>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from the cube and ETR, this is Breaking Analysis with Dave Vellante. >> Organizations have considerable room to improve their performance without making expensive changes to their talent, their structure, or their fundamental business model. You don't need a slew of consultants to tell you what to do. You already know. What you need is to immediately ratchet up expectations, energy, urgency, and intensity. You have to fight mediocrity every step of the way. Amp it up and the results will follow. This is the fundamental premise of a hard-hitting new book written by Frank Slootman, CEO of Snowflake, and published earlier this year. It's called "Amp It Up, Leading for Hypergrowth "by Raising Expectations, Increasing Urgency, "and Elevating Intensity." Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. At Snowflake Summit last month, I was asked to interview Frank on stage about his new book. I've read it several times. And if you haven't read it, you should. Even if you have read it, in this Breaking Analysis, we'll dig deeper into the book and share some clarifying insights and nuances directly from Slootman himself from my one-on-one conversation with him. My first question to Slootman was why do you write this book? Okay, it's kind of a common throwaway question. And how the heck did you find time to do it? It's fairly well-known that a few years ago, Slootman put up a post on LinkedIn with the title Amp It Up. It generated so much buzz and so many requests for Frank's time that he decided that the best way to efficiently scale and share his thoughts on how to create high-performing companies and organizations was to publish a book. Now, he wrote the book during the pandemic. And I joked that they must not have Netflix in Montana where he resides. In a pretty funny moment, he said that writing the book was easier than promoting it. Take a listen. >> Denise, our CMO, you know, she just made sure that this process wasn't going to. It was more work for me to promote this book with all these damn podcasts and other crap, than actually writing the book, you know. And after a while, I was like I'm not doing another podcast. >> Now, the book gives a lot of interesting background information on Slootman's career and what he learned at various companies that he led and participated in. Now, I'm not going to go into most of that today, which is why you should read the book yourself. But Slootman, he's become somewhat of a business hero to many people, myself included. Leaders like Frank, Scott McNealy, Jayshree Ullal, and my old boss, Pat McGovern at IDG, have inspired me over the years. And each has applied his or her own approach to building cultures and companies. Now, when Slootman first took over the reins at Snowflake, I published a Breaking Analysis talking about Snowflake and what we could expect from the company now that Slootman and CFO Mike Scarpelli were back together. In that post, buried toward the end, I referenced the playbook that Frank used at Data Domain and ServiceNow, two companies that I followed quite closely as an analyst, and how it would be applied at Snowflake, that playbook if you will. Frank reached out to me afterwards and said something to the effect of, "I don't use playbooks. "I am a situational leader. "Playbooks, you know, they work in football games. "But in the military, they teach you "situational leadership." Pretty interesting learning moment for me. So I asked Frank on the stage about this. Here's what he said. >> The older you get, the more experience that you have, the more you become a prisoner of your own background because you sort of think in terms of what you know as opposed to, you know, getting outside of what you know and trying to sort of look at things like a five-year-old that has never seen this before. And then how would you, you know, deal with it? And I really try to force myself into I've never seen this before and how do I think about it? Because at least they're very different, you know, interpretations. And be open-minded, just really avoid that rinse and repeat mentality. And you know, I've brought people in from who have worked with me before. Some of them come with me from company to company. And they were falling prey to, you know, rinse and repeat. I would just literally go like that's not what we want. >> So think about that for a moment. I mean, imagine coming in to lead a new company and forcing yourself and your people to forget what they know that works and has worked in the past, put that aside and assess the current situation with an open mind, essentially start over. Now, that doesn't mean you don't apply what has worked in the past. Slootman talked to me about bringing back Scarpelli and the synergistic relationship that they have and how they build cultures and the no BS and hard truth mentality they bring to companies. But he bristles when people ask him, "What type of CEO are you?" He says, "Do we have to put a label on it? "It really depends on the situation." Now, one of the other really hard-hitting parts of the book was the way Frank deals with who to keep and who to let go. He uses the Volkswagen tagline of drivers wanted. He says in his book, in companies there are passengers and there are drivers, and we want drivers. He said, "You have to figure out really quickly "who the drivers are and basically throw the wrong people "off the bus, keep the right people, bring in new people "that fit the culture and put them "in the right seats on the bus." Now, these are not easy decisions to make. But as it pertains to getting rid of people, I'm reminded of the movie "Moneyball." Art Howe, the manager of the Oakland As, he refused to play Scott Hatteberg at first base. So the GM, Billy Bean played by Brad Pitt says to Peter Brand who was played by Jonah Hill, "You have to fire Carlos Pena." Don't learn how to fire people. Billy Bean says, "Just keep