(soft electronic music) >> Good afternoon guys and gals. Welcome back to theCube's Live coverage of AWS re:Invent 2022. We've been in Sin City since Monday night, giving you a load of content. I'm sure you've been watching the whole time, so you already know. Lisa Martin here with John Furrier. John, we love having these conversations at AWS re:Invent. So many different topics of conversation. We also love talking to AWS's partner ecosystem. There's so much emphasis on it, so much growth and innovation. >> Yeah, and the thing is we got two great leaders from a very popular company that's doing very well. Security, security's a big part of the story. Data and security. Taking up all the keynote time, you're hearing a lot of it. This company's a company we've been following from the beginning. Doing really good stuff in open source, cloud native, security, shifting-left. Snyk's just a great company. With the CTO and the head of the product organization, these guys have the keys to the kingdom in security. We're going to have a great conversation. >> Yeah, we are. Both from Snyk, Manoj Nair joins us, rejoins us, for your, I believe, 11th visit. Chief Product Officer of Snyk. Adi Sharabani, Chief Technology Officer. Welcome guys. Great to have you. >> Yeah, thank you. >> Great to be back. >> So what's going on at Snyk? I know we get to talk to you often, but Manoj, give us the lowdown on what are some of the things that are new since we last connected with Snyk. >> A lot of innovation going on. We just had a major launch last month and you know when we talked to our customers three big themes are happening in parallel. One is the shift to going from traditional development to, really, DevOps, but we need to make that DevSecOps and Snyk was ahead of, that was the genesis of Snyk, but we're still, you know, maybe 15, 20% of organizations have realized that. So that one big theme. Supply chain security, top of mind for everyone. And then really, cloud and, you know, how do you really take advantage of cloud. Cloud is code. So our innovation map to those three big themes, we have done a lot in terms of that shift-left. And Adi will talk about, kind of, some of our original, like, you know, thinking behind that. But we flipped the security paradigm on its head. Was to make sure developers loved what they were, you know, experiencing with Snyk. And oh, by the way, they're fixing security issues. The second one, supply chain. So you know, SBOMs and everyone hears about this and executive orders, what do you do? Who does what with that? So we launched a few things in terms of simplifying that. You can go to our website and, you know, just upload your SBOM. It'll tell you using the best security intelligence data. In fact, the same data is used by AWS inside their products, inside Inspector. So we use that data from Snyk's intelligence to light up and tell you what vulnerabilities do your third party code have. Even things that you might not be scanning. And then the last one is really code to cloud. Cloud is code. So we have brought the ability to monitor your cloud environments all the way into your platform and the security engineering teams, rather than later on and after the fact. Those are some of the big ones that we're working on. >> Lisa: Lots going on. >> Yeah. >> Lisa: Wow. >> Lots going on there. I mean, SBOMs, Software Bill of Materials. I mean, who would've thought in the developer community, going back a decade, that we'd be talking about bill of materials, open source becomes so popular. You guys are cloud native. Developer productivity's a hot trend. Not much going on here, talking about developer productivity. Maybe Werner, keynote tomorrow will talk about it. Software supply chain, huge security risk. You guys are in the front lines. I want to understand, if you can share, why is Snyk successful? Everyone is hearing about you guys. Your business is doing great. What's the secret sauce of your success? Why are you guys so successful? >> I think that, you know, I've been doing application security for more than two decades now and in the past we always saw the potential associated with transferring, shifting-left in a sense, before the term, right? Taking those security solutions out of the hands of the security people and putting it in the hands of developers. It's speeds up the process. It's very, very clear to anyone. The problem was that we always looked at it the wrong way. We did shift-left, and shift-left is not enough because in my terminology shift-left, meaning let's take those security solution put it earlier in the cycle, but that's not enough because the developer is not speaking those terms. The developer is not a security persona. The security persona is thinking in terms of risk. What are the risks that a specific issue creates? The developer is thinking in terms of the application. What would be the impact on application of a change I would might make into it. And so the root cause of Snyk success, in my opinion, is the fact that from the get-go we scratch that, we build a solution for the developer that is based on how the workflows of the developer, whether it's the ID, whether it's the change management, the pull request. Whether it's integration with the Gits and so on. And whether it's with integration with the cloud and the interaction with the cloud providers. And doing that properly, addressing the developers how they want to context, to get, with the context they want to get as part of the issues, with the workflows they want to get. That's kind of the secret sauce, in a sense. And very easy maybe to say, but very, very hard to implement properly. >> This is huge. I want to unpack that. I want to just, great call out, great description. This is huge. This is a, we're seeing the past three years in particular, maybe three with the pandemic. Okay, maybe go a couple years earlier, then. The developers' behavior is driving the change. And you know, if you look at the past three DockerCons we've covered, we've been powering that site, been following that community very closely since the beginning, as well. It just seems in the past three to four years that the developers choices at scale, not what they're buying or who's pushing tools to them, has been one big trend. >> Yeah. >> They're setting the pace. >> Developer is the king. >> If it's self-service, we've seen self-service. Whether it's freemium to paid, that works. This is the new equation. Developer, developer choice is critical. So self-service they want. And two, the language barrier or jargon between or mindsets between security and developers. Okay, so DevOps brings IT into the workflow. Check. DevSecOps brings in there. You guys crack the code on that, is that what you're saying? >> Yes, and it's both the product, like how do you use the solution, as well as the go to market. How do you consume the solution? And you alluded to that with the PLG motion, that I think Synk has done the superb job at and that really helped our businesses. >> Okay, so Manoj, product, you got the keys to the kingdom, you got the product roadmap. I could imagine, and what I'd love to get your reaction too Adi, if you don't mind. If you do that, what you've done, the consequence of that is now security teams and the data teams can build guardrails. We're reporting a lot of that in the queue. We're hearing that we can provide guardrails. So the velocity of the developer seems to be increasing. Do you see that? Is that a consequence? >> That's something that we actually measure in the product. Right, so Snyk's focus is not finding issues, it's fixing issues. So one of the things we have been able to heuristically look at our thousands of customers and say, they're fixing issues 27 days faster than they were prior to Snyk. So, you know, I'm a Formula one fan. Guardrails, you say. I say there's a speed circuit. Developers love speed. We give them the speed. We give the security teams the ability to sit on those towers and, you know, put the right policies and guardrails in place to make sure that it's not speed without safety. >> And then I'm sure you guys are in the luxury box now, partying while the developers are (Lisa laughing) no more friction, no more fighting, right? >> The culture is changing. I had a discussion with a Fortune 50 CISO a month ago, and they told me, "Adi, it's the first time in my life where the development teams are coming to me, asking me, hey I want you to buy us this security solution." And for, that was mind blowing for him, right? Because it really changes the discussion with the security teams and the development teams >> Before Lisa jumps in, well how long, okay, let me ask you that question on that point. When did that tipping point change, culturally? Was it just the past few years? Has there, has DevOps kind of brought that in, can you? >> Yeah, I think it's a journey that happened together with Snyk's, kind of, growth. So if three years ago it was the very early adopters that were starting to consume that. So companies that are very, you know, modern in the way they developed and so on. And we saw it in our business. In the early days, most of our business came from the high tech industry. And now it's like everywhere. You have manufacturing, you have banks, you have like every segment whatsoever. >> Talk about that cultural shift. That's really challenging for organizations to achieve. Are you seeing, so that, that CISO was quite surprised that the developer came and said, this is what I want. Are you seeing more of that cultural changes? Is that becoming pervasive? >> Yeah, so I think that the root cause of that is that, you mentioned the growth, like the increased speed of velocity in applications. We have 30 million developers in the world today. 30 millions. By the end of the decade it's going to be 45 millions and all of them are using open source, third party code. Look at what's going on here in the event, right? This accelerates the speed for which they develop. So with that, what happened in the digital transformation world, the organizations are facing that huge growth, exponential growth in the amount of technology and products that are being built by their teams. But the way they manage that before, from a security perspective, just doesn't scale. And it breaks and it breaks and it breaks. This is why you need a different approach. A solution that is based on the developers, who are the ones that created the problems and the ones that will be responsible of fixing the issues. This is why we are kind of centering ourselves around them. >> And the world has changed, right? What is cloud? It's code, it's not infrastructure. Old infrastructure, hosted infrastructure. So if cloud is code and cloud native applications are all code and they're being deployed with Terraform packages and cloud formations, that's code. Why take an old school approach of scanning it outside-in. I talked to CISO today who said, I feel bad that, you know, our policy makes it such that a terraform change takes six months. What did I do? I made cloud look like infrastructure. >> Yeah, it's too slow. >> So that, you know, so both sides, you know, CISOs want something that the business, you know, accepts and adopts and it's, culture changes happen because the power is with the developers because all of this is code, and we enabled that whole seamless journey, all the way from code to cloud. So it's kind, you know, I think that this is a part of it. It's by direction, it's a bridge and both sides are meeting in the middle here. >> It's a bridge. I'm curious, how are you facilitating that bridge? You, we talk about the developers being the kings and queens and really so influential in business decisions these days. And you're talking about the developers now embracing Snyk. But you're also talking to CISOs. Is your customer conversation level changing as a result of security folks understanding why it needs to shift-left. >> We had a breakfast meeting with customers, prospects and everyone, I think this morning. It was interesting, we were remarking. There are CTOs, VPs of engineering, CISOs, VPs of AppSec. And it was such a rich conversation on both sides, right? So just the joy of facilitating that conversation and dialogue. CISOs, and so the levels are changing. It started for us in CTOs and VPs of engineering and now it's both because, you know, one of the things Adi talks about is, like, that security has to become development aware. And that's starting to be like the reality. Me getting another solution, with maybe a better acronym than the old acronym, but it's still outside-in, it's scan based. I light up up the Christmas tree, who is going to fix it? And with the speed of cloud, now I got throw in more lights. Those lights are no longer valid. >> The automation. >> The automation without prioritization and actual empowerment is useless. >> All right, I know we got a couple minutes left, but I want to get into that point about automation because inside-out, you've made me think about this. I want to get your thought Adi, if you don't mind. The integration challenges now are much more part of the ecosystem, more joint engineering. You mentioned these meetings are not just salesperson and customer buyer, it's teams are talking to each other. There's a lot of that going on. How do you guys look at that? Because now the worst things that I hear and when I talk to customers is, I hate the word PenTest and AppSec review. It slows things down. People want to go faster. So how do you guys look at that? What's Snyk doing around making the AppSec review process, integration across companies, work better? >> So I'll give you an example from the cloud and then I will relate to the AppSec. And this relates to what you mentioned before. We had a discussion yesterday with a CISO that said, we are scanning the cloud, we are opening the lights, we see this issue. Now what do I do? Who needs to fix this? So they have this long process of finding the actual team that is required to fix it. Now they get to the team and they say, why didn't you tell me about it when I developed it? The same goes for AppSec, right? The audit is a very late stage of the game. You want to make sure that the testing, that the policies, everything is under the same structure, the same policies. So when you do the same thing, it's part of the first time of code that you create, it's part of the change management, it's part of the build, it's part of the deployment and it's part of the audit. And you have everything together being done under the same platform. And this is, kind of, one of the strengths that we bring to the table. The discussion changes because now you have an aligned strategy, rather than kind of blocks that we have, kind of, mashed up together. >> So the new workflow, it's a new workflow, basically, in the mindset of the customer. They got to get their arms around that thing. If we don't design it in, the wheels could come off the bus at the 11th hour. >> Adi: Yeah. >> And everything slows down. >> I had a discussion with Amazon today, actually, that they had an internal discussion and they said, like, some of the teams were like, why have you blocked my app from being released? And they said, have you ever scanned your app? Have you ever looked at your, like, and, and they're like, if you haven't, then you're not really onboard with the platform and it just breaks. This is what happens. >> Great conversation. I know we don't, I wish we had more time. We'll do a follow up on theCube for sure. Should we get into the new twist? >> I've got one final question for you guys. We're making some Instagram reels, so think about your elevator pitch in 30 seconds. And I want to ask you about Snyk's evolution. Manoj, I want to start with you. What is that elevator pitch about Snyk's evolution to the end user customer? >> Empower developers, help them go faster, more productive and do it in a way that security is really built in, not bolted on. And that's really, you know, from a, the evolution and the power that we are giving is make the organization more productive because security is just happening as a part of making the developer more productive. >> Awesome. And Adi, question for you, how, your elevator pitch on how Snyk is really an enabler for CISOs these days? >> Yeah, so I always ask the CISO first of all, are you excited about the way your environment looks like today? Do you need to have a cultural change? Because if you need to have a cultural change, if you want to get those two teams working closely together, we are here to enable that. And it goes from the product, it goes from our education pieces that we can talk about in another section, and it works around the language that we build to allow and enable that discussion. >> Awesome. Guys, that was a double mic drop for both of you. >> Manoj: Thank you. >> Adi: Thank you, Lisa. >> Thank you so much for joining John and me, talking about what's happening with Snyk, what you're enabling customers to do and how, really, you're enabling cultural change. That's hard to do. That's awesome stuff guys. And congratulations on your 11th and your first Cube. >> Second, second, >> Second. >> Adi: I will be here more, but (laughs) >> You got it, you got it. You have to come back because we have too much to talk about. >> Adi: Exactly. (laughs) >> Thanks guys, we appreciate it. >> If we can without Manoj, so I can catch up. (Manoj laughs) >> Okay. We'll work on that. >> Bring you in the studio. (everyone laughing) >> Exactly. >> Eight straight interviews. (John and Lisa laughing) >> We hope you've enjoyed this conversation. We want to thank our guests. For John Furrier, I'm Lisa Martin. You're watching theCUBE, the leader in emerging and enterprise tech coverage. (soft electronic music)

(inspirational music) >> The history of high performance computing is unique and storied. You know, it's generally accepted that the first true supercomputer was shipped in the mid 1960s by Controlled Data Corporations, CDC, designed by an engineering team led by Seymour Cray, the father of Supercomputing. He left CDC in the 70's to start his own company, of course, carrying his own name. Now that company Cray, became the market leader in the 70's and the 80's, and then the decade of the 80's saw attempts to bring new designs, such as massively parallel systems, to reach new heights of performance and efficiency. Supercomputing design was one of the most challenging fields, and a number of really brilliant engineers became kind of quasi-famous in their little industry. In addition to Cray himself, Steve Chen, who worked for Cray, then went out to start his own companies. Danny Hillis, of Thinking Machines. Steve Frank of Kendall Square Research. Steve Wallach tried to build a mini supercomputer at Convex. These new entrants, they all failed, for the most part because the market at the time just wasn't really large enough and the economics of these systems really weren't that attractive. Now, the late 80's and the 90's saw big Japanese companies like NEC and Fujitsu entering the fray and governments around the world began to invest heavily in these systems to solve societal problems and make their nations more competitive. And as we entered the 21st century, we saw the coming of petascale computing, with China actually cracking the top 100 list of high performance computing. And today, we're now entering the exascale era, with systems that can complete a billion, billion calculations per second, or 10 to the 18th power. Astounding. And today, the high performance computing market generates north of $30 billion annually and is growing in the high single digits. Supercomputers solve the world's hardest problems in things like simulation, life sciences, weather, energy exploration, aerospace, astronomy, automotive industries, and many other high value examples. And supercomputers are expensive. You know, the highest performing supercomputers used to cost tens of millions of dollars, maybe $30 million. And we've seen that steadily rise to over $200 million. And today we're even seeing systems that cost more than half a billion dollars, even into the low billions when you include all the surrounding data center infrastructure and cooling required. The US, China, Japan, and EU countries, as well as the UK, are all investing heavily to keep their countries competitive, and no price seems to be too high. Now, there are five mega trends going on in HPC today, in addition to this massive rising cost that we just talked about. One, systems are becoming more distributed and less monolithic. The second is the power of these systems is increasing dramatically, both in terms of processor performance and energy consumption. The x86 today dominates processor shipments, it's going to probably continue to do so. Power has some presence, but ARM is growing very rapidly. Nvidia with GPUs is becoming a major player with AI coming in, we'll talk about that in a minute. And both the EU and China are developing their own processors. We're seeing massive densities with hundreds of thousands of cores that are being liquid-cooled with novel phase change technology. The third big trend is AI, which of course is still in the early stages, but it's being combined with ever larger and massive, massive data sets to attack new problems and accelerate research in dozens of industries. Now, the fourth big trend, HPC in the cloud reached critical mass at the end of the last decade. And all of the major hyperscalers are providing HPE, HPC as a service capability. Now finally, quantum computing is often talked about and predicted to become more stable by the end of the decade and crack new dimensions in computing. The EU has even announced a hybrid QC, with the goal of having a stable system in the second half of this decade, most likely around 2027, 2028. Welcome to theCUBE's preview of SC22, the big supercomputing show which takes place the week of November 13th in Dallas. theCUBE is going to be there. Dave Nicholson will be one of the co-hosts and joins me now to talk about trends in HPC and what to look for at the show. Dave, welcome, good to see you. >> Hey, good to see you too, Dave. >> Oh, you heard my narrative up front Dave. You got a technical background, CTO chops, what did I miss? What are the major trends that you're seeing? >> I don't think you really- You didn't miss anything, I think it's just a question of double-clicking on some of the things that you brought up. You know, if you look back historically, supercomputing was sort of relegated to things like weather prediction and nuclear weapons modeling. And these systems would live in places like Lawrence Livermore Labs or Los Alamos. Today, that requirement for cutting edge, leading edge, highest performing supercompute technology is bleeding into the enterprise, driven by AI and ML, artificial intelligence and machine learning. So when we think about the conversations we're going to have and the coverage we're going to do of the SC22 event, a lot of it is going to be looking under the covers and seeing what kind of architectural things contribute to these capabilities moving forward, and asking a whole bunch of questions. >> Yeah, so there's this sort of theory that the world is moving toward this connectivity beyond compute-centricity to connectivity-centric. We've talked about that, you and I, in the past. Is that a factor in the HPC world? How is it impacting, you know, supercomputing design? >> Well, so if you're designing an island that is, you know, tip of this spear, doesn't have to offer any level of interoperability or compatibility with anything else in the compute world, then connectivity is important simply from a speeds and feeds perspective. You know, lowest latency connectivity between nodes and things like that. But as we sort of democratize supercomputing, to a degree, as it moves from solely the purview of academia into truly ubiquitous architecture leverage by enterprises, you start asking the question, "Hey, wouldn't it be kind of cool if we could have this hooked up into our ethernet networks?" And so, that's a whole interesting subject to explore because with things like RDMA over converged ethernet, you now have the ability to have these supercomputing capabilities directly accessible by enterprise computing. So that level of detail, opening up the box of looking at the Nix, or the storage cards that are in the box, is actually critically important. And as an old-school hardware knuckle-dragger myself, I am super excited to see what the cutting edge holds right now. >> Yeah, when you look at the SC22 website, I mean, they're covering all kinds of different areas. They got, you know, parallel clustered systems, AI, storage, you know, servers, system software, application software, security. I mean, wireless HPC is no longer this niche. It really touches virtually every industry, and most industries anyway, and is really driving new advancements in society and research, solving some of the world's hardest problems. So what are some of the topics that you want to cover at SC22? >> Well, I kind of, I touched on some of them. I really want to ask people questions about this idea of HPC moving from just academia into the enterprise. And the question of, does that mean that there are architectural concerns that people have that might not be the same as the concerns that someone in academia or in a lab environment would have? And by the way, just like, little historical context, I can't help it. I just went through the upgrade from iPhone 12 to iPhone 14. This has got one terabyte of storage in it. One terabyte of storage. In 1997, I helped build a one terabyte NAS system that a government defense contractor purchased for almost $2 million. $2 million! This was, I don't even know, it was $9.99 a month extra on my cell phone bill. We had a team of seven people who were going to manage that one terabyte of storage. So, similarly, when we talk about just where are we from a supercompute resource perspective, if you consider it historically, it's absolutely insane. I'm going to be asking people about, of course, what's going on today, but also the near future. You know, what can we expect? What is the sort of singularity that needs to occur where natural language processing across all of the world's languages exists in a perfect way? You know, do we have the compute power now? What's the interface between software and hardware? But really, this is going to be an opportunity that is a little bit unique in terms of the things that we typically cover, because this is a lot about cracking open the box, the server box, and looking at what's inside and carefully considering all of the components. >> You know, Dave, I'm looking at the exhibitor floor. It's like, everybody is here. NASA, Microsoft, IBM, Dell, Intel, HPE, AWS, all the hyperscale guys, Weka IO, Pure Storage, companies I've never heard of. It's just, hundreds and hundreds of exhibitors, Nvidia, Oracle, Penguin Solutions, I mean, just on and on and on. Google, of course, has a presence there, theCUBE has a major presence. We got a 20 x 20 booth. So, it's really, as I say, to your point, HPC is going mainstream. You know, I think a lot of times, we think of HPC supercomputing as this just sort of, off in the eclectic, far off corner, but it really, when you think about big data, when you think about AI, a lot of the advancements that occur in HPC will trickle through and go mainstream in commercial environments. And I suspect that's why there are so many companies here that are really relevant to the commercial market as well. >> Yeah, this is like the Formula 1 of computing. So if you're a Motorsports nerd, you know that F1 is the pinnacle of the sport. SC22, this is where everybody wants to be. Another little historical reference that comes to mind, there was a time in, I think, the early 2000's when Unisys partnered with Intel and Microsoft to come up with, I think it was the ES7000, which was supposed to be the mainframe, the sort of Intel mainframe. It was an early attempt to use... And I don't say this in a derogatory way, commodity resources to create something really, really powerful. Here we are 20 years later, and we are absolutely smack in the middle of that. You mentioned the focus on x86 architecture, but all of the other components that the silicon manufacturers bring to bear, companies like Broadcom, Nvidia, et al, they're all contributing components to this mix in addition to, of course, the microprocessor folks like AMD and Intel and others. So yeah, this is big-time nerd fest. Lots of academics will still be there. The supercomputing.org, this loose affiliation that's been running these SC events for years. They have a major focus, major hooks into academia. They're bringing in legit computer scientists to this event. This is all cutting edge stuff. >> Yeah. So like you said, it's going to be kind of, a lot of techies there, very technical computing, of course, audience. At the same time, we expect that there's going to be a fair amount, as they say, of crossover. And so, I'm excited to see what the coverage looks like. Yourself, John Furrier, Savannah, I think even Paul Gillin is going to attend the show, because I believe we're going to be there three days. So, you know, we're doing a lot of editorial. Dell is an anchor sponsor, so we really appreciate them providing funding so we can have this community event and bring people on. So, if you are interested- >> Dave, Dave, I just have- Just something on that point. I think that's indicative of where this world is moving when you have Dell so directly involved in something like this, it's an indication that this is moving out of just the realm of academia and moving in the direction of enterprise. Because as we know, they tend to ruthlessly drive down the cost of things. And so I think that's an interesting indication right there. >> Yeah, as do the cloud guys. So again, this is mainstream. So if you're interested, if you got something interesting to talk about, if you have market research, you're an analyst, you're an influencer in this community, you've got technical chops, maybe you've got an interesting startup, you can contact David, david.nicholson@siliconangle.com. John Furrier is john@siliconangle.com. david.vellante@siliconangle.com. I'd be happy to listen to your pitch and see if we can fit you onto the program. So, really excited. It's the week of November 13th. I think November 13th is a Sunday, so I believe David will be broadcasting Tuesday, Wednesday, Thursday. Really excited. Give you the last word here, Dave. >> No, I just, I'm not embarrassed to admit that I'm really, really excited about this. It's cutting edge stuff and I'm really going to be exploring this question of where does it fit in the world of AI and ML? I think that's really going to be the center of what I'm really seeking to understand when I'm there. >> All right, Dave Nicholson. Thanks for your time. theCUBE at SC22. Don't miss it. Go to thecube.net, go to siliconangle.com for all the news. This is Dave Vellante for theCUBE and for Dave Nicholson. Thanks for watching. And we'll see you in Dallas. (inquisitive music)

>>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.

