to take that. Yeah. Because in bakeoffs, they're gonna lose on a head-to-head best of breed. And so the customer's gonna say, Hey, you know, I love your, your consolidation play, your esty win's. Just, okay, how about a little discount on that? And you know, these guys are premium priced. Yes. So, you know, are they in essentially through their pricing strategies, sort of creating that stuff, fighting that, is that friction for them where they've got, you know, the customer says, all right, well forget it, we're gonna go stove pipe with the SD WAN will consolidate some of the stuff. Are you seeing that? >>Yeah, I, I, I still think the sales model is that way. And I think that's something they need to work on changing. If they get into a situation where they have to get down into a feature battle of my SD WAN versus your SD wan, my firewall versus your firewall, frankly they've already lost, you know, because their value prop is the suite and, and is the platform. And I was talking to the CISO here that told me, he realizes now that you don't need best of breed everywhere to have best in class threat protection. In fact, best of breed everywhere leads to suboptimal threat protection. Cuz you have all these data data sets that are in silos, right? And so from a data scientist standpoint, right, there's the good data leads to good insights. Well, partial data leads to fragmented insights and that's, that's what the best, best of breed approach gives you. And so I was talking with Palo about this, can they have this vision of being best of breed and platform? I don't really think you can maintain best of breed everywhere across this portfolio this big, but you don't need to. >>That was my second point of my >>Question. That's the point. >>Yeah. And so, cuz cuz because you know, we've talked about this, that that sweets always win in the long run, >>Sweets >>Win. Yeah. But here's the thing, I, I wonder to your your point about, you know, the customer, you know, understanding that that that, that this resonates with them. I, my guess is a lot of customers, you know, at that mid-level and the fat middle are like still sort of wed, you know, hugging that, that tool. So there's, there's work to be done here, but I think they, they, they got it right Because if they devolve, to your point, if they devolve down to that speeds and feeds, eh, what's the point of that? Where's their valuable? >>You do not wanna get into a knife fight. And I, and I, and I think for them the, a big challenge now is convincing customers that the suite, the suite approach does work. And they have to be able to do that in actual customer examples. And so, you know, I I interviewed a bunch of customers here and the ones that have bought into XDR and xor and even are looking at their sim have told me that the, the, so think of soc operations, the old way heavily manually oriented, right? You have multiple panes of glass and you know, and then you've got, so there's a lot of people work before you bring the tools in, right? If done correctly with AI and ml, the machines would do all the heavy lifting and then you'd bring people in at the end to clean up the little bits that were missed, right? >>And so you, you moved to, from something that was very people heavy to something that's machine heavy and machines can work a lot faster than people. And the, and so the ones that I've talked that have, that have done that have said, look, our engineers have moved on to a lot different things. They're doing penetration testing, they're, you know, helping us with, with strategy and they're not fighting that, that daily fight of looking through log files. And the only proof point you need, Dave, is look at every big breach that we've had over the last five years. There's some SIM vendor up there that says, we caught it. Yeah. >>Yeah. We we had the data. >>Yeah. But, but, but the security team missed it. Well they missed it because you're, nobody can look at that much data manually. And so the, I I think their approach of relying heavily on machines to fight the fight is actually the right way. >>Is that a differentiator for them versus, we were talking before we went live that you and I first hit our very first segment back in 2017 at Fort Net. Is that, where do the two stand in your >>Yeah, it's funny cuz if you talk to the two vendors, they don't really see each other in a lot of accounts because Fort Net's more small market mid-market. It's the same strategy to some degree where Fort Net relies heavily on in-house development and Palo Alto relies heavily on acquisition. Yeah. And so I think from a consistently feature set, you know, Fort Net has an advantage there because it, it's all run off their, their their silicon. Where, where Palo's able to innovate very quickly. The, it it requires a lot of work right? To, to bring the front end and back ends together. But they're serving different markets. So >>Do you see that as a differentiator? The integration strategy that Palo Alto has as a differentiator? We talk to so many companies who have an a strong m and a strategy and, and execution arm. But the challenge is always integrating the technology so that the customer to, you know, ultimately it's the customer. >>I actually think they're, they're underrated as a, an acquirer. In fact, Dave wrote a post to a prior on Silicon Angle prior to Accelerate and he, he on, you put it on Twitter and you asked people to rank 'em as an acquirer and they were in the middle of the pack, >>Right? It was, it was. So it was Oracle, VMware, emc, ibm, Cisco, ServiceNow, and Palo Alto. Yeah. Or Oracle got very high marks. It was like 8.5 out of, you know, 10. Yeah. VMware I think was 6.5. Nice. Era was high emc, big range. IBM five to seven. Cisco was three to eight. Yeah. Yeah, right. ServiceNow was a seven. And then, yeah, Palo Alto was like a five. And I, which I think it was unfair. >>Well, and I think it depends on how you look at it. And I, so I think a lot of the acquisitions Palo Altos made, they've done a good job of integrating their backend data and they've almost ignored the front end. And so when you buy some of the products, it's a little clunky today. You know, if you work with Prisma Cloud, it could be a little bit cleaner. And even with, you know, the SD wan that took 'em a long time to bring CloudGenix in and stuff. But I think the approach is right. I don't, I don't necessarily believe you should integrate the front end until you've integrated the back end. >>That's >>The hard part, right? Because UL ultimately what you're gonna get, you're gonna get two panes of glass and one pane of glass and it might look pretty all mush together, but ultimately you're not solving the bigger problem, right. Of, of being able to create that big data like the, the fight security. And so I think, you know, the approach they've taken is the right one. I think from a user standpoint, maybe it doesn't show up as neatly because you don't see the frontend integration, but the way they're doing it is the right way to do it. And I'm glad they're doing it that way versus caving to the pressures of what, you know, the industry might want >>Showed up in the performance of the company. I mean, this company was basically gonna double revenues to 7 billion from 2020 to >>2023. Three. Think about that at that, that >>Make a, that's unbelievable, right? I mean, and then and they wanna double again. Yeah. You know, so, well >>What did, what did Nikesh was quoted as saying they wanna be the first cyber company that's a hundred billion dollars. He didn't give a timeline market cap. >>Right. >>Market cap, right. Do what I wanna get both of your opinions on what you saw and heard and felt this week. What do you think the likelihood is? And and do you have any projections on how, you know, how many years it's gonna take for them to get there? >>Well, >>Well I think so if they're gonna get that big, right? And, and we were talking about this pre-show, any company that's becoming a big company does it through ecosystem >>Bingo. >>Right? And that when you look around the show floor, it's not that impressive. And if that, if there's an area they need to focus on, it's building that ecosystem. And it's not with other security vendors, it's with application vendors and it's with the cloud companies and stuff. And they've got some relationships there, but they need to do more. I actually challenge 'em on that. One of the analyst sessions. They said, look, we've got 800 cortex partners. Well where are they? Right? Why isn't there a cortex stand here with a bunch of the small companies here? So I do think that that is an area they need to focus on. If they are gonna get to that, that market caps number, they will do so do so through ecosystem. Because every company that's achieved that has done it through ecosystem. >>A hundred percent agree. And you know, if you look at CrowdStrike's ecosystem, it's pretty similar. Yeah. You know, it doesn't really, you know, make much, much, not much different from this, but I went back and just looked at some, you know, peak valuations during the pandemic and shortly thereafter CrowdStrike was 70 billion. You know, that's what their roughly their peak Palo Alto was 56, fortune was 59 for the actually diverged. Right. And now Palo Alto has taken the, the top mantle, you know, today it's market cap's 52. So it's held 93% of its peak value. Everybody else is tanking. Even Okta was 45 billion. It's been crushed as you well know. But, so Palo Alto wasn't always, you know, the number one in terms of market cap. But I guess my point is, look, if CrowdStrike could got to 70 billion during Yeah. During the frenzy, I think it's gonna take, to answer your question, I think it's gonna be five years. Okay. Before they get back there. I think this market's gonna be tough for a while from a valuation standpoint. I think generally tech is gonna kind of go up and down and sideways for a good year and a half, maybe even two years could be even longer. And then I think there's gonna be some next wave of productivity innovation that that hits. And then you're gonna, you're almost always gonna exceed the previous highs. It's gonna take a while. Yeah, >>Yeah, yeah. But I think their ability to disrupt the SIM market actually is something I, I believe they're gonna do. I've been calling for the death of the sim for a long time and I know some people at Palo Alto are very cautious about saying that cuz the Splunks and the, you know, they're, they're their partners. But I, I think the, you know, it's what I said before, the, the tools are catching them, but they're, it's not in a way that's useful for the IT pro and, but I, I don't think the SIM vendors have that ecosystem of insight across network cloud endpoint. Right. Which is what you need in order to make a sim useful. >>CISO at an ETR roundtable said, if, if it weren't for my regulators, I would chuck my sim. >>Yes. >>But that's the only reason that, that this person was keeping it. So, >>Yeah. And I think the, the fact that most of those companies have moved to a perpetual MO or a a recurring revenue model actually helps unseat them. Typically when you pour a bunch of money into something, you remember the old computer associate days, nobody ever took it out cuz the sunk dollars you spent to do it. But now that you're paying an annual recurring fee, it's actually makes it easier to take out. So >>Yeah, it's it's an ebb and flow, right? Yeah. Because the maintenance costs were, you know, relatively low. Maybe it was 20% of the total. And then, you know, once every five years you had to do a refresh and you were still locked into the sort of maintenance and, and so yeah, I think you're right. The switching costs with sas, you know, in theory anyway, should be less >>Yeah. As long as you can migrate the data over. And I think they've got a pretty good handle on that. So, >>Yeah. So guys, I wanna get your perspective as a whole bunch of announcements here. We've only been here for a couple days, not a big conference as, as you can see from behind us. What Zs in your opinion was Palo Alto's main message and and what do you think about it main message at this event? And then same question for you. >>Yeah, I, I think their message largely wrapped around disruption, right? And, and they, in The's keynote already talked about that, right? And where they disrupted the firewall market by creating a NextGen firewall. In fact, if you look at all the new services they added to their firewall, you, you could almost say it's a NextGen NextGen firewall. But, but I do think the, the work they've done in the area of cloud and cortex actually I think is, is pretty impressive. And I think that's the, the SOC is ripe for disruption because it's for, for the most part, most socks still, you know, run off legacy playbooks. They run off legacy, you know, forensic models and things and they don't work. It's why we have so many breaches today. The, the dirty little secret that nobody ever wants to talk about is the bad guys are using machine learning, right? And so if you're using a signature based model, all they're do is tweak their model a little bit and it becomes, it bypasses them. So I, I think the only way to fight the the bad guys today is with you gotta fight fire with fire. And I think that's, that's the path they've, they've headed >>Down and the bad guys are hiding in plain sight, you know? >>Yeah, yeah. Well it's, it's not hard to do now with a lot of those legacy tools. So >>I think, I think for me, you know, the stat that we threw out earlier, I think yesterday at our keynote analysis was, you know, the ETR data shows that are, that are that last survey around 35% of the respondents said we are actively consolidating, sorry, 44%, sorry, 35 says we're actively consolidating vendors, redundant vendors today. That number's up to 44%. Yeah. It's by far the number one cost optimization technique. That's what these guys are pitching. And I think it's gonna resonate with people and, and I think to your point, they're integrating at the backend, their beeps are technical, right? I mean, they can deal with that complexity. Yeah. And so they don't need eye candy. Eventually they, they, they want to have that cuz it'll allow 'em to have deeper market penetration and make people more productive. But you know, that consolidation message came through loud and clear. >>Yeah. The big change in this industry too is all the new startups are all cloud native, right? They're all built on Amazon or Google or whatever. Yeah. And when your cloud native and you buy a cloud native integration is fast. It's not like having to integrate this big monolithic software stack anymore. Right. So I I think their pace of integration will only accelerate from here because everything's now cloud native. >>If a customer comes to you or when a customer comes to you and says, Zs help us with this cyber transformation we have, our board isn't necessarily with our executives in terms of execution of a security strategy. How do you advise them where Palo Alto is concerned? >>Yeah. You know, a lot, a lot of this is just fighting legacy mindset. And I've, I was talking with some CISOs here from state and local governments and things and they're, you know, they can't get more budget. They're fighting the tide. But what they did find is through the use of automation technology, they're able to bring their people costs way down. Right. And then be able to use that budget to invest in a lot of new projects. And so with that, you, you have to start with your biggest pain points, apply automation where you can, and then be able to use that budget to reinvest back in your security strategy. And it's good for the IT pros too, the security pros, my advice to, to it pros is if you're doing things today that aren't resume building, stop doing them. Right? Find a way to automate the money your job. And so if you're patching systems and you're looking through log files, there's no reason machines can't do that. And you go do something a lot more interesting. >>So true. It's like storage guys 10 years ago, provisioning loans. Yes. It's like, stop doing that. Yeah. You're gonna be outta a job. And so who, last question I have is, is who do you see as the big competitors, the horses on the track question, right? So obviously Cisco kind of service has led for a while and you know, big portfolio company, CrowdStrike coming at it from end point. You know who, who, who do you see as the real players going for that? You know, right now the market's three to 4%. The leader has three, three 4% of the market. You know who they're all going for? 10, 15, maybe 20% of the market. Who, who are the likely candidates? Yeah, >>I don't know if CrowdStrike really has the breadth of portfolio to compete long term though. I I think they've had a nice run, but I, we might start to see the follow 'em. I think Microsoft is gonna be for middle. They've laid down the gauntlet, right? They are a security vendor, right? We, we were at Reinvent and a AWS is the platform for security vendors. Yes. Middle, somewhere in the middle. But Microsoft make no mistake, they're in security. They've got some good products. I think a lot of 'em are kind of good enough and they, they tie it to the licensing and I'm not sure that works in security, but they've certainly got the ear of a lot of it pros. >>It might work in smb. >>Yeah. Yeah. It, it might. And, and I do like Zscaler. I, I know these guys poo poo the proxy model, but they've, they've done about as much with proxies as you can. And I, I think it's, it's a battle of, I love the, the, the near, you know, proxies are dead and Jay's model, you know, Jay over at c skater throw 'em back at 'em. So I, it's good to see that kind of fight going on between the two. >>Oh, it's great. Well, and, and again, ZScaler's coming at it from their cloud security angle. CrowdStrike's coming at it from endpoint. I, I do think CrowdStrike has an opportunity to build out the portfolio through m and a and maybe ecosystem. And then obviously, you know, Palo Alto's getting it done. How about Cisco? >>Yeah. Cisco's interesting. And I, I think if Cisco can make the network matter in security and it should, right? We're talking about how a lot of you need a lot of forensics to fight security today. Well, they're gonna see things long before anybody else because they have all that network data. If they can tie network security, I, I mean they could really have that business take off. But we've been saying that about Cisco for 20 years. >>But big install based though. Yeah. It's hard for a company, any company to just say, okay, hey Cisco customer sweep the floor and come with us. That's, that's >>A tough thing. They have a lot of good peace parts, right? And like duo's a good product and umbrella's a good product. They've, they've not done a good job. >>They're the opposite of these guys. >>They've not done a good job of the backend integration that, that's where Cisco needs to, to focus. And I do think g G two Patel there fixed the WebEx group and I think he's now, in fact when you talk to him, he's doing very little on WebEx that that group's running itself and he's more focused in security. So I, I think we could see a resurgence there. But you know, they have a, from a revenue perspective, it's a little misleading cuz they have this big legacy base that's in decline while they're moving to cloud and stuff. So, but they, but they, there's a lot of work there're trying to, to tie to network. >>Right. Lots of fuel for conversation. We're gonna have to carry this on, on Silicon angle.com guys. Yes. And Wikibon, lets do see us. Thank you so much for joining Dave and me giving us your insights as to this event. Where are you gonna be next? Are you gonna be on vacation? >>There's nothing more fun than mean on the cube, so, right. What's outside of that though? Yeah, you know, Christmas coming up, I gotta go see family and do the obligatory, although for me that's a lot of travel, so I guess >>More planes. Yeah. >>Hopefully not in Vegas. >>Not in Vegas. >>Awesome. Nothing against Vegas. Yeah, no, >>We love it. We >>Love it. Although I will say my year started off with ces. Yeah. And it's finishing up with Palo Alto here. The bookends. Yeah, exactly. In Vegas bookends. >>Well thanks so much for joining us. Thank you Dave. Always a pleasure to host a show with you and hear your insights. Reading your breaking analysis always kicks off my prep for show and it's always great to see, but predictions come true. So thank you for being my co-host bet. All right. For Dave Valante Enz as Carla, I'm Lisa Martin. You've been watching The Cube, the leader in live, emerging and enterprise tech coverage. Thanks for watching.

>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Welcome back everyone. We're so glad that you're still with us. It's the Cube Live at the MGM Grand. This is our second day of coverage of Palo Alto Networks Ignite. This is takeaways from Ignite 22. Lisa Martin here with two really smart guys, Dave Valante. Dave, we're joined by one of our cube alumni, a friend, a friend of the, we say friend of the Cube. >>Yeah, F otc. A friend of the Cube >>Karala joins us. Guys, it's great to have you here. It's been an exciting show. A lot of cybersecurity is one of my favorite topics to talk about. But I'd love to get some of the big takeaways from both of you. Dave, we'll start with >>You. A breathing room from two weeks ago. Yeah, that was, that was really pleasant. You know, I mean, I know was, yes, you sat in the analyst program, interested in what your takeaways were from there. But, you know, coming into this, we wrote a piece, Palo Alto's Gold Standard, what they need to do to, to keep that, that status. And we hear it a lot about consolidation. That's their big theme now, which is timely, right? Cause people wanna save money, they wanna do more with less. But I'm really interested in hearing zeus's thoughts on how that's playing in the market. How customers, how easy is it to just say, oh, hey, I'm gonna consolidate. I wanna get into that a little bit with you, how well the strategy's working. We're gonna get into some of the m and a activity and really bring your perspectives to the table. Well, >>It's, it's not easy. I mean, people have been calling for the consolidation of security for decades, and it's, it's, they're the first company that's actually made it happen. Right? And, and I think this is what we're seeing here is the culmination of this long-term strategy, this company trying to build more of a platform. And they, you know, they, they came out as a firewall vendor. And I think it's safe to say they're more than firewall today. That's only about two thirds of their revenue now. So down from 80% a few years ago. And when I think of what Palo Alto has become, they're really a data company. Now, if you look at, you know, unit 42 in Cortex, the, the, the Cortex Data Lake, they've done an excellent job of taking telemetry from their products and from the acquisitions they have, right? And bringing that together into one big data lake. >>And then they're able to use that to, to do faster threat notification, forensics, things like that. And so I think the old model of security of create signatures for known threats, it's safe to say it never really worked and it wasn't ever gonna work. You had too many days, zero exploits and things. The only way to fight security today is with a AI and ML based analytics. And they have, they're the gold standard. I think the one thing about your post that I would add, they're the gold standard from a data standpoint. And that's given them this competitive advantage to go out and become a platform for security. Which, like I said, the people have tried to do that for years. And the first one that's actually done it, well, >>We've heard this from some of the startups, like Lacework will say, oh, we treat security as a data problem. Of course there's a startup, Palo Alto's got, you know, whatever, 10, 15 years of, of, of history. But one of the things I wanted to explore with you coming into this was the notion of can you be best of breed and develop a suite? And we, we've been hearing a consistent answer to that question, which is, and, and do you need to, and the answer is, well, best of breed in security requires that full spectrum, that full view. So here's my question to you. So, okay, let's take Estee win relatively new for these guys, right? Yeah. Okay. And >>And one of the few products are not top two, top three in, right? >>Exactly. Yeah. So that's why I want to take that. Yeah. Because in bakeoffs, they're gonna lose on a head-to-head best of breed. And so the customer's gonna say, Hey, you know, I love your, your consolidation play, your esty win's. Just, okay, how about a little discount on that? And you know, these guys are premium priced. Yes. So, you know, are they in essentially through their pricing strategies, sort of creating that stuff, fighting that, is that friction for them where they've got, you know, the customer says, all right, well forget it, we're gonna go stove pipe with the SD WAN will consolidate some of the stuff. Are you seeing that? >>Yeah, I, I, I still think the sales model is that way. And I think that's something they need to work on changing. If they get into a situation where they have to get down into a feature battle of my SD WAN versus your SD wan, my firewall versus your firewall, frankly they've already lost, you know, because their value prop is the suite and, and is the platform. And I was talking with the CISO here that told me, he realizes now that you don't need best of breed everywhere to have best in class threat protection. In fact, best of breed everywhere leads to suboptimal threat protection. Cuz you have all these data data sets that are in silos, right? And so from a data scientist standpoint, right, there's the good data leads to good insights. Well, partial data leads to fragmented insights and that's, that's what the best, best of breed approach gives you. And so I was talking with Palo about this, can they have this vision of being best of breed and platform? I don't really think you can maintain best of breed everywhere across this portfolio this big, but you don't need to. >>That was my second point of my question. That's the point I'm saying. Yeah. And so, cuz cuz because you know, we've talked about this, that that sweets always win in the long run, >>Sweets win. >>Yeah. But here's the thing, I, I wonder to your your point about, you know, the customer, you know, understanding that that that, that this resonates with them. I, my guess is a lot of customers, you know, at that mid-level and the fat middle are like still sort of wed, you know, hugging that, that tool. So there's, there's work to be done here, but I think they, they, they got it right Because if they devolve, to your point, if they devolve down to that speeds and feeds, eh, what's the point of that? Where's their >>Valuable? You do not wanna get into a knife fight. And I, and I, and I think for them the, a big challenge now is convincing customers that the suite, the suite approach does work. And they have to be able to do that in actual customer examples. And so, you know, I I interviewed a bunch of customers here and the ones that have bought into XDR and xor and even are looking at their sim have told me that the, the, so think of soc operations, the old way heavily manually oriented, right? You have multiple panes of glass and you know, and then you've got, so there's a lot of people work before you bring the tools in, right? If done correctly with AI and ml, the machines would do all the heavy lifting and then you'd bring people in at the end to clean up the little bits that were missed, right? >>And so you, you moved to, from something that was very people heavy to something that's machine heavy and machines can work a lot faster than people. And the, and so the ones that I've talked that have, that have done that have said, look, our engineers have moved on to a lot different things. They're doing penetration testing, they're, you know, helping us with, with strategy and they're not fighting that, that daily fight of looking through log files. And the only proof point you need, Dave, is look at every big breach that we've had over the last five years. There's some SIM vendor up there that says, we caught it. Yeah. >>Yeah. We we had the data. >>Yeah. But, but, but the security team missed it. Well they missed it because you're, nobody can look at that much data manually. And so the, I I think their approach of relying heavily on machines to fight the fight is actually the right way. >>Is that a differentiator for them versus, we were talking before we went live that you and I first hit our very first segment back in 2017 at Fort Net. Is that, where do the two stand in your >>Yeah, it's funny cuz if you talk to the two vendors, they don't really see each other in a lot of accounts because Fort Net's more small market mid-market. It's the same strategy to some degree where Fort Net relies heavily on in-house development in Palo Alto relies heavily on acquisition. Yeah. And so I think from a consistently feature set, you know, Fort Net has an advantage there because it, it's all run off their, their their silicon. Where, where Palo's able to innovate very quickly. The, it it requires a lot of work right? To, to bring the front end and back ends together. But they're serving different markets. So >>Do you see that as a differentiator? The integration strategy that Palo Alto has as a differentiator? We talk to so many companies who have an a strong m and a strategy and, and execution arm. But the challenge is always integrating the technology so that the customer to, you know, ultimately it's the customer. >>I actually think they're, they're underrated as a, an acquirer. In fact, Dave wrote a post to a prior on Silicon Angle prior to Accelerate and he, he on, you put it on Twitter and you asked people to rank 'em as an acquirer and they were in the middle of the pack, >>Right? It was, it was. So it was Oracle, VMware, emc, ibm, Cisco, ServiceNow, and Palo Alto. Yeah. Or Oracle got very high marks. It was like 8.5 out of, you know, 10. Yeah. VMware I think was 6.5. Naira was high emc, big range. IBM five to seven. Cisco was three to eight. Yeah. Yeah, right. ServiceNow was a seven. And then, yeah, Palo Alto was like a five. And I, which I think it was unfair. Well, >>And I think it depends on how you look at it. And I, so I think a lot of the acquisitions Palo Alto's made, they've done a good job of integrating the backend data and they've almost ignored the front end. And so when you buy some of the products, it's a little clunky today. You know, if you work with Prisma Cloud, it could be a little bit cleaner. And even with, you know, the SD wan that took 'em a long time to bring CloudGenix in and stuff. But I think the approach is right. I don't, I don't necessarily believe you should integrate