it quick. "Tell him he's been traded and that's it." So I asked Frank, "Okay, I get it. "Like the movie, when you have the wrong person "on the bus, you just have to make the decision, "be straightforward, and do it." But I asked him, "What if you're on the fence? "What if you're not completely sure if this person "is a driver or a passenger, if he or she "should be on the bus or not on the bus? "How do you handle that?" Listen to what he said. >> I have a very simple way to break ties. And when there's doubt, there's no doubt, okay? >> When there's doubt, there's no doubt. Slootman's philosophy is you have to be emphatic and have high conviction. You know, back to the baseball analogy, if you're thinking about taking the pitcher out of the game, take 'em out. Confrontation is the single hardest thing in business according to Slootman but you have to be intellectually honest and do what's best for the organization, period. Okay, so wow, that may sound harsh but that's how Slootman approaches it, very Belichickian if you will. But how can you amp it up on a daily basis? What's the approach that Slootman takes? We got into this conversation with a discussion about MBOs, management by objective. Slootman in his book says he's killed MBOs at every company he's led. And I asked him to explain why. His rationale was that individual MBOs invariably end up in a discussion about relief of the MBO if the person is not hitting his or her targets. And that detracts from the organizational alignment. He said at Snowflake everyone gets paid the same way, from the execs on down. It's a key way he creates focus and energy in an organization, by creating alignment, urgency, and putting more resources into the most important things. This is especially hard, Slootman says, as the organization gets bigger. But if you do approach it this way, everything gets easier. The cadence changes, the tempo accelerates, and it works. Now, and to emphasize that point, he said the following. Play the clip. >> Every meeting that you have, every email, every encounter in the hallway, whatever it is, is an opportunity to amp things up. That's why I use that title. But do you take that opportunity? >> And according to Slootman, if you don't take that opportunity, if you're not in the moment, amping it up, then you're thinking about your golf game or the tennis match that's going on this weekend or being out on your boat. And to the point, this approach is not for everyone. You're either built for it or you're not. But if you can bring people into the organization that can handle this type of dynamic, it creates energy. It becomes fun. Everything moves faster. The conversations are exciting. They're inspiring. And it becomes addictive. Now let's talk about priorities. I said to Frank that for me anyway, his book was an uncomfortable read. And he was somewhat surprised by that. "Really," he said. I said, "Yeah. "I mean, it was an easy read but uncomfortable "because over my career, I've managed thousands of people, "not tens of thousands but thousands, "enough to have to take this stuff very seriously." And I found myself throughout the book, oh, you know, on the one hand saying to myself, "Oh, I got that right, good job, Dave." And then other times, I was thinking to myself, "Oh wow, I probably need to rethink that. "I need to amp it up on that front." And the point is to Frank's leadership philosophy, there's no one correct way to approach all situations. You have to figure it out for yourself. But the one thing in the book that I found the hardest was Slootman challenged the reader. If you had to drop everything and focus on one thing, just one thing, for the rest of the year, what would that one thing be? Think about that for a moment. Were you able to come up with that one thing? What would happen to all the other things on your priority list? Are they all necessary? If so, how would you delegate those? Do you have someone in your organization who can take those off your plate? What would happen if you only focused on that one thing? These are hard questions. But Slootman really forces you to think about them and do that mental exercise. Look at Frank's body language in this screenshot. Imagine going into a management meeting with Frank and being prepared to share all the things you're working on that you're so proud of and all the priorities you have for the coming year. Listen to Frank in this clip and tell me it doesn't really make you think. >> I've been in, you know, on other boards and stuff. And I got a PowerPoint back from the CEO and there's like 15 things. They're our priorities for the year. I'm like you got 15, you got none, right? It's like you just can't decide, you know, what's important. So I'll tell you everything because I just can't figure out. And the thing is it's very hard to just say one thing. But it's really the mental exercise that matters. >> Going through that mental exercise is really important according to Slootman. Let's have a conversation about what really matters at this point in time. Why does it need to happen? And does it take priority over other things? Slootman says you have to pull apart the hairball and drive extraordinary clarity. You could be wrong, he says. And he admits he's been wrong on many things before. He, like everyone, is fearful of being wrong. But if you don't have the conversation according to Slootman, you're already defeated. And one of the most important things Slootman emphasizes in the book is execution. He said that's one of the reasons he wrote "Amp It Up." In our discussion, he referenced Pat Gelsinger, his former boss, who bought Data Domain when he was working for Joe Tucci at EMC. Listen to Frank describe the interaction with Gelsinger. >> Well, one of my prior bosses, you know, Pat Gelsinger, when they acquired Data Domain through EMC, Pat was CEO of Intel. And he quoted Andy Grove as saying, 'cause he was Intel for a long time when