(bright upbeat music) >> Hi, everyone, welcome back to theCUBE's Unstoppable Domains Partner Showcase. I'm John Furrier, host of theCUBE. This segment in this session is about expansion into Asia Pacific and Europe for Unstoppable Domains. It's a hot startup in the Web3 area, really creating a new innovation around NFTs, crypto, single sign-on, and digital identity, giving users the power like they should. We've got two great guests, Sajjad Rehman, Head of Europe, and Nilkanth, known as Nil, Iyer, head of Asia. Sajjad, Nil, welcome to this CUBE, and let's talk about the expansion. It's not really an expansion, the global economy is global, but showcase here about Unstoppables going to Europe. Thanks for coming on. >> Thanks for inviting us. >> Thanks John, for inviting us. >> So we're living in a global world, obviously, crypto, blockchain, decentralized applications. You're starting to see mainstream adoption, which means the shift is happening. There are more apps coming, and it means more infrastructure, and things got to get easier, right? So, reduce the steps it takes to do stuff, makes the wallets better, give people more secure access and control of their data. This is what Unstoppable is all about. You guys are in the middle of it, you're on this wave. What is the potential of Web3 with Unstoppable, and in general, in Asia and in Europe? >> I can go first. So, now, let's look at the Asia market. I mean, typically, we see the US market, the Europe markets, for typical Web 2.0 software and infrastructure is definitely the larger markets, with US typically accounting for about 60%, and Europe about 20 to 30%, and Asia has always been small. But we see in this whole world of blockchain, crypto, Web 3.0, Asia already has about 160 million users. They have more than 35 local exchanges. And if you really look at the number of countries, in terms of the rate of adoption, many of the Asian countries, which probably you'd have never even heard of, like Vietnam, actually topping the list, right? One of the reasons that this is happening, again, if you go through the Asian Development Bank's latest report, you have these Gen Zs and millennials, of that's 50% of the Asian population. And if you really look at 50% of the Asian population, that's 1.1 billion people out of the total, 1.8 billion Gen Z and millennials that you have have in the world. And these folks are digitally native, they're people, in fact, the Gen Zs are mobile first, and millennials, many of us, like myself, at least, are people who are digital, and 20% of the world's economy is currently digital, and the rest, 40 to 50%, which is going to happen in the Web 3.0 world, and that's going to be driven by millennials and Gen Zs. I think that's why this whole space is so exciting, because it's being driven by the users, by the new generation. I mean, that's my broad thought on this whole thing. >> Before we get get this started, I want to just comment, Asia, also, in other areas where mobile first came, you had the younger demographics absolutely driving the change, because they're like, "Well, I don't want the old way." They go right from scratch at the beginning, they're using the technologies. That has propelled the crypto world. I mean, that is absolutely true. Everyone's kind of seeing that. And that's now influencing some of these developer nations, like say, in Europe, for instance, and even North America, I think Europe's more advanced than North America, in my opinion, but we'll get to that. Oh, so potential in Europe. Sajjad, take us through your thoughts on... As head of Europe, for our audience. >> Absolutely, so, Nil's right. I think Asia is way ahead in terms of Gen Z user adopting crypto, Europe is actually a distant second, but it's surprising to note that Europe actually has the highest transactional activity in crypto over the last year and a half. And if you dig a bit deeper, I'd say, arguably, for Europe, I think the opportunity in Web3 is perhaps the largest. And then perhaps it can mean the most for Europe. Europe, for the last decade, has been trailing behind Asia and North America, when it comes to birthing unicorns, and I think Web3 can provide a StepChain opportunity. This belief, for me, stems from the fact that Europe's policy, right, like, for example, GDPR, is focused on enabling your data ownership. And I think I recently read a very good paper out of Stanford, by Patrick Henson. He speaks about Web3 being the best part, here, for Europe enabling patient sovereignty. So what that means is users control the data, they're paying to enter it, and they harness the value from it. And on one hand, while Europe is enabling that regulation, that's entered in that code, Web3 actually brings it into action. So I think with more enablement, better regulation, and we'll see more hubs, like the Crypto Valley in Switzerland pop up, that will bring, I think, I'd rather be careful, better to say, not over-regulation, the right regulation. We can expect more in prop capital, more builder talent, that then drives more adoption. So I think the prospects for Europe in terms of usage, as well as builders, are quite bright. >> Yeah, and I think, also, you guys are in areas where the cultural shift is so dramatic. You mentioned Asia, the demographics, even the entrepreneurial culture in Europe right now is booming. You look at all the venture-backed startups, and the young generation building companies! And again, cloud computing is a big part of that, obviously. But look at, compared to the United States, you go back 15 years ago, Europe was way behind, on the startup scene. Now it's booming and pumping on all cylinders. And it kind of points at this cultural shift. It's almost like a generational... It's like the digital hippies changing the world. The Web3, it's kind of, "I don't want to be Web2, Web2 is so old, I don't want to do that." And then it's all because it's changing, right? And there are things inadequate with Web2, on the naming system. Also the arbitrage around fake information, bots, users being manipulated, and also merchandised and monetized through these portals. Okay, that's kind of ending. So talk about the dynamic of Web2, 3, at those areas. You've got users and you've got companies, who build applications. They're going to shift and be forced, in our opinion, and I want to get your reaction to that. Do you think applications are going to have to be Web3, or users will reject them? >> Yeah, I think that I'll jump in and add to there in Nil's part. I think the Web3 is built on three principles, right? They're decentralization, ownership, and composability. And I think these are not binary. So if I look further on in the future, I don't see a future where you have just Web3. I think there's going to be coexistence or cooperation between Web2 companies, Web3, building bridges. I think there's going to be... There's a sliding scale to decentralization, versus centralization. Similarly, ownership. And I think users will find what works best for them in different contexts. I think what Unstoppable is doing is essentially providing the identity system for Web3, and that's way more powerful when it comes to being built on blockchains, than with the naming system we had for Web2, right? The identity system can serve the purpose of taking a user's personal identifier, password, blockchain, domain name, and attaching all kinds of attributes that define who you are, both in the physical and digital world, and filling out information that you can transact on the basis of. And I think the users would, as we go to a no-code and low-code future, right, where in Web2, more of the users were essentially consumers, or readers of the internet. And in Web3, with more low-code and no-code technology platforms taking shape and getting proliferation, you would see more users being actually writers, publishers, and developers on the internet. And they would value owning their data, and to harness the most amount of value from it. So I think that's the power concept, and I think that's the future I see, where Web3 will dominate. Nil, what do you think? >> Well, I think you put it very, very nicely, Sajjad. I think you covered most of the points, I think. But I'm seeing a lot of different things that are happening at the ground. I think a lot of the governments, a lot of the Web 2.0 players, the traditional banks, these guys are not sitting quiet on the blockchain space. There are a lot of pilots happening in the blockchain space, right? I mean, I can give you real life examples. I mean, one of the biggest examples is in my home state of Maharashtra, where Mumbai is. They actually partnered with Polygon (MATIC), right? Actually built a private blockchain-based capability to kind of deliver your COVID vaccination certificates with the QR code, right? And that's the only way they could deliver that kind of volumes in that short a time, with the kind of user control, the user control the user has on the data. That could only be possible because of blockchain. Of course, it's still private, because it's healthcare data, they still want to keep it, something that's not fully on a blockchain. But that is something. Similarly, there is a consortium of about nine banks who have actually trying to work on making things like remittances or trade finance much, much easier. I mean, remittances through a traditional, Web 2.0 world is very, very costly. And especially in the Asian countries, a lot of people from Southeast Asia work across the world and send back money home. It's a very costly and a time-taking affair. So they have actually partnered and built a blockchain-based capability, again, in a pilot stage, to kind of reduce the transaction costs. For example, if you just look at the trade finance days where there are 14 million traders, who do 2.4, 5 trillion dollars, of transaction, they were able to actually reduce the time that it takes from eight to nine days, to about two to three days. And so, to add on to what you're saying, I think these two worlds are going to meet, and meet very soon. And when they meet, what they need is a single digital identity, a human-readable way of being able to send and receive and do commerce. I think that's where I see Unstoppable Domains, very nicely positioned to be able to integrate these two worlds, so that's my thought on all the logistics. >> That was a great point. I was going to get into which industries, and kind of what areas, you see in your geographies. But it's a good point about saving time. I like how you brought that up, because in these new waves, you either got to reduce the steps it takes to do something, or save time, make it easy. And this is the successful formula, in anything, whether it's an app or UI or whatever, but what specifically are they doing in your areas? And what about Unstoppable are they attracted to? Is it because of the identity? Is it because of the apps? Is it because of the single sign-on? What is the reason that they're leaning in, and unpacking this further into their pilots? >> Sajjad, do you want to take that? >> Yeah, absolutely, man. >> Because. >> Yeah, I'm happy. Please jump in if you want. So I think, and let me clarify the question, John, you're talking about Web2 companies, looking to partner in software, or potential partnerships, right? >> Yeah, what are they seeing, and what are they seeing as the value that these pilots we heard from Nilkanth around the financial industry? And obviously, gaming's one, it's obvious. Huge: financial, healthcare, I mean, these are obviously verticals that are going to be heavily impacted in a positive way. What are they seeing as value? What's getting them motivated to do these pilots? Why are they jumping in, with both feet, if you will, on these projects? Is it because it's saving money, is it time, or both, is it ease of use, is it the user's expectations? Trying to tease out how you guys see that evolving. >> Yeah, yeah, I think... This is still, the space is, the movement is going very fast, but I think the space is still young. And right now, a lot of these companies are seeing the potential that Web3 offers. And I think the key, key dimensions, right, composability, decentralization, and ownership. So I think the key thing I'm seeing in EU is these Web2 companies seeing the momentum and looking to harness that by enabling bridges to Web3. One of the key trends in Europe has been Fintech, I think over the last five to six years, we have the Revolut, N26, e-TOTAL creating platforms, new banks and super finance, super apps rising to the forefront. And they are all enabling, or also connecting a bridge with Web3 in some shape and form, either enabling creating of crypto, some are launching their own native wallets, and these are, essentially, ways that they can, one, attract users. So the Gen Z who are looking for more friction in finance, to get them on board, but also to look to enable more adoption by their own users, who are not using these services that potentially create new revenue streams, and create allocation of capital that they could not access, to have access to otherwise. So I think that's one trend I'm seeing over here. I think the other key trend is, in Europe, at least, has been games. And again, dead links or damaged, web creators would call the metaverse. So a lot of game companies are looking to step into Game Fire, which is, again, a completely different business model to what traditional game companies used to use. Similarly, metaverse is where again, ownership creates a different business model and they see that users and gamers of the future would want to engage with that, versus just being monetized on the basis of subscription or ads. And I think that's something that they're becoming aware of, and moving quickly in the space, launching their own metaverses, or game by applications. Or creating interoperability with these decentralized applications. >> You know, I wanted to get into this point, but I was going to ask about the community empowerment piece of this equation, 'cause digital identity is about the user's identity, which implies they're part of a community. Web3 is very community-centric. But you mentioned gaming, I mean, people who have been watching the gaming world, like ourselves, know that communities and marketplaces have been very active for years, many years, over 15 years. Community, games, currency, in-game activity, has been out there, right, but siloed within the games themselves. So now, it seems that that paradigm's coming in and empowering all communities. Is this something that you guys see and agree with? And if so, what's different about that? How are communities being empowered? I guess that's the question. >> Yeah, I can maybe take that, Sajjad. So, I mean, I must have heard of Axie Infinity, I mean, 40% of their user base is in Vietnam. And the average earning that a person makes in a month, out of playing this game, is more than the national, daily or minimum wage that is there, right? So that's the kind of potential. Actually, going back, as a combination of actually answering your earlier question, and I think over and above what Sajjad said, what's very unique in Asia is we still have a lot of unbanked people, right? So if you really look at the total unbanked population of the world, it's 1.6 billion, and 24% of that is in Asia, so almost 375 million people are in Asia. So these are people who do not have access to finance or credit. So the whole idea is, how do we get these people on to a banking system, onto peer-to-peer lending, or peer-to-peer finance kind of capabilities. I think, again, Unstoppable Domains kind of helps in that, right? If you just look at the pure Web 3.0 world, and the complex, technical way in which money or other crypto is transferred from one wallet to the other, it's very difficult for an unbanked person who probably cannot even do basic communication, cannot read and write, to actually be able to do it. But something that's very human-readable, something that's very easy for him to understand, something that's visual, something that he can see on his mobile. With 2G network, we are not talking of... The world is talking about 5G, but there are parts of Asia, which are still using 2G and 2.5G kind of network, right? So I think that's one key use case. I think the banks are trying to solve because for them, this is a whole new customer segment. And, sorry, I actually went back a little bit, to your earlier question, but coming to this whole community-building, right? So on March 8th, we're launching something called this Women of Web3, or, oh, that is WoW3, right? This is basically to, again, empower. So if you, again, look at Asia, women need a lot of training, they need a lot of enablement, for them to be able to leverage the power of Web 3.0. I can talk about India, of course, being from India. A lot of the women do not... They do all the small businesses, but the money is taken by middlemen, or taken by their husbands. With Web 3.0, fundamentally, the money comes to them, because that's what they use to educate their children. And it's the same thing in a lot of other Southeast Asian countries as well. I think it's very important to build those communities, communities of women entrepreneurs. I think this is a big opportunity to really get the section of society, which probably will take 10 more years, if we go through the normal Web1 to Web 2.0 progression, where the power is with corporations, and not with the individuals. >> And that's a great announcement, by the way, you mentioned the $10 million worth of domains being issued out for... This is democratization, it's what it's all about. Again, this is a new revolution. I mean, this is a new thing. So great stuff, more education, more learning. And going to get the banks up and running, get those people banking, 'cause once they're banking, they get wallets, right? So they need the wallets. So let's get to the real meat here. You guys are in the territory, Europe and Asia, where there's a lot of wallets. There's a lot of exchanges, 'cause that's... They're not in the United States. There's a few of them there, but most of them outside the United States. And you've got a lot of dApps developing, decentralized applications, okay? So you got all this coming together in your territory. What's the strategy, how you going to attack that? You got the wallets, you got the exchanges, and you got D applications. DApps. >> Yeah, I'm happy to (indistinct). So I think, and just quickly there, I think one point is, and Nil really expressed it beautifully, is finding inclusion. That is something that has inspired me, how Web3 can make the internet more inclusive. That inspired my move here. Yeah, I think, for us, I think we are at the base start when it comes to Europe, right? And the key focus, in terms of our approach in Europe would be that, we want to do two things. One, we want to increase the utility of these domain names. And the second thing is, we will invite proliferation with our partners. So when I speak about utility, I think utility is when you have a universal identifier, which is a domain name, and then you have these attributes around it, right? What then defines your identity. So in the context, in Europe, we would look to find partners to help us enrich that identity around the domain name. And that adds value for users, in terms of acquiring these domains and new clients. And on the other end, when it comes to proliferation, I think it's about working with all those crypto, and crypto and Web3, Web3 participants as well as Web3-adjacent companies, brands, and services, who can help us educate current and future, and upcoming Web3 users about the utility of domain names, and help us onboard them to the decentralized internet. So I think that's going to be the general focus. I think the key is that, as, oh, and hopefully, we'll be having one, overarching regulation, EU, that allowed us to do this at a vision level. But I would say I think it's going to be tackling it country by country, identifying countries where there's deeper penetration for Web3, and then making sure that we are partnered with local, trusted partners that are already developing for local communities there. So, yeah, that's my view and Nil, I believe those are wants in, for Asia. >> Oh, I think, yeah, so again, in Asia, one is you have a significant part of humanity living in Asia, right? So obviously, all the other challenges and the opportunities that we talk about, I think the first area of focus would be educating the people on the massive opportunity that they have, and if you're able to get them in early, I think it's great for them as well, right? Because by the time governments, regulations, large banking, financial companies move, but if you can get the larger population into this whole space, it's good for them, so they are first movers in that space. I think we are doing a lot of things on this, worldwide. I think we've done more than 100 past podcasts, just educating people on what is Web 3.0, what are NFT domains? What is DeFi, and so on and so forth. I think it would need some bit of localization, customization, in Asia, given that India itself has about 22 languages. And then there are the other countries which, each of them with their own local languages and syntax, semantics and all those things, right? So I think that that is very important, to be able to disseminate the knowledge, although it's global, but I think to get the grassroot people to understand the opportunity, I think it would need some amount of work there. I think also building communities, I think, John, you talked about communities, so did Sajjad talk about communities. I think it's very important to build communities, because communities create ideation. It talks about... People share their challenges, so that people don't repeat the same mistakes. So I think it's very important to build communities based on interest. I think we all know in the technology world, you can build communities around Elegram, Telegram, Discord, Twitter spaces, and all those things. But, again, when you're talking of financial inclusion, you're talking of a different kind of community-building. I think that that would be important. And then of course I will kind of, primarily from a company perspective, I think getting the 35 odd exchanges in Asia, the wallets to partner with us. Just as an example, MATIC. They had, until September of last year, about 3,500 apps. In just one quarter, it doubled to 7,000 dApps on their platform. But that is the pace, or the speed of innovation that we are seeing on this whole 3.0 space. I think it's very important to get those key partners, Who are developing those dApps. See the power of single sign-on, having a human-readable, digital identity, being able to seamlessly transfer all your assets, digital assets, across multiple cryptos, across multiple NFT marketplaces, and so on and so forth. >> Yeah, and I think the whole community thing, too, is also you seeing the communities being part of, certainly in the entertainment area, and the artistry, creator world, the users are art of the community, they own it, too. So it goes both ways, but this brings up the marketplace, too, as well, because you guys have the opportunity to have trust built into the software layer, right? So now you can keep the reputation data. You can be anonymous, but it's trustworthy, versus bots, which we all know bots can be killed and then started again with... And no one knows what the tagalong has been around. So the whole inadequacy of Web2, which is just growing pains, right? This is what it evolution looks like, next abstraction layer. So I love that vibe. How advanced do you think that thinking is, where people are saying, Hey, we need this abstraction layer. We need this digital identity. We need to start expanding our applications so that the users can move across these and break down those silos where the data is, 'cause that's... This is like the nerd problem, right? It's the data silos that are holding it back. What's your guys' reaction to that? The killing the silos and making it horizontally scalable? >> Yeah, I think it's a nerd problem. It is a problem of people who understand technology. It's a problem of a lot of the people in the business who want to compete effectively against those giants, which are holding all the data. So I think those are the people who will innovate and move. Again, coming back to financial inclusion, coming back to the unbanked, those guys just want to do their business. They want to live their daily life. I think that's not where you'll see... You will see innovation in a different form, but they're not going to disrupt the disrupters. I think that would be the people, Fintechs, I think they would be the first to move on to something like that. I mean, that's my humble opinion. >> Sajjad, you heard. >> Yeah, I think- >> Go ahead. >> I mean, absolutely. I think, I mean, I touched on creators, right? So, like I said earlier, right, we are heading to a future where more people will be creators on the internet. Whether you're publishing, writing something, you're creating video content, and that means that they have data they own, but that's their data, they bring it to the internet. That's more powerful, more useful, and they should be able to transact on that basis. So I think people are recognizing that, and they will increasingly look to do so. And as they do that, they would want these systems that enable them to hold permission to their data. They will want to be able to control what their permission and what they want to provide, dApp. And at the end of the day, these applications have to work backwards from customers, and the customer's looking for that. That's where... That's what they will build. >> The users want freedom. They want to be able to be connected, and not be restricted. They want to freely move around the global internet and do whatever they want with the friends and apps that they want to consume, and not feel arbitraged. They don't want to feel like they're kind of nailed into a walled garden and stuck there and having to come back. It's the new normal. >> They don't want to be the product, right, so. >> They don't want to be the product. Gentlemen, great to have you on, great conversation. We're going to continue this later. Certainly want to keep the updates coming. You guys are in a very hot area in Europe and Asia Pacific. That's where a lot of the action is happening. We see the entrepreneurial activity, the business transformation, certainly with the new paradigm shift, and this big wave that's coming. It's here, it's mainstream. Thanks for coming on and sharing your insights. Appreciate it. >> Thanks, John. >> Thanks, John, Thanks for the opportunity, have a good day. >> Okay, okay, great conversation. All the action's moving and happening real fast. This is theCUBE Unstoppable Domains Partner Showcase. I'm John Furrier, your host. Thanks for watching. (contemplative music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage of the "AWS Startup Showcase", season two, episode one. I'm Lisa Martin, and I'm excited to be joined by Snyk, next in this episode. Liran Tal joins me, the director of developer advocacy. Liran, welcome to the program. >> Lisa, thank you for having me. This is so cool. >> Isn't it cool? (Liran chuckles) All the things that we can do remotely. So I had the opportunity to speak with your CEO, Peter McKay, just about a month or so ago at AWS re:Invent. So much growth and momentum going on with Snyk, it's incredible. But I wanted to talk to you about specifically, let's start with your role from a developer advocate perspective, 'cause Snyk is saying modern development is changing, so traditional AppSec gatekeeping doesn't apply anymore. Talk to me about your role as a developer advocate. >> It is definitely. The landscape is changing, both developer and security, it's just not what it was before, and what we're seeing is developers need to be empowered. They need some help, just working through all of those security issues, security incidents happening, using open source, building cloud native applications. So my role is basically about making them successful, helping them any way we can. And so getting that security awareness out, or making sure people are having those best practices, making sure we understand what are the frustrations developers have, what are the things that we can help them with, to be successful day to day. And how they can be a really good part of the organization in terms of fixing security issues, not just knowing about it, but actually being proactively on it. >> And one of the things also that I was reading is, Shift Left is not a new concept. We've been talking about it for a long time. But Snyk's saying it was missing some things and proactivity is one of those things that it was missing. What else was it missing and how does Snyk help to fix that gap? >> So I think Shift Left is a good idea. In general, the idea is we want to fix security issues as soon as we can. We want to find them. Which I think that is a small nuance that what's kind of missing in the industry. And usually what we've seen with traditional security before was, 'cause notice that, the security department has like a silo that organizations once they find some findings they push it over to the development team, the R&D leader or things like that, but until it actually trickles down, it takes a lot of time. And what we needed to do is basically put those developer security tools, which is what Snyk is building, this whole security platform. Is putting that at the hands and at the scale of, and speed of modern development into developers. So, for example, instead of just finding security issues in your open source dependencies, what we actually do at Snyk is not just tell you about them, but you actually open a poll request to your source codes version and management system. And through that we are able to tell you, now you can actually merge it, you can actually review it, you can actually have it as part of your day-to-day workflows. And we're doing that through so many other ways that are really helpful and actually remediating the problem. So another example would be the IDE. So we are actually embedding an extension within your IDEs. So, once you actually type in your own codes, that is when we actually find the vulnerabilities that could exist within your own code, if that's like insecure code, and we can tell you about it as you hit Command + S and you will save the file. Which is totally different than what SaaS tools starting up application security testing was before because, when things started, you usually had SaaS tools running in the background and like CI jobs at the weekend and in deltas of code bases, because they were so slow to run, but developers really need to be at speed. They're developing really fast. They need to deploy. One development is deployed to production several times a day. So we need to really enable developers to find and fix those security issues as fast as we can. >> Yeah, that speed that you mentioned is absolutely critical to their workflow and what they're expecting. And one of the unique things about Snyk, you mentioned, the integration into how this works within development workflow with IDE, CIDC, they get environment enabling them to work at speed and not have to be security experts. I imagine are two important elements to the culture of the developer environment, right? >> Correct, yes. It says, a large part is we don't expect developers to be security experts. We want to help them, we want to, again, give them the tools, give them the knowledge. So we do it in several ways. For example, that IDE extension has a really cool thing that's like kind of unique to it that I really like, and that is, when we find, for example, you're writing code and maybe there's a batch traversal vulnerability in the function that you just wrote, what we'll actually do when we tell you about it, it will actually tell you, hey, look, these are some other commits made by other open source projects where we found the same vulnerability and those commits actually fixed it. So actually giving you example cases of what potentially good code looks like. So if you think about it, like who knows what patch reversal is, but prototype pollution like many types of vulnerabilities, but at the same time, we don't expect developers to actually know, the deep aspects of security. So they're left off with, having some findings, but not really, they want to fix them, but they don't really have the expertise to do it. So what we're doing is we're bridging that gap and we're being helpful. So I think this is what really proactive security is for developers, that says helping them remediate it. And I can give like more examples, like the security database, it's like a wonderful place where we also like provide examples and references of like, where does their vulnerability come from if there's like, what's fogging in open-source package? And we highlight that with a lot of references that provide you with things, the pull requests that fixed date, or the issue with where this was discussed. You have like an entire context of what is the... What made this vulnerability happen. So you have like a little bit more context than just specifically, emerging some stuff and updating, and there's a ton more. I'm happy to like dive more into this. >> Well, I can hear your enthusiasm for it, a developer advocate it seems like you are. But talking about the burdens of the gaps that you guys are filling it also seems like the developers and the security folks that this is also a bridge for those teams to work better together. >> Correct. I think that is not siloed anymore. I think the idea of having security champions or having threat modeling activities are really, really good, or like insightful both like developers and security, but more than just being insightful, useful practices that organizations should actually do actually bringing a discussion together to actually creating a more cohesive environment for both of those kind of like expertise, development and security to work together towards some of these aspects of like just mitigating security issues. And one of the things that actually Snyk is doing in that, in bringing their security into the developer mindset is also providing them with the ability to prioritize and understand what policies to put in place. So a lot of the times security organizations actually, the security org wants to do is put just, guardrails to make sure that developers have a good leeway to work around, but they're not like doing things that like, they definitely shouldn't do that, like prior to bringing a big risk into today organizations. And that's what I think we're doing also like great, which is the fact that we're providing the security folks to like put the policies in place and then developers who actually like, work really well within those understand how to prioritize vulnerabilities is an important part. And we kind of like quantify that, we put like an urgency score that says, hey, you should fix this vulnerability first. Why? Because it has, first of all, well, you can upgrade really quickly. It has a fix right there. Secondly, there's like an exploit in the wild. It means potentially an attacker can weaponize this vulnerability and like attack your organizations, in an automated fashion. So you definitely want to put that put like a lead on that, on that broken window, if so to say. So we ended up other kind of metrics that we can quantify and put this as like an urgency score, which we called a priority score that helps again, developers really know what to fix first, because like they could get a scan of like hundreds of vulnerabilities, but like, what do I start first with? So I find that like very useful for both the security and the developers working together. >> Right, and especially now, as we've seen such changes in the last couple of years to the threat landscape, the vulnerabilities, the security issues that are impacting every industry. The ability to empower developers to not only work at the speed with which they are accustomed and need to work, but also to be able to find those vulnerabilities faster prioritize which ones need to be fixed. I mean, I think of Log4Shell, for example, and when the challenge is going on with the supply chain, that this is really a critical capability from a developer empowerment perspective, but also from a overall business health and growth perspective. >> Definitely. I think, first of all, like if you want to step just a step back in terms of like, what has changed. Like what is the landscape? So I think we're seeing several things happening. First of all, there's this big, tremendous... I would call it a trend, but now it's like the default. Like of the growth of open source software. So first of all as developers are using more and more open source and that's like a growing trend of have like drafts of this. And it's like always increasing across, by the way, every ecosystem go, rust, .net, Java, JavaScript, whatever you're building, that's probably like on a growing trend, more open source. And that is, we will talk about it in a second what are the risks there. But that is one trend that we're saying. The other one is cloud native applications, which is also worth to like, I think