the front end until you've integrated the back end. >>That's >>The hard part, right? Because UL ultimately what you're gonna get, you're gonna get two panes of glass and one pane of glass and it might look pretty and all mush together, but ultimately you're not solving the bigger problem, right. Of, of being able to create that big data lake to, to fight security. And so I think, you know, the approach they've taken is the right one. I think from a user standpoint, maybe it doesn't show up as neatly because you don't see the frontend integration, but the way they're doing it is the right way to do it. And I'm glad they're doing it that way versus caving to the pressures of what, you know, the industry might want or >>Showed up in the performance of the company. I mean, this company was basically gonna double revenues to 7 billion from 2020 to >>2023. Think about that at that. That makes, >>I mean that's unbelievable, right? I mean, and then and they wanna double again. Yeah. You know, so, well >>What did, what did Nikesh was quoted as saying they wanna be the first cyber company that's a hundred billion dollars. He didn't give a timeline market >>Cap. Right. >>Market cap, right. Do what I wanna get both of your opinions on what you saw and heard and felt this week. What do you think the likelihood is? And and do you have any projections on how, you know, how many years it's gonna take for them to get there? >>Well, >>Well I think so if they're gonna get that big, right? And, and we were talking about this pre-show, any company that's becoming a big company does it through ecosystem >>Bingo >>Go, right? And that when you look around the show floor, it's not that impressive. No. And if that, if there's an area they need to focus on, it's building that ecosystem. And it's not with other security vendors, it's with application vendors and it's with the cloud companies and stuff. And they've got some relationships there, but they need to do more. I actually challenge 'em on that. One of the analyst sessions. They said, look, we've got 800 cortex partners. Well where are they? Right? Why isn't there a cortex stand here with a bunch of the small companies here? So I do think that that is an area they need to focus on. If they are gonna get to that, that market caps number, they will do so do so through ecosystem. Because every company that's achieved that has done it through ecosystem. >>A hundred percent agree. And you know, if you look at CrowdStrike's ecosystem, it's, I mean, pretty similar. Yeah. You know, it doesn't really, you know, make much, much, not much different from this, but I went back and just looked at some, you know, peak valuations during the pandemic and shortly thereafter CrowdStrike was 70 billion. You know, that's what their roughly their peak Palo Alto was 56, fortune was 59 for the actually diverged. Right. And now Palo Alto has taken the, the top mantle, you know, today it's market cap's 52. So it's held 93% of its peak value. Everybody else is tanking. Even Okta was 45 billion. It's been crushed as you well know. But, so Palo Alto wasn't always, you know, the number one in terms of market cap. But I guess my point is, look, if CrowdStrike could got to 70 billion during Yeah. During the frenzy, I think it's gonna take, to answer your question, I think it's gonna be five years. Okay. Before they get back there. I think this market's gonna be tough for a while from a valuation standpoint. I think generally tech is gonna kind of go up and down and sideways for a good year and a half, maybe even two years could be even longer. And then I think there's gonna be some next wave of productivity innovation that that hits. And then you're gonna, you're almost always gonna exceed the previous highs. It's gonna take a while. Yeah. >>Yeah, yeah. But I think their ability to disrupt the SIM market actually is something that I, I believe they're gonna do. I've been calling for the death of the sim for a long time and I know some people of Palo Alto are very cautious about saying that cuz the Splunks and the, you know, they're, they're their partners. But I, I think the, you know, it's what I said before, the, the tools are catching them, but they're, it's not in a way that's useful for the IT pro and, but I, I don't think the SIM vendors have that ecosystem of insight across network cloud endpoint. Right. Which is what you need in order to make a sim useful. >>CISO at an ETR round table said, if, if it weren't for my regulators, I would chuck my sim. >>Yes. >>But that's the only reason that, that this person was keeping it. No. >>Yeah. And I think the, the fact that most of those companies have moved to a perpetual MO or a a recurring revenue model actually helps unseat them. Typically when you pour a bunch of money into something, you remember the old computer associate says nobody ever took it out cuz the sunk dollars you spent to do it. But now that you're paying an annual recurring fee, it's actually makes it easier to take out. So >>Yeah, it's just an ebb and flow, right? Yeah. Because the maintenance costs were, you know, relatively low. Maybe it was 20% of the total. And then, you know, once every five years you had to do a refresh and you were still locked into the sort of maintenance and, and so yeah, I think you're right. The switching costs with sas, you know, in theory anyway, should be less >>Yeah. As long as you can migrate the data over. And I think they've got a pretty good handle on that. So, >>Yeah. So guys, I wanna get your perspective as a whole bunch of announcements here. We've only been here for a couple days, not a big conference as, as you can see from behind us. What Zs in your opinion was Palo Alto's main message and and what do you think about it main message at this event? And then same question for you. >>Yeah, I, I think their message largely wrapped around disruption, right? And, and they, and The's keynote already talked about that, right? And where they disrupted the firewall market by creating a NextGen firewall. In fact, if you look at all the new services they added to their firewall, you, you could almost say it's a NextGen NextGen firewall. But, but I do think the, the work they've done in the area of cloud and cortex actually I think is, is pretty impressive. And I think that's the, the SOC is ripe for disruption because it's for, for the most part, most socks still, you know, run off legacy playbooks. They run off legacy, you know, forensic models and things and they don't work. It's why we have so many breaches today. The, the dirty little secret that nobody ever wants to talk about is the bad guys are using machine learning, right? And so if you're using a signature based model, all they gotta do is tweak their model a little bit and it becomes, it bypasses them. So I, I think the only way to fight the the bad guys today is with you're gonna fight fire with fire. And I think that's, that's the path they've, they've headed >>Down. Yeah. The bad guys are hiding in plain sight, you know? Yeah, >>Yeah. Well it's, it's not hard to do now with a lot of those legacy tools. So >>I think, I think for me, you know, the stat that we threw out earlier, I think yesterday at our keynote analysis was, you know, the ETR data shows that are, that are that last survey around 35% of the respondents said we are actively consolidating, sorry, 44%, sorry, 35 says who are actively consolidating vendors, redundant vendors today that number's up to 44%. Yeah. It's by far the number one cost optimization technique. That's what these guys are pitching. And I think it's gonna resonate with people and, and I think to your point, they're integrating at the backend, their beeps are technical, right? I mean, they can deal with that complexity. Yeah. And so they don't need eye candy. Eventually they, they, they want to have that cuz it'll allow 'em to have deeper market penetration and make people more productive. But you know, that consolidation message came through loud and clear. >>Yeah. The big change in this industry too is all the new startups are all cloud native, right? They're all built on Amazon or Google or whatever. Yeah. And when your cloud native and you buy a cloud native integration is fast. It's not like having to integrate this big monolithic software stack anymore. Right. So I, I think their pace of integration will only accelerate from here because everything's now cloud native. >>If a customer comes to you or when a customer comes to you and says, Zs help us with this cyber transformation we have, our board isn't necessarily aligned with our executives in terms of execution of a security strategy. How do you advise them where Palo Alto is concerned? >>Yeah. You know, a lot, a lot of this is just fighting legacy mindset. And I've, I was talking with some CISOs here from state and local governments and things and they're, you know, they can't get more budget. They're fighting the tide. But what they did find is through the use of automation technology, they're able to bring their people costs way down. Right. And then be able to use that budget to invest in a lot of new projects. And so with that, you, you have to start with your biggest pain points, apply automation where you can, and then be able to use that budget to reinvest back in your security strategy. And it's good for the IT pros too, the security pros, my advice to the IT pros is, is if you're doing things today that aren't resume building, stop doing them. Right. Find a way to automate the money your job. And so if you're patching systems and you're looking through log files, there's no reason machines can't do that. And you go do something a lot more interesting. >>So true. It's like storage guys 10 years ago, provisioning loans. Yes. It's like, stop doing that. Yeah. You're gonna be outta a job. So who, last question I have is, is who do you see as the big competitors, the horses on the track question, right? So obviously Cisco kind of service has led for a while and you know, big portfolio company, CrowdStrike coming at it from end point. You know who, who, who do you see as the real players going for that? You know, right now the market's three to 4%. The leader has three, three 4% of the market. You know who they're all going for? 10, 15, maybe 20% of the market. Who, who are the likely candidates? Yeah, >>I don't know if CrowdStrike really has the breadth of portfolio to compete long term though. I I think they've had a nice run, but I, we might start to see the follow 'em. I think Microsoft is gonna be for middle. They've laid down the gauntlet, right? They are a security vendor, right? We, we were at Reinvent and a AWS is the platform for security vendors. Yes. Middle, somewhere in the middle. But Microsoft make no mistake, they're in security. They've got some good products. I think a lot of 'em are kind of good enough and they, they tie it to the licensing and I'm not sure that works in security, but they've certainly got the ear of a lot of it pros. >>It might work in smb. >>Yeah, yeah. It, it might. And, and I do like Zscaler. I, I know these guys poo poo the proxy model, but they've, they've done about as much with prox as you can. And I, I think it's, it's a battle of, I love the, the, the near, you know, proxies are dead and Jay's model, you know, Jay over at csca, throw 'em back at 'em. So I, it's good to see that kind of fight going on between the >>Two. Oh, it's great. Well, and, and again, ZScaler's coming at it from their cloud security angle. CrowdStrike's coming at it from endpoint. I, I do think CrowdStrike has an opportunity to build out the portfolio through m and a and maybe ecosystem. And then obviously, you know, Palo Alto's getting it done. How about Cisco? >>Yeah, Cisco's interesting. And I I think if Cisco can make the network matter in security and it should, right? We're talking about how a lot of you need a lot of forensics to fight security today. Well, they're gonna see things long before anybody else because they have all that network data. If they can tie network security, I, I mean they could really have that business take off. But we've been saying that about Cisco for 20 years. >>But big install based though. Yeah. It's hard for a company, any company to say, okay, hey Cisco customer sweep the floor and come with us. That's, that's >>A tough thing. They have a lot of good peace parts, right? And like duo's a good product and umbrella's a good product. They've, they've not done a good job. >>They're the opposite of these guys. >>They've not done a good job of the backend integration and that, that's where Cisco needs to, to focus. And I do think g G two Patel there fixed the WebEx group and I think he's now, in fact when you talk to him, he's doing very little on WebEx that that group's running itself and he's more focused in security. So I, I think we could see a resurgence there. But you know, they have a, from a revenue perspective, it's a little misleading cuz they have this big legacy base that's in decline while they're moving to cloud and stuff. So, but they, but they, there's a lot of Rick there trying to, to tie to network. >>Lots of fuel for conversation. We're gonna have to carry this on, on Silicon angle.com guys. Yes. And Wi KeePon. Lets do see us. Thank you so much for joining Dave and me giving us your insights as to this event. Where are gonna be next? Are you gonna be on >>Vacation? There's nothing more fun than mean on the cube. So what's outside of that though? Yeah, you know, Christmas coming up, I gotta go see family and be the obligatory, although for me that's a lot of travel, so I guess >>More planes. Yeah. >>Hopefully not in Vegas. >>Not in Vegas. >>Awesome. Nothing against Vegas. Yeah, no, >>We love it. We love >>It. Although I will say my year started off with ces. Yeah. And it's finishing up with Palo Alto here. The bookends. Yeah, exactly. In Vegas bookends. >>Well thanks so much for joining us. Thank you Dave. Always a pleasure to host a show with you and hear your insights. Reading your breaking analysis always kicks off my prep for show. And it, it's always great to see, but predictions come true. So thank you for being my co-host bet. All right. For Dave Valante Enz as Carla, I'm Lisa Martin. You've been watching The Cube, the leader in live, emerging and enterprise tech coverage. Thanks for watching.

>>In the early part of this century, we're talking about the 2005 to 2007 timeframe. There was a lot of talk about so-called green it. And at that time there was some organizational friction. Like for example, the line was that the CIO never saw the power bill, so he or she didn't care, or that the facilities folks, they rarely talked to the IT department. So it was kind of that split brain. And, and then the oh 7 0 8 financial crisis really created an inflection point in a couple of ways. First, it caused organizations to kind of pump the brakes on it spending, and then they took their eye off the sustainability ball. And the second big trend, of course, was the cloud model, you know, kind of became a benchmark for it. Simplicity and automation and efficiency, the ability to dial down and dial up capacity as needed. >>And the third was by the end of the first decade of the, the two thousands, the technology of virtualization was really hitting its best stride. And then you had innovations like flash storage, which largely eliminated the need for these massive farms of spinning mechanical devices that sucked up a lot of power. And so really these technologies began their march to mainstream adoption. And as we progressed through the 2020s, the effect of climate change really come into focus as a critical component of esg. Environmental, social, and governance. Shareholders have come to demand metrics around sustainability. Employees are often choosing employers based on their ESG posture. And most importantly, companies are finding that savings on power cooling and footprint, it has a bottom line impact on the income statement. Now you add to that the energy challenges around the world, particularly facing Europe right now, the effects of global inflation and even more advanced technologies like machine intelligence. >>And you've got a perfect storm where technology can really provide some relief to organizations. Hello and welcome to the Path to Sustainable It Made Possible by Pure Storage and Collaboration with the Cube. My name is Dave Valante and I'm one of the host of the program, along with my colleague Lisa Martin. Now, today we're gonna hear from three leaders on the sustainability topic. First up, Lisa will talk to Nicole Johnson. She's the head of Social Impact and Sustainability at Pure Storage. Nicole will talk about the results from a study of around a thousand sustainability leaders worldwide, and she'll share some metrics from that study. And then next, Lisa will speak to AJ Singh. He's the Chief Product Officer at Pure Storage. We've had had him on the cube before, and not only will he share some useful stats in the market, I'll also talk about some of the technology innovations that customers can tap to address their energy consumption, not the least of which is ai, which is is entering every aspect of our lives, including how we deal with energy consumption. And then we'll bring it back to our Boston studio and go north of Italy with Mattia Ballero of Elec Informatica, a services provider with deep expertise on the topic of sustainability. We hope you enjoyed the program today. Thanks for watching. Let's get started >>At Pure Storage, the opportunity for change and our commitment to a sustainable future are a direct reflection of the way we've always operated and the values we live by every day. We are making significant and immediate impact worldwide through our environmental sustainability efforts. The milestones of change can be seen everywhere in everything we do. Pure's Evergreen Storage architecture delivers two key environmental benefits to customers, the reduction of wasted energy and the reduction of e-waste. Additionally, Pure's implemented a series of product packaging redesigns, promoting recycled and reuse in order to reduce waste that will not only benefit our customers, but also the environment. Pure is committed to doing what is right and leading the way with innovation. That has always been the pure difference, making a difference by enabling our customers to drive out energy usage and their data storage systems by up to 80%. Today, more than 97% of pure arrays purchased six years ago are still in service. And tomorrow our goal for the future is to reduce Scope three. Emissions Pure is committing to further reducing our sold products emissions by 66% per petabyte by 2030. All of this means what we said at the beginning, change that is simple and that is what it has always been about. Pure has a vision for the future today, tomorrow, forever. >>Hi everyone, welcome to this special event, pure Storage, the Path to Sustainable it. I'm your host, Lisa Martin. Very pleased to be joined by Nicole Johnson, the head of Social Impact and Sustainability at Pure Storage. Nicole, welcome to the Cube. Thanks >>For having me, Lisa. >>Sustainability is such an important topic to talk about and I understand that Pure just announced a report today about sustainability. What can you tell me what nuggets are in this report? >>Well, actually quite a few really interesting nuggets, at least for us. And I, I think probably for you and your viewers as well. So we actually commissioned about a thousand sustainability leaders across the globe to understand, you know, what are their sustainability goals, what are they working on, and what are the impacts of buying decisions, particularly around infrastructure when it comes to sustainable goals. I think one of the things that was really interesting for us was the fact that around the world we did not see a significant variation in terms of sustainability being a top priority. You've, I'm sure you've heard about the energy crisis that's happening across Europe. And so, you know, there was some thought that perhaps that might play into AMEA being a larger, you know, having sustainability goals that were more significant. But we actually did not find that we found sustainability to be really important no matter where the respondents were located. >>So very interesting at Pure sustainability is really at the heart of what we do and has been since our founding. It's interesting because we set out to make storage really simple, but it turns out really simple is also really sustainable. And the products and services that we bring to our customers have really powerful outcomes when it comes to decreasing their, their own carbon footprints. And so, you know, we often hear from customers that we've actually really helped them to significantly improve their storage performance, but also allow them to save on space power and cooling costs and, and their footprint. So really significant findings. One example of that is a company called Cengage, which is a global education technology company. They recently shared with us that they have actually been able to reduce their overall storage footprint by 80% while doubling to tripling the performance of their storage systems. So it's really critical for, for companies who are thinking about their sustainability goals, to consider the dynamic between their sustainability program and their IT teams who are making these buying decisions, >>Right? Those two teams need to be really inextricably linked these days. You talked about the fact that there was really consistency across the regions in terms of sustainability being of high priority for organizations. You had a great customer story that you shared that showed significant impact can be made there by bringing the sustainability both together with it. But I'm wondering why are we seeing that so much of the vendor selection process still isn't revolving around sustainability or it's overlooked? What are some of the things that you received despite so many people saying sustainability, huge priority? >>Well, in this survey, the most commonly cited challenge was really around the fact that there was a lack of management buy-in. 40% of respondents told us this was the top roadblock. So getting, I think getting that out of the way. And then we also just heard that sustainability teams were not brought into tech purchasing processes until after it's already rolling, right? So they're not even looped in. And that being said, you know, we know that it has been identified as one of the key departments to supporting a company sustainability goals. So we, we really want to ensure that these two teams are talking more to each other. When we look even closer at the data from the respondents, we see some really positive correlations. We see that 65% of respondents reported that they're on track to meet their sustainability goals. And the IT of those 65%, it is significantly engaged with reporting data for those sustainability initiatives. We saw that, that for those who did report, the sustainability is a top priority for vendor selection. They were twice as likely to be on track with their goals and their sustainability directors said that they were getting involved at the beginning of the tech purchasing program. Our process, I'm sorry, rather than towards the end. And so, you know, we know that to curb the impact of climate crisis, we really need to embrace sustainability from a cross-functional viewpoint. >>Definitely has to be cross-functional. So, so strong correlations there in the report that organizations that had closer alignment between the sustainability folks and the IT folks were farther along in their sustainability program development, execution, et cetera, those co was correlations, were they a surprise? >>Not entirely. You know, when we look at some of the statistics that come from the, you know, places like the World Economic Forum, they say that digitization generated 4% of greenhouse gas emissions in 2020. So, and that, you know, that's now almost three years ago, digital data only accelerates, and by 2025, we expect that number could be almost double. And so we know that that communication and that correlation is gonna be really important because data centers are taking up such a huge footprint of when companies are looking at their emissions. And it's, I mean, quite frankly, a really interesting opportunity for it to be a trailblazer in the sustainability journey. And, you know, perhaps people that are in IT haven't thought about how they can make an impact in this area, but there really is some incredible ways to help us work on cutting carbon emissions, both from your company's perspective and from the world's perspective, right? >>Like we are, we're all doing this because it's something that we know we have to do to drive down climate change. So I think when you, when you think about how to be a trailblazer, how to do things differently, how to differentiate your own department, it's a really interesting connection that IT and sustainability work together. I would also say, you know, I'll just note that of the respondents to the survey we were discussing, we do over half of those respondents expect to see closer alignment between the organization's IT and sustainability teams as they move forward. >>And that's really a, a tip a hat to those organizations embracing cultural change. That's always hard to do, but for those two, for sustainability in IT to come together as part of really the overall ethos of an organization, that's huge. And it's great to see the data demonstrating that, that those, that alignment, that close alignment is really on its way to helping organizations across industries make a big impact. I wanna dig in a little bit to here's ESG goals. What can you share with us about >>That? Absolutely. So as I mentioned peers kind of at the beginning of our formal ESG journey, but really has been working on the, on the sustainability front for a long time. I would, it's funny as we're, as we're doing a lot of this work and, and kind of building our own profile around this, we're coming back to some of the things that we have done in the past that consumers weren't necessarily interested in then but are now because the world has changed, becoming more and more invested in. So that's exciting. So we did a baseline scope one, two, and three analysis and discovered, interestingly enough that 70% of our emissions comes from use of sold products. So our customers work running our products in their data centers. So we know that we, we've made some ambitious goals around our Scope one and two emissions, which is our own office, our utilities, you know, those, they only account for 6% of our emissions. So we know that to really address the issue of climate change, we need to work on the use of sold products. So we've also made a, a really ambitious commitment to decrease our carbon emissions by 66% per bed per petabyte by 2030 in our product. So decreasing our own carbon footprint, but also affecting our customers as well. And we've also committed to a science-based target initiative and our road mapping how to achieve the ambitious goals set out in the Paris agreement. >>That's fantastic. It sounds like you really dialed in on where is the biggest opportunity for us as Pure Storage to make the biggest impact across our organization, across our customers organizations. There lofty goals that pure set, but knowing what I know about Pure, you guys are probably well on track to, to accomplish those goals in record time, >>I hope So. >>Talk a little bit about advice that you would give to viewers who might be at the very beginning of their sustainability journey and really wondering what are the core elements besides it, sustainability, team alignment that I need to bring into this program to make it actually successful? >>Yeah, so I think, you know, understanding that you don't have to pick between really powerful technology and sustainable technology. There are opportunities to get both and not just in storage right in, in your entire IT portfolio. We know that, you know, we're in a place in the world where we have to look at things from the bigger picture. We have to solve new challenges and we have to approach business a little bit differently. So adopting solutions and services that are environmentally efficient can actually help to scale and deliver more effective and efficient IT solutions over time. So I think that that's something that we need to, to really remind ourselves, right? We have to go about business a little bit differently and that's okay. We also know that data centers utilize an incredible amount of, of energy and, and carbon. And so everything that we can do to drive that down is going to address the sustainability goals for us individually as well as, again, drive down that climate change. So we, we need to get out of the mindset that data centers are, are about reliability or cost, et cetera, and really think about efficiency and carbon footprint when you're making those business decisions. I'll also say that, you know, the earlier that we can get sustainability teams into the conversation, the more impactful your business decisions are going to be and helping you to guide sustainable decision making. >>So shifting sustainability and IT left almost together really shows that the correlation between those folks getting together in the beginning with intention, the report shows and the successes that peers had demonstrate that that's very impactful for organizations to actually be able to implement even the cultural change that's needed for sustainability programs to be successful. My last question for you goes back to that report. You mentioned in there that the data show a lot of organizations are hampered by management buy-in, where sustainability is concerned. How can pure help its customers navigate around those barriers so that they get that management buy-in and they understand that the value in it for >>Them? Yeah, so I mean, I think that for me, my advice is always to speak to hearts and minds, right? And help the management to understand, first of all, the impact right on climate change. So I think that's the kind of hearts piece on the mind piece. I think it's addressing the sustainability goals that these companies have set for themselves and helping management understand how to, you know, how their IT buying decisions can actually really help them to reach these goals. We also, you know, we always run kind of TCOs for customers to understand what is the actual cost of, of the equipment. And so, you know, especially if you're in a, in a location in which energy costs are rising, I mean, I think we're seeing that around the world right now with inflation. Better understanding your energy costs can really help your management to understand the, again, the bigger picture and what that total cost is gonna be. Often we see, you know, that maybe the I the person who's buying the IT equipment isn't the same person