he was younger man. And he said no strategy is better than its execution, which if I find one of the most brilliant things. >> Now, before you go changing your strategy, says Slootman, you have to eliminate execution as a potential point of failure. All too often, he says, Silicon Valley wants to change strategy without really understanding whether the execution is right. All too often companies don't consider that maybe the product isn't that great. They will frequently, for example, make a change to sales leadership without questioning whether or not there's a product fit. According to Slootman, you have to drive hardcore intellectual honesty. And as uncomfortable as that may be, it's incredibly important and powerful. Okay, one of the other contrarian points in the book was whether or not to have a customer success department. Slootman says this became really fashionable in Silicon Valley with the SaaS craze. Everyone was following and pattern matching the lead of salesforce.com. He says he's eliminated the customer service department at every company he's led which had a customer success department. Listen to Frank Slootman in his own words talk about the customer success department. >> I view the whole company as a customer success function. Okay, I'm customer success, you know. I said it in my presentation yesterday. We're a customer-first organization. I don't need a department. >> Now, he went on to say that sales owns the commercial relationship with the customer. Engineering owns the technical relationship. And oh, by the way, he always puts support inside of the engineering department because engineering has to back up support. And rather than having a separate department for customer success, he focuses on making sure that the existing departments are functioning properly. Slootman also has always been big on net promoter score, NPS. And Snowflake's is very high at 72. And according to Slootman, it's not just the product. It's the people that drive that type of loyalty. Now, Slootman stresses amping up the big things and even the little things too. He told a story about someone who came into his office to ask his opinion about a tee shirt. And he turned it around on her and said, "Well, what do you think?" And she said, "Well, it's okay." So Frank made the point by flipping the situation. Why are you coming to me with something that's just okay? If we're going to do something, let's do it. Let's do it all out. Let's do it right and get excited about it, not just check the box and get something off your desk. Amp it up, all aspects of our business. Listen to Slootman talk about Steve Jobs and the relevance of demanding excellence and shunning mediocrity. >> He was incredibly intolerant of anything that he didn't think of as great. You know, he was immediately done with it and with the person. You know, I'm not that aggressive, you know, in that way. I'm a little bit nicer, you know, about it. But I still, you know, I don't want to give into expediency and mediocrity. I just don't, I'm just going to fight it, you know, every step of the way. >> Now, that story was about a little thing like some swag. But Slootman talked about some big things too. And one of the major ways Snowflake was making big, sweeping changes to amp up its business was reorganizing its go-to-market around industries like financial services, media, and healthcare. Here's some ETR data that shows Snowflake's net score or spending momentum for key industry segments over time. The red dotted line at 40% is an indicator of highly elevated spending momentum. And you can see for the key areas shown, Snowflake is well above that level. And we cut this data where responses were greater, the response numbers were greater than 15. So not huge ends but large enough to have meaning. Most were in the 20s. Now, it's relatively uncommon to see a company that's having the success of Snowflake make this kind of non-trivial change in the middle of steep S-curve growth. Why did they make this move? Well, I think it's because Snowflake realizes that its data cloud is going to increasingly have industry diversity and unique value by industry, that ecosystems and data marketplaces are forming around industries. So the more industry affinity Snowflake can create, the stronger its moat will be. It also aligns with how the largest and most prominent global system integrators, global SIs, go to market. This is important because as companies are transforming, they are radically changing their data architecture, how they think about data, how they approach data as a competitive advantage, and they're looking at data as specifically a monetization opportunity. So having industry expertise and knowledge and aligning with those customer objectives is going to serve Snowflake and its ecosystems well in my view. Slootman even said he joined the board of Instacart not because he needed another board seat but because he wanted to get out of his comfort zone and expose himself to other industries as a way to learn. So look, we're just barely scratching the surface of Slootman's book and I've pulled some highlights from our conversation. There's so much more that I can share just even from our conversation. And I will as the opportunity arises. But for now, I'll just give you the kind of bumper sticker of "Amp It Up." Raise your standards by taking every opportunity, every interaction, to increase your intensity. Get your people aligned and moving in the same direction. If it's the wrong direction, figure it out and course correct quickly. Prioritize and sharpen your focus on things that will really make a difference. If you do these things and increase the urgency in your organization, you'll naturally pick up the pace and accelerate your company. Do these things and you'll be able to transform, better identify adjacent opportunities and go attack them, and create a lasting and meaningful experience for your employees, customers, and partners. Okay, that's it for today. Thanks for watching. And thank you to Alex Myerson who's on production and he manages the podcast for Breaking Analysis. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters. And Rob Hove is our EIC over at Silicon Angle who does some wonderful and tremendous editing. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can email me at david.vellante@siliconangle.com or DM me @dvellante or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in enterprise tech. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. Be well. And we'll see you next time on Breaking Analysis. (upbeat music)