dive deep into it in terms of the way that we're building applications today has completely shifted. And I think what AWS is doing in that sense is also creating a tremendous shift in the mindset of things. For example, out of the cloud infrastructure has basically democratized infrastructure. I do not need to, own my servers and own my monitoring and configure everything out. I can actually write codes that when I deploy it, when something parses this and runs this, it actually creates servers and monitoring, logging, different kinds of things for me. So it democratize the whole sense of building applications from what it was decades ago. And this whole thing is important and really, really fast. It makes things scalable. It also introduces some rates. For example, some of these configuration. So there's a lot that has been changed. And in that landscape of like what modern developer is and I think in that sense, we kind of can need a lead to a little bit more, be helpful to developers and help them like avoid all those cases. And I'm like happy to dive into like the open source and the cloud native. That was like follow-ups on this one. >> I want to get into a little bit more about your relationship with AWS. When I spoke with Peter McKay for re:Invent, he talked about the partnership being a couple of years old, but there's some kind of really interesting things that AWS is doing in terms of leveraging, Snyk. Talk to me about that. >> Indeed. So Snyky integrates with almost, I think probably a lot of services, but probably almost all of those that are unique and related to developers building on top of the AWS platform. And for example, that would be, if you actually are building your code, it connects like the source code editor. If you are pushing that code over, it integrates with code commits. As you build and CIS are running, maybe code build is something you're using that's in code pipeline. That is something that you have like native integrations. At the end of the day, like you have your container registry or Lambda. If you're using like functions as a service for your obligations, what we're doing is integrating with all of that. So at the end of the day, you really have all of that... It depends where you're integrating, but on all of those points of integration, you have like Snyk there to help you out and like make sure that if we find on any of those, any potential issues, anything from like licenses to vulnerabilities in your containers or just your code or your open source code in those, they actually find it at that point and mitigate the issue. So this kind of like if you're using Snyk, when you're a development machine, it kind of like accompanies you through this journey all over what a CIC kind of like landscape looks like as an architectural landscape for development, kind of like all the way there. And I think what you kind of might be I think more interested, I think to like put your on and an emphasis would be this recent integration with the Amazon Inspector. Which is as it's like very pivotal parts on the AWS platform to provide a lot of, integrate a lot of services and provide you with those insights on security. And I think the idea that now that is able to leverage vulnerability data from the Snyk's security intelligence database that says that's tremendous. And we can talk about that. We'd look for shell and recent issues. >> Yeah. Let's dig into that. We've have a few minutes left, but that was obviously a huge issue in November of 2021, when obviously we're in a very dynamic global situation period, but it's now not a matter of if an organization is going to be hit by vulnerabilities and security threats. It's a matter of when. Talk to me about really how impactful Snyk was in the Log4Shell vulnerability and how you help customers evade probably some serious threats, and that could have really impacted revenue growth, customer satisfaction, brand reputation. >> Definitely. The Log4Shell is, well, I mean was a vulnerability that was disclosed, but it's probably still a major part and going to be probably for the foreseeable future. An issue for organizations as they would need to deal with us. And we'll dive in a second and figure out like why, but in like a summary here, Log4Shell was the vulnerability that actually was found in Java library called Log4J. A logging library that is so popular today and used. And the thing is having the ability to react fast to those new vulnerabilities being disclosed is really a vital part of the organizations, because when it is asking factful, as we've seen Log4Shell being that is when, it determines where the security tool you're using is actually helping you, or is like just an added thing on like a checkbox to do. And that is what I think made Snyk's so unique in the sense. We have a team of those folks that are really boats, manually curating the ecosystem of CVEs and like finding by ourselves, but also there's like an entire, kind of like an intelligence platform beyond us. So we get a lot of notifications on chatter that happens. And so when someone opens an issue on an open source repository says, Hey, I found an issue here. Maybe that's an XSS or code injection or something like that. We find it really fast. And we at that point, before it goes to CVE requirement and stuff like that through like a miter and NVD, we find it really fast and can add it to the database. So this has been something that we've done with Log4Shell, where we found that as it was disclosed, not on the open source, but just on the open source system, but it was generally disclosed to everyone at that point. But not only that, because look for J as the library had several iterations of fixes they needed. So they fixed one version. Then that was the recommendation to upgrade to then that was actually found as vulnerable. So they needed to fix the another time and then another time and so on. So being able to react fast, which is, what I think helped a ton of customers and users of Snyk is that aspect. And what I really liked in the way that this has been received very well is we were very fast on creating those command line tools that allow developers to actually find cases of the Log4J library, embedded into (indistinct) but not true a package manifest. So sometimes you have those like legacy applications, deployed somewhere, probably not even legacy, just like the Log4J libraries, like bundled into a net or Java source code base. So you may not even know that you're using it in a sense. And so what we've done is we've like exposed with Snyk CLI tool and a command line argument that allows you to search for all of those cases. Like we can find them and help you, try and mitigate those issues. So that has been amazing. >> So you've talked in great length, Liran about, and detail about how Snyk is really enabling and empowering developers. One last question for you is when I spoke with Peter last month at re:Invent, he talked about the goal of reaching 28 million developers. Your passion as a director of developer advocacy is palpable. I can feel it through the screen here. Talk to me about where you guys are on that journey of reaching those 28 million developers and what personally excites you about what you're doing here. >> Oh, yeah. So many things. (laughs) Don't know where to start. We are constantly talking to developers on community days and things like that. So it's a couple of examples. We have like this dev site community, which is a growing and kicking community of developers and security people coming together and trying to work and understand, and like, just learn from each other. We have those events coming up. We actually have this, "The Big Fix". It's a big security event that we're launching on February 25th. And the idea is, want to help the ecosystem secure security obligations, open source or even if it's closed source. We like help you fix that though that yeah, it's like helping them. We've launched this Snyk ambassadors program, which is developers and security people, CSOs are even in there. And the idea is how can we help them also be helpful to the community? Because they are like known, they are passionate as we are, on application security and like helping developers code securely, build securely. So we launching all of those programs. We have like social impact related programs and the way that we like work with organizations, like maybe non-profit maybe they just need help, like getting, the security part of things kind of like figured out, students and things like that. Like, there's like a ton of those initiatives all over the boards, helping basically the world be a little bit more secure. >> Well, we could absolutely use Snyk's help in making the world more secure. Liran it's been great talking to you. Like I said, your passion for what you do and what Snyk is able to facilitate and enable is palpable. And it was a great conversation. I appreciate that. And we look forward to hearing what transpires during 2022 for Snyk so you got to come back. >> I will. Thank you. Thank you, Lisa. This has been fun. >> All right. Excellent. Liran Tal, I'm Lisa Martin. You're watching theCUBE's second season, season two of the "AWS Startup Showcase". This has been episode one. Stay tuned for more great episodes, full of fantastic content. We'll see you soon. (upbeat music)

(calm electronic music) >> Hey, welcome back everyone to theCUBE coverage of AWS re:Invent 2021. I'm John Furrier, your host. We're here with two sets with live content, pumping out 120 years over the course of a couple of days, 28 hours of programming from the people making things happen, sharing the news, and the insight. We've got Sandy Carter, worldwide public sector vice president of partners and programs for Amazon web services. Sandy, CUBE alumni, welcome back to theCUBE. Great to see you. >> Great to see you too, John. It's so awesome to be here in person, right? >> The news is coming more and more. We got health care news. We got this news, we got all kinds of certification. We just recently talked on a segment about all the great stuff on certifications, but healthcare is booming, okay? We got talking about delivering the kind of performance that people need in healthcare with data, and you've got delivery, destination is healthcare. Let's talk health care, what's going on? >> Yeah, so we made a couple of really awesome announcements around healthcare today. So if you think about it, one of the big trends in healthcare is digitizing health records, so electronic healthcare records to really help and assist with patient care. So, because that is so big, we launched an initiative for electronic healthcare records, migration assistance. And what that means is that, we have now added technical subject matter experts and industry subject matter experts in the healthcare space who understand EHR, electronic health records, to help us migrate at least 500 ISV applications over to AWS. This is really big news, because so far, most of those applications are running on-premises. So getting them over to the cloud gives them the scalability, gives them the agility, that they need to provide all of us better healthcare. >> Well, one of the big themes is the Epic performance, the database on the cloud. Cloud has given so much agility and has changed the game. I mean, I'm old enough to remember, I mean, we can look back on the shifts in technology. You had that era of healthcare where data and the records were super important. Privacy, lock it down. Don't talk to each other. Are we going to respect the privacy of the individuals? That's all now changed with horizontal scalable data, as Swami pointed out, who's the SVP leader of AI and the data for AWS, whole new paradigm of data architecture. This is disrupting healthcare. >> Yes And you've got the Epic situation. Take us through, why is this important? Why are we talking about Epic? >> Well, so EHR is one of the announcements. And then the second big announcement, is our Epic on AWS announcement. So, you may have covered this back in the August, September timeframe, we announced a new EC2 instance, called the M6I. And Epic, which is one of the leading global healthcare providers in the world, has been migrated to the cloud. And so, they started testing themselves, Epic started testing on the M6I. And so what we saw is a 40% performance improvement. Now that is, that's huge, as well as a 30% reduction in total cost of ownership. So if you're a partner out there, you're going to see, as your application runs on top of Epic, you're going to get that performance gain. And Epic has an amazing ecosystem, John. They have what they call the code travelers. They kind of exist on Epic, cause everybody uses Epic. Those ISBs are now going to get that benefit, and 90% of the current Epic customers. And then, our consulting partners are also going to see the benefit, because of that total cost of ownership reduction of 30%. So imagine you're a consulting partner, you're now going to go into a hospital that's using Epic and tell them that you can reduce their total cost of ownership by 30%. That's amazing! >> Well, first of all, the cost thing is amazing. But also, when you mentioned the instances, what's happening with the graviton and the processors and the performance you're getting in the cloud now, the applications are running faster and lower cost. So, you know, databases, they really want the boast horsepower. So you've got the cloud performance, you've got the lower cost. Why wouldn't anyone want to run it anywhere else? This is what I'm saying on my story I wrote Sunday night. All the modern applications will go to the best performance, even legacy apps. >> That's right, and I think this is so important because you know, you need performance, you need speed. You need to get the rest of this application migrated over. That's why we got the EHR migration initiative. And then if you couple that with our third announcement around authority to operate that now gives you that security and compliance, right? Because if you're a hospital, you can't risk having that patient information exposed. And so we introduced as an authority to operate a program that enables our partners to get HIPAA and high trust authorization faster, cheaper, so that they can move with this new digital trend that's happening all across healthcare. I mean, it is our fastest growing area today, growing at 105%. >> Yeah, it points to examine, it's another one of those areas that is urgent under COVID. It's exploding because of the demand, just on performance. And Swami said it today, also in the keynote, the AI data keynote, governance should be an enabler, not an inhibitor. >> Sandy: That's right. So when you start getting into governance where you can start managing the data in a way that's cool for people to use the data, but protect the privacy, you then can have the modern apps. >> And if I could just add on one thing there, today we talked about, you know, when you go on your digital transformation journey, it requires digital security, especially in healthcare. And so as you have those requirements, you have to be able to, not just get stuff to the cloud, it's got to be secure. And that's why HIPAA and high trust exist today. >> And these fine grain controls now available are amazing. So again, I love the way you guys are going in this direction with AWS. I got to say every year, it's like, wow, again. But I want to get back to this ISV angle because I think this is super important. Again, I teased this out on my post Sunday night, when I, after my sit down with Adam Selipski was that, if I'm a software vendor, an ISV, an independent software vendor, or a software owner, I want my app to run faster, period, okay? I want my app to make money, which means valued by customers. I don't want my app to be slower and not be seen in front of my customers. So again, ISV is now an opportunity, Epic is a shining example of that, where now as an ISV, I can innovate and not have to do the heavy lifting. This is a huge point. Can you just share some color on this, because this is like, I think kind of the elephant in the room. The ISVs are going to go where the action is. >> That's right, and you know, the Epic ecosystem is such a force. Epic being a global healthcare leader, getting that performance level, all of those codes, they call them code travelers, that exist around Epic. All of those applications can now take advantage of that performance improvement, which for me is a game changer because all that data, I mean, I know that, you know, I was just in an emergency room with my daughter. She had a trouble, we thought she broke her elbow. And, you know, we were sitting there waiting as the person's entering and waiting and entering and waiting. So that performance really makes a difference, right? In your customer satisfaction, in your patient care, all the things that really matter, the business outcome areas, not just the technology side. It's a game changer for healthcare. >> It's the delivery of one, your health, your life. And two, hassle time, avoiding the steps, waiting in the wrong room, going here, waiting for this, getting a test you don't need. >> Sandy: That's right. >> It's a hassle for the customer, but also puts pressure on the supply chain, the operational bandwidth, and with telemedicine around the corner, you know, everything is happening with telemedicine. Why I might not need to go to the hospital if I don't have to, so again, another big wave coming is telemedicine. >> Yeah, that's right, and in fact, we launched that healthcare startup accelerator, where we invited healthcare companies from around the world to come in and get extra support as a brand new partner, as a next gen partner, and that was actually one of the top areas of focus. About 40% of the companies came in around telemedicine. And one of the really interesting partners that came in through that accelerator was a partner named Get lab. They do, you know, surgeon training, which is quite fascinating, and they were doing that and Time named them one of the top, most innovative companies of the year in 2021. And they accredited a lot of their success to the healthcare accelerator that we just launched as well. >> So much action going on. I got to get your thoughts on just in general healthcare, do you find the vibe to be more from the doctors and the service providers? Because they're the ones on the front lines. They're in the foxhole, so to speak. It always seems to me that they always wish things went faster, similar to government workers, right? It's like, I wish there wasn't red tape. I wish it was easier. Why aren't we doing this? That seems to have been like, the culture. And now it's shifting back to, all right, now we're having fun. We're delivering care. We're riding the right wave. >> I agree, you know, these business outcomes make a huge difference, I think. And I think that that transformation that you're talking about, is occurring much faster than anybody anticipated. I predict in 2022, you're going to see this increased focus, not just on telemedicine, patient care overall. Like how do you combine the two together? How are you able to move quicker to provide more diagnostics? So for example, one of our partners, GE Healthcare, was using AI and ML with one of our partner programs and was able to automate the radiology workflow. I mean, just think about radiology, reading X-rays, how fast that can be with AI and ML. It increased the diagnostic accuracy by 30%. I think you're going to see lots more use of technology to speed up diagnosis, to increase that customer, patient care. I think that's really going to be the trend in 2022. And it's great for all of us. >> And computer vision, by the way, with explainable AI, can come in, talk about analyzing x-rays and or film, more and more tech coming in and machine learning is driving a lot of it. >> I completely agree. Machine learning, I would say machine learning and analytics, you know? Now that we've got the data and you know, the data, IDC says that data coming in from IOT sensors increased by four x since COVID, so imagine, you know, there are now robots working in the hospital, gathering your readings of your, you know, how strong you breathe, your temperature, all your vital signs are now coming in from IOT sensors. So you're just seeing this explosion of data and healthcare, which only makes diagnosis and hopefully cures, new vaccines, more possible because now you've got more data to work with, right? That data accuracy is going up. Data sources are going up. It's just a really powerful combination. >> Yeah, healthcare is great. Sandy, it's been an amazing run on the healthcare side. It's continuing to change, in a good way, how care is managed and delivered and dispensed and cost savings. I do want to ask you if you could point out to the audience, just from within the partner base, what's the big trend there? Because obviously they're all engaged, seeing all kinds of new things. Where's the innovation vibe? What are some, what's the pattern in the partners, more software development, more cloud, more AI? What's the, what would you, how would you rank the activities of innovation? >> Yeah, I would say there are five prime drivers today on the technology side, you know. First and foremost right now is IOT, believe it or not. And IOT, because it's driving so much data and you have to have data for the second big trend, which is artificial intelligence and machine learning. So that data is essential for feeding all the modeling that's going on. We're also seeing the edge come to pass really fast, right? A lot of work on outpost. In fact, at the conference, we announced that we just opened an outpost innovation center with WWT and Intel MDC. We already have an innovation center for outpost in Seattle. So we opened one in DC for our partner community as well. So we're seeing a lot of focus on that edge. Containers, as we talked about earlier, 60% of customers want containers. So our partners to be, need to be all over it. And then another huge trend in public sector is blockchain. So if you think about, you know, Panama, El Salvador, Ukraine, they're all moving to Bitcoin. And I just went over to the Wynn hotel cause we're here in Vegas, did you see how many vendors are taking Bitcoin out? It's amazing! And so all of that is built on blockchain. So we also introduced a set of workshops and POCs with our partners around blockchain because we see it happening in states, in countries, and then the countries drive everything else to have to use or leverage that chain for Bitcoin. >> Great trends, the tailwind, the wave is here. It's a big wave, healthcare, public sector, a lot of change. Sandy Carter. Thank you for the great commentary. Great insight, great to see you. Thanks for coming back on theCUBE. >> Nice to see you too, yep. >> It's theCUBE coverage. I'm John Furrier, your host of theCUBE. We got two sets wall-to-wall coverage, here in person, live event, as well as hybrid, we have the software as well. You're watching theCUBE, the leader in global tech coverage. I'm John Furrier, thanks for watching. (calming electronic music)

(bright upbeat music) >> Hello, and welcome back to theCUBE's continuous coverage of AWS re:Invent 2021. I'm John Furrier your host of theCUBE wall-to-wall coverage, Sumit Dhawan president of VMware is joining me today. Sumit, welcome to theCUBE. >> Great to be here, John, good to see you. >> You know, I remember Raghu when we were talking to him when the original AWS deal, we covered it many, many years ago. It seems like yesterday, but since then, again, it was a lot of people who were kind of like looking at that deal, not understanding. We were very clear that we thought that that was going to create clarity. If you look at the success of VMware's cloud strategy, since that moment in time, it really has been an amazing run for VMware. And so congratulations and looking at that trajectory, we're going into what even a bigger wave now we're seeing, coming out of the pandemic with Edge, 5g, Cloud Native going mainstream. This is like another tipping point, another inflection. Well, how are we want to look at it? This is really big. Can you share your thoughts on how you see your customers and AWS customers coming together with the VMware. >> Yeah, we are excited about sort of this phase, era or whatever you want to call it, where customers are looking at just the power of cloud for all of their applications. And in fact, what we call multicloud, where they are looking at private cloud, public cloud, sometimes even multiple public clouds and Edge and how they are going to leverage all of this power of cloud across all their applications. And we're excited about the partnership, like you said, John, we did with AWS, customers have last two years, have had a hard time modernizing their infrastructure. And now they're looking at their tier one applications, which are oftentimes the lifeline of their businesses and they have not been, the infrastructure has not been modernized. And our partnership with AWS brings to the customers a fully modernized infrastructure as a service, which is optimized for their tier one application. So they can embrace the power of cloud, not just for new modern applications that they have built for running their new digital services, but also all of their tier one enterprise applications instantly modernize their infrastructure, secure it run their tier one applications through the power and the scale of public cloud. And then gradually start modernizing, like you mentioned, modernization of application is a key element and we have provided a rich stack for customers to be able to build their new SRE and DevOps practices and enable developers to have a fast journey to build these modern applications, leveraging the power of public cloud and in fact multiple public clouds seamlessly, and we're extending the same thing to the Edge. So it's actually exciting times in the industry. We call it the multicloud era and VMware is enabling our customers what we call smartest path to cloud. >> Well, congratulations, first of all, on the new independent company, VMware, that's great news. You guys now are on your own very valuable company in and of itself, under Dell Technologies now out on the open and we've been covering VMware, theCube's been to VMware every year. And looking at this year's VMware and looking at VMware for the old folks, the veterans VMware has been synonymous with operations, IT operations, running workloads in data centers to power business, enterprise classic innovation for business value. Now with the cloud, you see operations DevOps being discussed in security. You're talking about, and you mentioned SRE the workloads. The game is still the same, but it is shifting landscape wise. You got cloud scale, you mentioned on premises and multi-cloud. So with operations going to full scale, your customers are building and running their businesses on VMware and AWS and other clouds. This is the same game, but different world. Can you just share what's the current similarities and differences from where operations used to be from a workload standpoint. >> John, you're a hundred percent, right. The need for operational scale and discipline is always, there has always been there and now it's extended to potentially lot more complex world of what we call multicloud. In this new world, the whole aspect of operations is no longer the world of system admins, where you would have people pushing buttons to control the infrastructure and it's lot more where infrastructure is now designed to be managed as a code. There is a lot more of what is considered shift left, where more and more of power of orchestrating the infrastructure as given to the developers because they're oftentimes the sort of ones who understand the business logic and understand how the infrastructure is required to scale up and down the applications. And so along those two key trends, there is still a critical element of how a platform is needed for customers to operate that environment okay. You can't sort of have operational discipline be lost just because you have the paradigm changed and that's what VMware is enabling now with VMware stack, you can manage your entire infrastructure, not just public cloud, but even private cloud as a code, you can create a platform where developers get this freedom and a great experience to leverage any public cloud, to build their services and work closely with DevOps and SRE functions, to make sure that the orchestration of all of their cloud environment in a multicloud environment is available and enabled seamlessly through Kubernetes. This doesn't have to be done through virtual machines anymore it could be virtual machines or Kubernetes orchestrated containers across all clouds. And so bottom line operations has always been critical, but it has been done in a certain way in the world of multicloud it's changed to where it's more and more of infrastructure as a service shift left to developers and cybersecurity is extremely important where it needs to be built into the platform. And that's what VMware solutions are now enabling for our customers. >> Yeah, and for all the young guns coming into the business that have developers, the DevOps is still the same game. You've got developers and you've got operations now at large scale. And I think this whole multi-cloud is really kind of the multi-vendor equation so I think clear synergies and congratulations on the trajectory. I think it's really relevant. Can you take us through on how this means for the businesses, because at VMWorld this year, you guys talked about cross-cloud services. Can you talk about what that is and what does it mean for the customers, and what's the focus at reInvent this year? >> Yeah, so VMware this year at VMworld announced our sort of portfolio for enabling customers to embrace the power of multicloud easily. We call it cross-cloud services and they fit into five major categories. First is our cloud infrastructure that is available through partnership with all major cloud providers. We started with AWS and we expanded with all major cloud providers, including Azure, Google, Ali in China, Oracle, IBM. Secondly, our cloud native platform, Cloud native platform is where it doesn't have to be traditional VM based applications, applications built using modern cloud native technologies container-based, or that can be orchestrated using Kubernetes that are operationalized using our platform where customers can get any Kubernetes on any public cloud and operate them in a consistent and scalable fashion and enable a great developer experience at the same time. Third is networking and security services, which are underlay across both the cloud infrastructure, as well as cloud native services for this cloud management, how infrastructure as a code and shift-left developer function can be enabled through our management technologies designed for both private and public cloud, both VM based or VMware based infrastructure, as well as native public cloud infrastructure. And then lastly, at workspace and Edge services, enabling customers to build today's requirements of people working from anywhere and anywhere workspace experience for a hybrid workforce. So these are our five cloud services, John, that we call collectively as cross-cloud services, which enable customers to embrace the power of multicloud easily. These are modular, easy to acquire services designed to run across all clouds. And obviously for customers looking at leveraging the power of AWS, these services enable you to embrace it AWS at the fastest speed. >> Yeah and I think anything cross-cloud, multi-cloud, the ease of use and choice is key, you have to have choice that's cool. Open source is driving a lot of that, which I want to get to with the Tanzu, but you guys have had a great partnership with AWS, both on a development level, as well as a business partnership. Take us through the evolution of the partnership between VMware and AWS, because I know Raghu was really into this with Pat Gelsinger and then Andy Jassy, we covered that. But if you look at what Amazon web services is doing under Adam's leadership now they're going to set the table for the next 15 years. And you've got Outpost is going to be a big part of that. You've got all of the cloud native high level services inside the cloud, inside AWS as well. So take us through your view of the evolution of the VMware AWS partnership. >> Yeah I mean, AWS and VMware started a partnership for those of you who don't know, we started our partnership about five years ago, where we announced the availability of VMware cloud on AWS, which is all of our fully sort of modernized software defined data centers infrastructure available for running tear one enterprise applications on top of AWS all of their data centers globally. So our software with AWS hardware together as a managed service means customers could get fully modern infrastructure without refactoring any of their applications. They can run on AWS. And that relationship has grown significantly. We have continued to enable more and more of sort of different sized sort of platform infrastructure that we have continually made available. And the business has led to great success. We have at this point in time thousands of customers, joint customers running all of their tier one business applications, whether it's banking to healthcare, to insurance on top of our infrastructure, and it's been great. We then gradually expanded that partnership to other industries. Now we have customers in telcos running major telco cloud on top of our platform, we've expanded our partnership to other solutions. We brought our Tanzu, which is our cloud native platform for managing native cloud services on AWS, in an enterprise fashion, connected to all of their enterprise requirements as well in the marketplace we have brought other offerings, including security services on AWS marketplace for customers to get so over time. >> Hold on Sumit if you don't mind me asking, so you saying that Tanzu Carbon Black and VMware cloud are all in AWS marketplace. >> They're all available in AWS marketplace and they're all available to be transacted through even just the AWS's EDP. So the commercial relationship with AWS has strengthened significantly over time. >> EDP is their sales channel that's their direct. >> EDP is their enterprise agreement that's right. >> So you go to market together with AWS under the marketplace. >> Joint support integration so their customers can get joint support with us. So over time, the technology integration that started has led to strong commercial integrations, helping making sure customers can get one commercial agreement and one support agreement with VMware and AWS together. And that's been great for customers, customers have loved it and we are continuing to build upon it. Your second question was, well, what happens when AWS has new modern native services? And what we have done is for example, at Tanzu Solution, it is integrated with AWS's EKS. So their Kubernetes distribution can be fully operationalized as well as a great developer experience can be created for AWS native services using VMware Tanzu solution. So we are embracing the power of more and more of AWS services for our enterprise solutions. >> You know I love following VMware, especially and AWS. I spoke to companies, both very technical, pragmatic, very smart companies So congratulations on success. I got to ask you from a customer perspective, as you look at the landscape of the commercial side, what are the customers saying? What's the big summary of where they're at? What's the vibe, where's their head, what are they thinking? Take us through some anecdotal customer sentiment or data. >> Yeah, our customers tell us three things consistently. Number one, they say that they have, at this point of time, just decided that they're going to have some kind of a black solution, which will span multiple clouds, which could have public cloud, private cloud and Edge or multiple public clouds. In fact, we just did a recent survey, John and we found that 74% of our customers are already using multiple clouds. And 90 plus percent said that they want that freedom and choice to be able to use cloud of their choice and not be encumbered by any particular sort of just choice that they make. So that's the first trend we see, secondly, customers want to modernize their infrastructure and modernize their applications. They haven't been able to do so over the course of last two years, and modernization is a key requirement and VMware and AWS gives them that ability to do so now at this point in time, very, very quickly. And then third thing we hear is that customers are looking for some solution where cybersecurity is built in it's something where they are standardizing their enterprise requirements via a platform, which has a great experience for the developers, great operational scale and cybersecurity. And these are the three trends John, that VMware is solely focused on as part of our services and solutions and our partnership with AWS. >> Sumit, always great to talk to you. One final point. I want to get your reaction to a VMware has made a couple of big bets in the past decade. One, the deal with Amazon, which opened the door for multicloud, that path is clear. Cloud-scale check the box well done. And the other one was cloud native technologies and Kubernetes specifically, two big bets that don't, that kind of no one kind of saw coming, turns out they turned out pretty well. What's your reaction to that? Would you agree? And how would you talk about those two events? >> Yeah, we at VMware always considered sort of how we are going to keep innovating and the way we see the world is follow where the applications are going. It's pretty simple. Okay we saw that a few years ago where cloud and container technologies are where the applications are going. And we innovated through both our organic investments, as well as inorganic investments to bring our VMware cloud Solutions and Tanzu Solutions. And similarly, John, we're looking at now the next generation of applications where we fast forward three years down the road, we envision a great degree of innovation is going to happen in the Edge. And that's the third sort of area of innovation for us. So that public cloud or multi-cloud cloud native applications, as well as Edge applications can all be orchestrated using VMware's cross-cloud services. >> Sumit Dhawan, president of VMware thanks for coming on theCUBE we appreciate it. Enjoy the rest of the event. I'm John Furrier host of theCUBE. Thanks for watching. (bright upbeat music)