who's purchasing, who's paying the, the electricity bills, right? And so sometimes even those two teams aren't talking. And there's a great opportunity there, I think, to just to just, you know, look at it from a more high level lens to better understand what total cost of ownership is. >>That's a great point. Great advice. Nicole, thank you so much for joining me on the program today, talking about the new report that on sustainability that Pure put out some really compelling nuggets in there, but really also some great successes that you've already achieved internally on your own ESG goals and what you're helping customers to achieve in terms of driving down their carbon footprint and emissions. We so appreciate your insights and your thoughts. >>Thank you, Lisa. It's been great speaking with you. >>AJ Singh joins me, the Chief Product Officer at Peer Storage. Aj, it's great to have you back on the program. >>Great to be back on, Lisa, good morning. >>Good morning. And sustainability is such an important topic to talk about. So we're gonna really unpack what PEER is doing, we're gonna get your viewpoints on what you're seeing and you're gonna leave the audience with some recommendations on how they can get started on their ESG journey. First question, we've been hearing a lot from pure AJ about the role that technology plays in organizations achieving sustainability goals. What's been the biggest environmental impact associated with, with customers achieving that given the massive volumes of data that keep being generated? >>Absolutely, Lisa, you can imagine that the data is only growing and exploding and, and, and, and there's a good reason for it. You know, data is the new currency. Some people call it the new oil. And the opportunity to go process this data gain insights is really helping customers drive an edge in the digital transformation. It's gonna make a difference between them being on the leaderboard a decade from now when the digital transformation kind of pans out versus, you know, being kind of somebody that, you know, quite missed the boat. So data is super critical and and obviously as part of that we see all these big benefits, but it has to be stored and, and, and that means it's gonna consume a lot of resources and, and the, and therefore data center usage has only accelerated, right? You can imagine the amount of data being generated, you know, recent study pointed to roughly by twenty twenty five, a hundred and seventy five zetabytes, which where each zettabyte is a billion terabytes. So just think of that size and scale of data. That's huge. And, and they also say that, you know, pretty soon, today, in fact in the developed world, every person is having an interaction with the data center literally every 18 seconds. So whether it's on Facebook or Twitter or you know, your email, people are constantly interacting with data. So you can imagine this data is only exploding. It has to be stored and it consumes a lot of energy. In fact, >>It, oh, go ahead. Sorry. >>No, I was saying in fact, you know, there's some studies have shown that data center usage literally consumes one to 2% of global energy consumption. So if there's one place we could really help climate change and, and all those aspects, if you can kind of really, you know, tamp down the data center, energy consumption, sorry, you were saying, >>I was just gonna say, it's, it's an incredibly important topic and the, the, the stats on data that you provided and also I, I like how you talked about, you know, every 18 seconds we're interacting with a data center, whether we know it or not, we think about the long term implications, the fact that data is growing massively. As you shared with the stats that you mentioned. If we think about though the responsibility that companies have, every company in today's world needs to be a data company, right? And we consumers expect it. We expect that you are gonna deliver these relevant, personalized experiences whether we're doing a transaction in our personal lives or in business. But what is the, what requirements do technology companies have to really start billing down their carbon footprints? >>No, absolutely. If you can think about it, just to kind of finish up the data story a little bit, the explosion is to the point where, in fact, if you just recently was in the news that Ireland went up and said, sorry, we can't have any more data centers here. We just don't have the power to supply them. That was big in the news and you know, all the hyperscale that was crashing the head. I know they've come around that and figured out a way around it, but it's getting there. Some, some organizations and and areas jurisdictions are saying pretty much no data center the law, you know, we're, we just can't do it. And so as you said, so companies like Pure, I mean, our view is that it has an opportunity here to really do our bit for climate change and be able to, you know, drive a sustainable environment. >>And, and at Pure we believe that, you know, today's data success really ultimately hinges on energy efficiency, you know, so to to really be energy efficient means you are gonna be successful long term with data. Because if you think of classic data infrastructures, the legacy infrastructures, you know, we've got disk infrastructures, hybrid infrastructures, flash infrastructures, low end systems, medium end systems, high end systems. So a lot of silos, you know, a lot of inefficiency across the silos. Cause the data doesn't get used across that. In fact, you know, today a lot of data centers are not really built with kind of the efficiency and environmental mindset. So there's a big opportunity there. >>So aj, talk to me about some of the steps that Pure is implementing as its chief product officer. Would love to get your your thoughts, what steps is it implementing to help Pures customers become more sustainable? >>No, absolutely. So essentially we are all inherently motivated, like pure and, and, and, and everybody else to solve problems for customers and really forward the status quo, right? You know, innovation, you know, that's what we are all about. And while we are doing that, the challenge is to how do you make technology and the data we feed into it faster, smarter, scalable obviously, but more importantly sustainable. And you can do all of that, but if you miss the sustainability bit, you're kind of missing the boat. And I also feel from an ethical perspective, that's really important for us. Not only you do all the other things, but also kind of make it sustainable. In fact, today 80% of the companies, the companies are realizing this, 80% today are in fact report out on sustainability, which is great. In fact, 80% of leadership at companies, you know, CEOs and senior executives say they've been impacted by some climate change event, you know, where it's a fire in the place they had to evacuate or floods or storms or hurricanes, you, you name it, right? >>So mitigating the carbon impact can in fact today be a competitive advantage for companies because that's where the puck is going and everybody's, you know, it's skating, wanting to skate towards the, and it's good, it's good business too to be sustainable and, and, and meet these, you know, customer requirements. In fact, the the recent survey that we released today is saying that more and more organizations are kickstarting, their sustainability initiatives and many take are aiming to make a significant progress against that over the next decade. So that's, that's really, you know, part of the big, the really, so our view is that that IT infrastructure, you know, can really make a big push towards greener it and not just kind of greenwash it, but actually, you know, you know, make things more greener and, and, and really take the, the lead in, in esg. And so it's important that organizations can reach alignment with their IT teams and challenge their IT teams to continue to lead, you know, for the organization, the sustainability aspects. >>I'm curious, aj, when you're in customer conversations, are you seeing that it's really the C-suite plus it coming together and, and how does peer help facilitate that? To your point, it needs to be able to deliver this, but it's, it's a board level objective these days. >>Absolutely. We're seeing increasingly, especially in Europe with the, you know, the war in Ukraine and the energy crisis that, you know, that's, that's, you know, unleashed. We definitely see it's becoming a bigger and bigger board level objective for, for a lot of companies. And we definitely see customers in starting to do that. So, so in particular, I do want to touch briefly on what steps we are taking as a company, you know, to to to make it sustainable. And obviously customers are doing all the things we talked about and, and we're also helping them become smarter with data. But the key difference is, you know, we have a big focus on efficiency, which is really optimizing performance per wat with unmatched storage density. So you can reduce the footprint and dramatically lower the power required. And and how efficient is that? You know, compared to other old flash systems, we tend to be one fifth, we tend to take one fifth the power compared to other flash systems and substantially lower compared to spinning this. >>So you can imagine, you know, cutting your, if data center consumption is a 2% of global consumption, roughly 40% of that tends to be storage cause of all the spinning disc. So you add about, you know, 0.8% to global consumption and if you can cut that by four fifths, you know, you can already start to make an impact. So, so we feel we can do that. And also we're quite a bit more denser, 10 times more denser. So imagine one fifth the power, one 10th the density, but then we take it a step further because okay, you've got the storage system in the data center, but what about the end of life aspect? What about the waste and reclamation? So we also have something called non-disruptive upgrades. We, using our AI technology in pure one, we can start to sense when a particular part is going to fail and just before it goes to failure, we actually replace it in a non-disruptive fashion. So customer's data is not impacted and then we recycle that so you get a full end to end life cycle, you know, from all the way from the time you deploy much lower power, much lower density, but then also at the back end, you know, reduction in e-waste and those kind of things. >>That's a great point you, that you bring up in terms of the reclamation process. It sounds like Pure does that on its own, the customer doesn't have to be involved in that. >>That's right. And we do that, it's a part of our evergreen, you know, service that we offer. A lot of customers sign up for that service and in fact they don't even, we tell them, Hey, you know, that part's about to go, we're gonna come in, we're gonna swap it out and, and then we actually recycle that part, >>The power of ai. Love that. What are some of the, the things that companies can do if they're, if they're early in this journey on sustainability, what are some of the specific steps companies can take to get started and maybe accelerate that journey as it's becoming climate change and things are becoming just more and more of a, of a daily topic on the news? >>No, absolutely. There's a lot of things companies can do. In fact, the four four item that we're gonna highlight, the first one is, you know, they can just start by doing a materiality assessment and a materiality assessment essentially engages all the stakeholders to find out which specific issues are important for the business, right? So you identify your key priorities that intersect with what the stakeholders want, you know, your different groups from sales, customers, partners, you know, different departments in the organization. And for example, for us, when we conducted our materiality assessment, for us, our product we felt was the biggest area of focus that could contribute a lot towards, you know, making an impact in, in, in from a sustainability standpoint. That's number one. I think number two companies can also think about taking an Azure service approach. The beauty of the Azure service approach is that you are buying a, your customer, they're buying outcomes with SLAs and, and when you are starting to buy outcomes with SLAs, you can start small and then grow as you consume more. >>So that way you don't have systems sitting idle waiting for you to consume more, right? And that's the beauty of the as service approach. And so for example, for us, you know, we have something called Evergreen one, which is our as service offer, where essentially customers are able to only use and have systems turned onto as much as they're consuming. So, so that reduces the waste associated with underutilized systems, right? That's number two. Number three is also you can optimize your supply chains end to end, right? Basically by making sure you're moving, recycling, packaging and eliminating waste in that thing so you can recycle it back to your suppliers. And you can also choose a sustainable supplier network that following sort of good practices, you know, you know, across the globe and such supply chains that are responsive and diverse can really help you. Also, the big business benefit benefited. >>You can also handle surges and demand, for example, for us during the pandemic with this global supply chain shortages, you know, whereas most of our competitors, you know, lead times went to 40, 50 weeks, our lead times went from three to six weeks cuz you know, we had this sustainable, you know, supply chain. And so all of these things, you know, the three things important, but the fourth thing I say more cultural and, and the cultural thing is how do you actually begin to have sustainability become a core part of your ethos at the company, you know, across all the departments, you know, and we've at Pure, definitely it's big for us, you know, you know, around sustainability starting with a product design, but all of the areas as well, if you follow those four items, they'll do the great place to start. >>That's great advice, great recommendations. You talk about the, the, the supply chain, sustainable supply chain optimization. We've been having a lot of conversations with businesses and vendors alike about that and how important it is. You bring up a great point too on supplier diversity, if we could have a whole conversation on that. Yes. But I'm also glad that you brought up culture that's huge to, for organizations to adopt an ESG strategy and really drive sustainability in their business. It has to become, to your point, part of their ethos. Yes. It's challenging. Cultural change management is challenging. Although I think with climate change and the things that are so public, it's, it's more on, on the top mindset folks. But it's a great point that the organization really as a whole needs to embrace the sustainability mindset so that it as a, as an organization lives and breathes that. Yes. And last question for you is advice. So you, you outlined the Four Steps organizations can take. I look how you made that quite simple. What advice would you give organizations who are on that journey to adopting those, those actions, as you said, as they look to really build and deploy and execute an ESG strategy? >>No, absolutely. And so obviously, you know, the advice is gonna come from, you know, a company like Pure, you know, our background kind of being a supplier of products. And so, you know, our advice is for companies that have products, usually they tend to be the biggest generator, the products that you sell to your, your customers, especially if they've got hardware components in it. But, you know, the biggest generator of e-waste and, and and, and, and, and kind of from a sustainability standpoint. So it's really important to have an intentional design approach towards your products with sustainability in mind. So it's not something that's, that you can handle at the very back end. You design it front in the product and so that sustainable design becomes very intentional. So for us, for example, doing these non-disruptive upgrades had to be designed up front so that, you know, a, you know, one of our repair person could go into a customer shop and be able to pull out a card and put in a new card without any change in the customer system. >>That non-receptive approach, it has to be designed into the hardware software systems to be able to pull that on. And that intentional design enables you to recover pieces just when they're about to fail and then putting them through a recovery, you know, waste recovery process. So that, that's kind of the one thing I would say that philosophy, again, it comes down to if that is, you know, seeping into the culture, into your core ethos, you will start to do, you know, you know, that type of work. So, so I mean it's important thing, you know, look, this year, you know, with the spike in energy prices, you know, you know, gas prices going up, it's super important that all of us, you know, do our bit in there and start to drive products that are fundamentally sustainable, not just at the initial, you know, install point, but from an end to end full life cycle standpoint. >>Absolutely. And I love that you brought up intention that is everything that peers doing is with, with such thought and intention and really for organizations and any industry to become more sustainable, to develop an ESG strategy. To your point, it all needs to start with intention. And of course that that cultural adoption, aj, it's been so great to have you on the program talking about what PEER is doing to help organizations really navigate that path to sustainable it. We appreciate your insights on your time. >>Thank you, Lisa. Pleasure being on board >>At Pure Storage. The opportunity for change and our commitment to a sustainable future are a direct reflection of the way we've always operated and the values we live by every day. We are making significant and immediate impact worldwide through our environmental sustainability efforts. The milestones of change can be seen everywhere in everything we do. Pures Evergreen storage architecture delivers two key environmental benefits to customers, the reduction of wasted energy and the reduction of e-waste. Additionally, pures implemented a series of product packaging redesigns, promoting recycle and reuse in order to reduce waste that will not only benefit our customers, but also the environment. Pure is committed to doing what is right and leading the way with innovation. That has always been the pure difference, making a difference by enabling our customers to drive out energy usage and their data storage systems by up to 80% today, more than 97% of Pure Array purchased six years ago are still in service. And tomorrow our goal for the future is to reduce Scope three emissions Pure is committing to further reducing our sold products emissions by 66% per petabyte by 2030. All of this means what we said at the beginning, change that is simple and that is what it has always been about. Pure has a vision for the future today, tomorrow, forever. >>We're back talking about the path to sustainable it and now we're gonna get the perspective from Mattia Valerio, who is with Elec Informatica and IT services firm and the beautiful Lombardi region of Italy north of Milano. Mattia, welcome to the Cube. Thanks so much for coming on. >>Thank you very much, Dave. Thank you. >>All right, before we jump in, tell us a little bit more about Elec Informatica. What's your focus, talk about your unique value add to customers. >>Yeah, so basically Alma Informatica is middle company from the north part of Italy and is managed service provider in the IT area. Okay. So the, the main focus area of Al Meca is reach digital transformation innovation to our clients with focus on infrastructure services, workplace services, and also cybersecurity services. Okay. And we try to follow the path of our clients to the digital transformation and the innovation through technology and sustainability. >>Yeah. Obviously very hot topics right now. Sustainability, environmental impact, they're growing areas of focus among leaders across all industries. A particularly acute right now in, in Europe with the, you know, the energy challenges you've talked about things like sustainable business. What does that mean? What does that term Yeah. You know, speak to and, and what can others learn from it? >>Yeah. At at, at our approach to sustainability is grounded in science and, and values and also in customer territory, but also employee centered. I mean, we conduct regular assessments to understand the most significant environment and social issues for our business with, with the goal of prioritizing what we do for a sustainability future. Our service delivery methodology, employee care relationship with the local supplier and local area and institution are a major factor for us to, to build a such a responsibility strategy. Specifically during the past year, we have been particularly focused on define sustainability governance in the company based on stakeholder engagement, defining material issues, establishing quantitative indicators to monitor and setting medium to long-term goals. >>Okay, so you have a lot of data. You can go into a customer, you can do an assessment, you can set a baseline, and then you have other data by which you can compare that and, and understand what's achievable. So what's your vision for sustainable business? You know, that strategy, you know, how has it affected your business in terms of the evolution? Cuz this wasn't, hasn't always been as hot a topic as it is today. And and is it a competitive advantage for you? >>Yeah, yeah. For, for, for all intense and proposed sustainability is a competitive advantage for elec. I mean, it's so, because at the time of profound transformation in the work, in the world of work, CSR issues make a company more attractive when searching for new talent to enter in the workforce of our company. In addition, efforts to ensure people's proper work life balance are a strong retention factor. And regarding our business proposition, ELEX attempts is to meet high standard of sustainability and reliability. Our green data center, you said is a prime example of this approach as at the same time, is there a conditioning activity that is done to give a second life to technology devices that come from back from rental? I mean, our customer inquiries with respect to sustainability are increasingly frequent and in depth and which is why we monitor our performance and invest in certification such as EcoVadis or ISO 14,001. Okay, >>Got it. So in a previous life I actually did some work with, with, with power companies and there were two big factors in it that affected the power consumption. Obviously virtualization was a big one, if you could consolidate servers, you know, that was huge. But the other was the advent of flash storage and that was, we used to actually go in with the, the engineers and the power company put in alligator clips to measure of, of, of an all flash array versus, you know, the spinning disc and it was a big impact. So you, I wanna talk about your, your experience with Pure Storage. You use Flash Array and the Evergreen architecture. Can you talk about what your experience there, why did you make that decision to select Pure Storage? How does that help you meet sustainability and operational requirements? Do those benefits scale as your customers grow? What's your experience been? >>Yeah, it was basically an easy and easy answer to our, to our business needs. Okay. Because you said before that in Elec we, we manage a lot of data, okay? And in the past we, we, we see it, we see that the constraints of managing so many, many data was very, very difficult to manage in terms of power consumption or simply for the, the space of storing the data. And when, when Pure came to us and share our products, their vision to the data management journey for Element Informatica, it was very easy to choose pure why with values and numbers. We, we create a business case and we said that we, we see that our power consumption usage was much less, more than 90% of previous technology that we used in the past. Okay. And so of course you have to manage a grade oil deploy of flash technology storage, but it was a good target. >>So we have tried to monitoring the adoption of flash technology and monitor monitoring also the power consumption and the efficiency that the pure technology bring to our, to our IT systems and of course the IT systems of our clients. And so this is one, the first part, the first good part of our trip with, with Pure. And after that we approach also the sustainability in long term of choosing pure technology storage. You mentioned the Evergreen models of Pure, and of course this was, again, challenge for us because it allows, it allow us to extend the life cycle management of our data centers, but also the, IT allows us to improve the facility of the facilities of using technology from our technical side. Okay. So we are much more efficient than in the past with the choose of Pure storage technologies. Okay. Of course, this easy users, easy usage mode, let me say it, allow us to bring this value to our, to all our clients that put their data in our data centers. >>So you talked about how you've seen a 90% improvement relative to previous technologies. I always, I haven't put you in the spot. Yeah, because I, I, I was on Pure's website and I saw in their ESG report some com, you know, it was a comparison with a generic competitor presuming that competitor was not, you know, a 2010 spinning disc system. But, but, so I'm curious as to the results that you're seeing with Pure in terms of footprint and power usage. You, you're referencing some of that. We heard some metrics from Nicole and AJ earlier in the program. Do you think, again, I'm gonna put you in the spot, do you think that Pure's architecture and the way they've applied, whether it's machine intelligence or the Evergreen model, et cetera, is more competitive than other platforms that you've seen? >>Yeah, of course. Is more competitor improve competitive because basically it allows to service provider to do much more efficient value proposition and offer services that are more, that brings more values to, to the customers. Okay. So the customer is always at the center of a proposition of a service provider and trying to adopt the methodology and also the, the value that pure as inside by design in the technology is, is for us very, very, very important and very, very strategic because, because with like a glass, we can, our self transfer try to transfer the values of pure, pure technologies to our service provider client. >>Okay. Matta, let's wrap and talk about sort of near term 2023 and then longer term it looks like sustainability is a topic that's here to stay. Unlike when we were putting alligator clips on storage arrays, trying to help customers get rebates that just didn't have legs. It was too complicated. Now it's a, a topic that everybody's measuring. What's next for elec in its sustainability journey? What advice would you might have? Sustainability leaders that wanna make a meaningful impact on the environment, but also on the bottom line. >>Okay, so sustainability is fortunately a widely spread concept. And our role in, in this great game is to define a strategy, align with the common and fundamentals goals for the future of planet and capable of expressing our inclination and the, and the particularities and accessibility goals in the near future. I, I say, I can say that are will be basically free one define sustainability plan. Okay? It's fundamentals to define a sustainability plan. Then it's very important to monitor the its emissions and we will calculate our carbon footprint. Okay? And least button list produces certifiable and comprehensive sustainability report with respect to the demands of customers, suppliers, and also partners. Okay. So I can say that this three target will be our direction in the, in the future. Okay. >>Yeah. So I mean, pretty straightforward. Make a plan. You gotta monitor and measure, you can't improve what you can't measure. So you gonna set a baseline, you're gonna report on that. Yep. You're gonna analyze the data and you're gonna make continuous improvement. >>Yep. >>Matea, thanks so much for joining us today in sharing your perspectives from the, the northern part of Italy. Really appreciate it. >>Yeah, thank you for having aboard. Thank you very >>Much. It was really our pleasure. Okay, in a moment, I'm gonna be back to wrap up the program and share some resources that could be valuable in your sustainability journey. Keep it right there. >>Sustainability is becoming increasingly important and is hitting more RFPs than ever before as a critical decision point for customers. Environmental benefits are not the only impetus. Rather bottom line cost savings are proving that sustainability actually means better business. You can make a strong business case around sustainability and you should, many more organizations are setting mid and long-term goals for sustainability and putting forth published metrics for shareholders and customers. Whereas early green IT initiatives at the beginning of this century, were met with skepticism and somewhat disappointing results. Today, vendor r and d is driving innovation in system design, semiconductor advancements, automation in machine intelligence that's really beginning to show tangible results. Thankfully. Now remember, all these videos are available on demand@thecube.net. So check them out at your convenience and don't forget to go to silicon angle.com for all the enterprise tech news of the day. You also want to check out pure storage.com. >>There are a ton of resources there. As an aside, pure is the only company I can recall to allow you to access resources like a Gartner Magic Quadrant without forcing you to fill out a lead gen form. So thank you for that. Pure storage, I love that. There's no squeeze page on that. No friction. It's kind of on brand there for pure well done. But to the topic today, sustainability, there's some really good information on the site around esg, Pure's Environmental, social and Governance mission. So there's more in there than just sustainability. You'll see some transparent statistics on things like gender and ethnic diversity, and of course you'll see that Pure has some work to do there. But kudos for publishing those stats transparently and setting goals so we can track your progress. And there's plenty on the sustainability topic as well, including some competitive benchmarks, which are interesting to look at and may give you some other things to think about. We hope you've enjoyed the path to Sustainable it made possible by Pure Storage produced with the Cube, your leader in enterprise and emerging tech, tech coverage.