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

(upbeat music) >> Hey everyone. Welcome to theCUBE's coverage of the International Women's Showcase for 2022. I'm your host, Lisa Martin. I'm really excited because for the first time in my CUBE career of six years, I have a father daughter duo maybe the first time in CUBE's history. Frank and Emma Arrigo from AWS join me guys it's great to have you on the program. >> Great to be here thank you. >> So, Emma, let's go ahead and start with you. Talk to us about how you got to AWS and a little bit about your background. >> Yes, thanks Lisa. So I've joined AWS as a recent graduate from university. So I did my masters of data science and I was going through the grad, the grad job hunt applying for all these different places. And AWS appeared on my radar for an intern program. And Frank was there at the time and so I was like, "Should I do it?" But I still applied cause it was a great program. And so I went did that internship for three months over the summer of 2019-2020, and then I went back and finished my degree. And another grad role came up for in AWS in Tech U to be an associate solutions architect. And so I was approached to apply for that. And I got through to that program and joined the team almost a year ago in March, 2021 through Tech U and yeah, that's how I ended up at AWS. >> Excellent and so Frank, this is a pretty unique situation, father daughter duo at AWS let alone Amazon, let alone probably a lot of companies. Talk to me about it the parental lens. >> Yeah, look it is unique, there's a few family connections within AWS, but you know, definitely here in Australia, it's really rare, but I think the family connection is, you know Emma and we've got four kids, I've got four kids in total. So Emma has three brothers, you know, I've lived in tech, my entire career and so they've been part of it. You know, we've lived in the States, lived in Seattle for a couple of years. And so they'd come to the office and see what dad did. And so it wasn't a big surprise for them to understand what the role was and what we did, so, you know, they kind of grew up with it. And you know, when the opportunity came up for Emma, did the internship, I was excited for it because it was in a different area. It was working in a startup team doing some interesting work that really lined up with some of the interest Emma had. And so she kind of learned what it was like to be Amazonian through that internship and that was... I call that a long audition for a job. And she was then able to join Tech U program, which is a early career bootcamp, I like to think of it, which is the six month program to help our grads learn some of the fundamental skills because the value of a solutions architect or some of these other tech roles is you need experience. You need to have been in the game a while to be a trusted advisor to a customer. And it's hard to do that when you're a grad. So the bootcamp gives them the practical experience and then they get another six months on the job experience where they develop those skills and hone it and get ready to, you know, be a trusted advisor to the customers. >> Right, and that's such a great... I'm sure that's a tremendous opportunity to learn how to become that trusted advisor, especially from peers, such as yourself and I want to go back to you. Talk to me about your interest in IT, in data science. Was this something that you were always interested in primary school or in high school? Or was this something that kind of came on later on? >> Yeah, so my interest in tech kind of emerged as I went along in my education. So when I was younger, I really wanted to be an orthodontist for some reason. I don't know why. And then you just sort of in year eight and like early school sort of didn't really know what I wanted to do. Just sort of going through just trying to survive as a teenage girl at high school at an all girls school, didn't really have many, didn't really have career aspirations, I guess, and then one year I attended a information day at a university about engineering and that just really sparked my interest, I don't know why, but I was like, I've always been obsessed with like factories and those types of things and how things are made. And so that really just sparked my interest and I never really thought of it before. And so then that put STEM engineering on my radar and then I guess spoke with it about with the parents. And then they mentioned that tech would be a like IT, Information Technology would be really useful. And so then we approached the school to ask if I could do IT in year 11. So that's sort of our second last year of high school. And they said, "No, we couldn't do IT." I couldn't go to the boys' school to do IT. That girls don't do it or that not good at it. And I wasn't allowed, and they wouldn't let me do physics either. So I moved school in for the final two of high school to be able to do IT and physics to help, you know, get to the course I wanted to do. And so that was my journey into STEM. So it wasn't really on my radar, but then events like this and at university isn't it? Organizations sparked my interest. And then still when I entered university, I didn't know exactly what I wanted to major in nor where I wanted to work would