(bright upbeat music) >> Hello, and welcome back to theCUBE's continuous coverage of AWS re:Invent 2021. I'm John Furrier your host of theCUBE wall-to-wall coverage, Sumit Dhawan president of VMware is joining me today. Sumit, welcome to theCUBE. >> Great to be here, John, good to see you. >> You know, I remember Raghu when we were talking to him when the original AWS deal, we covered it many, many years ago. It seems like yesterday, but since then, again, it was a lot of people who were kind of like looking at that deal, not understanding. We were very clear that we thought that that was going to create clarity. If you look at the success of VMware's cloud strategy, since that moment in time, it really has been an amazing run for VMware. And so congratulations and looking at that trajectory, we're going into what even a bigger wave now we're seeing, coming out of the pandemic with Edge, 5g, Cloud Native going mainstream. This is like another tipping point, another inflection. Well, how are we want to look at it? This is really big. Can you share your thoughts on how you see your customers and AWS customers coming together with the VMware. >> Yeah, we are excited about sort of this phase, era or whatever you want to call it, where customers are looking at just the power of cloud for all of their applications. And in fact, what we call multicloud, where they are looking at private cloud, public cloud, sometimes even multiple public clouds and Edge and how they are going to leverage all of this power of cloud across all their applications. And we're excited about the partnership, like you said, John, we did with AWS, customers have last two years, have had a hard time modernizing their infrastructure. And now they're looking at their tier one applications, which are oftentimes the lifeline of their businesses and they have not been, the infrastructure has not been modernized. And our partnership with AWS brings to the customers a fully modernized infrastructure as a service, which is optimized for their tier one application. So they can embrace the power of cloud, not just for new modern applications that they have built for running their new digital services, but also all of their tier one enterprise applications instantly modernize their infrastructure, secure it run their tier one applications through the power and the scale of public cloud. And then gradually start modernizing, like you mentioned, modernization of application is a key element and we have provided a rich stack for customers to be able to build their new SRE and DevOps practices and enable developers to have a fast journey to build these modern applications, leveraging the power of public cloud and in fact multiple public clouds seamlessly, and we're extending the same thing to the Edge. So it's actually exciting times in the industry. We call it the multicloud era and VMware is enabling our customers what we call smartest path to cloud. >> Well, congratulations, first of all, on the new independent company, VMware, that's great news. You guys now are on your own very valuable company in and of itself, under Dell Technologies now out on the open and we've been covering VMware, theCube's been to VMware every year. And looking at this year's VMware and looking at VMware for the old folks, the veterans VMware has been synonymous with operations, IT operations, running workloads in data centers to power business, enterprise classic innovation for business value. Now with the cloud, you see operations DevOps being discussed in security. You're talking about, and you mentioned SRE the workloads. The game is still the same, but it is shifting landscape wise. You got cloud scale, you mentioned on premises and multi-cloud. So with operations going to full scale, your customers are building and running their businesses on VMware and AWS and other clouds. This is the same game, but different world. Can you just share what's the current similarities and differences from where operations used to be from a workload standpoint. >> John, you're a hundred percent, right. The need for operational scale and discipline is always, there has always been there and now it's extended to potentially lot more complex world of what we call multicloud. In this new world, the whole aspect of operations is no longer the world of system admins, where you would have people pushing buttons to control the infrastructure and it's lot more where infrastructure is now designed to be managed as a code. There is a lot more of what is considered shift left, where more and more of power of orchestrating the infrastructure as given to the developers because they're oftentimes the sort of ones who understand the business logic and understand how the infrastructure is required to scale up and down the applications. And so along those two key trends, there is still a critical element of how a platform is needed for customers to operate that in Miami okay. You can sort of have operational discipline be lost just because you have the paradigm changed and that's what VMware is enabling now with VMware stack, you can manage your entire infrastructure, not just public cloud, but even private cloud as a code, you can create a platform where developers get this freedom and a great experience to leverage any public cloud, to build their services and work closely with DevOps and SRE functions, to make sure that the orchestration of all of their cloud environment in a multicloud environment is available and enabled seamlessly through Kubernetes. This doesn't have to be done through virtual machines anymore it could be virtual machines or Kubernetes orchestrated containers across all clouds. And so bottom line operations has always been critical, but it has been done in a certain way in the world of multicloud it's changed to where it's more and more of infrastructure as a service shift left to developers and cybersecurity is extremely important where it needs to be built into the platform. And that's what VMware solutions are now enabling for our customers. >> Yeah, and for all the young guns coming into the business that have developers, the DevOps is still the same game. You've got developers and you've got operations now at large scale. And I think this whole multi-cloud is really kind of the multi-vendor equation so I think clear synergies and congratulations on the trajectory. I think it's really relevant. Can you take us through on how this means for the businesses, because at VMWorld this year, you guys talked about cross-cloud services. Can you talk about what that is and what does it mean for the customers, and what's the focus at reInvent this year? >> Yeah, so VMware this year at VMworld announced our sort of portfolio for enabling customers to embrace the power of multicloud easily. We call it cross-cloud services and they fit into five major categories. First is our cloud infrastructure that is available through partnership with all major cloud providers. We started with AWS and we expanded with all major cloud providers, including Azure, Google, Ali in China, Oracle, IBM. Secondly, our cloud native platform, Cloud native platform is where it doesn't have to be traditional VM based applications, applications built using modern cloud native technologies container-based, or that can be orchestrated using Kubernetes that are operationalized using our platform where customers can get any Kubernetes on any public cloud and operate them in a consistent and scalable fashion and enable a great developer experience at the same time. Third is networking and security services, which are underlay across both the cloud infrastructure, as well as cloud native services for this cloud management, how infrastructure as a code and shift-left developer function can be enabled through our management technologies designed for both private and public cloud, both VM based or VMware based infrastructure, as well as native public cloud infrastructure. And then lastly, at workspace and Edge services, enabling customers to build today's requirements of people working from anywhere and anywhere workspace experience for a hybrid workforce. So these are our five cloud services, John, that we call collectively as cross-cloud services, which enable customers to embrace the power of multicloud easily. These are modular, easy to acquire services designed to run across all clouds. And obviously for customers looking at leveraging the power of AWS, these services enable you to embrace it AWS at the fastest speed. >> Yeah and I think anything cross-cloud, multi-cloud, the ease of use and choice is key, you have to have choice that's cool. Open source is driving a lot of that, which I want to get to with the Tanzu, but you guys have had a great partnership with AWS, both on a development level, as well as a business partnership. Take us through the evolution of the partnership between VMware and AWS, because I know Raghu was really into this with Pat Gelsinger and then Andy Jassy, we covered that. But if you look at what Amazon web services is doing under Adam's leadership now they're going to set the table for the next 15 years. And you've got Outpost is going to be a big part of that. You've got all of the cloud native high level services inside the cloud, inside AWS as well. So take us through your view of the evolution of the VMware AWS partnership. >> Yeah I mean, AWS and VMware started a partnership for those of you who don't know, we started our partnership about five years ago, where we announced the availability of VMware cloud on AWS, which is all of our fully sort of modernized software defined data centers infrastructure available for running tear one enterprise applications on top of AWS all of their data centers globally. So our software with AWS hardware together as a managed service means customers could get fully modern infrastructure without refactoring any of their applications. They can run on AWS. And that relationship has grown significantly. We have continued to enable more and more of sort of different sized sort of platform infrastructure that we have continually made available. And the business has led to great success. We have at this point in time thousands of customers, joint customers running all of their tier one business applications, whether it's banking to healthcare, to insurance on top of our infrastructure, and it's been great. We then gradually expanded that partnership to other industries. Now we have customers in telcos running major telco cloud on top of our platform, we've expanded our partnership to other solutions. We brought our Tanzu, which is our cloud native platform for managing native cloud services on AWS, in an enterprise fashion, connected to all of their enterprise requirements as well in the marketplace we have brought other offerings, including security services on AWS marketplace for customers to get so over time. >> Hold on Sumit if you don't mind me asking, so you saying that Tanzu Carbon Black and VMware cloud are all in AWS marketplace. >> They're all available in AWS marketplace and they're all available to be transacted through even just the AWS's EDP. So the commercial relationship with AWS has strengthened significantly over time. >> EDP is their sales channel that's their direct. >> EDP is their enterprise agreement that's right. >> So you go to market together with AWS under the marketplace. >> Joint support integration so their customers can get joint support with us. So over time, the technology integration that started has led to strong commercial integrations, helping making sure customers can get one commercial agreement and one support agreement with VMware and AWS together. And that's been great for customers, customers have loved it and we are continuing to build upon it. Your second question was, well, what happens when AWS has new modern native services? And what we have done is for example, at Tanzu Solution, it is integrated with AWS's EKS. So their Kubernetes distribution can be fully operationalized as well as a great developer experience can be created for AWS native services using VMware Tanzu solution. So we are embracing the power of more and more of AWS services for our enterprise solutions. >> You know I love following VMware, especially and AWS. I spoke to companies, both very technical, pragmatic, very smart companies So congratulations on success. I got to ask you from a customer perspective, as you look at the landscape of the commercial side, what are the customers saying? What's the big summary of where they're at? What's the vibe, where's their head, what are they thinking? Take us through some anecdotal customer sentiment or data. >> Yeah, our customers tell us three things consistently. Number one, they say that they have, at this point of time, just decided that they're going to have some kind of a black solution, which will span multiple clouds, which could have public cloud, private cloud and Edge or multiple public clouds. In fact, we just did a recent survey, John and we found that 74% of our customers are already using multiple clouds. And 90 plus percent said that they want that freedom and choice to be able to use cloud of their choice and not be encumbered by any particular sort of just choice that they make. So that's the first trend we see, secondly, customers want to modernize their infrastructure and modernize their applications. They haven't been able to do so over the course of last two years, and modernization is a key requirement and VMware and AWS gives them that ability to do so now at this point in time, very, very quickly. And then third thing we hear is that customers are looking for some solution where cybersecurity is built in it's something where they are standardizing their enterprise requirements via a platform, which has a great experience for the developers, great operational scale and cybersecurity. And these are the three trends John, that VMware is solely focused on as part of our services and solutions and our partnership with AWS. >> Sumit, always great to talk to you. One final point. I want to get your reaction to a VMware has made a couple of big bets in the past decade. One, the deal with Amazon, which opened the door for multicloud, that path is clear. Cloud-scale check the box well done. And the other one was cloud native technologies and Kubernetes specifically, two big bets that don't, that kind of no one kind of saw coming, turns out they turned out pretty well. What's your reaction to that? Would you agree? And how would you talk about those two events? >> Yeah, we at VMware always considered sort of how we are going to keep innovating and the way we see the world is follow where the applications are going. It's pretty simple. Okay we saw that a few years ago where cloud and container technologies are where the applications are going. And we innovated through both our organic investments, as well as inorganic investments to bring our VMware cloud Solutions and Tanzu Solutions. And similarly, John, we're looking at now the next generation of applications where we fast forward three years down the road, we envision a great degree of innovation is going to happen in the Edge. And that's the third sort of area of innovation for us. So that public cloud or multi-cloud cloud native applications, as well as Edge applications can all be orchestrated using VMware's cross-cloud services. >> Sumit Dhawan, president of VMware thanks for coming on theCUBE we appreciate it. Enjoy the rest of the event. I'm John Furrier host of theCUBE. Thanks for watching. (bright upbeat music)

>> Welcome back to The Cube's coverage of HPE's GreenLake announcements. My name is Dave Vellante and you're watching the Cube. I'm here with Holger Mueller, who is an analyst at Constellation Research. And Matt Maccaux is the global field CTO of Ezmeral software at HPE. We're going to talk data. Gents, great to see you. >> Holger: Great to be here. >> So, Holger, what do you see happening in the data market? Obviously data's hot, you know, digital, I call it the force marks to digital. Everybody realizes wow, digital business, that's a data business. We've got to get our data act together. What do you see in the market is the big trends, the big waves? >> We are all young enough or old enough to remember when people were saying data is the new oil, right? Nothing has changed, right? Data is the key ingredient, which matters to enterprise, which they have to store, which they have to enrich, which they have to use for their decision-making. It's the foundation of everything. If you want to go into machine learning or (indistinct) It's growing very fast, right? We have the capability now to look at all the data in enterprise, which weren't able 10 years ago to do that. So data is main center to everything. >> Yeah, it's even more valuable than oil, I think, right? 'Cause with oil, you can only use once. Data, you can, it's kind of polyglot. I can go in different directions and it's amazing, right? >> It's the beauty of digital products, right? They don't get consumed, right? They don't get fired up, right? And no carbon footprint, right? "Oh wait, wait, we have to think about carbon footprint." Different story, right? So to get to the data, you have to spend some energy. >> So it's that simple, right? I mean, it really is. Data is fundamental. It's got to be at the core. And so Matt, what are you guys announcing today, and how does that play into what Holger just said? >> What we're announcing today is that organizations no longer need to make a difficult choice. Prior to today, organizations were thinking if I'm going to do advanced machine learning and really exploit my data, I have to go to the cloud. But all my data's still on premises because of privacy rules, industry rules. And so what we're announcing today, through GreenLake Services, is a cloud services way to deliver that same cloud-based analytical capability. Machine learning, data engineering, through hybrid analytics. It's a unified platform to tie together everything from data engineering to advance data science. And we're also announcing the world's first Kubernetes native object store, that is hybrid cloud enabled. Which means you can keep your data connected across clouds in a data fabric, or Dave, as you say, mesh. >> Okay, can we dig into that a little bit? So, you're essentially saying that, so you're going to have data in both places, right? Public cloud, edge, on-prem, and you're saying, HPE is announcing a capability to connect them, I think you used the term fabric. I'm cool, by the way, with the term fabric, we can, we'll parse that out another time. >> I love for you to discuss textiles. Fabrics vs. mesh. For me, every fabric breaks down to mesh if you put it on a microscope. It's the same thing. >> Oh wow, now that's really, that's too detailed for my brain, right this moment. But, you're saying you can connect all those different estates because data by its very nature is everywhere. You're going to unify that, and what, that can manage that through sort of a single view? >> That's right. So, the management is centralized. We need to be able to know where our data is being provisioned. But again, we don't want organizations to feel like they have to make the trade off. If they want to use cloud surface A in Azure, and cloud surface B in GCP, why not connect them together? Why not allow the data to remain in sync or not, through a distributed fabric? Because we use that term fabric over and over again. But the idea is let the data be where it most naturally makes sense, and exploit it. Monetization is an old tool, but exploit it in a way that works best for your users and applications. >> In sync or not, that's interesting. So it's my choice? >> That's right. Because the back of an automobile could be a teeny tiny, small edge location. It's not always going to be in sync until it connects back up with a training facility. But we still need to be able to manage that. And maybe that data gets persisted to a core data center. Maybe it gets pushed to the cloud, but we still need to know where that data is, where it came from, its lineage, what quality it has, what security we're going to wrap around that, that all should be part of this fabric. >> Okay. So, you've got essentially a governance model, at least maybe you're working toward that, and maybe it's not all baked today, but that's the north star. Is this fabric connect, single management view, governed in a federated fashion? >> Right. And it's available through the most common API's that these applications are already written in. So, everybody today's talking S3. I've got to get all of my data, I need to put it into an object store, it needs to be S3 compatible. So, we are extending this capability to be S3 native. But it's optimized for performance. Today, when you put data in an object store, it's kind of one size fits all. Well, we know for those streaming analytical capabilities, those high performance workloads, it needs to be tuned for that. So, how about I give you a very small object on the very fastest disk in your data center and maybe that cheaper location somewhere else. And so we're giving you that balance as part of the overall management estate. >> Holger, what's your take on this? I mean, Frank Slootman says we'll never, we're not going halfway house. We're never going to do on-prem, we're only in the cloud. So that basically says, okay, he's ignoring a pretty large market by choice. You're not, Matt, you must love those words. But what do you see as the public cloud players, kind of the moves on-prem, particularly in this realm? >> Well, we've seen lots of cloud players who were only cloud coming back towards on-premise, right? We call it the next generation compute platform where I can move data and workloads between on-premise and ideally, multiple clouds, right? Because I don't want to be logged into public cloud vendors. And we see two trends, right? One trend is the traditional hardware supplier of on-premise has not scaled to cloud technology in terms of big data analytics. They just missed the boat for that in the past, this is changing. You guys are a traditional player and changing this, so congratulations. The other thing, is there's been no innovation for the on-premise tech stack, right? The only technology stack to run modern application has been invested for a long time in the cloud. So what we see since two, three years, right? With the first one being Google with Kubernetes, that are good at GKE on-premise, then onto us, right? Bringing their tech stack with compromises to on-premises, right? Acknowledging exactly what we're talking about, the data is everywhere, data is important. Data gravity is there, right? It's just the network's fault, where the networks are too slow, right? If you could just move everything anywhere we want like juggling two balls, then we'd be in different place. But that's the not enough investment for the traditional IT players for that stack, and the modern stack being there. And now every public cloud player has an on-premise offering with different flavors, different capabilities. >> I want to give you guys Dave's story of kind of history and you can kind of course correct, and tell me how this, Matt, maybe fits into what's happened with customers. So, you know, before Hadoop, obviously you had to buy a big Oracle database and you know, you running Unix, and you buy some big storage subsystem if you had any money left over, you know, you maybe, you know, do some actual analytics. But then Hadoop comes in, lowers the cost, and then S3 kneecaps the entire Hadoop market, right? >> I wouldn't say that, I wouldn't agree. Sorry to jump on your history. Because the fascinating thing, what Hadoop brought to the enterprise for the first time, you're absolutely right, affordable, right, to do that. But it's not only about affordability because S3 as the affordability. The big thing is you can store information without knowing how to analyze it, right? So, you mentioned Snowflake, right? Before, it was like an Oracle database. It was Starschema for data warehouse, and so on. You had to make decisions how to store that data because compute capabilities, storage capabilities, were too limited, right? That's what Hadoop blew away. >> I agree, no schema on, right. But then that created data lakes, which create a data swamps, and that whole mess, and then Spark comes in and help clean it out, okay, fine. So, we're cool with that. But the early days of Hadoop, you had, companies would have a Hadoop monolith, they probably had their data catalog in Excel or Google sheets, right? And so now, my question to you, Matt, is there's a lot of customers that are still in that world. What do they do? They got an option to go to the cloud. I'm hearing that you're giving them another option? >> That's right. So we know that data is going to move to the cloud, as I mentioned. So let's keep that data in sync, and governed, and secured, like you expect. But for the data that can't move, let's bring those cloud native services to your data center. And so that's a big part of this announcement is this unified analytics. So that you can continue to run the tools that you want to today while bringing those next generation tools based on Apache Spark, using libraries like Delta Lake so you can go anything from Tableaux through Presto sequel, to advance machine learning in your Jupiter notebooks on-premises where you know your data is secured. And if it happens to sit in existing Hadoop data lake, that's fine too. We don't want our customers to have to make that trade off as they go from one to the other. Let's give you the best of both worlds, or as they say, you can eat your cake and have it too. >> Okay, so. Now let's talk about sort of developers on-prem, right? They've been kind of... If they really wanted to go cloud native, they had to go to the cloud. Do you feel like this changes the game? Do on-prem developers, do they want that capability? Will they lean into that capability? Or will they say no, no, the cloud is cool. What's your take? >> I love developers, right? But it's about who makes the decision, who pays the developers, right? So the CXOs in the enterprises, they need exactly, this is why we call the next-gen computing platform, that you can move your code assets. It's very hard to build software, so it's very valuable to an enterprise. I don't want to have limited to one single location or certain computing infrastructure, right? Luckily, we have Kubernetes to be able to move that, but I want to be able to deploy it on-premise if I have to. I want to deploy it, would be able to deploy in the multiple clouds which are available. And that's the key part. And that makes developers happy too, because the code you write has got to run multiple places. So you can build more code, better code, instead of building the same thing multiple places, because a little compiler change here, a little compiler change there. Nobody wants to do portability testing and rewriting, recertified for certain platforms. >> The head of application development or application architecture and the business are ultimately going to dictate that, number one. Number two, you're saying that developers shouldn't care because it can write once, run anywhere. >> That is the promise, and that's the interesting thing which is available now, 'cause people know, thanks to Kubernetes as a container platform and the abstraction which containers provide, and that makes everybody's life easier. But it goes much more higher than the Head of Apps, right? This is the digital transformation strategy, the next generation application the company has to build as a response to a pandemic, as a pivot, as digital transformation, as digital disruption capability. >> I mean, I see a lot of organizations basically modernizing by building some kind of abstraction to their backend systems, modernizing it through cloud native, and then saying, hey, as you were saying Holger, run it anywhere you want, or connect to those cloud apps, or connect across clouds, connect to other on-prem apps, and eventually out to the edge. Is that what you see? >> It's so much easier said than done though. Organizations have struggled so much with this, especially as we start talking about those data intensive app and workloads. Kubernetes and Hadoop? Up until now, organizations haven't been able to deploy those services. So, what we're offering as part of these GreenLake unified analytics services, a Kubernetes runtime. It's not ours. It's top of branch open source. And open source operators like Apache Spark, bringing in Delta Lake libraries, so that if your developer does want to use cloud native tools to build those next generation advanced analytics applications, but prod is still on-premises, they should just be able to pick that code up, and because we are deploying 100% open-source frameworks, the code should run as is. >> So, it seems like the strategy is to basically build, now that's what GreenLake is, right? It's a cloud. It's like, hey, here's your options, use whatever you want. >> Well, and it's your cloud. That's, what's so important about GreenLake, is it's your cloud, in your data center or co-lo, with your data, your tools, and your code. And again, we know that organizations are going to go to a multi or hybrid cloud location and through our management capabilities, we can reach out if you don't want us to control those, not necessarily, that's okay, but we should at least be able to monitor and audit the data that sits in those other locations, the applications that are running, maybe I register your GKE cluster. I don't manage it, but at least through a central pane of glass, I can tell the Head of Applications, what that person's utilization is across these environments. >> You know, and you said something, Matt, that struck, resonated with me, which is this is not trivial. I mean, not as simple to do. I mean what you see, you see a lot of customers or companies, what they're doing, vendors, they'll wrap their stack in Kubernetes, shove it in the cloud, it's essentially hosted stack, right? And, you're kind of taking a different approach. You're saying, hey, we're essentially building a cloud that's going to connect all these estates. And the key is you're going to have to keep, and you are, I think that's probably part of the reason why we're here, announcing stuff very quickly. A lot of innovation has to come out to satisfy that demand that you're essentially talking about. >> Because we've oversimplified things with containers, right? Because containers don't have what matters for data, and what matters for enterprise, which is persistence, right? I have to be able to turn my systems down, or I don't know when I'm going to use that data, but it has to stay there. And that's not solved in the container world by itself. And that's what's coming now, the heavy lifting is done by people like HPE, to provide that persistence of the data across the different deployment platforms. And then, there's just a need to modernize my on-premise platforms. Right? I can't run on a server which is two, three years old, right? It's no longer safe, it doesn't have trusted identity, all the good stuff that you need these days, right? It cannot be operated remotely, or whatever happens there, where there's two, three years, is long enough for a server to have run their course, right? >> Well you're a software guy, you hate hardware anyway, so just abstract that hardware complexity away from you. >> Hardware is the necessary evil, right? It's like TSA. I want to go somewhere, but I have to go through TSA. >> But that's a key point, let me buy a service, if I need compute, give it to me. And if I don't, I don't want to hear about it, right? And that's kind of the direction that you're headed. >> That's right. >> Holger: That's what you're offering. >> That's right, and specifically the services. So GreenLake's been offering infrastructure, virtual machines, IaaS, as a service. And we want to stop talking about that underlying capability because it's a dial tone now. What organizations and these developers want is the service. Give me a service or a function, like I get in the cloud, but I need to get going today. I need it within my security parameters, access to my data, my tools, so I can get going as quickly as possible. And then beyond that, we're going to give you that cloud billing practices. Because, just because you're deploying a cloud native service, if you're still still being deployed via CapEx, you're not solving a lot of problems. So we also need to have that cloud billing model. >> Great. Well Holger, we'll give you the last word, bring us home. >> It's very interesting to have the cloud qualities of subscription-based pricing maintained by HPE as the cloud vendor from somewhere else. And that gives you that flexibility. And that's very important because data is essential to enterprise processes. And there's three reasons why data doesn't go to the cloud, right? We know that. It's privacy residency requirement, there is no cloud infrastructure in the country. It's performance, because network latency plays a role, right? Especially for critical appraisal. And then there's not invented here, right? Remember Charles Phillips saying how old the CIO is? I know if they're going to go to the cloud or not, right? So, it was not invented here. These are the things which keep data on-premise. You know that load, and HP is coming on with a very interesting offering. >> It's physics, it's laws, it's politics, and sometimes it's cost, right? Sometimes it's too expensive to move and migrate. Guys, thanks so much. Great to see you both. >> Matt: Dave, it's always a pleasure. All right, and thank you for watching the Cubes continuous coverage of HPE's big GreenLake announcements. Keep it right there for more great content. (calm music begins)