>> Good afternoon from Vegas, guys and gals. We're so happy that you're with us. This is theCUBE live at AWS re:Invent '22. This is our third day of coverage. We started Monday night, so we're counting that as day one. Loads of conversations we've had already. We know that you know that 'cause you've been watching. I'm here with Dave Vellante. Dave, great to be here with you with somewhere between 50,000 and 70,000 people. And we're excited for our next conversation. We've got two folks joining us who are new to theCUBE, soon will be alumni. Milan Bhatt joins us, the president and head of Cloud at Hexaware. And Nikhil Date, the Director of Engineering and Application Services at Domestic & General. Guys, welcome to the program. >> Thank you >> Thanks for having us. >> So Domestic & General, or D&G, is a customer of Hexaware, but Milan, we want to start with you. Give the audience an overview of Hexaware. What do you do? What's the business model? >> Yeah. So, Hexaware is a technology services company. We are a global partner of AWS, and essentially, we help customers like Domestic & General, you know, accelerate their digital transformation journeys. We like to think of ourselves as a billion dollar startup. And like Amazon, it is always day one at Hexaware. And, you know, I look forward to the conversation, but any company in the world that is looking at cloud-led digital transformation, they have to put Hexaware on the consideration list. Because, you know, not only do we work with a lot of customers, analysts like Gartner, they have rated us as a visionary in helping customers become, you know, digitally enabled, bring better customer experience to their end customers. >> Excellent. Well, we're glad to feature Hexaware on the program. >> Milan: Thank you. >> Nikhil let's bring you into the conversation. Talk to the audience about Domestic & General. What kind of business is it? What's the business model? >> Sure, thank you. So we are, you know, 110-year-old business, right? I mean, we started insuring sheep in Australia, if you believe it, you know, which is quite an origin story. But at the moment, you know, the primary business is keeping our customers world running. So what do I mean by that? We protect in warranty and out-of-warranty care for domestic appliances. You know, TVs, boilers, refrigerators, washing machines, that kind of thing. But we are also a B2B company in the sense that, you know, you might think you are getting a warranty from some of our biggest customers, like Whirlpool or, you know, Bosch, Siemens, or Samsung, but actually it's D&G at the back trying to administer that for you. So, you know, we are in 13 countries. Just launched in the US last year, but big plans. >> So it's really interesting because we all have appliances, and we can relate to, especially, you know pre or post-pandemic, how difficult it is to get service. So you're kind of like, in a way, you've got to build a digital platform like Uber, connecting drivers and passengers, right? And so you've got the supply of individuals who know how to fix stuff, right? And you want to make it as easy as possible for the customer. So was that the genesis of this digital transformation? Can you talk about those business drivers? >> It was, actually, and it's a fantastic point, because trying to become a platform business is what this journey has been all about for us, right? I think, you know, we are a pioneer in what we consider the subscription model. So customers pay a small amount per month as opposed to a big lump sum amount that they have to pay at the point you buy the appliance. And importantly, you can actually buy our product to pay in installments at the point something breaks down. So it's not just something that you buy at the point of sale or at the point you try to register. You can buy it at any time. And the goal really is to have warranty in a box that you can take anywhere, you know, anywhere in the world. So, you know, but it's a great point. Digital transformation is what it is all about. >> And there is a real lack right now of qualified technicians. >> That's right. >> Is there anything within the platform to incent those individuals to participate in your business? >> You know, this is what we consider a multi-tier approach. I think at the moment, the service that we offer is largely top tier, right? So we will get you an engineer that is certified by the manufacturer with the manufacturer warranty. And it's a no fix, no fee model, you know? So, you know, we guarantee either to repair or replace the appliance, you know? That's the model. But you are right, I think in the future stage would be, you know, why wouldn't we want to have anybody who's got the right skills to come in and work off the platform? Absolutely right. >> Nikhil, talk about, you said this is a legacy business, been around for quite some time. You've been there for not quite two years. What drew you to the organization? And where were they in their digital transformation journey? Because I always think legacy companies, this a big challenge, and it's cultural challenge to really transform, but companies these days have no choice. >> Again, a fantastic point, right? I think some of the, you know, 110-year-old business, right? And some of the tech, you would be forgiven for thinking it's that old. But the assets that we had are our people, right? Who are really passionate about the business. And I think what we had to do is to find a partner that can upskill the tech, but also upskill the people at the same time and upskill the delivery model, right? So we've a very traditional left-to-right waterfall, you know, planet first, big upfront planning, and then deliver kind of organization. And by working with a partner such as Hexaware and embracing cloud, because, you know, our first and our go-to will be a SaaS or a cloud provider. And, you know, doing that was the massive agenda that drew me to the company. But I think what is also fair is, you know, digitization or digitalization, is a misunderstood and often abused term, right? Because for the most part, when companies start, and I'm not saying it's right or wrong, but, you know, for the most part, when companies start on this journey, they take a journey that works in the brick and mortar world, and we were a contact center business, and just try to move it to the digital journey, right? It's not a great customer experience. I'll give you an example, right? Now, if you call our agent and say, "Yeah, I'm trying to register an appliance," they will tell you where to look for the serial number. But if you're on a digital channel, you don't know where to look. There's nobody, you know, who can help you. The model number, who remembers the model number of the washing machine they bought, right? I mean, you know, it's stuff like that, you know, which would feel, you know, for a digital native, my son, you know, for example, would think, "How can you even ask a customer for that?" But, you know, it's that change in the model, that's what this is all about. >> Yeah, it's like when you get to go, "What's your account number?" I have no idea what my account number is. So when did this whole project start? How was Hexaware involved? And where did Hexaware start? Like, how did you sort of gauge what the requirement was? Take us through that little- >> Sure. So, you know, when Nikhil and the rest of the management team came in, they came up with a competitive process where, you know, and it is refreshing to remember, I think they've stuck true to their vision. They were very clear that they were not looking for someone who can just digitize their paper processes, but who can help them completely re-imagine, you know, what the new process would look like what the new experience would look like. And, you know, remember, they were running this process at the height of the pandemic, so we couldn't meet anybody in person. We did everything virtual. And we were using cloud technology, but, you know, the way they run the process, they wanted to make sure that a provider brings in a mix of experience and engineering expertise. And that's really hard to find. But equally importantly, you remember those culture sessions that we did? They figured out some very creative ways of making sure that there is a cultural fit. So, for example, they did virtual breakout sessions where, you know, people were sort of asking each other, you know, if you want to have dinner with someone like a celebrity, who would it be? So, you know, these little things to make sure that there is a match and people can actually work. >> Relationship building too. >> The relationship building. It's hard to do in a virtual environment, but it was a competitive process. They looked at us in terms of engineering, you know, experience, our ability to transcend change and run, and, you know, really focus and align to keep their objectives first, right? Work as a true partnership. Do you agree? >> I would agree. And I think, you know, one of the biggest goals here was to make sure that, this is not an arms length vendor relationship, right? You know, this is an extension of our team. So these are our people, you know, for the people that work on D&G, you know, they work in the D&G way, you know, and that means that they can also challenge us, you know, which is quite refreshing, right? People stopping and saying, "Why are you asking me to do this?" You know, it's very refreshing, I think, you know, to work with a partner that is sold on the vision and committed to helping you achieve success. >> That synergy creates that flywheel. And like you said, at D&G, Hexaware, we're a team, we're working together. Nikhil, share with us some of the significant business outcomes that Hexaware services and AWS are helping the company to achieve? Because there's some big numbers there. >> Indeed. Yeah. So, you know, in the digital journey itself, like I said, we are also a B2B business. You know, one of the key challenges is every client wants their own brand, right? So, you know, a journey for customer X has to look like the customer X brand. And our journey for customer Y will have to do the same. You know, when you try to stretch this to a technology problem though, it means that, you know, we were trying to be too many things for too many people, and that slowed things down and increased complexity. So from our point of view, you know, when we started with the digital journey or in the middle of the digital journey, we thought, we need to have a library of reusable components. We need white labeling, right? So there was a root in branch re-engineering of the digital proposition to allow us to, you know, serve multiple clients with the same underlying technology. And that has meant that, you know, in some cases, we are going to market, you know, two, three times faster than what we were. Costs, obviously, you know, 50% cheaper. But, you know, I think the big thing here, and, you know, this is the unstated benefit, is because now there is a common underlying technology innovation that client X wants to do becomes available for client Y. You know, which means that, you know, there's a virtual circle of, you know, constant improvement. So, you know that, from my point of view, that's the big benefit. >> And would you agree that you are still only in the first quarter of a football game? >> Absolutely. >> I think a lot of ambitious plans. So, you know, this is just the beginning. And the way they have built the organization, the way they have driven the culture change, you know, I'm very hopeful for great things to come. >> Paint a picture of the tech. I'm interested in the architecture, and I'm really interested in the data component and how that's affected your business. >> So I mean, you know, multilayered tech architecture, as you can imagine. Then, you know, we still have a legacy, you know, legacy components running off our own PET mainframe, as we like to call it. But, you know, from a forward point of view, what we really want is to allow clients to self-serve, right? Not have to, you know, because at the moment, the only service we can offer is what I call the white glove, right? Which means, you know, somebody has to sit down with us, have a discussion on the requirements, but people should be able to self-serve, you know, look at the catalog of what it is we can do for them and go for it. Data is a very interesting point, right? Because not only are there, you know, geography restrictions around where customer data can go to, obviously, payments and PCI compliance is an issue. But last but not least, you know, some of this data is very, you know, unique to what the clients want to own and manage. And, you know, if you are a, you know, a typical homeowner, you will have appliance from all kinds of manufacturers, right? Many of whom would be our customers. But how much data we can share, because we recognize you as a person, but how much data we can share, there are restrictions. But, you know, building our data abstraction layer allows us to, you know, take care of that. But you're absolutely right, in terms of, But again, the potential for where the data can be mined, because, you know, the engineer also has to be local to where you live. You know, you can't come from 100 miles away. So, you know, the ability to use data to, you know, not just transform our business, but our client's business is phenomenal, you know? >> Do you actually have a mainframe? >> Yes >> We do do. (laughter) >> Adam Selinsky wants to move it into the cloud. (laughter) >> They have every possible technology that you can think of. I mean, 100-year-old business evolved over a period of time. And, you know, if I could add, you know, what has been really impressive about the decision making at D&G is that they have adopted cloud in the right way, right? So they are one of the few customers who have truly taken AWS well architected to heart. They have taken things like, you know, take the right workloads to the cloud and wait to do the right remediations before you take the rest of the workloads to the cloud. They've used native services available on AWS from apps perspective as well as a data perspective. So that's sort of a little bit more color on the technology and architecture. >> But you've essentially SaaSified your business and you basically have D&G cloud that you're delivering to your customers for self-serve. Is that fair? >> That's the vision, yes. The idea is to get there. And, you know, if we assemble what I call, you know, out-the-box solutions in a clever way, then that becomes the platform that we can replicate success on. And at the moment, our business needs what I call boots on the ground. When we are a true platform business, we should be able to operate without having, you know, any presence in country, with the partners leveraging the platform to do what what's next. >> I'm curious, Milan, you said that one of the great things that D&G has done is really adopted cloud in the right way. Do you, Nikhil, think of cloud first or cloud right approach? Because you've got a mainframe, so I'm just wondering if it's more what's right for cloud versus everything cloud first. >> Correct. I mean, I actually, you know, or we actually tend to start even two steps before that, right? I think it's really whether we need to buy or whether we need to build, right? And if we need to buy, then, you know, how easily would that thing that has been bought fit into what is a very complex architecture, as Milan said, right? I mean, any technology you can imagine we probably have it, but we want to simplify it, right? And this is a journey. So which means that, you know, we start with can SaaS product do it? And then we also want to go wherever we are building, then it has to be on the cloud. It has to be designed for scaling. It has to be designed to be in multiple geographies, multiple countries with the relevant data protection baked in. So, you know, that's the decision-thinking process. You know, that the goal is to not, I mean, you know, we had a project started 18 months ago that wanted to buy more tin, but we put a stop to that, right? And saying that, "You know, come on, you can't have that." Not in this day and age, you know, when the cloud can pretty much do everything that you need. >> Do you think of D&G, this is a question for you. We're almost out of time, but I'm just curious, I'm looking at your website, D&G, the experts who repair and replace the household products everyone relies on. Do you think about it as a repair company? Do you think about it as a tech company that delivers these repair services? >> I mean, this is the conversation we have in our teams all the time, right? That when our vision is successful, we will become a tech business. At the moment, I don't think we are, you know? At the moment, I think we are on a journey, you know, because, you know, we are multi-channel, you know, and our customers love us, you know, touch wood. But are we a true tech company? No, but we are getting there, right? I think, you know, that's the plan. >> You're on the journey? >> Yeah. >> Awesome stuff. Last question for each of you, a little bit different. Milan, question for you. You have a billboard or a bumper sticker, whichever, or maybe a sticker for your laptop and it's about Hexaware, and you want to really convey, in a compelling, but really short way, why are we so great? What would that sticker say? >> Awesome. Like I said at the beginning, if you are thinking about a digital transformation, if you are a company that has been around for a long time, you've got to think of us, you know, as a partner. So that's what I would say, because, you know, the purpose of our company is creating smiles through a combination of great people and technology. So that's what we live for. And, you know, brought a smile to me when Nikhil said that our customers love us, and somewhere, we have a small role to play in that. >> I love that. Nikhil, I'm going to ask the same question. I was going to ask you a different one, but I would love to, I mean, we talked a lot about D&G and the incredible business transformation that you've been on. What's that bumper sticker for D&G? What is that bumper sticker for D&G? >> Oh, yeah. Okay. We want keep your world running, right? I mean, you know, from our point of view, you know, you rely on the appliances to keep your home running, and we want you to rely on us to make sure your world keeps running. You know, that's what this is all about. It has to be slick. Touch wood, hopefully, you never have a problem, but if you do, we want to be there, you know, to make sure that your world keeps running. >> I love it. Awesome, guys. Thank you, Milan. Nikhil, thank you so much for joining Dave and me on the program. >> Thank you. I enjoyed the conversation. >> Great partnership. Hexaware, first time on theCUBE, now you're an alumni. You're an alumni too. We appreciate your insights, sharing the story. It's a really compelling story. Thank you. >> And thank you for all the support, Nikhil. >> Of course. >> All right. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.

>>We're back at Super Computing, 22 in Dallas, winding down the final day here. A big show floor behind me. Lots of excitement out there, wouldn't you say, Dave? Just >>Oh, it's crazy. I mean, any, any time you have NASA presentations going on and, and steampunk iterations of cooling systems that the, you know, it's, it's >>The greatest. I've been to hundreds of trade shows. I don't think I've ever seen NASA exhibiting at one like they are here. Dave Nicholson, my co-host. I'm Paul Gell, in which with us is Satish Ier. He is the vice president of emerging services at Dell Technologies and Satit, thanks for joining us on the cube. >>Thank you. Paul, >>What are emerging services? >>Emerging services are actually the growth areas for Dell. So it's telecom, it's cloud, it's edge. So we, we especially focus on all the growth vectors for, for the companies. >>And, and one of the key areas that comes under your jurisdiction is called apex. Now I'm sure there are people who don't know what Apex is. Can you just give us a quick definition? >>Absolutely. So Apex is actually Dells for a into cloud, and I manage the Apex services business. So this is our way of actually bringing cloud experience to our customers, OnPrem and in color. >>But, but it's not a cloud. I mean, you don't, you don't have a Dell cloud, right? It's, it's of infrastructure as >>A service. It's infrastructure and platform and solutions as a service. Yes, we don't have our own e of a public cloud, but we want to, you know, this is a multi-cloud world, so technically customers want to consume where they want to consume. So this is Dell's way of actually, you know, supporting a multi-cloud strategy for our customers. >>You, you mentioned something just ahead of us going on air. A great way to describe Apex, to contrast Apex with CapEx. There's no c there's no cash up front necessary. Yeah, I thought that was great. Explain that, explain that a little more. Well, >>I mean, you know, one, one of the main things about cloud is the consumption model, right? So customers would like to pay for what they consume, they would like to pay in a subscription. They would like to not prepay CapEx ahead of time. They want that economic option, right? So I think that's one of the key tenets for anything in cloud. So I think it's important for us to recognize that and think Apex is basically a way by which customers pay for what they consume, right? So that's a absolutely a key tenant for how, how we want to design Apex. So it's absolutely right. >>And, and among those services are high performance computing services. Now I was not familiar with that as an offering in the Apex line. What constitutes a high performance computing Apex service? >>Yeah, I mean, you know, I mean, this conference is great, like you said, you know, I, there's so many HPC and high performance computing folks here, but one of the things is, you know, fundamentally, if you look at high performance computing ecosystem, it is quite complex, right? And when you call it as an Apex HPC or Apex offering offer, it brings a lot of the cloud economics and cloud, you know, experience to the HPC offer. So fundamentally, it's about our ability for customers to pay for what they consume. It's where Dell takes a lot of the day to day management of the infrastructure on our own so that customers don't need to do the grunge work of managing it, and they can really focus on the actual workload, which actually they run on the CHPC ecosystem. So it, it is, it is high performance computing offer, but instead of them buying the infrastructure, running all of that by themself, we make it super easy for customers to consume and manage it across, you know, proven designs, which Dell always implements across these verticals. >>So what, what makes the high performance computing offering as opposed to, to a rack of powered servers? What do you add in to make it >>Hpc? Ah, that's a great question. So, I mean, you know, so this is a platform, right? So we are not just selling infrastructure by the drink. So we actually are fundamentally, it's based on, you know, we, we, we launch two validated designs, one for life science sales, one for manufacturing. So we actually know how these PPO work together, how they actually are validated design tested solution. And we also, it's a platform. So we actually integrate the softwares on the top. So it's just not the infrastructure. So we actually integrate a cluster manager, we integrate a job scheduler, we integrate a contained orchestration layer. So a lot of these things, customers have to do it by themself, right? If they're buy the infrastructure. So by basically we are actually giving a platform or an ecosystem for our customers to run their workloads. So make it easy for them to actually consume those. >>That's Now is this, is this available on premises for customer? >>Yeah, so we, we, we make it available customers both ways. So we make it available OnPrem for customers who want to, you know, kind of, they want to take that, take that economics. We also make it available in a colo environment if the customers want to actually, you know, extend colo as that OnPrem environment. So we do both. >>What are, what are the requirements for a customer before you roll that equipment in? How do they sort of have to set the groundwork for, >>For Well, I think, you know, fundamentally it starts off with what the actual use case is, right? So, so if you really look at, you know, the two validated designs we talked about, you know, one for, you know, healthcare life sciences, and one other one for manufacturing, they do have fundamentally different requirements in terms of what you need from those infrastructure systems. So, you know, the customers initially figure out, okay, how do they actually require something which is going to require a lot of memory intensive loads, or do they actually require something which has got a lot of compute power. So, you know, it all depends on what they would require in terms of the workloads to be, and then we do havet sizing. So we do have small, medium, large, we have, you know, multiple infrastructure options, CPU core options. Sometimes the customer would also wanna say, you know what, as long as the regular CPUs, I also want some GPU power on top of that. So those are determinations typically a customer makes as part of the ecosystem, right? And so those are things which would, they would talk to us about to say, okay, what is my best option in terms of, you know, kind of workloads I wanna run? And then they can make a determination in terms of how, how they would actually going. >>So this, this is probably a particularly interesting time to be looking at something like HPC via Apex with, with this season of Rolling Thunder from various partners that you have, you know? Yep. We're, we're all expecting that Intel is gonna be rolling out new CPU sets from a powered perspective. You have your 16th generation of PowerEdge servers coming out, P C I E, gen five, and all of the components from partners like Invidia and Broadcom, et cetera, plugging into them. Yep. What, what does that, what does that look like from your, from your perch in terms of talking to customers who maybe, maybe they're doing things traditionally and they're likely to be not, not fif not 15 G, not generation 15 servers. Yeah. But probably more like 14. Yeah, you're offering a pretty huge uplift. Yep. What, what do those conversations look >>Like? I mean, customers, so talking about partners, right? I mean, of course Dell, you know, we, we, we don't bring any solutions to the market without really working with all of our partners, whether that's at the infrastructure level, like you talked about, you know, Intel, amd, Broadcom, right? All the chip vendors, all the way to software layer, right? So we have cluster managers, we have communities orchestrators. So we usually what we do is we bring the best in class, whether it's a software player or a hardware player, right? And we bring it together as a solution. So we do give the customers a choice, and the customers always want to pick what you they know actually is awesome, right? So they that, that we actually do that. And, you know, and one of the main aspects of, especially when you talk about these things, bringing it as a service, right? >>We take a lot of guesswork away from our customer, right? You know, one of the good example of HPC is capacity, right? So customers, these are very, you know, I would say very intensive systems. Very complex systems, right? So customers would like to buy certain amount of capacity, they would like to grow and, you know, come back, right? So give, giving them the flexibility to actually consume more if they want, giving them the buffer and coming down. All of those things are very important as we actually design these things, right? And that takes some, you know, customers are given a choice, but it actually, they don't need to worry about, oh, you know, what happens if I actually have a spike, right? There's already buffer capacity built in. So those are awesome things. When we talk about things as a service, >>When customers are doing their ROI analysis, buying CapEx on-prem versus, versus using Apex, is there a point, is there a crossover point typically at which it's probably a better deal for them to, to go OnPrem? >>Yeah, I mean, it it like specifically talking about hpc, right? I mean, why, you know, we do have a ma no, a lot of customers consume high performance compute and public cloud, right? That's not gonna go away, right? But there are certain reasons why they would look at OnPrem or they would look at, for example, Ola environment, right? One of the main reasons they would like to do that is purely have to do with cost, right? These are pretty expensive systems, right? There is a lot of ingress, egress, there is a lot of data going back and forth, right? Public cloud, you know, it costs money to put data in or actually pull data back, right? And the second one is data residency and security requirements, right? A lot of these things are probably proprietary set of information. We talked about life sciences, there's a lot of research, right? >>Manufacturing, a lot of these things are just, just in time decision making, right? You are on a factory floor, you gotta be able to do that. Now there is a latency requirement. So I mean, I think a lot of things play, you know, plays into this outside of just cost, but data residency requirements, ingress, egress are big things. And when you're talking about mass moments of data you wanna put and pull it back in, they would like to kind of keep it close, keep it local, and you know, get a, get a, get a price >>Point. Nevertheless, I mean, we were just talking to Ian Coley from aws and he was talking about how customers have the need to sort of move workloads back and forth between the cloud and on-prem. That's something that they're addressing without posts. You are very much in the, in the on-prem world. Do you have, or will you have facilities for customers to move workloads back and forth? Yeah, >>I wouldn't, I wouldn't necessarily say, you know, Dell's cloud strategy is multi-cloud, right? So we basically, so it kind of falls into three, I mean we, some customers, some workloads are suited always for public cloud. It's easier to consume, right? There are, you know, customers also consume on-prem, the customers also consuming Kohler. And we also have like Dell's amazing piece of software like storage software. You know, we make some of these things available for customers to consume a software IP on their public cloud, right? So, you know, so this is our multi-cloud strategy. So we announced a project in Alpine, in Delta fold. So you know, if you look at those, basically customers are saying, I love your Dell IP on this, on this product, on the storage, can you make it available through, in this public environment, whether, you know, it's any of the hyper skill players. So if we do all of that, right? So I think it's, it shows that, you know, it's not always tied to an infrastructure, right? Customers want to consume the best thumb and if we need to be consumed in hyperscale, we can make it available. >>Do you support containers? >>Yeah, we do support containers on hpc. We have, we have two container orchestrators we have to support. We, we, we have aner similarity, we also have a container options to customers. Both options. >>What kind of customers are you signing up for the, for the HPC offerings? Are they university research centers or is it tend to be smaller >>Companies? It, it's, it's, you know, the last three days, this conference has been great. We probably had like, you know, many, many customers talking to us. But HC somewhere in the range of 40, 50 customers, I would probably say lot of interest from educational institutions, universities research, to your point, a lot of interest from manufacturing, factory floor automation. A lot of customers want to do dynamic simulations on factory floor. That is also quite a bit of interest from life sciences pharmacies because you know, like I said, we have two designs, one on life sciences, one on manufacturing, both with different dynamics on the infrastructure. So yeah, quite a, quite a few interest definitely from academics, from life sciences, manufacturing. We also have a lot of financials, big banks, you know, who wants to simulate a lot of the, you know, brokerage, a lot of, lot of financial data because we have some, you know, really optimized hardware we announced in Dell for, especially for financial services. So there's quite a bit of interest from financial services as well. >>That's why that was great. We often think of Dell as, as the organization that democratizes all things in it eventually. And, and, and, and in that context, you know, this is super computing 22 HPC is like the little sibling trailing around, trailing behind the super computing trend. But we definitely have seen this move out of just purely academia into the business world. Dell is clearly a leader in that space. How has Apex overall been doing since you rolled out that strategy, what, two couple? It's been, it's been a couple years now, hasn't it? >>Yeah, it's been less than two years. >>How are, how are, how are mainstream Dell customers embracing Apex versus the traditional, you know, maybe 18 months to three year upgrade cycle CapEx? Yeah, >>I mean I look, I, I think that is absolutely strong momentum for Apex and like we, Paul pointed out earlier, we started with, you know, making the infrastructure and the platforms available to customers to consume as a service, right? We have options for customers, you know, to where Dell can fully manage everything end to end, take a lot of the pain points away, like we talked about because you know, managing a cloud scale, you know, basically environment for the customers, we also have options where customers would say, you know what, I actually have a pretty sophisticated IT organization. I want Dell to manage the infrastructure, but up to this level in the layer up to the guest operating system, I'll take care of the rest, right? So we are seeing customers who are coming to us with various requirements in terms of saying, I can do up to here, but you take all of this pain point away from me or you do everything for me. >>It all depends on the customer. So we do have wide interest. So our, I would say our products and the portfolio set in Apex is expanding and we are also learning, right? We are getting a lot of feedback from customers in terms of what they would like to see on some of these offers. Like the example we just talked about in terms of making some of the software IP available on a public cloud where they'll look at Dell as a software player, right? That's also is absolutely critical. So I think we are giving customers a lot of choices. Our, I would say the choice factor and you know, we are democratizing, like you said, expanding in terms of the customer choices. And I >>Think it's, we're almost outta our time, but I do wanna be sure we get to Dell validated designs, which you've mentioned a couple of times. How specific are the, well, what's the purpose of these designs? How specific are they? >>They, they are, I mean I, you know, so the most of these valid, I mean, again, we look at these industries, right? And we look at understanding exactly how would, I mean we have huge embedded base of customers utilizing HPC across our ecosystem in Dell, right? So a lot of them are CapEx customers. We actually do have an active customer profile. So these validated designs takes into account a lot of customer feedback, lot of partner feedback in terms of how they utilize this. And when you build these solutions, which are kind of end to end and integrated, you need to start anchoring on something, right? And a lot of these things have different characteristics. So these validated design basically prove to us that, you know, it gives a very good jump off point for customers. That's the way I look at it, right? So a lot of them will come to the table with, they don't come to the blank sheet of paper when they say, oh, you know what I'm, this, this is my characteristics of what I want. I think this is a great point for me to start from, right? So I think that that gives that, and plus it's the power of validation, really, right? We test, validate, integrate, so they know it works, right? So all of those are hypercritical. When you talk to, >>And you mentioned healthcare, you, you mentioned manufacturing, other design >>Factoring. We just announced validated design for financial services as well, I think a couple of days ago in the event. So yep, we are expanding all those DVDs so that we, we can, we can give our customers a choice. >>We're out of time. Sat ier. Thank you so much for joining us. Thank you. At the center of the move to subscription to everything as a service, everything is on a subscription basis. You really are on the leading edge of where, where your industry is going. Thanks for joining us. >>Thank you, Paul. Thank you Dave. >>Paul Gillum with Dave Nicholson here from Supercomputing 22 in Dallas, wrapping up the show this afternoon and stay with us for, they'll be half more soon.