never have thought it would be where, with my father, like I was aware of the world of IT and everything, but I wouldn't, if you'd asked me in first year, it wouldn't have been that I would probably, we would've said, I don't know an academic or something. I don't know. And then, but again, as the university went on and you attend networking events or club things, you sort of learn a bit more about the ecosystem. And then that's where yeah. Tech company sort of became where I was looking for jobs and roles for when I finished up. So that was kind of my journey to... >> So what I love though, that you and Frank, this is going to be a question for you, how Emma was told. "No, you can't study IT. No, you can't study physics. You can't go to the boys school and do that either." Talk to me about that, Frank, from your perspective as a parent of a daughter, and you said, I think she's got three brothers lucky, Emma, but talk to me about that from your perspective, in terms of going, my daughter has really has an in a strong interest in this and they're telling her no we're going to pivot and actually change schools to be able give her the opportunities that she wants to pursue. >> Yeah. Look, as a parent, we were shocked. You know, it was just an unexpected response, you know, in a lot of ways, the school that she was at was more of a finishing school than anything else, you know, preparing young ladies for marriage and, you know, career as a, I don't know, I will leave it at that. So we were really disappointed. And so very quickly we looked at other alternatives and other options and we pulled Emma out of school and we knew it was like the last two years are critical in Australia. We don't have a middle school and a senior school, it's all one, you know, combined thing. But those last two years are all about getting ready for university. And so we made a really tough call and we picked her up, dropped her into a totally new school. It was co-ed school. And then when we told her previous, her girl's school. I actually spoke to the vice principal and he said, "Oh, I can't believe you're sending her to a co-ed school. She's going to struggle 'cause boys are so much better in tech." And I was totally, I was lost for words, right? Because I felt back in my career and I had some amazing female managers, leaders, role models in my time that I worked for and I followed and they were always struggling because, you know, they were in the minority, but they were incredible, you know, technologists and leaders. And I just couldn't believe it. So as parents we made the tough call. We picked Emma up. We put her into another high school and she flourished, you know, Emma started a club, she got convolved with a whole bunch of other things. When she graduated, the teachers felt that she'd been there six years, right? The whole time of it. So she really made a mark, made an impact at this school and so much so that her younger brother then followed and went to that school and completed his high school there as well. But it, we just can't believe it. And we tell it everyone, this story, you know, we name the school, we won't name. We choose not to name them here, but we name the school because we just think it's really terrible guidance and terrible advice. Like we want people to follow their passion. I tell my kids and I tell the folks when I speak to, you know, early career folks, follow your passion first, guess what the job will appear. Right? You know, there'll be the... The work will come if you do something that you love. And then the second piece that I always say is, "Every future job is going to be a tech job." Technology is embedded in everything that we do. So the fact that you say, "A girl can't do technology," you're limiting yourselves, right? You don't want to think that, you want to think about the possibilities rather than the things you can't do. It's the things you can do. And the things that you haven't even thought about doing. So that's why, you know, it was so exciting to see that experience with Emma, and just seeing her grow through that and she became a bit of a STEM advocate at a high school as well. So, she saw the value of her role model that helped her. And she wants to be a.... Continue being a role model for others as well, which again, I think is admirable, right? It's about- >> Absolutely. >> Shining a light and leading and as a parent, irrespective that we work at the same company as a parent, that's what you want to see. You want to see your kids aim high and inspire others. That's what she does. >> Well, she's already been a role model too, I mean, to your younger brother, but one of the things that we say often, and theCUBE does a lot for women in technology events. And I'm fortunate to get to host a lot of those, we say, "You can't be what you can't see." So needing to have those role models who are visible. Now, it doesn't have to be female necessarily. and Frank you mentioned that you had female mentors and role models and in your illustrious career. But the important point is being able to elevate women into positions where others can see and can identify, "Oh, there's a role model. There's somebody that might be a mentor for me, or a sponsor down the road, it's critically important." And as of course, we look at the numbers in tech, women in technical roles are still quite low, but Emma, tell me a little bit about, you've been through the program. You talked about that. What are some of the things that you feel in like the last six months that you've been able to learn that had you not had this opportunity, maybe you wouldn't have. >> You know, I think that's a great point. So as a solutions architect, I get to be both technical. So hands on building an AWS, helping customers solve their problems, whether it be a data leak or I don't know, an image recognition tool to look for garbage dumped on the street or, and also thinking from the business