>> Voice Over: Data is at the heart of transformation, and the change every company needs to succeed. But it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you, it's time to lead the way, it's time for thought leaders. (soft upbeat music) >> Welcome to Thought.Leaders a digital event brought to you by ThoughtSpot, my name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers, and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not, ThoughtSpot is disrupting analytics, by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology but leadership, a mindset and a culture, that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action? And today we're going to hear from experienced leaders who are transforming their organizations with data, insights, and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, chief data strategy officer of the ThoughtSpot is Cindi Howson, Cindi is an analytics and BI expert with 20 plus years experience, and the author of Successful Business Intelligence: Unlock the Value of BI & Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics Magic Quadrant. In early last year, she joined ThoughtSpot to help CEOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi great to see you, welcome to the show. >> Thank you Dave, nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair Hello Sudheesh, how are you doing today? >> I'm well, good to talk to you again. >> That's great to see you, thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course to our audience, and what they're going to learn today. (upbeat music) >> Thanks Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been you know, cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with, invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one, that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time, we want to make sure that we value your time, then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people, that you want to hang around with long after this event is over. And number three, as we plan through this, you know we are living through these difficult times we want this event to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents, because teens and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, changes sort of like, if you've ever done bungee jumping, and it's like standing on the edges, waiting to make that one more step you know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step today. Change requires a lot of courage, and when we are talking about data and analytics, which is already like such a hard topic not necessarily an uplifting and positive conversation most businesses, it is somewhat scary, change becomes all the more difficult. Ultimately change requires courage, courage to first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that you know, maybe I don't have the power to make the change that the company needs, sometimes they feel like I don't have the skills, sometimes they may feel that I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations when it comes to data and insights that you talked about. You know, that are people in the company who are going to have the data because they know how to manage the data, how to inquire and extract, they know how to speak data, they have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions, and there is gap, this sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process but sometimes no matter how big the company is or how small the company is you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun, you will have that exhilarating feeling of jumping for a bungee jump, all four of them are exceptional, but my owner is to introduce Michelle. And she's our first speaker, Michelle I am very happy after watching our presentation and reading your bio that there are no country vital worldwide competition for cool parents, because she will beat all of us. Because when her children were small, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL, what a cool mom. I am extremely excited to see what she's going to talk about. I've seen this slides, a bunch of amazing pictures, I'm looking to see the context behind it, I'm very thrilled to make that client so far, Michelle, I'm looking forward to her talk next. Welcome Michelle, it's over to you. (soft upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one, and I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking our digital revolution using insights data, and of course as you said, leadership. First a little bit about myself, a little background as I said, I always wanted to play football, and this is something that I wanted to do since I was a child, but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines, and a female official on the field. I'm a lifelong fan and student of the game of football, I grew up in the South, you can tell from the accent and in the South is like a religion and you pick sides. I chose Auburn University working in the Athletic Department, so I'm testament to you can start the journey can be long it took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football you know, this is a really big rivalry. And when you choose sides, your family is divided, so it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands. Delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team, that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event every game, every awesome moment is execution, precise repeatable execution. And most of my career has been behind the scenes, doing just that, assembling teams to execute these plans, and the key way that companies operate at these exceptional levels, is making good decisions, the right decisions at the right time and based upon data, so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world-class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney, in the 90s I was at Disney, leading a project called destination Disney, which it's a data project, it was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, just these magical express. My career at Disney began in finance, but Disney was very good about rotating you around, and it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team, asking for data more and more data. And I learned that all of that valuable data was locked up in our systems, all of our point of sales systems, our reservation systems, our operation systems, and so I became a shadow IT person in marketing, ultimately leading to moving into IT, and I haven't looked back since. In the early 2000s I was at Universal Studios Theme Park as their CIO, preparing for and launching the wizarding world of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wine shop. As today at the NFL, I am constantly challenged to do leading edge technologies using things like sensors, AI, machine learning, and all new communication strategies, and using data to drive everything from player performance, contracts to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data. Talk about data, actually enabling your business without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform, and collaboration with video message and phone, all in one solution in the cloud. And Quotient Technologies, whose product is actually data. The tagline at quotient is the result in knowing. I think that's really important, because not all of us are data companies, where your product is actually data. But we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about, as thought leaders in your companies. First just hit on it is change, how to be a champion and a driver of change. Second, how to use data to drive performance for your company, and measure performance of your company. Third, how companies now require intense collaboration to operate, and finally, how much of this is accomplished through solid data-driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it, and thankfully for the most part knock on wood we were prepared for it. But this year everyone's cheese was moved, all the people in the back rooms, IT, data architects and others, were suddenly called to the forefront. Because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 Draft. We went from planning, a large event in Las Vegas under the bright lights red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee dress jumping, this is really what it felt like. It was one in which no one felt comfortable, because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky but it ended up being Oh, so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at this level, highest level. As an example, the NFL has always measured performance obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact, those with the best stats, usually win the games. The NFL has always recorded stats, since the beginning of time, here at the NFL a little this year as our 100 and first year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us, is both how much more we can measure, and the immediacy with which it can be measured. And I'm sure in your business, it's the same, the amount of data you must have has got to have quadrupled recently and how fast you need it and how quickly you need to analyze it, is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to a next level, it's powered by Amazon Web Services, and we gathered this data real time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast, and of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns speed, matchups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that we'll gather more and more information about player's performance as it relates to their health and safety. The third trend is really I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes it's important to think about for those of you that are IT professionals and developers, you know more than 10 years ago, agile practices began sweeping companies or small teams would work together rapidly in a very flexible, adaptive and innovative way, and it proved to be transformational. However today, of course, that is no longer just small teams the next big wave of change, and we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career when I was at Disney, we owned everything 100%, we made a decision, we implemented it, we were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy in from the top down, you got the people from the bottom up to do it, and you executed. At Universal, we were a joint venture, our attractions and entertainment was licensed, our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem. We have 32 clubs that are all separate businesses 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved centralized control has gotten less and less and has been replaced by intense collaboration not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top down decision making is going by the wayside in favor of ecosystems that require cooperation, yet competition to coexist. I mean the NFL is a great example of what we call coopertition, which is cooperation and competition. When in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough, you must be able to turn it to insights, partnerships between technology teams who usually hold the keys to the raw data, and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave, and drive, don't do the ride along program, it's very important to drive, driving can be high risk but it's also high reward. Embracing the uncertainty of what will happen, is how you become brave, get more and more comfortable with uncertainty be calm and let data be your map on your journey, thanks. >> Michelle, thank you so much. So you and I share a love of data, and a love of football. You said you want to be the quarterback, I'm more an old wine person. (Michelle laughing) >> Well, then I can do my job without you. >> Great, and I'm getting the feeling now you know, Sudheesh is talking about bungee jumping. My boat is when we're past this pandemic, we both take them to the Delaware Water Gap and we do the cliff jumping. >> That sounds good, I'll watch. >> You'll watch, okay, so Michelle, you have so many stakeholders when you're trying to prioritize the different voices, you have the players, you have the owners you have the league, as you mentioned to the broadcasters your, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? I think balancing across stakeholders starts with aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread ties them all together you sort of do get them to naturally prioritize their work, and I think that's very important. So for us at the NFL, and even at Disney, it was our core values and our core purpose is so well known, and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it, is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So I thank you for your metership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (soft upbeat music) >> So we're going to take a hard pivot now and go from football to Chernobyl, Chernobyl, what went wrong? 1986, as the reactors were melting down they had the data to say, this is going to be catastrophic and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone," which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure the additional thousands getting cancer, and 20,000 years before the ground around there and even be inhabited again, This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with, and this is why I want you to focus on having fostering a data-driven culture. I don't want you to be a laggard, I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, isn't really two sides of the same coin, real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology, and recently a CDO said to me, "You know Cindi, I actually think this is two sides of the same coin. One reflects the other, what do you think?" Let me walk you through this, so let's take a laggard. What is the technology look like? Is it based on 1990s BI and reporting largely parameterized reports on-premises data warehouses, or not even that operational reports, at best one enterprise data warehouse very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to. Or is there also a culture of fear, afraid of failure, resistance to change complacency and sometimes that complacency it's not because people are lazy, it's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded, let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics, search and AI-driven insights not on-premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data lake, and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust, there is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this, oh, well, I didn't invent that, I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized, knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision makers. Or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? They've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager a warehouse manager, a financial services advisor. 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools, the sad reality only 20% of organizations are actually doing this, these are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state of the art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets really just taking data out of ERP systems that were also on-premises, and state of the art was maybe getting a management report, an operational report. Over time visual based data discovery vendors, disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data sometimes coming from a data warehouse, the current state of the art though, Gartner calls it augmented analytics, at ThoughtSpot, we call it search and AI-driven analytics. And this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses, and I think this is an important point. Oftentimes you, the data and analytics leaders, will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights, and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot I'll just show you what this looks like, instead of somebody's hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom getting to a visualization that then can be pinned to an existing Pinboard that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard, because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years, now it's maybe three years, and the time to maturity has also accelerated. So you have these different components the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI-driven insights. Competitors have followed suit, but be careful if you look at products like Power BI or SAP Analytics Cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift or Azure Synapse or Google BigQuery, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. The pace of change, it's acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI, and that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you've read any of my books or used any of the maturity models out there whether the Gartner IT score that I worked on, or the data warehousing institute also has a maturity model. We talk about these five pillars to really become data-driven, as Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources. It's the talent, the people, the technology, and also the processes, and often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar, and in fact, in polls that we've done in these events, look at how much more important culture is, as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is, and let's take an example of where you can have great data but if you don't have the right culture there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data, that said, "Hey, we're not doing good cross selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts, facing billions in fines, change in leadership, that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying that culture has not changed. Let's contrast that with some positive examples, Medtronic a worldwide company in 150 countries around the world, they may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes you know, this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients, they took the bold move of making their IP for ventilators publicly available, that is the power of a positive culture. Or Verizon, a major telecom organization, looking at late payments of their customers, and even though the US federal government said "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, he said, "You know what? We will spend the time upskilling our people giving them the time to learn more about the future of work, the skills and data and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent identify the relevance, or I like to call it WIIFM, and organize for collaboration. So the CDO whatever your title is, chief analytics officer chief digital officer, you are the most important change agent. And this is where you will hear, that oftentimes a change agent has to come from outside the organization. So this is where, for example in Europe, you have the CDO of Just Eat takeout food delivery organization, coming from the airline industry or in Australia, National Australian Bank, taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in disrupt, it's a hard job. As one of you said to me, it often feels like Sisyphus, I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM, what is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline as well as those analysts, as well as the executives. So if we're talking about players in the NFL they want to perform better, and they want to stay safe. That is why data matters to them. If we're talking about financial services this may be a wealth management advisor, okay, we could say commissions, but it's really helping people have their dreams come true whether it's putting their children through college, or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers, you asked them about data, they'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better that is WIIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard Business Review Study, found that 44% said lack of change management is the biggest barrier to leveraging both new technology but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI Competency Center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model, centralized for economies of scale, that could be the common data, but then in bed, these evangelists, these analysts of the future, within every business unit, every functional domain, and as you see this top bar, all models are possible but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time, because data is helping organizations better navigate a tough economy lock in the customer loyalty, and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at thought leaders, and next I'm pleased to introduce our first change agent Thomas Mazzaferro, chief data officer of Western Union, and before joining Western Union, Tom made his mark at HSBC and JP Morgan Chase spearheading digital innovation in technology operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (soft upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable, different business teams and technology teams into the future. As we look across our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive over the shift from a data standpoint, into the future. That includes being able to have the right information with the right quality of data at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that, as part of that partnership, and it's how we've looked to integrated into our overall business as a whole. We've looked at how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go on to google.com or you go on to Bing, or go to Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability is allowed us to actually enable our overall business teams in our company, to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end users or the business executives, right? Search for what they need, what they want, at the exact time that action needed, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our (indistinct) environments, and as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive into organize our information and our data, then drive these new solutions and capabilities forward. So big portion of us though is culture, so how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked, and to predict based upon different economic trends or different trends in your business, what does is be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward right into this new age, especially with COVID, with COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating, and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities, and those solutions forward. As we go through this journey, both of my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only a celebrating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint, tools, but also what our customers want, what do our customers need, and how do we then surface them with our information, with our data, with our platform, with our products and our services, to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization such as how do you use your data to support the current business lines. But how do you actually use your information your data, to actually better support your customers better support your business, better support your employees, your operations teams and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon, thank you. >> Tom, that was great, thanks so much. Now I'm going to have to brag on you for a second, as a change agent you've come in disrupted, and how long have you been at Western Union? >> Only nine months, I just started this year, but there'd be some great opportunities and big changes, and we have a lot more to go, but we're really driving things forward in partnership with our business teams, and our colleagues to support those customers forward. >> Tom, thank you so much that was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent. Most recently with Schneider Electric, but even going back to Sam's Club, Gustavo welcome. (soft upbeat music) >> So hi everyone my name is Gustavo Canton and thank you so much Cindi for the intro. As you mentioned, doing transformations is a you know, high effort, high reward situation. I have empowerment in transformation and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today, is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are nontraditional sometimes. And so how do we get started? So I think the answer to that is, you have to start for you, yourself as a leader and stay tuned. And by that, I mean you need to understand not only what is happening in your function or your field, but you have to be very into what is happening in society, socioeconomically speaking, wellbeing, you know, the common example is a great example. And for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential, for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be you know, stay in tune and have the skillset and the courage. But for me personally, to be honest to have this courage is not about not being afraid. You're always afraid when you're making big changes and your swimming upstream. But what gives me the courage is the empathy part, like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business, and what the leaders are trying to do, what I do it thinking about the mission of how do I make change for the bigger, you know workforce so the bigger good, despite the fact that this might have a perhaps implication, so my own self interest in my career, right? Because you have to have that courage sometimes to make choices, that are not well seeing politically speaking what are the right thing to do, and you have to push through it. So the bottom line for me is that, I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past, and what they show is that if you look at the four main barriers, that are basically keeping us behind budget, inability to add, cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, this topic about culture is actually gaining more and more traction, and in 2018, there was a story from HBR and it was for about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand, and are aware that we need to transform, commit to the transformation and set us deadline to say, "Hey, in two years, we're going to make this happen, what do we need to do to empower and enable these search engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through, as I think the intro information most recently as Cindi mentioned in Schneider. There are three main areas, legacy mindset, and what that means is that we've been doing this in a specific way for a long time, and here is how we have been successful. We're working the past is not going to work now, the opportunity there is that there is a lot of leaders who have a digital mindset, and their up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people you know, three to five years for them to develop, because the world is going to in a way that is super fast. The second area and this is specifically to implementation of AI is very interesting to me, because just example that I have with ThoughtSpot, right? We went to an implementation and a lot of the way the IT team functions, so the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, your opportunity here is that you need to really find what success look like, in my case, I want the user experience of our workforce to be the same as your experience you have at home. It's a very simple concept, and so we need to think about how do we gain that user experience with this augmented analytics tools, and then work backwards to have the right talent, processes and technology to enable that. And finally, and obviously with COVID a lot of pressure in organizations and companies to do more with less, and the solution that most leaders I see are taking is to just minimize cost sometimes and cut budget. We have to do the opposite, we have to actually invest some growth areas, but do it by business question. Don't do it by function, if you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership, to see more digitally, if you actually invest on fixing your data platform is not just an incremental cost, it's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work in working very hard but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there, and you just to put it into some perspective, there have been some studies in the past about you know, how do we kind of measure the impact of data? And obviously this is going to vary by organization, maturity there's going to be a lot of factors. I've been in companies who have very clean, good data to work with, and I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study what I think is interesting is, they try to put a tagline or attack price to what is a cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work, when you have data that is flawed as opposed to have imperfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be a $100. But now let's say you have any percent perfect data and 20% flow data, by using this assumption that flow data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100, this just for you to really think about as a CIO, CTO, you know CSRO, CEO, are we really paying attention and really closing the gaps that we have on our infrastructure? If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these barriers, right? I think the key is I am in analytics, I know statistics obviously, and love modeling and you know, data and optimization theory and all that stuff, that's what I can do analytics, but now as a leader and as a change agent, I need to speak about value, and in this case, for example for Schneider, there was this tagline coffee of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the right leaders, because you need to, you know, focus on the leaders that you're going to make the most progress. You know, again, low effort, high value, you need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution, and finally you need to make it super simple for the you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics, I pulled up, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers, but one thing that is really important is as you bring along your audience on this, you know, you're going from Excel, you know in some cases or Tableau to other tools like you know, ThoughtSpot, you need to really explain them, what is the difference, and how these two can truly replace some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool, there are other many tools that you might have in your toolkit. But in my case, personally I feel that you need to have one portal going back to seeing these points that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to these stations. Like I said it's been years for us to kind of lay the foundation, get the leadership and chasing culture, so people can understand why you truly need to invest what I meant analytics. And so what I'm showing here is an example of how do we use basically, you know a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week per employee save on average, user experience or ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot we were able to achieve five hours, per week per employee savings. I used to experience for 4.3 out of five, and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications obviously the operations things and the users, in HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy, you are a change agent, you need to have a courage to make these decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very souls for this organization, and that gave me the confidence to know that the work has been done, and we are now in a different stage for the organization. And so for me it safe to say, thank you for everybody who has believed obviously in our vision, everybody who has believed in, you know, the word that we were trying to do and to make the life for, you know workforce or customers that are in community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream you know, what would mentors what people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort but is well worth it. And with that said, I hope you are well and it's been a pleasure talking to you, talk to you soon, take care. >> Thank you Gustavo, that was amazing. All right, let's go to the panel. (soft upbeat music) >> I think we can all agree how valuable it is to hear from practitioners, and I want to thank the panel for sharing their knowledge with the community, and one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top, why? Because it directs the middle, and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard, is that you all prioritize database decision making in your organizations, and you combine two of your most valuable assets to do that, and create leverage, employees on the front lines, and of course the data. That was rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID's broken everything. And it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo let's start with you if I'm an aspiring change agent, and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business as you know, I come from, you know, Sam's Club Walmart retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement that's just going to take you so far. What you have to do is and that's what I tried to do is I try to go into areas, businesses and transformations that make me, you know stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions organizations, and do these change management and decisions mindset as required for these kinds of efforts. >> Thank you for that is inspiring and Cindi, you love data, and the data is pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation. >> Yeah, so Michelle has a new fan here because she has found her voice, I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment. But why I think diversity matters more now than ever before, and this is by gender, by race, by age, by just different ways of working and thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority, you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible >> Great perspectives thank you, Tom, I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually you know, in a digital business over the last 12 months really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers and today, that there's been a huge need, right? To send money, to support family, to support friends and loved ones across the world. And as part of that, you know, we are very honored to support those customers that we across all the centers today. But as part of that celebration, we need to make sure that we had the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did celebrate some of our plans on digital to help support that overall growth coming in, and to support our customers going forward. Because there were these times during this pandemic, right? This is the most important time, and we need to support those that we love and those that we care about. And in doing that, it's one of those ways is actually by sending money to them, support them financially. And that's where really are part of that our services come into play that, you know, I really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level, and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much and doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing, or you pushing your people too hard, can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization I ask the question, Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right? It forces us to remove silos and collaborate in a faster way, so to me it was an opportunity to actually integrate with other areas and drive decisions faster. But make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay, you know debating points or making repetitive business cases onto people connect with the decision because you understand, and you are seeing that, hey, the CEO is making a one, two year, you know, efficiency goal, the only way for us to really do more with less is for us to continue this path. We cannot just stay with the status quo, we need to find a way to accelerate transformation... >> How about you Tom, we were talking earlier was Sudheesh had said about that bungee jumping moment, what can you share? >> Yeah you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right? That's what I tell my team is that you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right? Expand and support that the ever changing needs the marketplace and industry and our customers today and that pace of change that's happening, right? And what customers are asking for, and the competition the marketplace, it's only going to accelerate. So as part of that, you know, as we look at what how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan into align, to drive the actual transformation, so that you can scale even faster into the future. So as part of that, so we're putting in place here, right? Is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> We're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that you know, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch for whatever variety of reasons, but it's being forced on them now, but knowing what you know now that you know, we're all in this isolation economy how would you say that advice has changed, has it changed? What's your number one action and recommendation today? >> Yeah well, first off, Tom just freaked me out. What do you mean this is the slowest ever? Even six months ago, I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power in politics and how to bring people along in a way that they are comfortable, and now I think it's, you know what? You can't get comfortable. In fact, we know that the organizations that were already in the cloud, have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's Sudheesh going to go on bungee jumping? (all chuckling) >> That's fantastic discussion really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just as I said before lip service. And sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today, is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions that can drive you revenue, cut costs, speed, access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh please bring us home. >> Thank you, thank you Dave, thank you theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I was simply put it, she said it really well, that is be brave and drive. Don't go for a drive along, that is such an important point. Often times, you know that I think that you have to do to make the positive change that you want to see happen. But you wait for someone else to do it, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice, taking that chair, whether it's available or not and making sure that your ideas, your voices are heard and if it requires some force then apply that force, make sure your ideas are good. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the courtroom. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom instead of a single take away, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in, and they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to thoughtspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to thoughtspot.com/beyond, our global user conferences happening in this December, we would love to have you join us. It's again, virtual, you can join from anywhere, we are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we would have been up to since the last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing, you'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas for engineers I've been cooking up. All of those things will be available for you at ThoughtSpot Beyond, thank you, thank you so much.