>>Hello >>Everyone and welcome back to Dallas where we're live from, Super computing. My name is Savannah Peterson, joined with my co-host David, and we have a rocket of a show for you this afternoon. The doctors are in the house and we are joined by nasa, ladies and gentlemen. So excited. Please welcome Dr. Dan Duffy and Dr. Bill Putman. Thank you so much for being here, guys. I know this is kind of last minute. How's it to be on the show floor? What's it like being NASA here? >>What's exciting? We haven't, we haven't been here for three years, so this is actually really exciting to come back and see everybody, to see the showroom floor, see the innovations that have happened over the last three years. It's pretty exciting. >>Yeah, it's great. And, and so, because your jobs are so cool, and I don't wanna even remotely give even too little of the picture or, or not do it justice, could you give the audience a little bit of background on what you do as I think you have one of the coolest jobs ever. YouTube bill. >>I, I appreciate that. I, I, I run high Performance Computing Center at NASA Goddard for science. It's high performance information technology. So we do everything from networking to security, to high performance computing, to data sciences, artificial intelligence and machine learning is huge for us now. Yeah, large amounts of data, big data sets, but we also do scientific visualizations and then cloud and commercial cloud computing, as well as on premises cloud computing. And quite frankly, we support a lot of what Bill and his team does. >>Bill, why don't you tell us what your team >>Does? Yeah, so I'm a, I'm an earth scientist. I work as the associate chief at the global modeling assimilation office. And our job is to really, you know, maximize the use of all the observations that NASA takes from space and build that into a coherent, consistent physical system of the earth. Right? And we're focused on utilizing the HC that, that Dan and the folks at the nccs provide to us, to the best of our abilities to integrate those observations, you know, on time scales from hours, days to, to seasonal to to monthly time scales. That's, that's the essence of our focus at the GMA o >>Casual modeling, all of NASA's earth data. That, that in itself as a sentence is pretty wild. I imagine you're dealing with a ton of data. >>Oh, massive amounts of data. Yes, >>Probably, I mean, as much as one probably could, now that I'm thinking about it. I mean, and especially with how far things have to travel. Bill, sticking with you, just to open us up, what technology here excites you the most about the future and that will make your job easier? Let's put it that way. >>To me, it's the accelerator technologies, right? So there's the limited, the limiting factor for, for us as scientists is how fast we can get an answer. And if we can get our answer faster through accelerated technologies, you know, with the support of the, of the nccs and the computing centers, but also the software engineers enabling that for us, then we can do more, right. And push the questions even further, you know, so once we've gotten fast enough to do what we want to do, there's always something next that we wanna look for. So, >>I mean, at nasa you have to exercise such patience, whether that be data, coming back, images from a rover, doesn't matter what it is. Sometimes there's a lot of time, days, hours, years, depending on the situation. Right? I really, I really admire that. What about you, Dan? What's got you really excited about the future here? So >>Bill talked about the, the accelerated technology, which is absolutely true and, and, and is needed to get us not to only to the point where we have the compute resources to do the simulations that Bill wants to do, and also do it in a energy efficient way. But it's really the software frameworks that go around that and the software frameworks, the technology that dealing with how to use those in an energy efficient and and most efficient way is extremely important. And that's some of the, you know, that's what I'm really here to try to understand better about is how can I support these scientists with not just the hardware, but the software frameworks by which they can be successful. >>Yeah. We've, we've had a lot of kind of philosophical discussion about this, the difference between the quantitative increases in power in computing that we're seeing versus the question of whether or not we need truly qualitative changes moving forward. Where do you see the limits of, of, of, you know, if you, if you're looking at the ability to gather more data and process more data more quickly, what you can do with that data changes when you're getting updates every second versus every month seems pretty obvious. Is there a, is there, but is there, is there a near term target that you have specifically where once you reach that target, if you weren't thinking ahead of that target, you'd kind of be going, Okay, well we solved that problem, we're getting the data in so fast that you can, you can ask me, what is the temperature in this area? And you can go, Oh, well, huh, an hour ago the data said this. Beyond that, do you need a qualitative change in our ability to process information and tease insight into out of chaos? Or do you just need more quantity to be able to get to the point where you can do things like predict weather six months in advance? What are, what are your thoughts on that? Yeah, >>It's an interesting question, right? And, and you ended it with predicting whether six months in advance, and actually I was thinking the other way, right? I was thinking going to finer and finer scales and shorter time scales when you talk about having data more frequently, right? So one of the things that I'm excited about as a modeler is going to hire resolution and representing smaller scale processes at nasa, we're, we're interested in observations that are global. So our models are global and we'd like to push those to as fine a resolution as possible to do things like severe storm predictions and so forth. So the faster we can get the data, the more data we can have, and that area would improve our ability to do that as well. So, >>And your background is in meteorology, right? >>Yes, I'm a meteorologist. >>Excellent. Okay. Yeah, yeah, >>Yeah. So, so I have to ask a question, and I'm sure all the audience cares about this. And I went through this when I was talking about the ghost satellites as well. What, what is it about weather that makes it so hard to predict? >>Oh, it's the classic chaos problem. The, the butterfly effects problem, and it's just true. You know, you always hear the story of a butterfly in Africa flaps, its rings and wings, and the weather changes in, in New York City, and it's just, computers are an excellent example of that, right? So we have a model of the earth, we can run it two times in a row and get the exact same answer, but if we flip a bit somewhere, then the answer changes 10 days later significantly. So it's a, it's a really interesting problem. So, >>Yeah. So do you have any issue with the fact that your colleague believes that butterflies are responsible for weather? No, I does that, does that, is it responsible for climate? Does that bother you at all? >>No, it doesn't. As a matter of fact, they actually run those butterfly like experi experiments within the systems where they do actually flip some bits and see what the uncertainties are that happen out 7, 8, 9 days out in advance to understand exactly what he's saying, to understand the uncertainties, but also the sensitivity with respect to the observations that they're taking. So >>Yeah, it's fascinating. It is. >>That is fascinating. Sticking with you for a second, Dan. So you're at the Center for Climate Simulation. Is that the center that's gonna help us navigate what happens over the next decade? >>Okay, so I, no one center is gonna help us navigate what's gonna happen over the next decade or the next 50 or a hundred years, right. It's gonna be everybody together. And I think NASA's role in that is really to pioneer the, the, the models that that bill and others are doing to understand what's gonna happen in not just the seasonal sub, but we also work with G, which is the God Institute for Space Studies. Yeah. Which does the decatal and, and the century long studies. Our, our job is to really help that research, understand what's happening with the client, but then feed that back into what observations we need to make next in order to better understand and better quantify the risks that we have to better quantify the mitigations that we can make to understand how and, and, and affect how the climate is gonna go for the future. So that's really what we trying to do. We're trying to do that research to understand the climate, understand what mitigations we can have, but also feedback into what observations we can make for the future. >>Yeah. And and what's the partnership ecosystem around that? You mentioned that it's gonna take all of us, I assume you work with a lot of >>Partners, Probably both of you. I mean, obviously the, the, the federal agencies work huge amounts together. Nasa, Noah is our huge partnerships. Sgs, a huge partnerships doe we've talked to doe several times this, so this, this this week already. So there's huge partnerships that go across the federal agency. We, we work also with Europeans as much as we can given the, the, the, you know, sort of the barriers of the countries and the financials. But we do collaborate as much as we can with, And the nice thing about NASA, I would say is the, all the observations that we take are public, they're paid for by the public. They're public, everybody can down them, anybody can down around the world. So that's also, and they're global measurements as Bill said, they're not just regional. >>Do you have, do you have specific, when you think about improving your ability to gain insights from data that that's being gathered? Yeah. Do you set out specific milestones that you're looking for? Like, you know, I hope by June of next year we will have achieved a place where we are able to accomplish X. Yeah. Do you, do you, Yeah. Bill, do you put, what, >>What milestones do we have here? So, yeah, I mean, do you have >>Yeah. Are, are you, are you sort of kept track of that way? Do you think of things like that? Like very specific things? Or is it just so fluid that as long as you're making progress towards the future, you feel okay? >>No, I would say we absolutely have milestones that we like to keep in track, especially from the modeling side of things, right? So whether it's observations that exist now that we want to use in our system, milestones to getting those observations integrated in, but also thinking even further ahead to the observations that we don't have yet. So we can use the models that we have today to simulate those kind of observations that we might want in the future that can help us do things that we can do right now. So those missions are, are aided by the work that we do at the GBO and, and the nccs, but, >>Okay, so if we, if we extrapolate really to the, to the what if future is really trying to understand the entire earth system as best as we can. So all the observations coming in, like you said, in in near real time, feeding that into an earth system model and to be able to predict short term, midterm or even long term predictions with, with some degree of certainty. And that may be things like climate change or it may be even more important, shorter term effects of, of severe weather. Yeah. Which is very important. And so we are trying to work towards that high resolution, immediate impact model that we can, that we can, you know, really share with the world and share those results as best, as best we can. >>Yeah. I, I have a quick, I have a quick follow up on that. I I bet we both did. >>So, so if you think about AI and ml, artificial intelligence and machine learning, something that, you know, people, people talk about a lot. Yeah. There's the concept of teaching a machine to go look for things, call it machine learning. A lot of it's machine teaching we're saying, you know, hit, you know, hit the rack on this side with a stick or the other side with the stick to get it to, to kind of go back and forth. Do you think that humans will be able to guide these systems moving forward enough to tease out the insights that we want? Or do you think we're gonna have to rely on what people think of as artificial intelligence to be able to go in with this massive amount of information with an almost infinite amount of variables and have the AI figure out that, you know what, it was the butterfly, It really was the butterfly. We all did models with it, but, but you understand the nuance that I'm saying. It's like we, we, we think we know what all the variables are and that it's chaotic because there's so many variables and there's so much data, but maybe there's something we're not taking into >>A account. Yeah, I I, I'm, I'm, I'm sure that's absolutely the case. And I'll, I'll start and let Bill, Bill jump in here. Yeah, there's a lot of nuances with a aiml. And so the, the, the, the real approach to get to where we want to be with this earth system model approach is a combination of both AI ML train models as best as we can and as unbiased way as we can. And there's a, there's a big conversation we have around that, but also with a physics or physical based model as well, Those two combined with the humans or the experts in the loop, we're not just gonna ask the artificial intelligence to predict anything and everything. The experts need to be in the loop to guide the training in as best as we, as, as we can in an unbiased, equitable way, but also interpret the results and not just give over to the ai. But that's the combination of that earth system model that we really wanna see. The future's a combination of AI l with physics based, >>But there's, there's a, there's an obvious place for a AI and ML in the modeling world that is in the parameterizations of the estimations that we have to do in our systems, right? So when we think about the earth system and modeling the earth system, there are many things like the equations of motions and thermodynamics that have fixed equations that we know how to solve on a computer. But there's a lot of things that happen physically in the atmosphere that we don't have equations for, and we have to estimate them. And machine learning through the use of high resolution models or observations in training the models to understand and, and represent that, yeah, that that's the place where it's really useful >>For us. There's so many factors, but >>We have to, but we have to make sure that we have the physics in that machine learning in those, in those training. So physics informed training isn't very important. So we're not just gonna go and let a model go off and do whatever it wants. It has to be constrained within physical constraints that the, that the experts know. >>Yeah. And with the wild amount of variables that affect our, our earth, quite frankly. Yeah, yeah. Which is geez. Which is insane. My god. So what's, what, what technology or what advancement needs to happen for your jobs to get easier, faster for our ability to predict to be even more successful than it is currently? >>You know, I think for me, the vision that I have for the future is that at some point, you know, all data is centrally located, essentially shared. We have our applications are then services that sit around all that data. I don't have to sit as a user and worry about, oh, is this all this data in place before I run my application? It's already there, it's already ready for me. My service is prepared and I just launch it out on that service. But that coupled with the performance that I need to get the result that I want in time. And I don't know when that's gonna happen, but at some point it might, you know, I don't know rooting for you, but that's, >>So there are, there are a lot of technologies we can talk about. What I'd like to mention is, is open science. So NASA is really trying to make a push and transformation towards open science. 2023 is gonna be the year of open science for nasa. And what does that mean? It means a lot of what Bill just said is that we have equity and fairness and accessibility and you can find the data, it's findability, it's fair data, you know, a fair findability accessibility reproducibility, and I forget what the eye stands for, but these are, these are tools and, and, and things that we need to, as, as a computing centers and including all the HC centers here, as well as the scientists need to support, to be as transparent as possible with the data sets and the, and the research that we're doing. And that's where I think is gonna be the best thing is if we can get this data out there that anybody can use in an equitable way and as transparent as possible, that's gonna eliminate, in my opinion, the bias over time because mistakes will be found and mistakes will be corrected over time. >>I love that. Yeah. The open source science end of this. No, it's great. And the more people that have access people I find in the academic world, especially people don't know what's going on in the private sector and vice versa. And so I love that you just brought that up. Closing question for you, because I suspect there might be some members of our audience who maybe have fantasized about working at nasa. You've both been working there for over a decade. Is it as cool as we all think of it? It is on the outside. >>I mean, it's, it's definitely pretty cool. >>You don't have to be modest about it, you know, >>I mean, just being at Goddard and being at the center where they build the James web web telescope and you can go to that clean room and see it, it's just fascinating. So it, it's really an amazing opportunity. >>Yeah. So NASA Goddard as a, as a center has, you know, information technologist, It has engineers, it has scientists, it has support staff, support team members. We have built more things, more instruments that have flown in this space than any other place in the world. The James Lab, we were part of that, part of a huge group of people that worked on James. We and James, we came through and was assembled in our, our, our clean room. It's one of the biggest clean rooms in, in, in the world. And we all took opportunities to go over and take selfies with this as they put those loveness mirrors on them. Yeah, it was awesome. It was amazing. And to see what the James we has done in such a short amount of time, the successes that they've gone through is just incredible. Now, I'm not a, I'm not a part of the James web team, but to be a, to be at the same center, to to listen to scientists like Bill talk about their work, to listen to scientists that, that talk about James, we, that's what's inspiring. And, and we get that all the time. >>And to have the opportunity to work with the astronauts that service the, the Hubble Telescope, you know, these things are, >>That's literally giving me goosebumps right now. I'm sitting over >>Here just, just an amazing opportunity. And woo. >>Well, Dan, Bill, thank you both so much for being on the show. I know it was a bit last minute, but I can guarantee we all got a lot out of it. David and I both, I know I speak for us in the whole cube audience, so thank you. We'll have you, anytime you wanna come talk science on the cube. Thank you all for tuning into our supercomputing footage here, live in Dallas. My name is Savannah Peterson. I feel cooler having sat next to these two gentlemen for the last 15 minutes and I hope you did too. We'll see you again soon.