(speaks in foreign language) >> Narrator: Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent, and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you. It's time to lead the way, it's time for thought leaders. >> Welcome to Thought Leaders, a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis, and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today, we're going to hear from experienced leaders, who are transforming their organizations with data, insights and creating digital-first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, Chief Data Strategy Officer for ThoughtSpot is Cindi Hausen. Cindi is an analytics and BI expert with 20 plus years experience and the author of Successful Business Intelligence Unlock The Value of BI and Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you, welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair. Hello Sudheesh, how are you doing today? >> I am well Dave, it's good to talk to you again. >> It's great to see you. Thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today? (gentle music) >> Thanks, Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our, you know, sort of effort to reach out to you with invites for events like this. So we are getting way more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time, and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, and generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, you know, we are living through these difficult times, we want an event to be, this event to be more of an uplifting and inspiring event too. Now, the challenge is, how do you do that with the team being change agents? Because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, change is sort of like, if you've ever done bungee jumping. You know, it's like standing on the edges, waiting to make that one more step. You know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage and when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation, in most businesses it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to to, first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that, "You know, maybe I don't have the power to make the change that the company needs. Sometimes I feel like I don't have the skills." Sometimes they may feel that, I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. You know, there are people in the company, who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data, they have the skills to do that, but they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is this silo of people with the answers and there is a silo of people with the questions, and there is gap. These sort of silos are standing in the way of making that necessary change that we all I know the business needs, and the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is. You may need to bring some external stimuli to start that domino of the positive changes that are necessary. The group of people that we have brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to trust the rope that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading her bio, that there are no country vital worldwide competition for cool patents, because she will beat all of us because when her children were small, you know, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age, where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom. I am extremely excited to see what she's going to talk about. I've seen the slides with a bunch of amazing pictures, I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle. I'm looking forward to her talk next. Welcome Michelle. It's over to you. (gentle music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. This is about as close as I'm ever going to get. So, I want to talk to you about quarterbacking our digital revolution using insights, data and of course, as you said, leadership. First, a little bit about myself, a little background. As I said, I always wanted to play football and this is something that I wanted to do since I was a child but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent and in the South football is like a religion and you pick sides. I chose Auburn University working in the athletic department, so I'm testament. Till you can start, a journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football, you know this is a really big rivalry, and when you choose sides your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL, he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight. From Universal Studios, Disney, to my current position as CIO of the NFL. In this job, I'm very privileged to have the opportunity to work with a team that gets to bring America's game to millions of people around the world. Often, I'm asked to talk about how to create amazing experiences for fans, guests or customers. But today, I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event, every game, every awesome moment, is execution. Precise, repeatable execution and most of my career has been behind the scenes doing just that. Assembling teams to execute these plans and the key way that companies operate at these exceptional levels is making good decisions, the right decisions, at the right time and based upon data. So that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves, and it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kind of world class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney. In '90s I was at Disney leading a project called Destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool and then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today. Like the MagicBand, Disney's Magical Express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data, more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately, leading to moving into IT and I haven't looked back since. In the early 2000s, I was at Universal Studio's theme park as their CIO preparing for and launching the Wizarding World of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wand shop. As today at the NFL, I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning and all new communication strategies, and using data to drive everything, from player performance, contracts, to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contact tracing devices joined with testing data. Talk about data actually enabling your business. Without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First, RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone, all-in-one solution in the cloud and Quotient Technologies, whose product is actually data. The tagline at Quotient is The Result in Knowing. I think that's really important because not all of us are data companies, where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First, just hit on it, is change. how to be a champion and a driver of change. Second, how to use data to drive performance for your company and measure performance of your company. Third, how companies now require intense collaboration to operate and finally, how much of this is accomplished through solid data-driven decisions. First, let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it. And thankfully, for the most part, knock on wood, we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, The 2020 Draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage, to smaller events in club facilities. And then ultimately, to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements and we only had a few weeks to figure it out. I found myself for the first time, being in the live broadcast event space. Talking about bungee jumping, this is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky, but it ended up being also rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at its level, highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact. Those with the best stats usually win the games. The NFL has always recorded stats. Since the beginning of time here at the NFL a little... This year is our 101st year and athlete's ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured and I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled recently. And how fast do you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to the next level. It's powered by Amazon Web Services and we gather this data, real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course, it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns, speed, match-ups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about, for those of you that are IT professionals and developers, you know, more than 10 years ago agile practices began sweeping companies. Where small teams would work together rapidly in a very flexible, adaptive and innovative way and it proved to be transformational. However today, of course that is no longer just small teams, the next big wave of change and we've seen it through this pandemic, is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you got the people from the bottom up to do it and you executed. At Universal, we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties, so influence and collaboration, and how to share across companies became very important. And now here I am at the NFL an even the bigger ecosystem. We have 32 clubs that are all separate businesses, 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company but across companies. The ability to work in a collaborative way across businesses and even other companies, that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation, yet competition to co-exist. I mean, the NFL is a great example of what we call co-oppetition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units, who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with, first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program, it's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, thank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an a line person. >> Well, then I can't do my job without you. >> Great and I'm getting the feeling now, you know, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take him to the Delaware Water Gap and we do the cliff jumping. >> Oh that sounds good, I'll watch your watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders, when you're trying to prioritize the different voices you have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there are so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with aligning on a mission and if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together. You sort of do get them to naturally prioritize their work and I think that's very important. So for us at the NFL and even at Disney, it was our core values and our core purpose is so well known and when anything challenges that, we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent and that means listening to every single stakeholder. Even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic, and having a mission, and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling, so thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. >> (gentle music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl, what went wrong? 1986, as the reactors were melting down, they had the data to say, "This is going to be catastrophic," and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again. This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with and this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, is it really two sides of the same coin? Real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "You know, Cindi, I actually think this is two sides of the same coin, one reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting, largely parametrized reports, on-premises data warehouses, or not even that operational reports. At best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change, complacency. And sometimes that complacency, it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, "No, we're measured on least to serve." So politics and distrust, whether it's between business and IT or individual stakeholders is the norm, so data is hoarded. Let's contrast that with the leader, a data and analytics leader, what does their technology look like? Augmented analytics, search and AI driven insights, not on-premises but in the cloud and maybe multiple clouds. And the data is not in one place but it's in a data lake and in a data warehouse, a logical data warehouse. The collaboration is via newer methods, whether it's Slack or Teams, allowing for that real-time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals. Whether it's the best fan experience and player safety in the NFL or best serving your customers, it's innovative and collaborative. There's none of this, "Oh, well, I didn't invent that. I'm not going to look at that." There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, to fail fast and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact, what we like to call the new decision-makers or really the frontline workers. So Harvard Business Review partnered with us to develop this study to say, "Just how important is this? We've been working at BI and analytics as an industry for more than 20 years, why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor." 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state-of-the-art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets, really just taking data out of ERP systems that were also on-premises and state-of-the-art was maybe getting a management report, an operational report. Over time, visual based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state-of-the-art though, Gartner calls it augmented analytics. At ThoughtSpot, we call it search and AI driven analytics, and this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses. And I think this is an important point, oftentimes you, the data and analytics leaders, will look at these two components separately. But you have to look at the BI and analytics tier in lock-step with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom, getting to a visual visualization that then can be pinned to an existing pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non-analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years. Now, it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization but I would also say, equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful, if you look at products like Power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure Synapse, or Google BigQuery, they do not. They require you to move it into a smaller in-memory engine. So it's important how well these new products inter-operate. The pace of change, its acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI and that is roughly three times the prediction they had just a couple of years ago. So let's talk about the real world impact of culture and if you've read any of my books or used any of the maturity models out there, whether the Gartner IT Score that I worked on or the Data Warehousing Institute also has a maturity model. We talk about these five pillars to really become data-driven. As Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology and also the processes. And often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders. You have told me now culture is absolutely so important, and so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data. It said, "Hey, we're not doing good cross-selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture and they're trying to fix this, but even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples. Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers and even though the U.S. Federal Government said, "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, They said, "You know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions. Bring in a change agent, identify the relevance or I like to call it WIIFM and organize for collaboration. So the CDO, whatever your title is, Chief Analytics Officer, Chief Digital Officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe you have the CDO of Just Eat, a takeout food delivery organization coming from the airline industry or in Australia, National Australian Bank taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in, disrupt. It's a hard job. As one of you said to me, it often feels like. I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM What's In It For Me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So, if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay, we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers you ask them about data. They'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better, that is WIIFM and sometimes we spend so much time talking the technology, we forget, what is the value we're trying to deliver with this? And we forget the impact on the people that it does require change. In fact, the Harvard Business Review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then embed these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time because data is helping organizations better navigate a tough economy, lock in the customer loyalty and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next, I'm pleased to introduce our first change agent, Tom Mazzaferro Chief Data Officer of Western Union and before joining Western Union, Tom made his Mark at HSBC and JP Morgan Chase spearheading digital innovation in technology, operations, risk compliance and retail banking. Tom, thank you so much for joining us today. (gentle music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and the technology teams into the future? As we look across our data ecosystems and our platforms, and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive an organization from a data standpoint, into the future. That includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that. As part of that partnership and it's how we've looked to integrate it into our overall business as a whole. We've looked at, how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go onto Bing or you go onto Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us is the same thing, but in the business world. So using ThoughtSpot and other AI capability is it's allowed us to actually enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone, or an engineer to go pull information or pull data. We actually can have the end users or the business executives, right. Search for what they need, what they want, at the exact time that they actually need it, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on a journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, our... The local environments and as we move that, we've actually picked two of our cloud providers going to AWS and to GCP. We've also adopted Snowflake to really drive and to organize our information and our data, then drive these new solutions and capabilities forward. So a big portion of it though is culture. So how do we engage with the business teams and bring the IT teams together, to really help to drive these holistic end-to-end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven. This is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what decisions need to be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization and as part of that, it really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, Especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both in my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes, both on the platform standpoint, tools, but also what do our customers want, what do our customers need and how do we then service them with our information, with our data, with our platform, and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization, such as how do you use your data to support your current business lines, but how do you actually use your information and your data to actually better support your customers, better support your business, better support your employees, your operations teams and so forth. And really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said, I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon. Thank you. >> Tom, that was great. Thanks so much and now going to have to drag on you for a second. As a change agent you've come in, disrupted and how long have you been at Western Union? >> Only nine months, so just started this year, but there have been some great opportunities to integrate changes and we have a lot more to go, but we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now, I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe and he is a serial change agent. Most recently with Schneider Electric but even going back to Sam's Clubs. Gustavo, welcome. (gentle music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro. As you mentioned, doing transformations is, you know, a high reward situation. I have been part of many transformations and I have led many transformations. And, what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so, in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started, barriers or opportunities as I see it, the value of AI and also, how you communicate. Especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so, how do we get started? So, I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand, not only what is happening in your function or your field, but you have to be very in tune what is happening in society socioeconomically speaking, wellbeing. You know, the common example is a great example and for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be, you know, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes and you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. But I do it thinking about the mission of, how do I make change for the bigger workforce or the bigger good despite the fact that this might have perhaps implication for my own self interest in my career. Right? Because you have to have that courage sometimes to make choices that are not well seen, politically speaking, but are the right thing to do and you have to push through it. So the bottom line for me is that, I don't think we're they're transforming fast enough. And the reality is, I speak with a lot of leaders and we have seen stories in the past and what they show is that, if you look at the four main barriers that are basically keeping us behind budget, inability to act, cultural issues, politics and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topic about culture is actually gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a deadline to say, "Hey, in two years we're going to make this happen. What do we need to do, to empower and enable these change agents to make it happen? You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So, I'll give you examples of some of the roadblocks that I went through as I've been doing transformations, most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset and what that means is that, we've been doing this in a specific way for a long time and here is how we have been successful. What worked in the past is not going to work now. The opportunity there is that there is a lot of leaders, who have a digital mindset and they're up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people, you know, three to five years for them to develop because the world is going in a way that is super-fast. The second area and this is specifically to implementation of AI. It's very interesting to me because just the example that I have with ThoughtSpot, right? We went on implementation and a lot of the way the IT team functions or the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, the opportunity here is that you need to redefine what success look like. In my case, I want the user experience of our workforce to be the same user experience you have at home. It's a very simple concept and so we need to think about, how do we gain that user experience with these augmented analytics tools and then work backwards to have the right talent, processes, and technology to enable that. And finally and obviously with COVID, a lot of pressure in organizations and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs sometimes and cut budget. We have to do the opposite. We have to actually invest on growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent and your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard but it's not efficient and it's not working in the way that you might want to work. So there is a lot of opportunity there and just to put in terms of perspective, there have been some studies in the past about, you know, how do we kind of measure the impact of data? And obviously, this is going to vary by organization maturity, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with and I've been with companies that we have to start basically from scratch. So it all depends on your maturity level. But in this study, what I think is interesting is they try to put a tagline or a tag price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to having perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have 80% perfect data and 20% flawed data. By using this assumption that flawed data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100. This just for you to really think about as a CIO, CTO, you know CHRO, CEO, "Are we really paying attention and really closing the gaps that we have on our data infrastructure?" If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this or how do I break through some of these challenges or some of these barriers, right? I think the key is, I am in analytics, I know statistics obviously and love modeling, and, you know, data and optimization theory, and all that stuff. That's what I came to analytics, but now as a leader and as a change agent, I need to speak about value and in this case, for example, for Schneider. There was this tagline, make the most of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that, I understood what kind of language to use, how to connect it to the overall strategy and basically, how to bring in the right leaders because you need to, you know, focus on the leaders that you're going to make the most progress, you know. Again, low effort, high value. You need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution. And finally, you need to make it super-simple for the, you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics portal. It was actually launched in July of this year and we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many, many factors but one thing that is really important is as you bring along your audience on this, you know. You're going from Excel, you know, in some cases or Tableu to other tools like, you know, ThoughtSpot. You need to really explain them what is the difference and how this tool can truly replace some of the spreadsheets or some of the views that you might have on these other kinds of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit but in my case, personally, I feel that you need to have one portal. Going back to Cindi's points, that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory and I will tell you why, because it took a lot of effort for us to get to this stage and like I said, it's been years for us to kind of lay the foundation, get the leadership, initiating culture so people can understand, why you truly need to invest on augmented analytics. And so, what I'm showing here is an example of how do we use basically, you know, a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics. Hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week for employee to save on average. User experience, our ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings, a user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations things and the users. In HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize, this kind of effort takes a lot of energy. You are a change agent, you need to have courage to make this decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these great resource for this organization and that give me the confident to know that the work has been done and we are now in a different stage for the organization. And so for me, it's just to say, thank you for everybody who has belief, obviously in our vision, everybody who has belief in, you know, the work that we were trying to do and to make the life of our, you know, workforce or customers and community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream, you know, work with mentors, work with people in the industry that can help you out and guide you on this kind of transformation. It's not easy to do, it's high effort, but it's well worth it. And with that said, I hope you are well and it's been a pleasure talking to you. Talk to you soon. Take care. >> Thank you, Gustavo. That was amazing. All right, let's go to the panel. (light music) Now I think we can all agree how valuable it is to hear from practitioners and I want to thank the panel for sharing their knowledge with the community. Now one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision making in your organizations. And you combine two of your most valuable assets to do that and create leverage, employees on the front lines, and of course the data. Now as as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID has broken everything and it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo, let's start with you. If I'm an aspiring change agent and let's say I'm a budding data leader, what do I need to start doing? What habits do I need to create for long-lasting success? >> I think curiosity is very important. You need to be, like I said, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I've been doing it for 50 years plus, but I think you need to understand wellbeing of the areas across not only a specific business. As you know, I come from, you know, Sam's Club, Walmart retail. I've been in energy management, technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to just continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do, is I try to go into areas, businesses and transformations, that make me, you know, stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions, organizations, and do the change management, the essential mindset that's required for this kind of effort. >> Well, thank you for that. That is inspiring and Cindi you love data and the data is pretty clear that diversity is a good business, but I wonder if you can, you know, add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine and it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before and this is by gender, by race, by age, by just different ways of working and thinking, is because as we automate things with AI, if we do not have diverse teams looking at the data, and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are, finding your voice, having a seat at the table and just believing in the impact of your work has never been more important and as Michelle said, more possible. >> Great perspectives, thank you. Tom, I want to go to you. So, I mean, I feel like everybody in our businesses is in some way, shape, or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth, actually, in our digital business over the last 12 months really, even acceleration, right, once COVID hit. We really saw that in the 200 countries and territories that we operate in today and service our customers in today, that there's been a huge need, right, to send money to support family, to support friends, and to support loved ones across the world. And as part of that we are very honored to be able to support those customers that, across all the centers today, but as part of the acceleration, we need to make sure that we have the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because during these times, during this pandemic, right, this is the most important time and we need to support those that we love and those that we care about. And doing that some of those ways is actually by sending money to them, support them financially. And that's where really our products and our services come into play that, you know, and really support those families. So, it was really a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. >> Awesome, thank you. Now, I want to come back to Gustavo. Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much in doing things with data or the technology that it was just maybe too bold, maybe you felt like at some point it was failing, or you're pushing your people too hard? Can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization, I ask the question, "Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right, it forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension or you need to be okay, you know, debating points or making repetitive business cases until people connect with the decision because you understand and you are seeing that, "Hey, the CEO is making a one, two year, you know, efficiency goal. The only way for us to really do more with less is for us to continue this path. We can not just stay with the status quo, we need to find a way to accelerate the transformation." That's the way I see it. >> How about Utah, we were talking earlier with Sudheesh and Cindi about that bungee jumping moment. What can you share? >> Yeah, you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right, this is what I tell my team, is that you need to be, you need to feel comfortable being uncomfortable. Meaning that we have to be able to basically scale, right? Expand and support the ever changing needs in the marketplace and industry and our customers today, and that pace of change that's happening, right? And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, you know, as you look at how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan and to align and to drive the actual transformation, so that you can scale even faster into the future. So it's part of that, that's what we're putting in place here, right? It's how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So Cindi, last question, you've worked with hundreds of organizations and I got to believe that, you know, some of the advice you gave when you were at Gartner, which was pre-COVID, maybe sometimes clients didn't always act on it. You know, not my watch or for whatever, variety of reasons, but it's being forced on them now. But knowing what you know now that, you know, we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well first off, Tom, just freaked me out. What do you mean, this is the slowest ever? Even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more very aware of the power in politics and how to bring people along in a way that they are comfortable and now I think it's, you know what, you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So, if you really want to survive, as Tom and Gustavo said, get used to being uncomfortable. The power and politics are going to happen, break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where Sudheesh is going to go bungee jumping. (all chuckling) >> Guys, fantastic discussion, really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really, virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things. Whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise-wide digital transformation, not just as I said before, lip service. You know, sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tournament results. You know, what does that mean? Getting it right. Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization, data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you, thank you, Dave. Thank you, theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I heard from all four of our distinguished speakers. First, Michelle, I will simply put it, she said it really well. That is be brave and drive, don't go for a drive alone. That is such an important point. Often times, you know the right thing that you have to do to make the positive change that you want to see happen, but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding, the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voice is heard and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes. The importance of building the quorum, and that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in and they were able to make the change that is necessary through this difficult time in a matter of months. If they could do it, anyone could. The second thing I want to do is to leave you with a takeaway, that is I would like you to go to ThoughtSpot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to ThoughtSpot.com/beyond. Our global user conference is happening in this December. We would love to have you join us, it's, again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we have been working to release, something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at ThoughtSpot Beyond. Thank you, thank you so much.

>> Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions all at the speed of digital. The transformation starts with you. It's time to lead the way it's time for Thought leaders. >> Welcome to "Thought Leaders" a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today we're going to hear from experienced leaders who are transforming their organizations with data, insights and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot first chief data strategy officer at the ThoughtSpot is Cindi Howson. Cindi is an analytics and BI expert with 20 plus years experience and the author of "Successful Business Intelligence "Unlock the Value of BI & Big Data." Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of the cube is ThoughtSpot CEO Sudheesh Nair Hello, Sudheesh how are you doing today? >> I'm well Dave, it's good to talk to you again. >> It's great to see you thanks so much for being here. Now Sudheesh please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today. (upbeat music) >> Thanks, Dave. I wish you were there to introduce me into every room and that I walk into because you have such an amazing way of doing it. Makes me feel all so good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, we are living through these difficult times. We want an event to be this event, to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like to do. The way I think of it sort of like a, if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage. And when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation in most businesses, it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to first of all challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they may feel that I'm probably not the right person do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. There are people in the company who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data. They have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool. It could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is, you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping, for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading our bio, that there are no country vital worldwide competition for cool patterns, because she will beat all of us because when her children were small, they were probably into Harry Potter and Disney. She was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom? I am extremely excited to see what she's going to talk about. I've seen the slides, tons of amazing pictures. I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle and looking forward to her talk next. Welcome Michelle, it's over to you. (upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. And I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking, our digital revolution using insights data. And of course, as you said, leadership, first a little bit about myself, a little background, as I said, I always wanted to play football. And this is something that I wanted to do since I was a child. But when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent. And in the South football is like a religion and you pick sides. I chose Auburn university working in the athletic department. So I'm Testament to you can start the journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little. He played offensive line for the Alabama Crimson Tide. And for those of you who know SCC football, you know this is a really big rivalry. And when you choose sides, your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL. He just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage because behind every event, every game, every awesome moment is execution, precise, repeatable execution. And most of my career has been behind the scenes doing just that assembling teams to execute these plans. And the key way that companies operate at these exceptional levels is making good decisions, the right decisions at the right time and based upon data so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world casts experiences are often seeking out and leveraging next-generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute a little bit first about Disney in the 90s, I was at Disney leading a project called destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up, but way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, Disney's magical express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately leading to moving into IT. And I haven't looked back since. In the early two thousands, I was at universal studios theme park as their CIO preparing for and launching "The Wizarding World of Harry Potter" bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wan selects you at a wan shop. As today at the NFL? I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning, and all new communication strategies and using data to drive everything from player performance, contracts, to where we build new stadiums and hold events with this year being the most challenging yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data, talk about data, actually enabling your business without it w wouldn't be having a season right now. I'm also on the board of directors of two public companies where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone all in one solution in the cloud and Quotient technologies whose product is actually data. The tagline at Quotient is the result in knowing I think that's really important because not all of us are data companies where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First just hit on it is change how to be a champion and a driver of change. Second, how do you use data to drive performance for your company and measure performance of your company? Third, how companies now require intense collaboration to operate. And finally, how much of this is accomplished through solid data driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it and thankfully for the most part, knock on what we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches GM's prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee jumping. This is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary. It was certainly very risky, but it ended up being all so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at it's level. Highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field. You can see points being scored in stats, and you immediately know that impact those with the best stats usually when the games. The NFL has always recorded stats since the beginning of time here at the NFL a little this year is our 101 year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured. And I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled and how fast you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys, to the data and the use of the data. Our next generation stats platform is taking data to a next level. It's powered by Amazon web services. And we gathered this data real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize route patterns, speed match-ups, et cetera. So much faster than ever before. We're continuing to roll out sensors too that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about for those of you that are IT professionals and developers, more than 10 years ago, agile practices began sweeping companies where small teams would work together rapidly in a very flexible, adaptive, and innovative way. And it proved to be transformational. However, today, of course, that is no longer just small teams, the next big wave of change. And we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture, but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you've got the people from the bottom up to do it and you executed. At Universal we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem, we have 32 clubs that are all separate businesses. 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation yet competition to co-exist. I mean, the NFL is a great example of what we call co-op petition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be. Data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask it's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program. It's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, tank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an old line person. (Michelle and Cindi laughing) >> Well, then I can do my job without you. >> Great. And I'm getting the feeling now, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take them to the Delaware water gap and we do the cliff jumping. >> That sounds good, I'll watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders when you're trying to prioritize the different voices. You have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with, aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together, you sort of do get them to naturally prioritize their work. And I think that's very important. So for us, at the NFL and even at Disney, it was our core values and our core purpose, is so well known and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic. And I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder, even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So, thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (upbeat music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl what went wrong? 1986, as the reactors were melting down, they had the data to say, this is going to be catastrophic. And yet the culture said, "no, we're perfect, hide it. "Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, the additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again, this is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology. Is it really two sides of the same coin, real-world impacts and then some best practices you can use to and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "Cindi, I actually think this is two sides "of the same coin. "One reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting largely parametrized reports, on premises data, warehouses, or not even that operational reports at best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change complacency. And sometimes that complacency it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics search and AI driven insights, not on premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data Lake and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods, whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized. And democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision-makers or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? We've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor. Everyone said that if our 87% said, they would be more successful if frontline workers were empowered with data driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality, only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture in technology. How did we get here? It's because state-of-the-art keeps changing. So the first-generation BI and analytics platforms were deployed on premises on small datasets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report. Over time visual-based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state of the art though, Gartner calls it augmented analytics at ThoughtSpot, we call it search and AI driven analytics. And this was pioneered for large scale datasets, whether it's on premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes you, the data and analytics leaders will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding, a report it's typing in search keywords and very robust keywords contains rank top bottom, getting to a visual visualization that then can be pinned to an existing Pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You use to be able to create an investment place a bet for maybe 10 years, a few years ago, that time horizon was five years, now it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse and pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful if you look at products like power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure synapse or Google big query, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. the pace of change, its acceleration Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gartner IT score that I worked on, or the data warehousing Institute also has the money surety model. We talk about these five pillars to really become data-driven. As Michelle, I spoke about it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology, and also the processes. And often when I would talk about the people and the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for Thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven it's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data, it said, "hey, we're not doing good cross selling, "customers do not have both a checking account "and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples, Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers. And even though the U.S federal government said, "well, you can't turn them off. They said, "we'll extend that even beyond "the mandated guidelines." And facing a slow down in the business because of the tough economy, they said, you know what? "We will spend the time up skilling our people, "giving them the time to learn more "about the future of work, the skills and data "and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent, identify the relevance, or I like to call it WIFM and organize for collaboration. So the CDO, whatever your title is, chief analytics officer, chief digital officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of Just Eat a takeout food delivery organization coming from the airline industry or in Australia, National Australian bank, taking a CDO within the same sector from TD bank going to NAB. So these change agents come in disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIFM. What is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is WIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard business review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state-of-the-art. Now for the biggest impact what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then in bed, these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead an exciting time, because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next I'm pleased to introduce our first change agent, Tom Mazzaferro chief data officer of Western union. And before joining Western union, Tom made his Mark at HSBC and JPMorgan Chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven, capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and technology teams into the future. As you look across, our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive and over the shift from a data standpoint, into the future, that includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot, to actually bring in the technology to help us drive that as part of that partnership. And it's how we've looked to integrate it into our overall business as a whole we've looked at how do we make sure that our business and our professional lives right, are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go on to Bing we go onto Yahoo and you search for what you want search to find and answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability it's allowed us to actually, enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end-users or the business executives, right. Search for what they need, what they want at the exact time that action need it to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, or our Eloqua environments. And as we move that, we've actually picked two of our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive and to organize our information and our data then drive these new solutions and capabilities forward. So they portion of us though is culture. So how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities to really support the actual business into the future? That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what does this is maybe be made and actually provide those answers to the business teams before they're even asking for it, that is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon, industries based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are accelerating and are changing rapidly to accommodate and to support customers in these very difficult times, as part of that, you need to make sure you have the right underlying foundation ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both of my career, but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint tools, but also what do our customers want? What do our customers need and how do we then service them with our information, with our data, with our platform and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data organization such as how do you use your data to support the current business lines, but how do you actually use your information, your data to actually put a better support your customers, better support your business, better support your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from this investments into the future. But that being said, hope you enjoy the segment on how to become and how to drive it data driven organization. And, looking forward to talking to you again soon. Thank you. >> Tom that was great thanks so much. Now I'm going to have to brag on you for a second as a change agent you've come in disrupted and how long have you been at Western union? >> Only nine months, so just started this year, but, doing some great opportunities and great changes. And we have a lot more to go, but, we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent, most recently with Schneider electric, but even going back to Sam's clubs, Gustavo welcome. (upbeat music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro, as you mentioned, doing transformations is high effort, high reward situation. I have empowered many transformations and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North star and where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also, how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so how do we get started? So I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand not only what is happening in your function or your field, but you have to be varying into what is happening in society, socioeconomically speaking wellbeing. The common example is a great example. And for me personally, it's an opportunity because the one core value that I have is well-being, I believe that for human potential, for customers and communities to grow wellbeing should be at the center of every decision. And as somebody mentioned is great to be, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes when you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. What I do it thinking about the mission of how do I make change for the bigger, workforce? for the bigger good. Despite this fact that this might have a perhaps implication on my own self-interest in my career, right? Because you have to have that courage sometimes to make choices that I know we'll see in politically speaking, what are the right thing to do? And you have to push through it. And you have to push through it. So the bottom line for me is that I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past. And what they show is that if you look at the four main barriers that are basically keeping us behind budget, inability to act cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topics culture is actually gaining, gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a state, deadline to say, "hey, in two years, we're going to make this happen. "What do we need to do to empower and enable "this change engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through as I think transformation most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset. And what that means is that we've been doing this in a specific way for a long time and here is how we have been successful what was working the past is not going to work now. The opportunity there is that there is a lot of leaders who have a digital mindset and there're up and coming leaders that are not yet fully developed. We need to mentor those leaders and take bets on some of these talent, including young talent. We cannot be thinking in the past and just wait for people, three to five years for them to develop because the world is going to in a way that is super fast. The second area, and this is specifically to implementation of AI is very interesting to me because just example that I have with ThoughtSpot, right, we went to implementation and a lot of the way is the IT team function of the leaders look at technology, they look at it from the prism of the prior all success criteria for the traditional Bi's. And that's not going to work. Again the opportunity here is that you need to really find what successful look like. In my case, I want the user experience of our workforce to be the same as user experience you have at home is a very simple concept. And so we need to think about how do we gain the user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, with COVID a lot of pressuring organizations, and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs, sometimes in cut budget, we have to do the opposite. We have to actually invest some growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have studies in the past about, how do we kind of measure the impact of data. And obviously this is going to vary by your organization maturity, is going to, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with. And I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study, what I think is interesting is they try to put attack line or attack price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to have perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have any percent perfect data and 20% flawed data by using this assumption that flawed data is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to $100. This is just for you to really think about as a CIO CTO, CHRO CEO, are we really paying attention and really closing the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact. But as you can tell the price that goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these various, right. I think the key is I am in analytics. I know statistics obviously, and love modeling and data and optimization theory and all that stuff. That's what I came to analytics. But now as a leader and as a change agent, I need to speak about value. And in this case, for example, for Schneider, there was this tagline called free up your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the, the right leaders, because you need to focus on the leaders that you're going to make the most progress. Again, low effort, high value. You need to make sure you centralize all the data as you can. You need to bring in some kind of augmented analytics solution. And finally you need to make it super simple for the, in this case, I was working with the HR teams in other areas, so they can have access to one portal. They don't have to be confused in looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to IT get leadership support, find the budgeting, get everybody on board, make sure the safe criteria was correct. And we call this initiative, the people analytics portal, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers. But one thing that is really important is as you bring along your audience on this, you're going from Excel, in some cases or Tableau to other tools like, ThoughtSpot, you need to really explain them what is the difference and how these tools can truly replace, some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit. But in my case, personally, I feel that you need to have one portal going back to Cindi's point. I really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership, and shaping culture so people can understand why you truly need to invest on (indistinct) analytics. And so what I'm showing here is an example of how do we use basically, a tool to capture in video the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved user experience and adoption. So for hours saved or a mission was to have 10 hours per week per employee save on average user experience, or ambition was 4.5. And adoption, 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings. Our user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations teams and the users in HR safety and other areas that might be, basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy. You are a change agent. You need to have a courage to make the decision and understand that I feel that in this day and age, with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very source for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it to say, thank you for everybody who has believed, obviously in our vision, everybody who has believe in the word that we were trying to do and to make the life of four workforce or customers or in community better. As you can tell, there is a lot of effort. There is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied. With the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream what would mentors, what would people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort, but is well worth it. And with that said, I hope you are well, and it's been a pleasure talking to you. Talk to you soon, take care. >> Thank you, Gustavo, that was amazing. All right, let's go to the panel. (air whooshing) >> Okay, now we're going to go into the panel and bring Cindi, Michelle, Tom, and Gustavo back and have an open discussion. And I think we can all agree how valuable it is to hear from practitioners. And I want to thank the panel for sharing their knowledge with the community. And one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision-making in your organizations and you combine two of your most valuable assets to do that and create leverage, employees on the front lines. And of course the data. And as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. The old saying, if it ain't broke don't fix it. Well COVID is broken everything. And it's great to hear from our experts, how to move forward. So let's get right into it. So Gustavo, let's start with you if I'm an aspiring change agent and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know I come from, Sam's club Walmart, retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do is I try to go into areas, businesses, and transformation that make me stretch and develop as a leader. That's what I'm looking to do so I can help transform the functions organizations and do the change management, change of mindset required for these kinds of efforts. >> Michelle, you're at the intersection of tech and sports and what a great combination, but they're both typically male oriented fields. I mean, we've talked a little bit about how that's changing, but two questions. Tell us how you found your voice and talk about why diversity matters so much more than ever now. >> No, I found my voice really as a young girl, and I think I had such amazing support from men in my life. And I think the support and sponsorship as well as sort of mentorship along the way, I've had amazing male mentors who have helped me understand that my voice is just as important as anyone else's. I mean, I have often heard, and I think it's been written about that a woman has to believe they'll 100% master topic before they'll talk about it where a man can feel much less mastery and go on and on. So I was that way as well. And I learned just by watching and being open, to have my voice. And honestly at times demand a seat at the table, which can be very uncomfortable. And you really do need those types of, support networks within an organization. And diversity of course is important and it has always been. But I think if anything, we're seeing in this country right now is that diversity among all types of categories is front and center. And we're realizing that we don't all think alike. We've always known this, but we're now talking about things that we never really talked about before. And we can't let this moment go unchecked and on, and not change how we operate. So having diverse voices within your company and in the field of tech and sports, I am often the first and only I'm was the first, CIO at the NFL, the first female senior executive. It was fun to be the first, but it's also, very challenging. And my responsibility is to just make sure that, I don't leave anyone behind and make sure that I leave it good for the next generation. >> Well, thank you for that. That is inspiring. And Cindi, you love data and the data's pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad. So he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before. And this is by gender, by race, by age, by just different ways of working in thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible. >> Great perspectives, thank you. Tom I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually in a digital business over the last, 12 months, really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers, today, that there's been a huge need, right? To send money, to support family, to support, friends and support loved ones across the world. And as part of that we are very, honored to get to support those customers that we, across all the centers today. But as part of that acceleration we need to make sure that we had the right architecture and the right platforms to basically scale, right, to basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, really our part of that our services come into play that we really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom I'd love for you to chime in too. Did you guys ever think like you were, you were pushing the envelope too much in doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing or you're pushing your people too hard. Can you share that experience and how you got through it? >> Yeah, the way I look at it is, again, whenever I go to an organization, I ask the question, hey, how fast you would like transform. And, based on the agreements from the leadership and the vision that we want to take place, I take decisions. And I collaborate in a specific way now, in the case of COVID, for example, right. It forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it. When you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay debating points or making repetitive business cases until people connect with the decision because you understand, and you are seeing that, "hey, the CEO is making a one two year, efficiency goal. "The only way for us to really do more with less "is for us to continue this path. "We cannot just stay with the status quo. "We need to find a way to accelerate the transformation." That's the way I see it. >> How about you Tom, we were talking earlier with Sudheesh and Cindi, about that bungee jumping moment. What could you share? >> Yeah, I think you hit upon it, right now, the pace of change with the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team is that you need to be, you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right, expand and support that the ever-changing needs in the marketplace and industry our customers today, and that pace of change that's happening, right. And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, as you look at what, how you're operating today in your current business model, right. Things are only going to get faster. So you have to plan into a line into drive the agile transformation so that you can scale even faster in the future. So as part of that, that's what we're putting in place here, right, is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. They're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well, first off, Tom just freaked me out. What do you mean? This is the slowest ever even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's, you know what you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's the dish going to go bungee jumping. >> Guys fantastic discussion, really. Thanks again to all the panelists and the guests. It was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in the Cube program. Recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just, as I said before, lip service. Sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done, right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay. Let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you. Thank you, Dave. Thank you, the Cube team, and thank goes to all of our customers and partners who joined us and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I will simply put it. She said it really well. That is be brave and drive. Don't go for a drive along. That is such an important point. Oftentimes, you know that I think that you have to do to make the positive change that you want to see happen but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I've picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voices are heard, and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the quorum. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in. And they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to topspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is please go to thoughtspot.com/beyond our global user conference is happening in this December. We would love to have you join us. It's again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we've have been working to release something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at the Thought Spot Beyond. Thank you. Thank you so much.