>>Good morning, brilliant humans. Good afternoon or good evening, depending on your time zone. My name is Savannah Peterson and I'm here live with the Cube. We are at CubeCon in Detroit, Michigan. And joining me is my beautiful co-host, Lisa, how you feeling? Afternoon of day three. >>Afternoon day three. We've had such great conversations. We have's been fantastic. The momentum has just been going like this. I love it. >>Yes. You know, sometimes we feel a little low when we're at the end of a conference. Not today. Don't feel that that way at all, which is very exciting. Just like the guests that we have up for you next. Kind of an unexpected player when we think about technology. However, since every company, one of the themes is every company is trying to be a software company. I love that we're talking to I n G. Joining us today is Ty Evers and Arno vk. Welcome to the show gentlemen. Thank >>You very much. Glad to be you. Thank you. >>Yes, it's wonderful. All the way in from Amsterdam. Probably some of the farthest flying folks here for this adventure. Starting off. I forgot what's going on with the shirts guys. You match very well. Tell, tell everyone. >>Well these are our VR code shirts. VR code is basically the player of our company to get people interested as an IT person in banking. Right? Actually, people don't think banking is a good place to work as an IT professional, but actually this, and we are using the OC went with these nice logos to get it attention. >>I love that. So let's actually, let's just talk about that for a second. Why is it such an exciting role to be working in technology at a company like I N G or traditional bank? >>I N G is a challenging environment. That's how do you make an engineer happy, basically give them a problem to solve. So we have lots and lots of problems to solve. So that makes it challenging. But yeah, also rewarding. And you can say a lot of things about banks and with looking at the IT perspective, we are doing amazing things in I and that's what we talked about. Can >>You, can you tell us any of those amazing things or are they secrets? >>Think we talked about last Tuesday at S shift commons conference. Yeah, so we had two, two presentations I presented with my coho sand on my journey over the last three years. So what has IG done? Basically building a secure container hosting platform. Yeah. How do we live a banking cot with cloud native technology and together with our coho young villa presented actually showed it by demo making life and >>Awesome >>In person. So we were not just presenting, >>It's not all smoke and mirrors. It's >>Not smoke and mirror, which we're not presenting our fufu marketing block now. We actually doing it today. And that's what we wanted to share here. >>Well, and as consumers we expect we can access our banking on any device 24 by seven. I wanna be able to do all my transactions in a way that I know is secure. Obviously security's a huge thing there, but talk about I n G Bank aren't always been around for a very long time. Talk about this financial institution as a software company. Really obviously a lot of challenges to solve, a lot of opportunity. But talk about what it's like working for a history and bank that's really now a tech company. >>Yes. It's been really changing as a bank to a tech company. Yeah. We have a lot of developers and operators and we do deliver offer. We OnPrem, we run in the public. So we have a huge engineers and people around to make our software. Yes. And I am responsible for the i Container Ocean platform and we deliver that the name space as a surface and as a real, real secure environment. So our developers, all our developers in, I can request it, but they only get a name space. Yeah, that's very important there. They >>Have >>Resources and all sort of things. Yeah. And it is, they cannot access it. They can only access it by one wifi. So, >>So Lisa and I were chatting before we brought you up here. Name space as a service. This is a newer term for us. Educate us. What does that mean? >>Basically it means we don't give a full cluster to our consumers, right? We only give them basically cpu, memory networking. That's all they need to host application. Everything else we abstract away. And especially in a banking context where compliance is a big thing, you don't need to do compliance for an entire s clusterized developer. It's really saves development time for the colleagues in the bank. It >>Decreases the complexity of projects, which is a huge theme here, especially at scale. I can imagine. I mean, my gosh, you're serving so many different people, it probably saves you time. Let's talk about regulation. What, how challenging is that for you as technologists to balance in all the regulations around banking and FinTech? It's, it's, it's, it's not like some of these kind of wild, wild west industries where we can just go out and play and prototype and do whatever we want. There's a lot of >>Rules. There's a lot of rules. And the problem is you have legislation and you have the real world. Right. And you have to find something in, they're >>Not the same thing. >>You have to find something in between with both parties on the stands and cannot adhere to. Yeah. So the challenge we had, basically we had to wide our, in our own container security standards to prove that the things we were doing were the white things to be in control as a bank because there was no market standard for container security. So basically we took some input from this. So n did a lot of good work. We basically added some things on top to be valid for a bank in Europe. So yeah, that's what we did. And the nice thing is today we take all the boxes we defined back in 2019. >>Hey, so you what it's, I guess, I guess the rules are a little bit easier when you get to help define them. Yep. Yeah. That it feels like a very good strategic call >>And they makes sense. Yeah. Right. Because the hardest problem is try to be compliant for something which doesn't make sense. Right, >>Right. Arnold, talk about, let's double click on namespace as a service. You talked about what that is, but give us a little bit of information on why I N G really believes this is the right approach for this company. >>It's protects for the security that developers doing things they don't shoot. Yeah. They cannot access their store anymore when it is running in production. And that is the most, most important. That is, it is immutable running in our platform. >>Excellent. Talk about both of you. How long have you, have you both been at I n G for a long time? >>I've been with I N G since September, 2001. So that's more than 20 years >>Now. Long time. Ana, what about you? >>Before 2000 already before. >>So both of your comment on that's a long time. Yeah. Talk about the culture of innovation that's at I N G to be able to move at such speed and be groundbreaking in what you're, how you're using technology, what, what's the appetite like at the bank to embrace new and emerging technologies? >>So we are really looking, basically the, the mantra of the bank is to help our customers get a step ahead in life and in business. And we do that by one superior customer service and secondly, sustainability at the heart. So anything which contributes to those targets, you can go to your manager and if you can make goods case why it contributes most of the cases you get some time or some budgets or even some additional colleagues to help you out and give it a try require from a culture perspective required open to trying things out before we reach production. Once you go to production. Yeah. Then we are back to being a bank and you need to take all the boxes to make really sure that we are confident with our customers data and basically we're still a bank but a lot of is possible. >>A lot. It is possible. And there's the customer on the other end who's expecting, like I said earlier, that they can access their data any time that they want, be able to do any transaction they want, making sure the content that's delivered to them is relevant, that it's secure. Obviously with, that's the biggest challenge especially is we think about how many generations are alive today and and those that aren't tech savvy. Yeah. Have challenges with that. Talk about what the bank's dedication is to ensuring from a security perspective that its customers don't have anything to worry about. >>That's always a thin line between security and the user experience. So I n g, like every other bank needs to make choices. Yes. We want the really ease of customers and take the risk that somebody abuses it or do we make it really, really secure and alienate part of our customer base. And that's an ongoing, that's a, that's a a hard, >>It's a trade off. That's >>A line. >>So it's really hard. Interesting part is in Netherlands we had some debates about banks closing down locations, but the moment we introduced our mobile weapon iPads, basically the debates became a lot quieter because a lot of elderly people couldn't work with an iPhone. It turned out they were perfectly fine with a well-designed iPad app to do their banking. Really? >>Okay. >>But that's already learning from like 15 years ago. >>What was the, what was the product roadmap on that? So how, I mean I can imagine you released a mobile app, you're not really thinking that. >>That's basically, I think that was a heavy coincidence. We just, Yeah, okay. Went out to design a very good mobile app. Yeah. And then looking out afterwards at the statistics we say, hey, who was using this way? We've got somebody who's signing on and I dunno the exact age, but it was something like somebody of 90 plus who signed on to use that mobile app. >>Wow. Wow. I mean you really are the five different generations living and working right now. Designing technology. Everybody has to go to the bank whether we are fans of our bank or we're not. Although now I'm thinking about IG as a bank in general. Y'all have a a very good attitude about it. What has kept you at the company for over 20 years? That is we, we see people move around, especially in this technology industry. Yes. Yeah. You know, every two to three years. Sometimes obviously you're in positions of leadership, they're obviously taking good care of you. But I mean multiple decades. Why have you stuck? >>Well first I didn't have the same job in I N D for two decades. Nice. So I went around the infrastructure domain. I did storage initially I did security, I did solution design and in the end I ended up in enterprise architecture. So yeah, it's not like I stuck 20 years in the same role. So every so years >>Go up the ladder but also grow your own skill sets. >>Explore. Yeah. >>So basically I think that's what's every, everybody should be thinking in these days. If you're in a cloud head industry, if you're good at it, you can out quite a nice salary. But it also means that you have some kind of obligation to society to make a difference. And I think, yeah, >>I wouldn't say that everybody feels that way. I >>Need to make a difference with I N G A difference for being more available to our consumers, be more secure to, to our consumers. I, I think that's what's driving me to stick with the company. >>What about you R Now? >>Yes, for me it's very important. Every two, three years are doing new things. I can work with the latest technology so I become really, really innovative so that it is the place to be. >>Yeah. You sort of get that rotation every two to three years with the different tools that you're using. Speaking of or here we're at Cuan, we're talking cloud native, we're talking Kubernetes. Do you think it's possible to, I'm coming back to the regulations. Do you think it's possible to get to banking grade security with cloud native Tech? >>Initially I said we would be at least as secure traditional la but last Tuesday we've proven we can get more secure than situational it. So yeah, definitely. Yes. >>Awesome. I mean, sounds like you proved it to yourself too, which is really saying something. >>Well we actually have Penta results and of course I cannot divulge those, but I about pretty good. >>Can you define, I wanna kind of double book on thanking great security, define what that is, thanking great security and how could other industries aim to Yeah, >>Hit that, that >>Standard. I want security everywhere. Especially my bank. The >>Architecture is zero privilege. So you hear a lot about lease privilege in all the security talks. That's not what you should be aiming for. Zero privilege is what you should be aiming for. And once you're at zero privileged environments, okay, who can leak data because no natural person has access to it. Even if you have somebody invading your infrastructure, there are no privileges. They cannot do privilege escalations. Yeah. So the answer for me is really clear. If you are handling customer data, if you're and customer funds aim for zero privilege architecture, >>What, what are you most excited about next? What's next for you guys? What's next for I n G? What are we gonna be talking about when we're chatting to you Right here? Atan next year or in Amsterdam actually, since we're headed that way in the spring, which is fun. Yes. >>Happy to be your host in Amsterdam. The >>Other way around. We're holding you to that. You've talked about how fun the culture is. Now you're gonna ask, she and I we need, but we need the tee-shirts. We, we obviously need a matching outfit. >>Definitely. We'll arrange some teachers for you as well. Yeah, no, for me, two highlights from this com. The first one was kcp. That can potentially be a paradigm change on how we deal with workloads on Kubernetes. So that's very interesting. I don't know if you see any implementations by next year, but it's definitely something. Looks >>Like we had them on the show as well. Yeah. So it's, it's very fun. I'm sure, I'm sure they'll be very flattered that you just just said. What about you Arnoldo that got you most excited? >>The most important for me was talking to a lot of Asian is other people. What if they thinking how we go forward? So the, the, the community and talk to each other. And also we found those and people how we go forward. >>Yeah, that's been a big thing for us here on the cube and just the energy, the morale. I mean the open source community is so collaborative. It creates an entirely different ethos. Arna. Ty, thank you so much for being here. It's wonderful to have you and hear what I n g is doing in the technology space. Lisa, always a pleasure to co-host with you. Of course. And thank you Cube fans for hanging out with us here on day three of Cuban Live from Detroit, Michigan. My name is Savannah Peterson and we'll see you up next for a great chat coming soon.

>>Keon Cloud Native Con kicks off in Detroit on October 24th, and we're pleased to have Stewart Miniman, who's the director of Market Insights, hi, at, for hybrid platforms at Red Hat back in the studio to help us understand the key trends to look for at the events. Do welcome back, like old, old, old >>Home. Thank you, David. It's great to, great to see you and always love doing these previews, even though Dave, come on. How many years have I told you Cloud native con, It's a hoodie crowd. They're gonna totally call you out for where in a tie and things like that. I, I know you want to be an ESPN sportscaster, but you know, I I, I, I still don't think even after, you know, this show's been around for so many years that there's gonna be too many ties into Troy. I >>Know I left the hoodie in my off, I'm sorry folks, but hey, we'll just have to go for it. Okay. Containers generally, and Kubernetes specifically continue to show very strong spending momentum in the ETR survey data. So let's bring up this slide that shows the ETR sectors, all the sectors in the tax taxonomy with net score or spending velocity in the vertical axis and pervasiveness on the horizontal axis. Now, that red dotted line that you see, that marks the elevated 40% mark, anything above that is considered highly elevated in terms of momentum. Now, for years, the big four areas of momentum that shine above all the rest have been cloud containers, rpa, and ML slash ai for the first time in 10 quarters, ML and AI and RPA have dropped below the 40% line, leaving only cloud and containers in rarefied air. Now, Stu, I'm sure this data doesn't surprise you, but what do you make of this? >>Yeah, well, well, Dave, I, I did an interview with at Deepak who owns all the container and open source activity at Amazon earlier this year, and his comment was, the default deployment mechanism in Amazon is containers. So when I look at your data and I see containers and cloud going in sync, yeah, that, that's, that's how we see things. We're helping lots of customers in their overall adoption. And this cloud native ecosystem is still, you know, we're still in that Cambridge explosion of new projects, new opportunities, AI's a great workload for these type type of technologies. So it's really becoming pervasive in the marketplace. >>And, and I feel like the cloud and containers go hand in hand, so it's not surprising to see those two above >>The 40%. You know, there, there's nothing to say that, Look, can I run my containers in my data center and not do the public cloud? Sure. But in the public cloud, the default is the container. And one of the hot discussions we've been having in this ecosystem for a number of years is edge computing. And of course, you know, I want something that that's small and lightweight and can do things really fast. A lot of times it's an AI workload out there, and containers is a great fit at the edge too. So wherever it goes, containers is a good fit, which has been keeping my group at Red Hat pretty busy. >>So let's talk about some of those high level stats that we put together and preview for the event. So it's really around the adoption of open source software and Kubernetes. Here's, you know, a few fun facts. So according to the state of enterprise open source report, which was published by Red Hat, although it was based on a blind survey, nobody knew that that Red Hat was, you know, initiating it. 80% of IT execs expect to increase their use of enterprise open source software. Now, the CNCF community has currently more than 120,000 developers. That's insane when you think about that developer resource. 73% of organizations in the most recent CNCF annual survey are using Kubernetes. Now, despite the momentum, according to that same Red Hat survey, adoption barriers remain for some organizations. Stu, I'd love you to talk about this specifically around skill sets, and then we've highlighted some of the other trends that we expect to see at the event around Stu. I'd love to, again, your, get your thoughts on the preview. You've done a number of these events, automation, security, governance, governance at scale, edge deployments, which you just mentioned among others. Now Kubernetes is eight years old, and I always hear people talking about there's something coming beyond Kubernetes, but it looks like we're just getting started. Yeah, >>Dave, It, it is still relatively early days. The CMC F survey, I think said, you know, 96% of companies when they, when CMC F surveyed them last year, were either deploying Kubernetes or had plans to deploy it. But when I talked to enterprises, nobody has said like, Hey, we've got every group on board and all of our applications are on. It is a multi-year journey for most companies and plenty of them. If you, you look at the general adoption of technology, we're still working through kind of that early majority. We, you know, passed the, the chasm a couple of years ago. But to a point, you and I we're talking about this ecosystem, there are plenty of people in this ecosystem that could care less about containers and Kubernetes. Lots of conversations at this show won't even talk about Kubernetes. You've got, you know, big security group that's in there. >>You've got, you know, certain workloads like we talked about, you know, AI and ml and that are in there. And automation absolutely is playing a, a good role in what's going on here. So in some ways, Kubernetes kind of takes a, a backseat because it is table stakes at this point. So lots of people involved in it, lots of activities still going on. I mean, we're still at a cadence of three times a year now. We slowed it down from four times a year as an industry, but there's, there's still lots of innovation happening, lots of adoption, and oh my gosh, Dave, I mean, there's just no shortage of new projects and new people getting involved. And what's phenomenal about it is there's, you know, end user practitioners that aren't just contributing. But many of the projects were spawned out of work by the likes of Intuit and Spotify and, and many others that created some of the projects that sit alongside or above the, the, you know, the container orchestration itself. >>So before we talked about some of that, it's, it's kind of interesting. It's like Kubernetes is the big dog, right? And it's, it's kind of maturing after, you know, eight years, but it's still important. I wanna share another data point that underscores the traction that containers generally are getting in Kubernetes specifically have, So this is data from the latest ETR survey and shows the spending breakdown for Kubernetes in the ETR data set for it's cut for respondents with 50 or more citations in, in by the IT practitioners that lime green is new adoptions, the forest green is spending 6% or more relative to last year. The gray is flat spending year on year, and those little pink bars, that's 6% or down spending, and the bright red is retirements. So they're leaving the platform. And the blue dots are net score, which is derived by subtracting the reds from the greens. And the yellow dots are pervasiveness in the survey relative to the sector. So the big takeaway here is that there is virtually no red, essentially zero churn across all sectors, large companies, public companies, private firms, telcos, finance, insurance, et cetera. So again, sometimes I hear this things beyond Kubernetes, you've mentioned several, but it feels like Kubernetes is still a driving force, but a lot of other projects around Kubernetes, which we're gonna hear about at the show. >>Yeah. So, so, so Dave, right? First of all, there was for a number of years, like, oh wait, you know, don't waste your time on, on containers because serverless is gonna rule the world. Well, serverless is now a little bit of a broader term. Can I do a serverless viewpoint for my developers that they don't need to think about the infrastructure but still have containers underneath it? Absolutely. So our friends at Amazon have a solution called Fargate, their proprietary offering to kind of hide that piece of it. And in the open source world, there's a project called Can Native, I think it's the second or third can Native Con's gonna happen at the cncf. And even if you use this, I can still call things over on Lambda and use some of those functions. So we know Dave, it is additive and nothing ever dominates the entire world and nothing ever dies. >>So we have, we have a long runway of activities still to go on in containers and Kubernetes. We're always looking for what that next thing is. And what's great about this ecosystem is most of it tends to be additive and plug into the pieces there, there's certain tools that, you know, span beyond what can happen in the container world and aren't limited to it. And there's others that are specific for it. And to talk about the industries, Dave, you know, I love, we we have, we have a community event that we run that's gonna happen at Cubans called OpenShift Commons. And when you look at like, who's speaking there? Oh, we've got, you know, for Lockheed Martin, University of Michigan and I g Bank all speaking there. So you look and it's like, okay, cool, I've got automotive, I've got, you know, public sector, I've got, you know, university education and I've got finance. So all of you know, there is not an industry that is not touched by this. And the general wave of software adoption is the reason why, you know, not just adoption, but the creation of new software is one of the differentiators for companies. And that is what, that's the reason why I do containers, isn't because it's some cool technology and Kubernetes is great to put on my resume, but that it can actually accelerate my developers and help me create technology that makes me respond to my business and my ultimate end users. Well, >>And you know, as you know, we've been talking about the Supercloud a lot and the Kubernetes is clearly enabler to, to Supercloud, but I wanted to go back, you and John Furrier have done so many of, you know, the, the cube cons, but but go back to Docker con before Kubernetes was even a thing. And so you sort of saw this, you know, grow. I think there's what, how many projects are in CNCF now? I mean, hundreds. Hundreds, okay. And so you're, Will we hear things in Detroit, things like, you know, new projects like, you know, Argo and capabilities around SI store and things like that? Well, you're gonna hear a lot about that. Or is it just too much to cover? >>So I, I mean the, the good news, Dave, is that the CNCF really is, is a good steward for this community and new things got in get in. So there's so much going on with the existing projects that some of the new ones sometimes have a little bit of a harder time making a little bit of buzz. One of the more interesting ones is a project that's been around for a while that I think back to the first couple of Cube Cuban that John and I did service Mesh and Istio, which was created by Google, but lived under basically a, I guess you would say a Google dominated governance for a number of years is now finally under the CNCF Foundation. So I talked to a number of companies over the years and definitely many of the contributors over the years that didn't love that it was a Google Run thing, and now it is finally part. >>So just like Kubernetes is, we have SEO and also can Native that I mentioned before also came outta Google and those are all in the cncf. So will there be new projects? Yes. The CNCF is sometimes they, they do matchmaking. So in some of the observability space, there were a couple of projects that they said, Hey, maybe you can go merge down the road. And they ended up doing that. So there's still you, you look at all these projects and if I was an end user saying, Oh my God, there is so much change and so many projects, you know, I can't spend the time in the effort to learn about all of these. And that's one of the challenges and something obviously at Red Hat, we spend a lot of time figuring out, you know, not to make winners, but which are the things that customers need, Where can we help make them run in production for our, our customers and, and help bring some stability and a little bit of security for the overall ecosystem. >>Well, speaking of security, security and, and skill sets, we've talked about those two things and they sort of go hand in hand when I go to security events. I mean, we're at reinforced last summer, we were just recently at the CrowdStrike event. A lot of the discussion is sort of best practice because it's so complicated. And, and, and will you, I presume you're gonna hear a lot of that here because security securing containers now, you know, the whole shift left thing and shield right is, is a complicated matter, especially when you saw with the earlier data from the Red Hat survey, the the gaps are around skill sets. People don't have the skill. So should we expect to hear a lot about that, A lot of sort of how to, how to take advantage of some of these new capabilities? >>Yeah, Dave, absolutely. So, you know, one of the conversations going on in the community right now is, you know, has DevOps maybe played out as we expect to see it? There's a newer term called platform engineering, and how much do I need to do there? Something that I, I know your, your team's written a lot about Dave, is how much do you need to know versus what can you shift to just a platform or a service that I can consume? I've talked a number of times with you since I've been at Red Hat about the cloud services that we offer. So you want to use our offering in the public cloud. Our first recommendation is, hey, we've got cloud services, how much Kubernetes do you really want to learn versus you want to do what you can build on top of it, modernize the pieces and have less running the plumbing and electric and more, you know, taking advantage of the, the technologies there. So that's a big thing we've seen, you know, we've got a big SRE team that can manage that for use so that you have to spend less time worrying about what really is un differentiated heavy lifting and spend more time on what's important to your business and your >>Customers. So, and that's, and that's through a managed service. >>Yeah, absolutely. >>That whole space is just taken off. All right, Stu I'll give you the final word. You know, what are you excited about for, for, for this upcoming event and Detroit? Interesting choice of venue? Yeah, >>Look, first of off, easy flight. I've, I've never been to Detroit, so I'm, I'm willing to give it a shot and hopefully, you know, that awesome airport. There's some, some, some good things there to learn. The show itself is really a choose your own adventure because there's so much going on. The main show of QAN and cloud Native Con is Wednesday through Friday, but a lot of a really interesting stuff happens on Monday and Tuesday. So we talked about things like OpenShift Commons in the security space. There's cloud Native Security Day, which is actually two days and a SIG store event. There, there's a get up show, there's, you know, k native day. There's so many things that if you want to go deep on a topic, you can go spend like a workshop in some of those you can get hands on to. And then at the show itself, there's so much, and again, you can learn from your peers. >>So it was good to see we had, during the pandemic, it tilted a little bit more vendor heavy because I think most practitioners were pretty busy focused on what they could work on and less, okay, hey, I'm gonna put together a presentation and maybe I'm restricted at going to a show. Yeah, not, we definitely saw that last year when I went to LA I was disappointed how few customer sessions there were. It, it's back when I go look through the schedule now there's way more end users sharing their stories and it, it's phenomenal to see that. And the hallway track, Dave, I didn't go to Valencia, but I hear it was really hopping felt way more like it was pre pandemic. And while there's a few people that probably won't come because Detroit, we think there's, what we've heard and what I've heard from the CNCF team is they are expecting a sizable group up there. I know a lot of the hotels right near the, where it's being held are all sold out. So it should be, should be a lot of fun. Good thing I'm speaking on an edge panel. First time I get to be a speaker at the show, Dave, it's kind of interesting to be a little bit of a different role at the show. >>So yeah, Detroit's super convenient, as I said. Awesome. Airports too. Good luck at the show. So it's a full week. The cube will be there for three days, Tuesday, Wednesday, Thursday. Thanks for coming. >>Wednesday, Thursday, Friday, sorry, >>Wednesday, Thursday, Friday is the cube, right? So thank you for that. >>And, and no ties from the host, >>No ties, only hoodies. All right Stu, thanks. Appreciate you coming in. Awesome. And thank you for watching this preview of CubeCon plus cloud Native Con with at Stu, which again starts the 24th of October, three days of broadcasting. Go to the cube.net and you can see all the action. We'll see you there.