>>Yeah, it's the queue covering the virtual vertical Big Data Conference 2020 Brought to You by vertical. >>Welcome back, everybody. My name is Dave Vellante, and you're watching the Cube's coverage of the verdict of Virtual Big Data conference. The Cube has been at every BTC, and it's our pleasure in these difficult times to be covering BBC as a virtual event. This digital program really excited to have Joy King joining us. Joy is the vice president of product and go to market strategy in particular. And if that weren't enough, he also runs marketing and education curve for him. So, Joe, you're a multi tool players. You've got the technical side and the marketing gene, So welcome to the Cube. You're always a great guest. Love to have you on. >>Thank you so much, David. The pleasure, it really is. >>So I want to get in. You know, we'll have some time. We've been talking about the conference and the virtual event, but I really want to dig in to the product stuff. It's a big day for you guys. You announced 10.0. But before we get into the announcements, step back a little bit you know, you guys are riding the waves. I've said to ah, number of our guests that that brick has always been good. It riding the wave not only the initial MPP, but you you embraced, embraced HD fs. You embrace data science and analytics and in the cloud. So one of the trends that you see the big waves that you're writing >>Well, you're absolutely right, Dave. I mean, what what I think is most interesting and important is because verdict is, at its core a true engineering culture founded by, well, a pretty famous guy, right, Dr Stone Breaker, who embedded that very technical vertical engineering culture. It means that we don't pretend to know everything that's coming, but we are committed to embracing the tech. An ology trends, the innovations, things like that. We don't pretend to know it all. We just do it all. So right now, I think I see three big imminent trends that we are addressing. And matters had we have been for a while, but that are particularly relevant right now. The first is a combination of, I guess, a disappointment in what Hadoop was able to deliver. I always feel a little guilty because she's a very reasonably capable elephant. She was designed to be HD fs highly distributed file store, but she cant be an entire zoo, so there's a lot of disappointment in the market, but a lot of data. In HD FM, you combine that with some of the well, not some the explosion of cloud object storage. You're talking about even more data, but even more data silos. So data growth and and data silos is Trend one. Then what I would say Trend, too, is the cloud Reality Cloud brings so many events. There are so many opportunities that public cloud computing delivers. But I think we've learned enough now to know that there's also some reality. The cloud providers themselves. Dave. Don't talk about it well, because not, is it more agile? Can you do things without having to manage your own data center? Of course you can. That the reality is it's a little more pricey than we expected. There are some security and privacy concerns. There's some workloads that can go to the cloud, so hybrid and also multi cloud deployments are the next trend that are mandatory. And then maybe the one that is the most exciting in terms of changing the world we could use. A little change right now is operationalize in machine learning. There's so much potential in the technology, but it's somehow has been stuck for the most part in science projects and data science lab, and the time is now to operationalize it. Those are the three big trends that vertical is focusing on right now. >>That's great. I wonder if I could ask you a couple questions about that. I mean, I like you have a soft spot in my heart for the and the thing about the Hadoop that that was, I think, profound was it got people thinking about, you know, bringing compute to the data and leaving data in place, and it really got people thinking about data driven cultures. It didn't solve all the problems, but it collected a lot of data that we can now take your third trend and apply machine intelligence on top of that data. And then the cloud is really the ability to scale, and it gives you that agility and that it's not really that cloud experience. It's not not just the cloud itself, it's bringing the cloud experience to wherever the data lives. And I think that's what I'm hearing from you. Those are the three big super powers of innovation today. >>That's exactly right. So, you know, I have to say I think we all know that Data Analytics machine learning none of that delivers real value unless the volume of data is there to be able to truly predict and influence the future. So the last 7 to 10 years has been correctly about collecting the data, getting the data into a common location, and H DFS was well designed for that. But we live in a capitalist world, and some companies stepped in and tried to make HD Fs and the broader Hadoop ecosystem be the single solution to big data. It's not true. So now that the key is, how do we take advantage of all of that data? And now that's exactly what verdict is focusing on. So as you know, we began our journey with vertical back in the day in 2007 with our first release, and we saw the growth of the dupe. So we announced many years ago verdict a sequel on that. The idea to be able to deploy vertical on Hadoop nodes and query the data in Hadoop. We wanted to help. Now with Verdict A 10. We are also introducing vertical in eon mode, and we can talk more about that. But Verdict and Ian Mode for HDs, This is a way to apply it and see sequel database management platform to H DFS infrastructure and data in each DFS file storage. And that is a great way to leverage the investment that so many companies have made in HD Fs. And I think it's fair to the elephant to treat >>her well. Okay, let's get into the hard news and auto. Um, she's got, but you got a mature stack, but one of the highlights of append auto. And then we can drill into some of the technologies >>Absolutely so in well in 2018 vertical announced vertical in Deon mode is the separation of compute from storage. Now this is a great example of vertical embracing innovation. Vertical was designed for on premises, data centers and bare metal servers, tightly coupled storage de l three eighties from Hewlett Packard Enterprises, Dell, etcetera. But we saw that cloud computing was changing fundamentally data center architectures, and it made sense to separate compute from storage. So you add compute when you need compute. You add storage when you need storage. That's exactly what the cloud's introduced, but it was only available on the club. So first thing we did was architect vertical and EON mode, which is not a new product. Eight. This is really important. It's a deployment option. And in 2018 our customers had the opportunity to deploy their vertical licenses in EON mode on AWS in September of 2019. We then broke an important record. We brought cloud architecture down to earth and we announced vertical in eon mode so vertical with communal or shared storage, leveraging pure storage flash blade that gave us all the advantages of separating compute from storage. All of the workload, isolation, the scale up scale down the ability to manage clusters. And we did that with on Premise Data Center. And now, with vertical 10 we are announcing verdict in eon mode on HD fs and vertically on mode on Google Cloud. So what we've got here, in summary, is vertical Andy on mode, multi cloud and multiple on premise data that storage, and that gives us the opportunity to help our customers both with the hybrid and multi cloud strategies they have and unifying their data silos. But America 10 goes farther. >>Well, let me stop you there, because I just wanna I want to mention So we talked to Joe Gonzalez and past Mutual, who essentially, he was brought in. And one of this task was the lead into eon mode. Why? Because I'm asking. You still had three separate data silos and they wanted to bring those together. They're investing heavily in technology. Joe is an expert, though that really put data at their core and beyond Mode was a key part of that because they're using S three and s o. So that was Ah, very important step for those guys carry on. What else do we need to know about? >>So one of the reasons, for example, that Mass Mutual is so excited about John Mode is because of the operational advantages. You think about exactly what Joe told you about multiple clusters serving must multiple use cases and maybe multiple divisions. And look, let's be clear. Marketing doesn't always get along with finance and finance doesn't necessarily get along with up, and I t is often caught the middle. Erica and Dion mode allows workload, isolation, meaning allocating the compute resource is that different use cases need without allowing them to interfere with other use cases and allowing everybody to access the data. So it's a great way to bring the corporate world together but still protect them from each other. And that's one of the things that Mass Mutual is going to benefit from, as well, so many of >>our other customers I also want to mention. So when I saw you, ah, last last year at the Pure Storage Accelerate conference just today we are the only company that separates you from storage that that runs on Prem and in the cloud. And I was like I had to think about it. I've researched. I still can't find anybody anybody else who doesn't know. I want to mention you beat actually a number of the cloud players with that capability. So good job and I think is a differentiator, assuming that you're giving me that cloud experience and the licensing and the pricing capability. So I want to talk about that a little >>bit. Well, you're absolutely right. So let's be clear. There is no question that the public cloud public clouds introduced the separation of compute storage and these advantages that they do not have the ability or the interest to replicate that on premise for vertical. We were born to be software only. We make no money on underlying infrastructure. We don't charge as a package for the hardware underneath, so we are totally motivated to be independent of that and also to continuously optimize the software to be as efficient as possible. And we do the exact same thing to your question about life. Cloud providers charge for note indignance. That's how they charge for their underlying infrastructure. Well, in some cases, if you're being, if you're talking about a use case where you have a whole lot of data, but you don't necessarily have a lot of compute for that workload, it may make sense to pay her note. Then it's unlimited data. But what if you have a huge compute need on a relatively small data set that's not so good? Vertical offers per node and four terabyte for our customers, depending on their use case, we also offer perpetual licenses for customers who want capital. But we also offer subscription for companies that they Nope, I have to have opt in. And while this can certainly cause some complexity for our field organization, we know that it's all about choice, that everybody in today's world wants it personalized just for me. And that's exactly what we're doing with our pricing in life. >>So just to clarify, you're saying I can pay by the drink if I want to. You're not going to force me necessarily into a term or Aiken choose to have, you know, more predictable pricing. Is that, Is that correct? >>Well, so it's partially correct. The first verdict, a subscription licensing is a fixed amount for the period of the subscription. We do that so many of our customers cannot, and I'm one of them, by the way, cannot tell finance what the budgets forecast is going to be for the quarter after I spent you say what it's gonna be before, So our subscription facing is a fixed amount for a period of time. However, we do respect the fact that some companies do want usage based pricing. So on AWS, you can use verdict up by the hour and you pay by the hour. We are about to launch the very same thing on Google Cloud. So for us, it's about what do you need? And we make it happen natively directly with us or through AWS and Google Cloud. >>So I want to send so the the fixed isn't some floor. And then if you want a surge above that, you can allow usage pricing. If you're on the cloud, correct. >>Well, you actually license your cluster vertical by the hour on AWS and you run your cluster there. Or you can buy a license from vertical or a fixed capacity or a fixed number of nodes and deploy it on the cloud. And then, if you want to add more nodes or add more capacity, you can. It's not usage based for the license that you bring to the cloud. But if you purchase through the cloud provider, it is usage. >>Yeah, okay. And you guys are in the marketplace. Is that right? So, again, if I want up X, I can do that. I can choose to do that. >>That's awesome. Next usage through the AWS marketplace or yeah, directly from vertical >>because every small business who then goes to a salesforce management system knows this. Okay, great. I can pay by the month. Well, yeah, Well, not really. Here's our three year term in it, right? And it's very frustrating. >>Well, and even in the public cloud you can pay for by the hour by the minute or whatever, but it becomes pretty obvious that you're better off if you have reserved instance types or committed amounts in that by vertical offers subscription. That says, Hey, you want to have 100 terabytes for the next year? Here's what it will cost you. We do interval billing. You want to do monthly orderly bi annual will do that. But we won't charge you for usage that you didn't even know you were using until after you get the bill. And frankly, that's something my finance team does not like. >>Yeah, I think you know, I know this is kind of a wonky discussion, but so many people gloss over the licensing and the pricing, and I think my take away here is Optionality. You know, pricing your way of That's great. Thank you for that clarification. Okay, so you got Google Cloud? I want to talk about storage. Optionality. If I found him up, I got history. I got I'm presuming Google now of you you're pure >>is an s three compatible storage yet So your story >>Google object store >>like Google object store Amazon s three object store HD fs pure storage flash blade, which is an object store on prim. And we are continuing on this theft because ultimately we know that our customers need the option of having next generation data center architecture, which is sort of shared or communal storage. So all the data is in one place. Workloads can be managed independently on that data, and that's exactly what we're doing. But what we already have in two public clouds and to on premise deployment options today. And as you said, I did challenge you back when we saw each other at the conference. Today, vertical is the only analytic data warehouse platform that offers that option on premise and in multiple public clouds. >>Okay, let's talk about the ah, go back through the innovation cocktail. I'll call it So it's It's the data applying machine intelligence to that data. And we've talked about scaling at Cloud and some of the other advantages of Let's Talk About the Machine Intelligence, the machine learning piece of it. What's your story there? Give us any updates on your embracing of tooling and and the like. >>Well, quite a few years ago, we began building some in database native in database machine learning algorithms into vertical, and the reason we did that was we knew that the architecture of MPP Columbia execution would dramatically improve performance. We also knew that a lot of people speak sequel, but at the time, not so many people spoke R or even Python. And so what if we could give act us to machine learning in the database via sequel and deliver that kind of performance? So that's the journey we started out. And then we realized that actually, machine learning is a lot more as everybody knows and just algorithms. So we then built in the full end to end machine learning functions from data preparation to model training, model scoring and evaluation all the way through to fold the point and all of this again sequel accessible. You speak sequel. You speak to the data and the other advantage of this approach was we realized that accuracy was compromised if you down sample. If you moved a portion of the data from a database to a specialty machine learning platform, you you were challenged by accuracy and also what the industry is calling replica ability. And that means if a model makes a decision like, let's say, credit scoring and that decision isn't anyway challenged, well, you have to be able to replicate it to prove that you made the decision correctly. And there was a bit of, ah, you know, blow up in the media not too long ago about a credit scoring decision that appeared to be gender bias. But unfortunately, because the model could not be replicated, there was no way to this Prove that, and that was not a good thing. So all of this is built in a vertical, and with vertical 10. We've taken the next step, just like with with Hadoop. We know that innovation happens within vertical, but also outside of vertical. We saw that data scientists really love their preferred language. Like python, they love their tools and platforms like tensor flow with vertical 10. We now integrate even more with python, which we have for a while, but we also integrate with tensorflow integration and PM ML. What does that mean? It means that if you build and train a model external to vertical, using the machine learning platform that you like, you can import that model into a vertical and run it on the full end to end process. But run it on all the data. No more accuracy challenges MPP Kilometer execution. So it's blazing fast. And if somebody wants to know why a model made a decision, you can replicate that model, and you can explain why those are very powerful. And it's also another cultural unification. Dave. It unifies the business analyst community who speak sequel with the data scientist community who love their tools like Tensorflow and Python. >>Well, I think joy. That's important because so much of machine intelligence and ai there's a black box problem. You can't replicate the model. Then you do run into a potential gender bias. In the example that you're talking about there in their many you know, let's say an individual is very wealthy. He goes for a mortgage and his wife goes for some credit she gets rejected. He gets accepted this to say it's the same household, but the bias in the model that may be gender bias that could be race bias. And so being able to replicate that in and open up and make the the machine intelligence transparent is very, very important, >>It really is. And that replica ability as well as accuracy. It's critical because if you're down sampling and you're running models on different sets of data, things can get confusing. And yet you don't really have a choice. Because if you're talking about petabytes of data and you need to export that data to a machine learning platform and then try to put it back and get the next at the next day, you're looking at way too much time doing it in the database or training the model and then importing it into the database for production. That's what vertical allows, and our customers are. So it right they reopens. Of course, you know, they are the ones that are sort of the Trailblazers they've always been, and ah, this is the next step. In blazing the ML >>thrill joint customers want analytics. They want functional analytics full function. Analytics. What are they pushing you for now? What are you delivering? What's your thought on that? >>Well, I would say the number one thing that our customers are demanding right now is deployment. Flexibility. What? What the what the CEO or the CFO mandated six months ago? Now shout Whatever that thou shalt is is different. And they would, I tell them is it is impossible. No, what you're going to be commanded to do or what options you might have in the future. The key is not having to choose, and they are very, very committed to that. We have a large telco customer who is multi cloud as their commit. Why multi cloud? Well, because they see innovation available in different public clouds. They want to take advantage of all of them. They also, admittedly, the that there's the risk of lock it right. Like any vendor, they don't want that either, so they want multi cloud. We have other customers who say we have some workloads that make sense for the cloud and some that we absolutely cannot in the cloud. But we want a unified analytics strategy, so they are adamant in focusing on deployment flexibility. That's what I'd say is 1st 2nd I would say that the interest in operationalize in machine learning but not necessarily forcing the analytics team to hammer the data science team about which tools or the best tools. That's the probably number two. And then I'd say Number three. And it's because when you look at companies like Uber or the Trade Desk or A T and T or Cerner performance at scale, when they say milliseconds, they think that flow. When they say petabytes, they're like, Yeah, that was yesterday. So performance at scale good enough for vertical is never good enough. And it's why we're constantly building at the core the next generation execution engine, database designer, optimization engine, all that stuff >>I wanna also ask you. When I first started following vertical, we covered the cube covering the BBC. One of things I noticed was in talking to customers and people in the community is that you have a community edition, uh, free addition, and it's not neutered ais that have you maintain that that ethos, you know, through the transitions into into micro focus. And can you talk about that a little bit >>absolutely vertical community edition is vertical. It's all of the verdict of functionality geospatial time series, pattern matching, machine learning, all of the verdict, vertical neon mode, vertical and enterprise mode. All vertical is the community edition. The only limitation is one terabyte of data and three notes, and it's free now. If you want commercial support, where you can file a support ticket and and things like that, you do have to buy the life. But it's free, and we people say, Well, free for how long? Like our field? I've asked that and I say forever and what he said, What do you mean forever? Because we want people to use vertical for use cases that are small. They want to learn that they want to try, and we see no reason to limit that. And what we look for is when they're ready to grow when they need the next set of data that goes beyond a terabyte or they need more compute than three notes, then we're here for them, and it also brings up an important thing that I should remind you or tell you about Davis. You haven't heard it, and that's about the Vertical Academy Academy that vertical dot com well, what is that? That is, well, self paced on demand as well as vertical essential certification. Training and certification means you have seven days with your hands on a vertical cluster hosted in the cloud to go through all the certification. And guess what? All of that is free. Why why would you give it for free? Because for us empowering the market, giving the market the expert East, the learning they need to take advantage of vertical, just like with Community Edition is fundamental to our mission because we see the advantage that vertical can bring. And we want to make it possible for every company all around the world that take advantage >>of it. I love that ethos of vertical. I mean, obviously great product. But it's not just the product. It's the business practices and really progressive progressive pricing and embracing of all these trends and not running away from the waves but really leaning in joy. Thanks so much. Great interview really appreciate it. And, ah, I wished we could have been faced face in Boston, but I think it's prudent thing to do, >>I promise you, Dave we will, because the verdict of BTC and 2021 is already booked. So I will see you there. >>Haas enjoyed King. Thanks so much for coming on the Cube. And thank you for watching. Remember, the Cube is running this program in conjunction with the virtual vertical BDC goto vertical dot com slash BBC 2020 for all the coverage and keep it right there. This is Dave Vellante with the Cube. We'll be right back. >>Yeah, >>yeah, yeah.

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS reInvent 2019. Brought to you by Amazon Web Services and Intel along with it's Ecosystem partners. >> Well, welcome back, everyone theCUBE's live coverage in Las Vegas for AWS reInvent. It's theCUBE's 10th year of operations, it's our seventh AWS reInvent and every year, it gets better and better and every year, we've had theCUBE at reInvent, Jerry Chen has been on as a guest. He's a VIP, Jerry Chen, now a general partner at Greylock Tier One, one of the leading global Venture capitals at Silicon Valley. Jerry, you've been on the journey with us the whole time. >> I guess I'm your good luck charm. >> (laughs) Well, keep it going. Keep on changing the game. So, thanks for coming on. >> Jerry: Thanks for having me. >> So, now that you're a seasoned partner now at Greylock. You got a lot of investments under your belt. How's it going? >> It's great, I mean look, every single year, I look around the landscape thinking, "What else could be coming? "What if we surprise this year?" What's the new trends? What both macro-trends, also company trends, like, who's going to buy who, who's going to go public? Every year, it just gets busier and busier and bigger and bigger. >> All these new categories are emerging with this new architecture. I call it Cloud 2.0, maybe next gen Cloud, whatever you want to call it, it's clear visibility now into the fact that DevOps is working, Cloud operations, large scale operations with Cloud is certainly a great value proposition. You're seeing now multiple databases, pick the tool, I think Jassy got that right in his keynote, I believe that, but now the data equation comes over the top. So, you got DevOps infrastructure as code, you got data now looking like it's going to go down that same path of data as code where developers don't have to deal with all the different nuances of how data's stored, how it's handled, where is it, warm or cold or at glacier. So, developers still don't have that yet today. Seems to be an area of Amazon. What's your take on all this? >> I think you saw, so what drove DevOps? Speed, right? It's basically how developers shows you operations, merging of two groups. So, we're seeing the same trend DataOps, right? How data engineers and data scientists can now have the same speeds developers had for the past 10 years, DataOps. So, A, what does that mean? Give me the menu of what I want like, Goldilocks, too big, too small, just right. Too hot, too cold, just right. Like, give me the storage tier, the data tier, the size I want, the temperature I want and the speed I want. So, you're seeing DataOps give the same kind of Goldilocks treatment as developers. >> And on terms of like Cloud evolution again, you've seen the movie from the beginning at VM where now through Amazon, seventh year. What jumps out at you, what do you look at as squinting through the trend lines and the fashion of the features, it still seems to be the same old game, compute memory storage and software. >> Well I mean, compute memory storage, there's an atomic building blocks of a compute, right? So, regardless of services these high level frameworks, deep down, you still have compute networking and storage. So, that's the building blocks but I think we're seeing 10th year of reInvent this kind of, it's not one size fits all but this really big fat long tail, small instances, micro-instances, server lists, big instances for like jumbo VMs, bare metal, right? So, you're seeing not one architecture but folks can kind of pick and choose buy compute by the drip, the drop or buy compute by the whole VM or whole server full. >> And a lot of people are like, the builders love that. Amazon owns the builder market. I mean, if anyone who's doing a startup, they pretty much start on Amazon. It's the most robust, you pick your tools, you build, but Steve Malaney was just on before us says, "Enterprise don't want power tools, "they're going to cut their hand off." (laughs) Right so, Microsoft's been winning with this approach of consumable Cloud and it's a nice card to play because they're not yet there with capabilities with Amazon, so it's a good call, they got an Enterprise sales force. Microsoft playing a different game than AWS because they have to. >> Sure I mean, what's football now, you have a running game, you need a passing game, right? So, if you can't beat them with the running game, you go with a passing game and so, Amazon has kind of like the fundamental building blocks or power tools for the builders. There's a large segment of population out there that don't want that level of building blocks but they want us a little bit more prescriptive. Microsoft's been around Enterprise for many many years, they understand prescriptive tools and architectures. So, you're going to become a little bit more prefab, if you will. Here's how you can actually construct the right application, ML apps, AI apps, et cetera. Let me give you the building blocks at a higher level abstraction. >> So, I want to get your take on value creations. >> Jerry: Sure. >> So, if it's still early (mumbles), it's took a lot more growth, you start to see Jassy even admit that in his keynotes that he said quote, "There are two types "of developers and customers. "People want the building blocks "or people who want solutions." Or prefab or some sort of more consumable. >> More prescriptive, yeah. >> So, I think Amazon's going to start going that way but that being said, there's still opportunities for startups. You're an investor, you invest in startups. Where do you see opportunities? If you're looking at the startup landscape, what is the playbook? How should you advise startups? Because ya know, have the best team or whatever but you look at Amazon, it's like, okay, they got large scale. >> Jerry: Yeah. >> I'm going to be a little nervous. Are they going to eat my lunch? Do I take advantage of them? Do I draft off them? There are wide spaces as vertical market's exploding that are available. What's your view on how startups should attack the wealth creation opportunity value creation? >> There, I mean, Amazon's creating a new market, right? So, you look at their list of many services. There's just like 175 services out there, which is basically too many for any one company to win every single service. So, but you look at that menu of services, each one of those services themselves can be a startup or a collection of services can be a startup. So, I look at that as a roadmap for opportunity of companies can actually go in and create value around AI, around data, around security, around observability because Amazon's not going to naturally win all of those markets. What they do have is distribution, right? They have a lot of developer mind share. So, if you're a startup, you play one or three themes. So like, one is how do I pick one area and go deep for IP, right? Like, cheaper, better, faster, own some IP and though, they're going to execute better and that's doable over and over again in different markets. Number two is, we talked about this before, there's not going to be a one Cloud wins all, Amazon's clearly in the lead, they have won most of the Cloud, so far, but it'll be a multi-Cloud world, it'll be On Premise world. So, how do I play a multi-Cloud world, is another angle, so, go deep in IP, go multi-Cloud. Number three is this end to end solution, kind of prescriptive. Amazon can get you 80% of the way there, 70% of the way there but if you're like, an AI developer, you're a CMO, you're a marketing developer, you kind of want this end to end solution. So, how can I put together a full suite of tools from beginning to end that can give me a product that's a better experience. So, either I have something that's a deeper IP play a seam between multiple Clouds or give it end to end solutions around a problem and solve that one problem for our customer. >> And in most cases, the underlay is Amazon or Azure. >> Or Google or Alley Cloud or On Premises. Not going to wait any time soon, right? And so, how do I create a single fabric, if you will that looks similar? >> I want to riff with you in real time here on theCUBE around data. So, data scale is obviously a big discussion that's starting to happen now, data tsunami, we've heard that for years. So, there's two scale benefits, horizontal scale with data and then vertical specialism, vertical scale or ya know, using AI machine learning in apps, having data, so, how do you view that? What's your reaction to the notion of creating the horizontal scale value and vertical specialism value? >> Both are a great place for startups, right? They're not mutually exclusive but I think if you go horizontal, the amount of data being created by your applications, your infrastructure, your sensors, time stories data, ridiculously large amount, right? And that's not going away any time soon. I recently did investment in ChronoSphere, 'cause you guys covered over at CUBEcon a few weeks ago, that's talking about metrics and observability data, time stories data. So, they're going to handle that horizontal amount of data, petabytes and petabytes, how can we quarry this quickly, deeply with a lot of insight? That's one play, right? Cheaper, better, faster at scale. The next play, like you said, is vertical. It's how do I own data or slice the data with more contacts than I know I was going to have? We talked about the virtual cycle of data, right? Just the system of intelligence, as well. If I own a set of data, be it healthcare, government or self-driving car data, that no one else has, I can build a solution end to end and go deep and so either pick a lane or pick a geography, you can go either way. It's hard to do both, though. >> It's hard for startup. >> For a startup. >> Any big company. >> Very few companies can do two things well, startups especially, succeed by doing one thing very well. >> I think my observation is that I think looking at Amazon, is that they want the horizontal and they're leaving offers on the table for our startups, the vertical. >> Yeah, if you look at their strategy, the lower level Amazon gets, the more open-sourced, the more ubiquitous you try to be for containers, server lists, networking, S3, basic sub straits, so, horizontal horizontal, low price. As you get higher up from like, deep mind like, AI technologies, perception, prediction, they're getting a little bit more specialized, right? As you see these solutions around retail, healthcare, voice, so, the higher up in the stack, they can build more narrow solutions because like any startup of any product, you need the right wedge. What's the right wedge in the customers? At the base level of developers, building blocks, ubiquitous. For solutions marketing, healthcare, financial services, retail, how do I find a fine point wedge? >> So, the old Venture business was all enamored with consumers over the years and then, maybe four years ago, Enterprise got hot. We were lowly Enterprise guys where no one-- >> Enterprise has been hot forever in my mind, John but maybe-- >> Well, first of all, we've been hot on Enterprise, we love Enterprise but then all of a sudden, it just seemed like, oh my God, people had an awakening like, and there's real value to be had. The IT spend has been trillions and the stats are roughly 20 or so percent, yet to move to the Cloud or this new next gen architecture that you're investing companies in. So, a big market... that's an investment thesis. So, a huge enterprise market, Steve Malaney of Aviation called it a thousand foot wave. So, there's going to be a massive enterprise money... big bag of money on the table. (laughs) A lot of re-transformations, lot of reborn on the Cloud, lot of action. What's your take on that? Do you see it the same way because look how they're getting in big time, Goldman Sachs on stage here. It's a lot of cash. How do you think it's going to be deployed and who's going to be fighting for it? >> Well, I think, we talked about this in the past. When you look to make an investment, as a startup founder or as a VC, you want to pick a wave bigger than you, bigger than your competitors. Right so, on the consumer side, ya know, the classic example, your Instagram fighting Facebook and photo sharing, you pick the mobile first wave, iPhone wave, right, the first mobile native photo sharing. If you're fighting Enterprise infrastructure, you pick the Cloud data wave, right? You pick the big data wave, you pick the AI waves. So, first as a founder startup, I'm looking for these macro-waves that I see not going away any time soon. So, moving from BaaS data to streaming real time data. That's a wave that's happening, that's inevitable. Dollars are floating from slower BaaS data bases to streaming real time analytics. So, Rocksett, one of the investors we talked about, they're riding that wave from going BaaS to real time, how to do analytics and sequel on real time data. Likewise, time servers, you're going from like, ya know, BaaS data, slow data to massive amounts of time storage data, Chronosphere, playing that wave. So, I think you have to look for these macro-waves of Cloud, which anyone knows but then, you pick these small wavelettes, if that's a word, like a wavelettes or a smaller wave within a wave that says, "Okay, I'm going to "pick this one trend." Ride it as a startup, ride it as an investor and because that's going to be more powerful than my competitors. >> And then, get inside the wave or inside the tornado, whatever metaphor. >> We're going to torch the metaphors but yeah, ride that wave. >> All right, Jerry, great to have you on. Seven years of CUBE action. Great to have you on, congratulations, you're VIP, you've been with us the whole time. >> Congratulations to you, theCUBE, the entire staff here. It's amazing to watch your business grow in the past seven years, as well. >> And we soft launch our CUBE 365, search it, it's on Amazon's marketplace. >> Jerry: Amazing. >> SaaS, our first SaaS offering. >> I love it, I mean-- >> John: No Venture funding. (laughs) Ya know, we're going to be out there. Ya know, maybe let you in on the deal. >> But now, like you broadcast the deal to the rest of the market. >> (laughs) Jerry, great to have you on. Again, great to watch your career at Greylock. Always happy to have ya on, great commentary, awesome time, Jerry Chen, Venture partner, general partner of Greylock. So keep coverage, breaking down the commentary, extracting the signal from the noise here at reInvent 2019, I'm John Furrier, back with more after this short break. (energetic electronic music)

>> we'LL run. Welcome to this special. Keep conversation. We're here in Mountain View, California. The pure storage headquarters here in Castro Tree, one of the many buildings they have here as they continue to grow as a public company. Our next guest is Kicks Vice President of strategy Employee number six Pure. Great to see you. Thanks for spending time. Thanks for having me. So cloud is the big wave that's coming around the future itself here. Now, people really impacted by it operationally coming to the reality that they got to actually use the cloud of benefits for many, many multiple benefits. But you guys have major bones in storage, flash arrays continuing to take take territory. So as you guys do that, what's the cloud play? How to customers who were using pure. And we've heard some good testimonials Yet a lot of happy customers. We've seen great performance, Easy to get in reliability performances. They're in the storage side on premise. Right? Okay. Now Operations says, Hey, I build faster. Cloud is certainly path there. Certainly. Good one. Your thoughts on strategy for the cloud? >> Absolutely. So look for about ten years into the journey here, a pure. And a lot of what we did in the first ten years was helped bring flash onto the scene. Um, and you know what a vision when we started the company of the All Flash Data Center and I'd like to first of all, remind people that look, we ain't there yet. If you look at the analyst numbers, about a third of the storage sold this year will be flashed two thirds disk. So we still have a long way to go in the old flash data center and a lot of work to do there. But of course, increasingly customers are wanting to move, were close to the cloud. And I think the last couple of years have almost seen a pendulum swing a little bit more back to reality. You know, when I met with CEOs to three years ago, you often heard we're going all cloud. We're going to cloud first and, you know, now there a few years into it. And they've realized that that cloud is a very powerful weapon in their in their arsenal for agility, for flexibility. But it's not necessarily cheaper on DH. So I think the swing back to really believe in in hybrid is the model of the day, and I think that I think people have realised in that journey is that the club early works best when you build a nap for the cloud natively. But what if you have a bunch of on prime maps that are in traditional architecture? How do I get in the cloud? And so one of the things we really focused on is how we can help customers take their mission critical applications and move them seamlessly to the cloud without re architecture. Because for most customers, that's really going to start. I mean, they could build some new stuff in the cloud, but the bulk of their business, if they want to move substantial portions of the cloud, they've got to figure out how to move what they've got. And we think we really had value in that. >> And the economics of the cloud is undeniable. People who are born in the cloud will testify that certainly as you guys have been successful on premise with the cloud, how do you make those economics, he seem, was as well as the operations. This seems to be the number one goal when you talk about how important that is and how hard it is, because it sounds easy just to say it. But it's actually really difficult to have seamless operations on Prime because, you know, Amazon, Google, Microsoft, they all got computing storage in the cloud and you got story. John Premise. This equation is a really important one to figure out what the importance and how hard is it to some of things that you guys are doing to solve that. >> Yeah, So I heard two things that question one around costs and one around operations on. You know, the first thing I think that has been nice to see over the last couple of years as people realizing that both the cloud and on from our cost effective in different ways, and I think a little bit about the way that I think about owning a car. Owning a car is relatively cost effective for me, and there's times and taken uber is relatively cost effective. I think they're both cheap when you look it on one metric, though, about what I pay per mile, it's way more expensive to own a car to take a number look about acquisition cost. It's way more expensive. Car, right? And so I think both of them provide value of my lives in the way that hybrid does today. But once you start to use both than the operational, part of your question comes in. How do I think about these two different worlds? And I think we believe that that storage is actually one of the areas where these two worlds are totally different on dso a couple things we've done to find a bridge together. First off on the cost side, one of the things we realised was that people that are going to run large amounts of on prime infrastructure increasingly want to do it in the cloud model. And so we introduced a new pricing model that we call the S to evergreen storage service, which will essentially allows you to subscribe to our storage even in your own data center. And so you can have an optics experience in the cloud. You gotta monoprix experience on Prem and when you buy and yes, to those licenses are transferrable so you can start on Prem, Move your stories to the cloud with pure go back and forth tons of flexibility. From the operational point of view, I think we're trying to get to the same experience as well such that you have a single storage experience for a manageability and automation point of view across both. And I think that last word of automation is key, because if you look at people who are really invested in cloud, it's all about automation. In one of the nice things I think that's made pure, so successful in on Prime Claude environments is this combination of simplicity and automation. You can't we automate what isn't simple to begin with on DH. So we started with simplicity. But as we've added rich FBI's, we're really seeing that become the dominant way that people administrated our storage. And so as we've gone to the cloud because it's the same software on both sides, literally the same integrations, the same AP calls everything works transparently across both places. >> That's a great point. We've been reporting on silicon ng on the Cube for years. Automation grave. You have to couple of manual taxes and automated, but the values and shifting and you guys in the storage business you know this data's data data is very valuable. You mentioned the car and Alice just take uber uber is an app. It's got Web services in the back end. So when you start thinking about cloud, you think you hear ap eyes You hear micro services as more and more applications going to need the data, they're going to need to have that in real time, some cases not near real time, either real time. And they're gonna need to have at the right time. So the role of data becomes important, which makes storage more important. So you automate the story, Okay, Take away that mundane tasks. Now the value shifts to making sure data is being presented properly. This is the renaissance of application development. Right now we're seeing this. How do you guys attack that market? How do you guys enable that? Mark, how do you satisfy that market? Because this is where the AP eyes could be connectors. This is where the data can be valuable. Whether it's analytic, score an app like uber. That's just, you know, slinging AP eyes together for a service that is now going to go public. Yeah, >> I think the mindset around data is one of the biggest differences between the old world in the New World. And if you think about the old world of applications. Yeah, monolithic databases that kind of privately owned their own data stores and the whole name of the game was delivering that as reliably as possible, kind of locking it down, making it super reliable. If you look at the idea of the Web scale application, the idea of an application is broken up into lots of little micro services, and those maker services somehow have to work together on data. And so what does it mean that the data level, it's not this kind of monolithic database anymore? It's got to be this open shared environment and, you know, as a result, if you look in the Web in Amazon's case, for example, the vast majority of applications are written on history object storage that's inherently shared. And so I think one of the bigger interesting challenges right now is how you get data constructs to actually go both ways. You know, if you want to take a non prime map that kind of is built around the database, you've got to figure out a way to move it to the cloud and ronit reliably on the flipside of the coin. If you want to build on Web skill tools and then be hybrid and run some of those things on Prem, well, you need an object store on prim and most people don't have that. And so you know, this whole kind of compatibility to make hybrid reality. It's forcing people on both sides of the weir to understand the other architecture er, and make sure they're compatible both ways >> and throw more complex into that equation. Is that skills, gaps? I know I know that cloud needed. But now men on premise so different skill got you guys had an announcement that's come out. So I want to ask you about your product announcement and your acquisitions. Go back to past six months. What's the most notable product announcements inequities that you guys have done? And what does that mean for pure and your customers? Yeah, >> absolutely. So I'll just kind of walk through it, So the first thing we announced was our new set of Cloud data services, and this was in essence, bringing our core software that runs on our purity. Operating environment right into the cloud. And so we call that cloud block store. And again, this is a lot of what I've been talking about, how you can take a tier one block storage application on Prem and seamlessly move it to the cloud along that same timeline. We also introduce something called P S O, which is the pure service orchestrator. And this was a tool set that we built specifically for the containers world for communities so that basically, in a container environment, our storage could be completely automated. It's been really fun watching customers use and just see how different that storage is in a container environment. You know, we look at our call home data with an R P. R. One application, and in our traditional on prime environment, the average array has about one administrative tasks per day. Make a volume. Delete something, Whatever. If you look in a container environment, that's tens of thousands, and so it's just a much more fluid environment, which there's no way a storage at Ben's going to do something ten thousand times a day they've got on, >> and that's where automation comes in. But what does that mean? the continuous station. That means the clients are using containers to be more flexible, they deploying more. What's the What's the inside of this container trend? >> You know, I think ultimately it's just a farm or fluid environment. It's totally automated, Andi. It's built on a world of share data. And so you need a shared, reliable data service that can power these containers, Um and then, you know, back to original question about about kind of product expansion. The next thing that we haven't announced last year was acquisition of a company called Story Juice, and we've subsequently brought out as a product that we call Object Engine. And this is all about a new type of data moving into the club, which is backup data and facilitating in this backup process. You know, in the past, people moved from tape back up to the space back up and, you know, we saw kind of two new inflection points here. Number one the opportunity Use flash on Prem. So the people have really fast recoveries on prep because in most environments now, space recovery just aren't fast enough, and then using low cost object storage in the cloud for retention. So the combination of flash on Prem and Object Storage in the Cloud can completely replace both disc and tape in the back of process >> case. I won the competition because you guys came in really with the vision of all Flash Data Center. You now have a cloud software that runs on Amazon and others with words. No hardware, he just the blocks are great solution. How have the competition fallen behind you guys really kind of catapulted into the lead, took share certainly from other vendors. In my public, someone predicted that pure would never make it to escape velocity. Some other pundits and other CEOs of tech company said that you guys achieve that, but their success now You guys go the next level. What is the importance of that ability you have? And what's the inability of the competition? So, you know, I like >> to joke with folks. When we started the company, I think flashes. It's an excuse, you know, We just tried to build a better storage company and we went out and I talkto many, many, many customers, and I found in general they didn't just not like their stories products they didn't like the companies that sold it to them, and so we tried to look at that overall experience. And, you know, we, of course, innovated around flash use. Consumer fresh brought the price down so I could actually afford to use it with the duplication. But we also just looked at that ownership experience. And when I talk to folks in the history, I think now we might even be better known for are evergreen approach that even for Flash. And it's been neat to watch customers now that even the earliest your customers or two or three cycles of refreshing they've seen a dramatic difference in just the storage experience that you can essentially subscribe to. A known over time through many generations of technology. Turn as opposed to that cycle of replacing a raise >> share a story of a custom that's been through that's reached fresh cycles from their first experience to what they're experienced. Now what what? Some of the experiences like any share some some insight. >> Yeah, so, you know, one of one of the first customers that really turn us on to this. That scale was a large telco provider, and they were interesting they run, you know, hundreds of here wanna raise from from competitors and you know, they do a three year cycle. But as they really like, looked at the cost of that three or cycle. They realized that it was eighteen months of usable life in those three years because it took him nine months to get the dirt on the array. And then when they knew the end was coming, it took him nine months to get the data off the array. And so parade it was cost him a million dollars just in data migration costs alone. Then you've wasted half of your life of the array, and so add that up over hundreds of raising your environment. You can quickly get the math. >> It's just it's a total cost of ownership, gets out of control, right? And >> so as we brought in Evergreen, there's just an immediate roo. I mean, it was accost equation. It was, you know, on parity with flash disk anyway. But if you look at all those operational savings, itjust is completed. And so I think what we started with Evergreen, we realised it was much more of a subscription model where people subscribe to a service with us. We updated. Refresh the hardware over time and it just keeps getting better over time. Sounds >> a lot like the cloud, right? And so we really your strategies bring common set of tools in there and read them again. That kind of service that been Kia. >> Yeah, I think you know another thing that we did from Day one was like, We're never gonna build a piece of on prime management software. So are on print. Our management experience from Day one was pure one, which is our SAS base management platform. You know, it started out as a call home application, but now is a very full featured south space management experience. And that's also served us well as you go to the cloud, because when you want to manage on permanent cloud together, we're about to do it from then the cloud itself >> tell about the application environment you mentioned earlier hybrid on multi class here. Ah, a lot of pressure and I t to get top line revenue, not just cost reduction was a good benefits you mentioned certainly gets their attention. But changing the organization's value proposition to their customers is about the experience either app driven or some other tech. This is now an imperative. It's happening very fast. Modernisation Renaissance. People call it all these things. How you guys helping that piece of the >> puzzle? Yeah, I mean, I think ultimately, for most customers, as they start toe really getting their mindset, that technology is there. Differentiation speed into Julia there, developers becomes key. And so you know, modern CEO is much less about being a cost cutting CEO today, and much more about that empower in Seo and how you can actually build the tools and bring them there for the ordination. Run faster. And a lot of that is about unlocking consumption. And so it's been it's been fun to see some of the lessons of the cloud in terms of instant consumption, agility growth actually come to the mindset of how people think about on Primus. Well, and so a lot of what we've done is tried Teo armed people on prom with those same capabilities so that they can easily deliver storage of service to their customers so folks can consume the FBI without having to call somebody to ask for storage. So things could take seconds, not weeks of procurement, right? And then now, as we bridge those models between on permanent cloud, it becomes a single spot where you can basically have that same experience to request storage wherever it may be. In the organization, >> the infrastructures code is really just, you know, pushing code not from local host or the machine, but to cloud or on prim and just kind of trickle all the way through. This is one of the focuses we're hearing in cloud native conversations, as you know, words like containers We talked briefly about you mentioned in the activities. Hi, Cooper Netease is really hot right now. Service meshes Micro services state ful Data's stateless data. These air like really hyped up areas, but a lot of traction force people take a look at it. How do you guys speak to the customers when they say, hey, kicks? We love all the pure stuff. We're on our third enter federation or anything about being a customer. I got this looming, you know, trend. I gotto understand, and either operationalize or not around. Cooper Netease service mesh these kinds of club native tools. How do you guys talk to that customer. What's the pitch? That's the value proposition. >> Yeah. I mean, I think you know, your your new Kupres environment is the last place you should consider a legacy Storage, You know, all all joking aside, we've We've been really, I think possibly impressed around how fast the adoption it started around containers in general. And Cooper, that is, You know, it started out as a developer thing. And, you know, we first saw it in our environment. When we started to build our second product up your flash blade four, five years ago, the engineering team started with honors from Day one. It was like, That's interesting. And so we started to >> see their useful. We have containers and communities worker straight, pretty nights. And >> so, you know, we just started to see that grow way also started to see it more within analytics and a I, you know, as we got into a I would area and are broader push around going after Big Gate and analytics. Those tool chains in particular, were very well set up to take advantage of containers because they're much more modern. That's much more about, you know, fluidly creating this data pipeline. And so it started in these key use cases. But I think you know, it's at a point right now where every enterprises considering it, there's certainly an opportunity in the development environment. And, you know, despite all of that, the folks who tend to use these containers, they don't think about storage. You know that if they go to the cloud and they start to build applications, they're not thinking many layers down in the organization. What the story is that supports me looks like. And so if you look at a storage team's job or never structure seems job is to provide the same experience to your container centric consumers, right? They should just be able Teo, orchestrate and build, and then stories should just happen underneath. >> I told Agree that I think that success milestone. If you could have that conversation that he had, you know you're winning what they do care about. We're hearing more of what you mentioned earlier about data pipeline data they care about because applications will be needing data. But it's a retail app or whatever. I might need to have access to multiple data, not some siloed or you know, data warehouse that might have little, you know. Hi, Leighton. See, they need data in the AP at the right moment. This has been a key discussion. Real time. I mean, this is the date. It's It's been a hard problem. Yeah. How do you guys look at that solution opportunity for your customers? I >> think one of the insights we had was that fundamentally folks needed infrastructure that cannot just run one tool or another tool, but a whole bunch of them. And, you know, you look at people building a data pipeline there, stitching together six, eight, ten tools that exist today and another twenty that don't exist tomorrow. And that flexibility is key, right? A lot of the original thought in that space was going to pick the right storage for this piece of the write stories for that piece. But as we introduced our flash blade product, we really position it as a data hub for these modern applications. And each of them requires something a little different. But the flexibility and scale of flash played was able to provide everything those applications needed. We're now seeing another opportunity in that space with Daz and the traditional architecture. You know, as we came out with envy me over fabrics within our flash ray product line. We see this is a way to really take Web scale architecture on Prem. You know, you look Quinn's within Google and Amazon and whatnot, right? They're not using hyper converge there, not using Daz disc inside of the same chassis that happens. We're on applications. They have dedicated in frustration for storage. That's simply design for dedicated servers. And they're connected with fast Internet, you know, networking on demand. And so we're basically trying to bring that same architecture to the on prime environment with nd me over fabric because they need me over fabric can make local disc feel like you know as fun. >> But this is the shift that's really going on here. This is a complete re architecture of computing and storage. Resource is >> absolutely, you know, and I think the thing that's changing it is that need for consolidation. In the early days, I might have said, Okay, I'm gonna deploy. I don't know, two hundred nodes of the Duke and all just design a server for her dupe with the right amount of discontent and put him over in those racks, and that will be like this. Then I'LL design something else for something else. Right now, people are looking for defining Iraq. They can print out, over and over and over and over again, and that rack needs to be flexible enough to deliver the right amount of storage to every application on demand over and >> over. You know, one trend I want get your reaction to a surveillance because this kind of points that value proposition functions have been very popular. It's still early days on what functions are, but is a tell sign a little bit on where this is going to your point around thinking, rethinking on Prem not in the radical wholesale business model change, but just more of operating change. I was deployed and how it works with the cloud because those two things, if working together, make server Lis very interesting. >> Yeah, absolutely. I mean, it's just a further form of abstraction, ultimately from the underlying hardware. And so you know, if you think about functions on demand or that kind of thing, that's absolute, something that just needs a big shared pool of storage and not to have any persistent findings to anything you know, Bill, to get to the storage needs, do its task, right? What it needs to and get out of the way. Right? >> Well, VP of strategy. A big roll. You guys did a good job. So congratulations being the number six employees of pure. How's the journey been? You guys have gone public, Still growing. Been around for it on those ten years. You're not really small little couple anymore. So you're getting into bigger accounts growing. How's that journey been for you? >> It's so it's been an amazing right. That's why I'm still here, coming in every day, excited to come to work. I think they think that we're the proudest of is it still feels like a small company. It still feels with, like we have a much aggression and much excitement to go out for the market everyday, as we always have the oranges very, very strong. But on the flip side, it's now fun that we get to solve customer problems at a scale that we probably could have even imagined in the early days. And I would also say right now it really feels like there's this next chapter opening up. You know, the first chapter was delivering the all flashes, and we're not even done with that yet. But as we bring our software to the cloud and really poured it natively be optimized for each of the clouds. It kind of opens up. Our engineers tto be creative in different ways. >> Generational shift happening. Seeing it, you know again. Application, modernization, hybrid multi clouded. Just some key pillars. But there's so much more opportunity to go. I want your thoughts. You've had the luxury of being working under two CEOs that have been very senior veterans Scott Dietzen and Charlie. What's it like working with both of them? And what's it like with Charlie? Now it's What's the big mandate? What what's the Hill you guys are trying to climb? Share some of the vision around Charlene's? Well, >> I'd say the thing that binds both Scott and truly together in DNA is that they're fundamentally both innovators. And, you know, if you look at pure, we're never going to be the low cost leader. We're not going to be. The company tells you everything, so we have to be the company that's most innovative in the spaces we playing. And so you know, that's job number one. It pure after reliability. So let's say that you remember, too. But that's key. And I think both of both of our CEOs have shared that common DNA, which is their fundamentally product innovators. And I think that's the fun thing about working for Charlie is he's really thoughtful about how you run a company of very large scale. How you how you manage the custom relationship to never sacrifice that experience because that's been great for pure but ultimately how you also, unlike people to run faster and a big organization, >> check every John Chambers, who Charlie worked with Cisco. With the back on the day, he said, One of the key things about a CEO is picking the right wave the right time. What is that way for pure. What do you guys riding that takes advantage of? The work still got to do in the data center on the story side. What's the big wave? >> So, you know, look, the first way was flash. That was a great way to be on and before its not over. But we really see a and an enormous opportunity where cloud infrastructure mentality comes on. And, you know, we think that's going to finally be the thing that gets people out of the mindset of doing things the old way. You know, you fundamentally could take the lessons we learned over here and apply it to the other side of my hybrid cloud. Every talks about hybrid cloud and all the thought processes what happens over the cloud half of the hybrid. Well, Ian from half of the hybrid is just as important. And getting that to be truly Cloudera is a key focus of >> Arya. And then again, micro Services only helped accelerate. And you want modern story, your point to make that work absolutely kicks. Thanks for spending time in sparing the insides. I really appreciate it. It's the Cube conversation here of Pure stores. Headquarters were in the arcade room. Get the insights and share in the data with you. I'm job for your Thanks for watching this cube conversation