>>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.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>>The Cube Presents HPD Discovered 2020 >>two. >>Brought to You by H. P E >>Good >>Morning Live from the Venetian Expo Centre Lisa Martin Day Volonte Day two of the Cubes Coverage of HP Discover 22 We've had some great conversations yesterday. Today, full day, a content coming your way. We've got one of our alumni back with us. Neil MacDonald joins us, the executive vice president and general manager of Compute at HPD Neale, Great to have you back on the Cube. >>It's great to be back. And how cool is it to be able to do this face to face again instead of on zoom. Right. So >>great. Great. The keynote yesterday absolutely packed, so refreshing to see that many people eager to hear what HP has been doing. It's been three years since we've all gotten together in person. >>It is, and we've been busy. We've been busy. We've got to share some great news yesterday about some of the work that we're doing with HB Green Lake Cloud Platform and really bringing together all the capabilities across the company in a very unified, cohesive way to enable our customers to embrace that as a service experience we committed to Antonio three years ago, said we were gonna deliver everything we do as a company as a service through Green Lake and we've done it. And it's fantastic to see the momentum that that's really building and how it's breaking down the silos from different types of infrastructure and offer to really create integrated solutions for our customers. So that's been a lot of fun. >>Give us the scope of your role, your areas of responsibility. And then I'd love to hear some feedback. You've been a couple of days here around customers. What some of the feedback help us understand that. >>So at HP, I lead the Compute business, which is our largest business. That includes our hardware and software and services in the compute space. Both, um, what flows through the green late model, but also what throws flows through a traditional purchase model. So, um, that's, uh, that's about $13 billion business for the company and the core of so much of what we do, and it's a real honour to be leading a business that's such a a legacy in a franchise with with 30 years of innovation for our customers in an ocean of followers. Um and it's great to be able to start to share some of the next chapters in that with our customers this week. >>Well, it's almost half the business H p e and as we've talked about, it's an awesome time to be in the computer business. What are you seeing in terms of the trends? Obviously you're all in on as a service. But some customers say, Tell me I got a lot of capital. Yeah, absolutely. I'm fine with Capex. What are you hearing from customers in that regard? And presumably you're happy to sell them in a kind of Capex model? >>Absolutely. And in the current environment, in particular with with some of the economic headwinds that we're starting to stare down here, it's really important for organisations to continue to transform digitally but to be able to match their investments with the revenues as they're building new services and new capabilities. And for some organisations, the challenge of investing all the Capex up front is a big lift and there's quite a delay before they can really monetise all of that. So the power of HP Green Lake is enabling them to match their investment in the infrastructure on a pay as you go basis with the actual revenue they're going to generate from their new capability. So for lots of people that works. But for many other customers, it's it's much more palatable to continue in a Capex purchase, but and we're delighted to do that. A lot of my business still is in that mode. What's changing the or what are the needs, whether you're in the green light environment or in the Capex environment? Um, increasingly, the edge has become a bigger and bigger part of all of our worlds, right, the edges where we all live and work. We've all seen over the last couple of years enormous change in how that work experience and how the shape of businesses has changed, and that creates some challenges for infrastructure. So one of the things that we've announced and we shared some more details of this week is HP Green Light for Computer Ops Management, which is a location agnostic, cloud based management set up that enables you to automate and lifecycle, manage your physical compute infrastructure wherever it lies, so that might be in a distributed environment in hotel locations or out at the edge for so much more data is now being gathered and has to be computed on. So we're really excited about that. And the great thing is because it's fully integrated with HP. Green Light Cloud Platform is in there alongside the storage, alongside the connectivity alongside all the other capabilities. And we can bring those together in a very cohesive infrastructure view for our customers and then build workloads and services and tops. And that's that's really exciting. How have >>your customer conversations evolved, especially over the last couple of years as the edge has exploded? But we've been living in such uncertain times. Are you seeing a change there in the stakeholders rising up the C suite stack in terms of how do we really fine tune this? Because we've got to be competitive. We've got to be a data company. >>Well, that's so true because everybody has seen seen data as a currency and is desperately innovating and Modernising their business model, and with it, the underlying infrastructure and how they think about development. And nowhere is that truer than in enterprises that really becoming digital. First, organisations more and more companies are doing their own in house full stack, cloud native development and pivoting hard from a more traditional view of in house enterprise i t. And in that regard, >>let's >>start to look a lot like a Saas company or a service provider in terms of the needs of the infrastructure you want linear performance scaling. You want to be very sensitive not just to the cost, as you call it, but also to the environmental cost and the power efficiency. And so yesterday we were really thrilled to announce the HBP Reliant are all 300 General Live in, which is the first of our general living platforms. And that's in partnership with Ampere is the first of several things that we're gonna go do together. We're looking forward to building out the rest of our Gen 11 portfolio broadly with all of our industry partners in the in the coming quarters. But we're thrilled about the feedback that we're starting to get from some of our customers about the gains in power efficiency that they're getting from using this new server line that we've developed with amber. >>So, you know, this is an area that I'm very interested in what I write about this a lot. So tell us the critical aspects of Gen 11, where ampere fits, is it is it being used for primarily offloads and there's a core share with us. So >>if you look at the opportunity here is really as a core compute tool for organisations that are doing that in house full snack cloud native development and in that environment, being able to do it with great power efficiency at a great cost point is the great combination. The maturity of the ecosystem, um, is really, really improving to the point where is much, much more accessible for those loads? And if you consider how the infrastructure evolves underneath it, the gains that you get from power efficiency multiply. It's a TCO benefit. It's obviously an environmental benefit, and we all have much, much more to do as an industry on that journey. But every little helps, and we're really excited about being able to bring that to market. The other thing that we've done is recognising the value that we bring in the prelim experience, everything with our integrated lights out management, all of the security, the, uh, hardware root of trust, the secure boot chains, all of that Reliant family values we brought to that platform, just as we do with our others. But we've also recognised that for some of our service provider customers, there's a lot of interest in leveraging open BMC and being able to integrate the management plane and control that in house and tie it to whatever orchestrations being done in the service product. So we have full support for open BMC out of the box out of the gate with Janna Levin. And that's one of the ways that we're evolving. Are offering to meet our customers where they are, including not just the assassin service providers but the enterprises who are starting to adopt more and more of those practises as they build out digital. First, >>tell us more about the architecture. If you would kneel. I mean, so where does ampere and that partnership add value? That's incremental to what you what you might think is a traditional server architecture. How's that evolving? >>Well, it's another alternative for certain workloads in that full stack in house proud Native Development model. Um, it's another choice. It's another option and something that's very excited about >>That's the right course for the horse, for the course that was back in internal development because it's just more efficient. It's lower power, more sustainable. All those things exactly. >>And the wonderful thing for us in the uh in this juncture in the market is there is so much architectural innovation. There are so many innovators out there in the industry creating different optimizations in technology with the lesson silicon or other aspects of the system. And that gives us a much broader palette to paint from as we meet our customers' needs as their businesses involving the requirements are evolving, we can be much more creative as we bring this all together. It's a real thrill to be able to bring some of these technologies into the HP reliant space because we've always felt that compute matters. We've always known that hardware matters, and we've been leading and innovating and meeting these needs as they've evolved over the decades, and it's really fun to be able to continue to do that. Hardware still >>matters. It doesn't matter. We know that here on the Cube, talk about the influence of the customer with so much architectural innovation. There's a lot of choice for customers in every industry. When you're in customer conversations, how are you helping them make decisions? One of the key differentiators that you articulate that's going to really help them achieve outcomes that they have to achieve? >>Well, I think that's exactly as you say. It's about the outcome. Too often, I think the conversation can get down into the lower level details of component, tree and technology and our philosophy. HP has always been focused on what it is that the customer is trying to achieve. How are they trying to serve their customers? What are their needs? And then we can bring an opinionated point of view on the best way to solve that problem, whether that's recommendations on the particular Capex, infrastructure and architecture to build or increasingly, the opportunity to serve that through HP Green Lake, either as hard or as a service. Or is HP Green Lake services further up the stack? Because when you start talking about what is the outcome you're trying to achieve, you have you have a much, much better opportunity to focus the technology to serve the business and not get wrapped up in managing the infrastructure and that's what we love to do. >>So where? Give us the telescope vision. Maybe not to tell a binocular vision as to where compute is going. We're clearly seeing more diversity in silicon. Uh, it's not just a you know x 86 CPU world anymore. There's all these other supporting components new workloads coming in. Where do you you mentioned Edge, whole new ballgame ai inference sing. And that was kind of new workloads, offloads and things of that. Where do you see it all going in the next 3 to 5 years? >>I think it's gonna be really, really exciting time because more and more of our data is getting captured to the edge. And because of the experiences that companies are trying to deliver and organisations are trying to deliver that requires more and more stories are more and more compute at the edge. The edge is not just about connectivity, and again, that's why with the F B green light cloud platform, the power of bringing together the connectivity with the compute with the storage with the other capabilities in that integrated way gives us the ability to serve that combined need at the edge in a very, very compelling way. The room moves a lot of friction and a lot of work for our customers. But as you see that happen, you're going to see more and more combining of functionalities. The silos are going to start to break down between different classes of building block in the data centre, and you've already seen shifts with more and more software to find more and more hybrid offerings running across a computing substrate. But perhaps delivering storage services are analytic services or other workloads, and you're gonna see that to conduct that continue to evolve. So it's gonna be very fun over the next few years to see that, uh, that diversification and a much more opinionated set of offers for particular use cases and workloads and at our job and value is going to be simplifying that complexity because choices great right up to the point where you're paralysed by too many choices. So the wonderful thing about the world that's been done here is that we're able to bring that opinionated point of view and help guide, and again it's all about starting with what are you trying to achieve. What are the outcomes you're trying to deliver? And if you start there were having a great time helping our customers find the right path forward. >>Wow, it sounds like a fun job. Talk to me about, you know, maybe one of your favourite examples that you really think articulates the value of of the choice and the opportunities that HP can deliver to customers, maybe favourite customer example where you think we really nailed it here and they're achieving some incredible outcomes. >>Well, we're really excited about this week as I was chatting with the CEO of Cloud Sigma, which is a global ideas and pass provider who's actually been using our new HP per client moral 300 general live in Are you on purpose? Server line? And, uh, their CEO was reporting to me yesterday that based on his benchmarking, they're seeing a significant improvement in power efficiency, and that's that's that's cool to an engineer. But what's even better is the next thing, he said. That's enabling them to deliver better cost to their customers and advanced their sustainability goals, which is such a core part of what we as an industry and we as society are going to have to continue to make stepwise progress against over the next decade in order to confront those challenges in the environment so that that's that's really fulfilling, not just to see the tech, which is always interesting to an engineer but actually see the impact that it's having an enabling that outcome foreclosed signal >>so many customers, including Cloud Sigma and customers in every industry. E S G is an incredibly important initiative. And so it's vital for companies that have a core focus on E. S G to partner with companies like HP who will help them facilitate that actually demonstrate outcomes to their own users. >>It's such an important journey and it's gonna be a journey of many steps together. But I think it's one of the most critical partnerships that as an industry and as an ecosystem, we still have a lot of work to do and we have to stay focused on it every day, continuing, moving the bar. >>You >>know, to your point about E. S G. You see these E s G reports. Now that they're unbelievable, the data that is in them and the responsibility that organisations mid and large organisations have to actually publish that and be held accountable. It's actually kind of daunting, but there's a lot of investments going on there. You're absolutely right. The >>accountability is key, and it's it's it's necessary to have an accountability partner and ecosystem that can facilitate that. Exactly. >>We just published last week our Own Living Progress report this year, talking about some of the steps that we're making the commitments that we pulled in in time. Um, and we're looking forward to continue to work on that with our customers and with the industry, because it's so critical that we make faster progress together on that >>last question. What's your favourite comment that you've heard the last couple of days being back in person with about 8000 customers, partners and execs? It's >>not. It's not the common. It's the sparkles in the eyes. It's the energy. It is so great to be back together, face to face. I think we, uh, we've soldiered through a couple of tough years. We've done a lot of things remotely together, but there's no substitute for being back together, and the energy is just palpable and it's it's fantastic to be able to share some of what we've been up to in the interim and see the excitement about getting adopted by customers and partners. >>I agree the energy has been fantastic. We were talking about that yesterday. You brought it today, Neil, Thank you so much for joining us. We're excited about Antonio coming up next, going to unpack all the announcements. Really good customers. Perspective from the top of H P E for Neil and Dave Volonte. I'm Lisa Martin joins us in just a few minutes as the CEO of HP, Antonio Neary joins us next.

>>Hey everyone. Welcome back to the cube. Lisa Martin here with Dave ante, we're covering snowflake summit 22. This is Dave two of our wall to wall cube coverage of three days. We've been talking with a lot of customers partners, and we've got some more partners to talk with us. Next. Informatica two of our guests are back with us on the program. Rick TA Daniels joins us the G P global ecosystems and technology at Informatica and Peter COO vice president and chief strategist banking and financial services. Welcome guys. >>Thank you guys. Thanks for having us, Peter, >>Talk to us about what some of the trends are that you're seeing in the financial services space with respect to cloud and data and AI. >>Absolutely. You know, I'd say 10 years ago, the conversation around cloud was what is that? Right? How do we actually, or no way, because there was a lot of concerns about privacy and security and so forth. You know, now, as you see organizations modernizing their business capabilities, they're investing in cloud solutions for analytics applications, as well as data data being not only just a byproduct of transactions and interactions in financial services, it truly fuels business success. But we have a term here in Informatica where data really has no value unless it's fit for business. Use data has to be accessible in the systems and applications you use to run your business. It has to be clean. It has to be valid. It has to be transparent. People need to understand where it comes from, where it's going, how it's used and who's using it. It also has to be understood by the business. >>You can have all the data in the world and your business applications, but people don't know what they need it to use it for how they should use it. It has no value as well. And then lastly, it has to be protected when it matters most what we're seeing across financial services, that with the evolution of cloud now, really being the center of focus for many of the net new investments, data is scattered everywhere, not just in one cloud environment, but in multiple cloud environments, but they're still dealing with many of the on premise systems that have been running this industry for many, many years. So organizations need to have the ability to understand what they need to do with their data. More importantly, tie that to a measurable business outcome. So we're seeing the data conversation really at the board level, right? It's an asset of the business. It's no longer just owned by it. Data governance brings both business technology and data leaders together to really understand how do we use manage, govern and really leverage data for positive business outcomes. So we see that as an imperative that cuts across all sectors of financial services, both for large firms, as well as for the mid-market so >>Quick follow up. If I, may you say it's a board level. I totally agree. Is it also a line of business level? Are you seeing increasingly that line of businesses are leaning in owning the data, be building data products and the like >>Absolutely. Because at the end of the day business needs information in order to be successful. And data ownership now really belongs in the front office. Business executives understand that data again is not just a bunch of zeros and ones. These are critical elements for them make decisions and to run their business, whether it's to improve customer experience, whether it's to grow Wallace share, whether it's to comply with regulations, manage risks in today's environment. And of course being agile business knows that data's important. They have ownership of it and technology and data organizations help facilitate that solutions. And of course the investments to ensure that business can make the decisions and take the appropriate actions. >>A lot of asks and requirements on data. That's a big challenge for organizations. You mentioned. Well, one of the things that we've mentioned many times on this program recently is every company has to be a data company. There is no more, it's not an option anymore. If you wanna be successful, how does Informatica help customers navigate all of the requirements on data for them to be able to extract that business value and create new products and services in a timely fashion? >>So Informatica announced what we call the intelligent data management cloud platform. The platform has capabilities to help organizations access the data that they need, share it across to applications that run their business, be able to identify and deal with data, quality issues and requirements. Being able to provide that transparency, the lineage that people need across multiple environments. So we've been investing in this platform that really allows our customers to take advantage of these critical data management, data governance and data privacy requirements, all in one single solution. So we're no longer out there just selling piecemeal products. The platform is the offering that we provide across all industries. >>So how has that affected the way Informatica does business over the last several years? Snowflake is relatively new. You guys have been around a long time. How has your business evolved and specifically, how are you serving the snowflake yeah. Joint customers with >>Informatica? Yeah, I think then when I've been talking with folks here at the event, there are two big areas that keep coming up. So, so data governance, data governance, data governance, right? It's such a hot topic out there. And as Peter was mentioning, data governance is a critical enabler of access to data. In fact, there is an IDC study for last year that said that, you know, 80, 84% of executives, you know, no surprise, right? They wanna have data driven outcomes, data driven organizations, but only 30% of practitioners actually use data to make decisions. There's a huge gap there. And really that's where governance comes in and creating trust around data and not only creating trust, but delivering data to and users. So that's one big trend. The other one is departmental user adoption. We're seeing a, a huge push towards agility and rapid startup of new projects, new data driven transformations that are happening at the departmental level, you know, individual contributors, that sort of thing. So Informatica, we did a made announcement yesterday with snowflake of a whole host of innovations that are really targeting those two big trend areas. >>I wanna get into the announcements, but you know, the point about governance and, and users, business users being reluctant, it's kind of chicken and egg, isn't it. If, if I don't have the governance, I'm, I'm afraid to use it. But even if I do have it, there's the architecture of my, my, my company, my, my data organization, you know, may not facilitate that. And so I'm gonna change the architect, but then it's a wild west. So it has to be governed. Isn't that a challenge that company companies >>Absolutely, and, and governance is, is a lot more than just technology, right? It's of a people process problem. And there really is a community or an ecosystem inside every organization for governance. So it's really important that when you think about deploying governance and being successful, that every stakeholder have the ability to interact with this common framework, right. They get what they need out of it. It's tailored for how they wanna work. You've got your it folks, you got your chief data officer data stewards, you have your privacy folks and you have your business users. They're all different personas. So we really focus on creating a holistic, single pane of glass view with our cloud data governance and catalog offering that that really takes all the way from the raw technical data and actually delivers data in, in a shopping cart, like experience for actual enterprise users. Right? And, and so I think that's when data governance goes from historically data, governments was seen as an impediment. It was seen as a tax, I think, but now it's really an accelerator, an enabler and driving consumption of data, which in turn for our friends here at snowflake is exactly what they're looking for. >>Talk about the news. So data loader, what does that do? >>Well, it's all in the name. We say, no, the data loader it, it's a free utility that we announced here at, at snowflake summit that allows any user to sign up. It's completely free, no capacity limits. You just need an email address, three simple steps start rapidly loading data into snowflake. Right? So that first step is just get data in there. Start working with snowflake. Informatica is investing and making that easy for every single user out there. And especially those departmental users who wanna get started quickly. >>Yeah. So, I mean, that's a key part point of getting data into the snowflake data cloud, right? It's like any cloud, you gotta get data in. How does it work with, with customers? I mean, you guys are, are known, you have a long history of, you know, extract transform ETL. How does it work in the snowflake world? Is it, is it different? Is it, you remember the Hadoop days? It was, it was E LT, right? How are customers doing that today in this environment? >>Yeah, it's different. I mean, there, there are a lot of the, the same patterns are still in play. There's a lot more of a rapid data loading, right. Is a key theme. Just get it into snowflake and then work on the data, transform it inside of snowflake. So it's, it's a flavor of T right. But it's really pushing down to the snowflake data cloud as opposed to Hado with spark or something like that. Right. So that, that's definitely how customers are using it. And, you know, majority of our customers actually with snowflake are using our cloud technology, but we're also helping customers who are on premise customers, automate the migration from our on-premises technology to our cloud native platform as well. Yeah. >>And I'd say, you know, in addition to that, if you think about building a snowflake environment, Informatica helps with our data loader solution, but that's not enough. Then now you need to get value out of your data. So you can put raw data into the snowflake environment, but then you realize the data's not actually fit for business use, what do we need to do actually transform it to clean it, to govern it. And our customers that use Informatica with snowflake are managing the entire data management and data governance process so that they can allow the business to get value out of the snowflake investment. >>How quickly can you enable a business to get value from that data to be able to make business decisions that can transform right. Deliver competitive advantage? >>I think it really depends on an organization on a case by case basis. At the end of the day, you need to understand why are you doing this in the first place, right? What's the business outcome that you're trying to achieve next, identify what data elements do you actually need to capture, govern and manage in order to support the decisions and the actions that the business needs to take. If you don't have those things defined, that's where data governance comes into play. Then all you're doing is setting up a technical environment with a bunch of zeros in ones that no one knows what to do with. So we talk about data governance more holistically, say, you need to align it to your business outcomes, but ensure that you have people, processes, roles, and responsibilities, and the underlying technology to not just load data into snowflake, but to leverage it again for the business needs across the organization. >>Oh, good, please. >>I just wanted to add to that real quickly. Yeah. One of the things Informatica we're philosophically focused on is how do you accelerate the entire business of data management? So with our, our cloud platform, we have what's called our clear AI engine, right? So we use AI techniques, machine learning recommendations to accelerate with the, the knowledge of the metadata of what's gone on the organization. For example, that when we discover data assets figure out is this customer data, is it product data that dramatically shortens the time to find data assets deliver them? And so across our whole portfolio, we're taking things that were traditionally months to do. We're taking 'em down to weeks and days and even hours, right? So that's the whole goal is just accelerate that entire journey and life cycle through cloud native approaches and AI. Yeah, >>You kind of just answered my question. I think Rick, so you have this joint value statement together. We help customers. This is informatic and snowflake together. We help customers modernize their data. Architecture enable the most critical workloads, provide AI driven data governance and accelerate added value with advanced analytics. I mean, you definitely touched on some of those, but kind of unpack the rest of that. What do you mean by modernize? What is their data architecture? What is that? Let's start there. What does that look like? Modernizing a data. Yeah. >>So, so a lot with so many customers, right? They, they built data warehouses, core data and analytics systems on premises, right? They're using ETL technology using those, those either warehouse, appliances or databases. And what they're looking for is they wanna move to a cloud native model, right. And all the benefits of cloud in terms of TCO elasticity, instant scale up agility, all those benefits. So we're looking, we're looking to do with our, our modernization programs for our, for our current customer base that are on premises. We automate the process to get them to a fully cloud native, which means they can now do hybrid. They can do multi-cloud elastic processing. And it's all also in a consumption based model that we introduced about about a year and a half ago. So, so they're looking for all those elements of a cloud native platform and they're, but they're solving the same problems, right? We still have to connect data. We still have to transform data, prepare it, cleanse it, all those things exist, but in a, in a cloud native footprint, and that's what we're helping them get to. >>And the modern architecture these days, quite honestly, it's no longer about getting best breed tools and stitching them together and hoping that it will actually work. And Informatica is value proposition that our platform has all those capabilities as services. So our customers don't have to deal with the costs and the risks of trying to make everything work behind the scenes and what we've done with IDMC or intelligent data management cloud for financial services, retail, CPG, and healthcare and life sciences. In addition to our core capabilities and our clear AI machine learning engine, we also have industry accelerators, prebuilt data, quality rules for certain regulations in within banking. We've got master data management, customer models for healthcare insurance industry, all prebuilt. So these are accelerators that we've actually built over the years. And we're now making available to our customers who adopt informatic as intelligent data management cloud for their data management and governance needs. >>And then, and then the other part of this statement that that's interesting is provide AI driven data governance. You know, we are seeing a move toward, you know, decentralized data architectures and, and, and organizations. And we talk to snowflake about that. They go, yeah, we're globally distributed cloud. Okay, great. So that's decent place, but what we see a lot of customers doing to say, okay, we're gonna give lines of business responsibility for data. We're gonna argue about who owns what. And then once we settle that here's your own, here's your own data lake. Maybe they they'll try to cobble together a catalog or a super catalog. Right. And then they'll try to figure out, you know, some algorithms to, to determine data quality, you know, best, you know, okay. Don't use. Right, right. So that, so if I understand it, you automate all that. >>So what we're doing with AI machine learning is really helping the data professional, whether in the business, in technology or in between not only to get the job done faster, better, and cheaper, but actually do it intelligently. What do we mean by that? For example, our AI engine machine learning will look at data patterns and determine not only what's wrong with your data, but how should you fix it and recommend data quality rules to actually apply them and get those errors addressed. We also infer data relationships across a multi-cloud environment where those definitions were never there in the beginning. So we have the ability to scan the metadata and determine, Hey, this data set is actually related to that data set across multiple clouds. It makes the organization more productive, but more importantly, it increases the confidence level that these organizations have the right infrastructure in place in order to manage and govern their data for what they're trying to do from a business perspective. >>And I add that as well. I think you're talking a lot about data mesh architectures, right? That, that are really kind of popular right now. And I think those kind of, they live or die on, on data governance. Right? If you don't have data governance to share taxonomy, these things, it's very hard to, I think, scale those individual working groups. But if you have a platform where they, the data owners can publish out visibility to what their data means, how to use it, how to interpret it and get that insight, that context directly to the data consumers that's game changing. Right. And that's exactly what we're doing with our cloud data governance and catalog. >>Well, the data mesh, you talk about data mesh, there's four principles, right? It's like decentralized architecture data products. So if, once you figure out those two yep. You just created two more problems, which is the other two parts of the Princip four, two parts of the four principles, self service infrastructure, and computational governance. And that's like the hardest part of federated, federated, computational governance. That's the hardest part. That's the problem that you're solving. >>Yeah. Yeah, absolutely. I mean, think about the whole decentralization and self-service, well, I may be able to access my data in mesh architecture, but if I don't know what it means, how to use it for what purpose, when not to use it, you're creating more problems than what you originally expected to solve. So what we're doing is addressing the data management and the governance requirements, regardless of what the architecture is, whether it's a mesh architecture, a fabric architecture or a traditional data lake or a data store. >>Yeah. Mean, I say, I think data mesh is more of an organizational construct than it is. I, I'm not quite sure what data fabric is. I think Gartner confused the issue that data fabric was an old NetApp term. Yeah. You're probably working in NetApp at the time and it made sense in the NetApp context. And then I think Gartner didn't like the fact that Jamma Dani co-opted this cool term. So they created data fabric, but whatever. But my, my point being, I think when I talk to customers that are they're, they're trying to get more value outta data and they recognize that going through all these hyper specialized roles is time consuming and it's not working for them. And they're frustrated to your points and your joint statement. They want to accelerate that. And they're realizing, and the only way to do that is to distribute responsibility, get more people involved in the process. >>And, and that's, it kind of dovetails with some, the announcements we made on data governance for snowflake, right, is you're taking these, these operational controls of the snowflake layer that are typically managed by SQL and you, and that decentralized architecture data owner doesn't know how to set those patterns and things like that. Right. So we're saying, all right, we're, we're creating these deep integration so that again, we have a fit for persona type experience where they can publish data assets, they can set the rules and policies, and we're gonna push that down to snowflake. So when it actually comes to provisioning data and doing data sharing through snowflake, it's all a seamless experience for the end user and the data owner. Yeah. >>That's great. Beautiful, >>Seamless experience absolutely necessary these days for everybody above guys. Thanks so much for joining David me today, talking about Informatica what's new, what you're doing with snowflake and what you're enabling customers to do in terms of really extracting value from that data. We appreciate your insights. >>Thank you. Yep. >>Thank you for having us >>For our guests and Dave ante. I'm Lisa Martin. You're watching the cubes coverage of snowflake summit day two of the cubes coverage stick around Dave. And I will be right back with our next guest.

(upbeat techno music) >> Hey everyone, and welcome back to theCUBE's coverage of Snowflake Summit '22 live from Caesar's Forum in beautiful, warm, and sunny Las Vegas. I'm Lisa Martin. I got the Chris and Chris show, next. Bear with me. Chris Degnan joins us again. One of our alumni, the Chief Revenue Officer at Snowflake. Good to have you back, Chris. >> Thank you for having us. >> Lisa: Chris Grusz also joins us. Director of Business Development AWS Marketplace and Service Catalog at AWS. Chris and Chris, welcome. >> Thank you. >> Thank you. >> Thank you. Good to be back in person. >> Isn't it great. >> Chris G: It's so much better. >> Chris D: Yeah. >> Nothing like it. So let's talk. There's been so much momentum, Chris D, at Snowflake the last few years. I mean the momentum at this show since we launched yesterday, I know you guys launched the day before with partners, has been amazing. A lot of change, and it's like this for Snowflake. Talk to us about AWS working together with Snowflake and some of the benefits in it from your customer. And then Chris G, I'll go to you for the same question. >> Chris G: Yep. >> You know, first of all, it's awesome. Like, I just, you know, it's been three years since I've had a Snowflake Summit in person, and it's crazy to see the growth that we've seen. You know, I can't, our first cloud that we ever launched on top of was, was AWS, and AWS is our largest cloud, you know, in in terms of revenue today. And they've been, they just kind of know how to do it right. And they've been a wonderful partner all along. There's been challenges, and we've kind of leaned in together and figured out ways to work together, you know, and to solve those challenges. So, been a wonderful partnership. >> And talk about it, Chris G, from your perspective obviously from a coopetition perspective. >> Yep. >> AWS has databases, cloud data forms. >> Chris G: Yeah. >> Talk to us about it. What was the impetus for the partnership with Snowflake from AWS's standpoint? >> Yeah, well first and foremost, they're building on top of AWS. And so that, by default, makes them a great partner. And it's interesting, Chris and I have been working together for, gosh, seven years now? And the relationship's come a really long way. You know, when we first started off, we were trying to sort out how we were going to work together, when we were competing, and when we're working together. And, you know, you fast forward to today, and it's just such a good relationship. Because both companies work backwards from customers. And so that's, you know, kind of in both of our DNA. And so if the customer makes that selection, we're going to support them, even from an AWS perspective. When they're going with Snowflake, that's still a really good thing for AWS, 'cause there's a lot of associated services that Snowflake either integrates to, or we're integrating to them. And so, it's really kind of contributed to how we can really work together in a co-sell motion. >> Talk to us, talk about that. The joint GOTO market and the co-selling motion from Snowflake's perspective, how do customers get engaged? >> Well, I think, you know, typically we, where we are really good at co-selling together is we identify on premise systems. So whether it's, you know, some Legacy UDP system, some Legacy database solution, and they want to move to the cloud? You know, Amazon is all in on getting everyone to the cloud. And I think that's their approach they've taken with us is saying we're really good at accelerating that adoption and moving all these, you know, massive workloads into the cloud. And then to Chris's point, you know, we've integrated so nicely into things like SageMaker and other tool sets. And we, we even have exciting scenarios where they've allowed us to use, you know, some of their Amazon.com retail data sets that we actually use in data sharing via the partnership. So we continue to find unique ways to partner with our great friends at Amazon. >> Sounds like a very deep partnership. >> Chris D: Yeah. Absolutely. >> Chris G: Oh, absolutely, yeah. We're integrating into Snowflake, and they're integrating to AWS. And so it just provides a great combined experience for our customers. And again, that's kind of what we're both looking forward from both of our organizations. >> That customer centricity is, >> Yeah. >> is I think the center of the flywheel that is both that both of you, your companies have. Chris D, talk about the the industry's solutions, specific, industry-specific solutions that Snowflake and AWS have. I know we talked yesterday about the pivot from a sales perspective >> Chris D: Yes. >> That snowflake made in recent months. Talk to us about the industries that you are help, really targeting with AWS to help customers solve problems. >> Yeah. I think there's, you know, we're focused on a number of industries. I think, you know, some of the examples, like I said, I gave you the example of we're using data sharing to help the retail space. And I think it's a really good partnership. Because some of the, some companies view Amazon as a competitor in the retail space, and I think we kind of soften that blow. And we actually leverage some of the Amazon.com data sets. And this is where the partnership's been really strong. In the healthcare space, in the life sciences space, we have customers like Anthem, where we're really focused on helping actually Anthem solve real business problems. Not necessarily like technical problems. It's like, oh no, they want to get, you know, figure out how they can get the whole customer and take care of their whole customer, and get them using the Anthem platform more effectively. So there's a really great, wonderful partnership there. >> We've heard a lot in the last day and a half on theCUBE from a lot of retail customers and partners. There seems to be a lot of growth in that. So there's so much change in the retail market. I was just talking with Click and Snowflake about Urban Outfitters, as an example. And you think of how what these companies are doing together and obviously AWS and Snowflake, helping companies not just pivot during the pandemic, but really survive. I mean, in the beginning with, you know, retail that didn't have a digital presence, what were they going to do? And then the supply chain issues. So it really seems to be what Snowflake and its partner Ecosystem is doing, is helping companies now, obviously, thrive. But it was really kind of like a no-go sort of situation for a lot of industries. >> Yeah, and I think the neat part of, you know, both the combined, you know, Snowflake and AWS solution is in, a good example is DoorDash, you know. They had hyper growth, and they could not have handled, especially during COVID, as we all know. We all used DoorDash, right? We were just talking about it. Chipotle, like, you know, like (laughter) and I think they were able to really take advantage of our hyper elastic platforms, both on the Amazon side and the Snowflake side to scale their business and meet the high demand that they were seeing. And that's kind of some of the great examples of where we've enabled customer growth to really accelerate. >> Yeah. Yeah, right. And I'd add to that, you know, while we saw good growth for those types of companies, a lot of your traditional companies saw a ton of benefit as well. Like another good example, and it's been talked about here at the show, is Western Union, right? So they're a company that's been around for a long time. They do cross border payments and cross currency, you know, exchanges, and, you know, like a lot of companies that have been around for a while, they have data all over the place. And so they started to look at that, and that became an inhibitor to their growth. 'Cause they couldn't get a full view of what was actually going on. And so they did a lengthy evaluation, and they ended up going with Snowflake. And, it was great, 'cause it provided a lot of immediate benefits, so first of all, they were able to take all those disparate systems and pull that into Snowflake. So they finally had a single source of the truth, which was lacking before that. So that was one of the big benefits. The second benefit, and Chris has mentioned this a couple times, is the fact that they could use data sharing. And so now they could pull in third data. And now that they had a holistic view of their entire data set, they could pull in that third party data, and now they could get insights that they never could get before. And so that was another large benefit. And then the third part, and this is where the relationship between AWS and Snowflake is great, is they could then use Amazon SageMaker. So one of the decisions that Western Union made a long time ago is they use R for their data science platform, and SageMaker supports R. And so it really allowed them to dovetail the skill sets that they had around data science into SageMaker. They could now look across all of Snowflake. And so that was just a really good benefit. And so it drove the cost down for Western Union which was a big benefit, but the even bigger benefit is they were now able to start to package and promote different solutions to their customers. So they were effectively able to monetize all the data that they were now getting and the information they were getting out of Snowflake. And then of course, once it was in there, they could also use things like Tableau or ThoughtSpot, both of which available in AWS Marketplace. And it allowed them to get all kinds of visualization of data that they never got in the past. >> The monetization piece is, is interesting. It's so challenging for organizations, one, to get that single source view, to be able to have a customer 360, but to also then be able to monetize data. When you're in customer conversations, how do you help customers on that journey, start? Because the, their competitors are clearly right behind them, ready to take first place spot. How do you help customers go, all right this is what we're going to do to help you on this journey with AWS to monetize your data? >> I think, you know, it's everything from, you know, looking at removing the silos of data. So one of the challenges they've had is they have these Legacy systems, and a lot of times they don't want to just take the Legacy systems and throw them into the cloud. They want to say, we need a holistic view of our customer, 360 view of our customer data. And then they're saying, hey, how can we actually monetize that data? That's where we do everything from, you know, Snowflake has the data marketplace where we list it in the data marketplace. We help them monetize it there. And we use some of the data sets from Amazon to help them do that. We use the technologies like Chris said with SageMaker and other tool sets to help them realize the value of their data in a real, meaningful way. >> So this sounds like a very strategic and technical partnership. >> Yeah, well, >> On both sides. >> It's technical and it's GOTO market. So if you take a look at, you know, Snowflake where they've built over 20 integrations now to different AWS services. So if you're using S3 for object storage, you can use Snowflake on top of that. If you want to load up Snowflake with Glue which is our ETL tool, you can do that. If you want to use QuickSite to do your data visualization on top of Snowflake, you can do that. So they've built integration to all of our services. And then we've built integrations like SageMaker back into Snowflake, and so that supports all kinds of specific customer use cases. So if you think of people that are doing any kind of cloud data platform workload, stuff like data engineering, data warehousing, data lakes, it could be even data applications, cyber security, unistore type things, Snowflake does an excellent job of helping our customers get into those types of environments. And so that's why we support the relationship with a variety of, you know, credit programs. We have a lot of co-sell motions on top of these technical integrations because we want to make sure that we not only have the right technical platform, but we've got the right GOTO market motion. And that's super important. >> Yeah, and I would add to that is like, you know one of the things that customers do is they make these large commitments to Amazon. And one of the best things that Amazon did was allow those customers to draw down Snowflake via the AWS Marketplace. So it's been wonderful to his point around the GOTO market, that was a huge issue for us. And, and again, this is where Amazon was innovative on identifying the ways to help make the customer have a better experience >> Chris G: Yeah. >> Chris D: and put the customer first. And this has been, you know, wonderful partnership there. >> Yeah. It really has. It's been a great, it's been really good. >> Well, and the customers are here. Like we said, >> Yep. >> Yes. Yes they are. >> we're north of 10,000 folks total, and customers are just chomping at the bit. There's been so much growth in the last three years from the last time, I think I heard the 2019 Snowflake Summit had about 1500 people. And here we are at 10,000 plus now, and standing-room-only keynote, the very big queue to get in, people turned away, pushed back to an overflow area to be able to see that, and that was yesterday. I didn't even get a chance to see what it was like today, but I imagine it was probably the same. Talk about the, when you're in customer conversations, where do you bring, from a GTM perspective, Where do you bring Snowflake into the conversation? >> Yeah >> Obviously, there's Redshift there, what does that look like? I imagine it follows the customer's needs, challenges. >> Exactly. >> Compelling events. >> Yeah. We're always going to work backwards from the customer need, and so that is the starting point for kindling both organizations. And so we're going to, you know, look at what they need. And from an AWS perspective, you know, if they're going with Snowflake, that's a very good thing. Right? 'Cause one of the things that we want to support is a selection experience to our AWS customers and make sure that no matter what they're doing, they're getting a very good, supported experience. And so we're always going to work backwards from the customer. And then once they make that technology decision, then we're going to support them, as I mentioned, with a whole bunch of co-sell resources. We have technical resources in the field. We have credit programs and in, you know, and, of course, we're going to market in a variety of different verticals as well with Snowflake. If you take a look at all the industry clouds that Snowflake has spun up, financial services and healthcare, and media entertainment, you know, those are all very specific use cases that are very valuable to an AWS customer. And AWS is going more and more to market on a vertical approach, and so Snowflake really just fits right in with our overall strategy. >> Right. Sounds like very tight alignment there. That mission alignment that Frank talked about yesterday. I know he was talking about that with respect to customers, but it sounds like there's a mission alignment between AWS and Snowflake. >> Mission alignment, yeah. >> I live that every week. (laughter) >> Sorry if I brought up a pain point. >> Yeah. Little bit. No. >> Guys, what's, in terms of use cases, obviously we've been here for a couple days. I'm sure you've had tremendous feedback, >> Chris G: Yeah. >> from, from customers, from partners, from the ecosystem. What's next, what can we expect to hear next? Maybe give us a preview of re:Invent in the few months. >> Preview of re:Invent. Yeah. No, well, one of the things we really want to start doing is just, you know, making the use case of, of launching Snowflake on AWS a lot easier. So what can we do to streamline those types of experiences? 'Cause a lot of times we'll find that customers, once they buy a third party solution like Snowflake, they have to then go through a whole series of configuration steps, and what can we do to streamline that? And so we're going to continue to work on that front. One of the other places that we've been exploring with Snowflake is how we work with channel partners. And, you know, when we first launched Marketplace it was really more of an app store model that was ISVs on one side and channel partners on the other, and there wasn't really a good fit for channel partners. And so four years ago we retrofitted the platform and have opened it up to resellers like an SHI or SIs like Salam or Deloitte who are top, two top SIs for Snowflake. And now they can use Marketplace to resell those technologies and also sell their services on top of that. So Snowflake's got a big, you know, practice with Salam, as I mentioned. You know, Salam can now sell through Marketplace and they can actually sell that statement of work and put that on the AWS bill all by virtue of using Marketplace, that automation platform. >> Ease of use for customers, ease of use for partners as well. >> Yes. >> And that ease of use is it's no joke. It's, it's not just a marketing term. It's measurable and it's about time-to-value, time-to-market, getting customers ahead of their competition so that they can be successful. Guys, thanks for joining me on theCUBE today. Talking about AWS and >> Nice to be back. Nice to be back in person. >> Isn't it nice to be back. It's great to be actually sitting across from another human. >> Exactly. >> Thank you so much for your insights, what you shared about the partnership and where it's going. We appreciate it. >> Thank you. >> Cool. Thank you. >> Thank you. >> All right guys. For Chris and Chris, I'm Lisa Martin, here watching theCUBE live from Las Vegas. I'll be back with my next guest momentarily, so stick around. (Upbeat techno music)

>>Mm. >>Amdocs is a leader in providing software and services to some key industries, like telecommunications, media and financial services. In our next session, >>we >>welcome Cedric Jay Gould, who is the head of technical product at Amdocs. And we'll learn about Amdocs modernisation journey and how it added value for their end customers. Cedric. Welcome. >>Welcome. Good. >>Thank you. So describe your modern application, your portfolio, and you know what you're delivering for customers. >>So home dogs is B s s S s players who we are providing a food digital suite for customers. Uh, our customers are communication service providers, which are have to deploy a full digital sweets customer experience. Um, we're for the full os BSS, BSS tax. So, actually, Amdocs is one of the leader in this kind of digital transformation. >>So of course you talk about this as and BS. I mean, you're talking about some really hardened, uh, stacks, right? Uh, telco industry. Uh, say what you want about it, but, boy, the phone works when you dial it. So So you've got this sort of a decades old, you know, platform that you guys have been evolving over the over the years. described this modernisation journey and and the role that couch base played. What value does this offer This modernisation offer to your organisation. And where does Couch based fit? >>Yeah, exactly the same. So that so. Basically what, uh, all solution is You know, it's a broad for you of a large number of components which have to deal with funds, uh, experience of the user and from and then dealing all the, uh, activation of the services in the network in order to deliver a solution, Uh, your services, like mobile services or communication services to, uh, Susan users. So we have a full suites, which, uh, was previously based on, you know, on technology is based on the oracle with web logic and things like that. And what we did is that we do a modernisation of, uh, this something, like, six years ago. A bit more than six years ago. We start to modernisation and transformation of our product into a creative solution. Collaborative solutions. So, uh, and when we did that, we start with Coach base as a partner, uh, to provide the nominative database. So we are actually delivery. We have a guarantee of more than 8000 people developing this product. It's a product which is used by more than 300 customers. Uh, so So it's it's real product that needs to be very flexible. That needs to address many kind of use cases from, uh, Telco or customers, which RCs PS usually till 0 to 1 telco. So we what we wanted to build is a food creative solution that can work on any cloud, then can can skill very, very easily and can address multiple use cases. Okay, And that's why, Coach Base, when we selected Coach Basit, it matched a lot of requirements and criteria as we had. And when we decided to modernise our product, we decided to work with >>you. So you had a lot of experience and and legacy with Oracle and Web logic. I'm curious just to follow up. Why didn't you stay with Oracle? You mentioned? Gotta run any cloud. You gotta be flexible. But could you could you double click on what Couch based delivered from a requirement standpoint, that was such a good fit? >>Well, there's there's a good fit with technology that such as, uh, coach basis. First it's a noise school detonates, right? So it's in terms of performance for some of the youth case that we have. It's very important to have, you know, technology which are are done and optimised for the noise secure use cases. That's the first thing. The second thing as I mentioned the scalability, the fact that you can, almost indefinitely infinitely you can increase the size of your cluster. You can have more, uh, servers and and and And this will skill, you know, very rapidly. And also what we're very interesting to have from coach bases the ability to have something which can be replicated across multiple sites. So with visual technology from coach base, which enable to build, you know, very modern architecture with deployment on multiple agents to have disaster recovery, active, active sites, you know, things like that which are very becoming like the main requirement for more customers now. >>Okay, so I'm presuming there were parts of your application portfolio that you weren't gonna touch and throw away that you had to collect or connect the new with the old. That's always, you know, you know, a challenge. I'm wondering what advice you give to an organisation. That's kind of investing in a similar path, trying to deliver the best digital experiences to customers. You know what? What would you say are the modernisation you gotta have must have, whether it's architecture, internal culture, what are some of those items? >>So so that yes, you're right. I think the integration with the legacy systems is actually, you know, very, very important topic in all domain in the domain. But we we made a very, uh, will see drastic choice or brave choice choice. When, uh, 60 years from now, when we decided to reformat to re platforms are completely or portfolio. Okay, So we we changed more than 95% of our portfolio and 95% of the portfolio today, Arklow native. Which means that they can be deployed on any cloud that actually, they are fully scalable and and and still, we did this transformation. Now, when we do the digital transformation of the, uh, customer system, then we need to integrate with legacy systems, and we need to help our customers to migrate from the legacy systems to creative solutions and doing so, it's important to have in the database domain. It's very important to have a solution which is very flexible in terms of, uh, what kind of data I can manage. And I can, as I said, skill easily, for sure. But also, it's sexual. Okay, Because when you are moving the data from a legacy system or record based or whatever to, uh, another type of, uh, database, you want to be sure that you are you can do it securely, and you're you're not, uh, compromising in any sense, Uh, in terms of security scalability, uh, etcetera. Right. So So, um, in this case, I mean, I will say And then in this opportunities journey, uh, this was very, very, very, very important component in, uh, you know, in our strategy, for all the reasons I mentioned right, it's very coordinative. It's scalable, It's secure. Uh, it's another product, uh, grade. So? So that's that's why it really is. So there's there's a chest back to you. >>You know, this notion that 90 per you really re platform 90% of your portfolio and made a cloud native. That's that's a It's a brave move because a lot of companies do that that I've talked to. They will build an abstraction layer and microservices and make that piece cloud native and then have that kind of overlay. You decided not to do that. Why is that? Was that for performance reasons? You were worried about just bringing along technical debt. I mean, that really must have been an interesting discussion internally in your company. >>Yeah, it's true. I mean, the main motivation, the main driver was business flexibility. Because now we live in a world where our customers, what they need is to be able to test the new feature quickly. And they need to be able to scale the system in a matter of hours. Okay, so we are not in a domain anymore. Where you you when you have to upgrade something, you need to take a few days. It needs to be done in a very, very quickly. And the only way to achieve those, uh, requirements business requirements is to be creative. It's to build microservices and to really realise one of those per cent of, uh, micro services architecture because this is the only way you will have the business flexibility. You will be able to have a resilient architecture. Uh, you know, you can, uh you can deploy this with full high availability across multiple zones, multiple regions and feeling that so, uh, any modern architecture today that that is competing with us, Actually, a micro services based architecture. There is no other way to achieve, uh to to to meet the requirement of the market today, and especially when five g is coming, things will become much more complex. Will become much more, uh, distributed. Uh, you cannot work anymore with the model it architecture. And again, I think the database is nowhere different. Needs to follow the same kind of architecture needs to follow the same principles. So that's that's why am I mean another another point about Yeah, >>So if I If I summarised, it sounds like your top three requirements would be flexibility, which you're getting from the cloud native and microservices piece the scale and the security. Is that right? That I get that right? The three top >>That's right. And the resilience as well. I mean the fact that now you know, with micro services architecture, if one of the system is done, he knows how to self to restart it himself. Right itself. Sorry. So So that's this kind of architecture that we built. It's an architecture which can be resilient in a sense that it can sense itself, and it can ensure full availability. And if something is going down, is not working properly, then on some kind of mechanisms will happen in order to go back to a stable state. >>Yeah. So you've got that automation in there. So you don't doesn't require the labour that it might have 10 years ago. So you're obviously embracing cloud native microservices. So you're on that jury. I'm curious. What are you doing with that? You're you're freeing up. You guys used to bring in lab coats and dig in and figure out what's wrong or restart the system. Where are you in your journey, and how are you? Sort of reallocating those resources. And where do you see that going? >>Yeah, Okay, so that's that's a very good point. Because actually, we when we build this new system, which is unable to do, you know, to self heal himself, right? Uh, actually, the question was more about how we can improve the system, even know how we can be sure that, uh, you know, issues that we we any issues which we are we are facing will not happen again. Well, not actual again. Okay. And this is a, uh, principle. Okay, Practise that we have now people are walking on automation. They're building automation around all these recovery procedures about, uh, fixing. So they're not actually digging into the application now anymore into the system, they learn how the system is walking and buildings all the right automation task to ensure that the system is constantly, constantly resilient. Alright, so that's the necessary practises organisation is now built around. You know, this kind of this approach developed computer develops being fully a geologically having sa reorganisation SRE oriented organisation. And, uh and that's the only way you know you can reach very high, uh, in terms of availability. >>So the big problem that your traditional telco customers have is the amount of data that they're servicing going through the roof and the cost per bit is sinking like that. And you have all the over the top providers coming in creating these customer experiences with modern applications and they've owned the customer data. You mentioned five g. So I'm interested in what the future of modern apps looks like for Amdocs and your customers because five G gives your traditional telco customers the ability if they can have these flexible systems that you're providing to now have better relationships with customers and actually kind of reclaim, you know, some of that that value that they've lost to a lot of competitors, your thoughts on the future. >>So first, you know, technically speaking, we we we will have two challenges. One is about data, and other one is about distribution of the work. Okay, because when we are speaking about five g, we're speaking about the age. We're speaking about the fact that an application may be located very closely to the network because it needs to be to to achieve, you know, to to deliver a very short latency, and, uh and this application can move. Okay, so you you you you will have to be able to distribute completely your your solutions. Okay. And that's why we are working closely with, uh, club providers at the US as you Google and because we we need to be sure that the applications of the systems that we are building will be able to distribute the application as close as possible to the end users. Okay, so that's that's one of the key challenges. Which means that the application is to be very possible and he'd be very scalable, and then it needs to be able to move very quickly from one place to another. That's really what is what What, what? What is happening now and what will become, uh, with five G? The other challenge is behind the communication of all these components is really the data, because now we will capture more and more that are coming from the different systems. And I'm not speaking only about the consequence the customer that are who they are, what they what they like and what they want to do, etcetera. And speaking also about, uh, monitoring that of the systems. Okay, so we will generate a lot of information and this this information needs to be traded very quickly, needs to be stored in very large data lake, and we need to have extraction and manipulation of the data very, very quickly to to give the right information to the applications. Um, in this case, okay, it's very important to have application to have databases that can as I said, skill very quickly. But also we'll be able to have very ideal city note, you know, sense that they with a certain amount of memory or sentiment of storage, you can store a lot of data. And this is where we are always, you know, checking what is the best technologies. And so far, not coach bases, technologies that we're using for for stalking, storing all the data. Because because it's it's a ratio in terms of, uh, performance on the number of data you can store, Uh is very high. Okay, so that's that's another challenge that we're addressing. Of course, God is not the only solution, but it's another another one. >>Excellent. Okay, we're gonna leave it there. Cedric, Thanks so much. A great storey and really appreciate your insights. >>You're welcome. Thank you very much. >>Okay, that's it for today. I hope you've enjoyed the application. Modernisation summit made possible by Couch Base. We shared some fresh survey data and got the perspectives of three expert analysts. We got an outstanding roadmap from Ravi Meyer. Um, who's the CEO of Couch base? And of course, we got the customer angle from Cedric. So look, Maybe you're an organisation going through a modernisation initiative. And if you're thinking about what the future of applications looks like cheque out couch. Based on the road this summer, the application modernisation summit is hitting the road traversing North America and Europe. Find out where they will be where they will be near you by visiting couch based dot com slash roadshow. Ravi is gonna be there along with other thought leaders and peers who will be sharing learnings and best practises on how to modernise now and for the future. And you'll get a chance to interact with some of those piers, something that everyone I know is looking forward to. This is Day Volonte. Thanks for joining us today. And thanks for watching the Cube. Mhm. Yeah. Mm, yeah.