perspective for the customers, so that's a fun part as the, of the role, but things I get to do. So currently I'm working on a demo for the conference in Sydney. So I'm building a traffic detection model using some computer vision and IOT so I get to bring my data science background to this build and also learn about new areas like IOT, Internet Of Things; Technologies. So that's been a really fun project and yeah, just having the ability to play around on AWS, we have... >> Right. Well, the exposure in the experiences is priceless. You can't put a price on that, but being able to get into the environment, learn it from a technical perspective, learn it from a practical perspective. And then of course get all the great things about getting to interact with customers and learning how different industries work, you mentioned you were in public sector. That just must be a field of dreams, I would imagine. >> I know. >> In some senses for you, right? >> Really have lucked out. I know it's, I'm like, "Wow, this my job is to play around with some new service, just because need to know about that for the customer meeting. Like I'm building a chatbot or helping build a chatbot for a customer, at the university. So yeah, things like that make it very, yeah. It's a pretty amazing role. >> It sounds, it sure sounds like it. And sounds like you're are excelling at it tremendously. Let me ask you Emma. For young girls who might be in a similar situation to where you were not that long ago with the school telling you, "No, you can't do IT." "No, you can't do physics." So you actually switched schools. What would you tell those young girls who might be in that situation about hearing the word, "No." And would you advise them to embrace a career in technology? >> Yeah, I would say that it really..... What makes me so sad is if my family didn't know about tech and had my... Supported me through that like if I would've just gone, "Oh, okay. I won't do it." You know what I mean? Like that just makes me really sad. How many people have missed out on studying what they wanted to study. So by having those types of experiences, so what I would say as advice is, "Back yourself, find supporters, whether it be your family or a teacher that you really sort of connect with, to be able to support you and through these decisions." And yeah, I think having those sponsors in a way, your advocates to help you make those choices and help support you through those choices. >> Yeah. I agree. And I have a feeling you're going to be one of those sponsors and mentors, if you aren't already Emma, I have a feeling that's just around the corner from you. So Frank, last question to you. What's the overall lesson here, if we look at statistics, I mentioned some of the stats about, you know, women in technical roles as usually less than 25% globally. But also we see data that shows that companies are more profitable and more performant when there's at least 30% of the executive suite it's women. So from your parental perspective, and from an Amazonian perspective, Frank, what's the lesson here? >> Well, look from an Amazonian perspective, we need to make sure that we have a team that represents our customers, right? And our customers aren't all boys. You know, they're not all blokes, as we say down here. So you've got to have a team that is made up of what represents your customers. So I think that's the Amazonian view. And so diverse perspectives, diverse experience, diverse backgrounds is what does that. The other from a parent, you know, I said it earlier. I think every future job is a tech job. And I think it's really important that as kids come through, you know, primary school, high school, whatever, they're prepared for that, they're already consumers of technology. You know, they need to be creators or, or participate in that environment. And I can give you an example, a few years ago, I worked for, at a large telco here. And we actually invested in a thing called code club, which was aimed at primary school kids, kids in grade four, five and six. So elementary school for my friends in America, it's kids in grade four, five and six. And they were learning how to use scratch. Scratch is this interactive tool like building lego to write programming and believe it or not, there were more girls interested and were part of code club. It was probably 60-40 was the ratio of young girls doing it compared to boys because it was creative, it was a creative outlet, they were building stuff and assembling and making these things that they loved to make. Right. But then what we saw was there'd be a drop off at high school, whether it's curriculum related or interests or distractions, I don't know what it is, but there things get lost along the way along high school. But I see it at the primary school stage at elementary school that the interest is there. So I think part of it is, there needs to be a bit of a switch up in education or other opportunities outside of school to really foster and nurture and develop this interest because it really does take all kinds to be successful in the role. And Emma talked about a chatbot that she's building and that's a conversational thing. I can't see geek boys having being able to impact and create a interesting conversation, right. Then there's other areas that seems to be skewed and biased based on a predominantly male view of the world. So we need the tech, the industry needs these diverse perspectives and these diverse views, because, you know, to your point, it's going to impact the bottom line. It's going to also deliver a better product and it's going to reflect society. It's going to reflect the customers that are using it because we're made up of every, every race and color, creed, gender. And we need a team that represents that. >> Exactly. I couldn't agree more. Well, it sounds like the Arrigo family are quite the supporters of this, but also we need more of both of you. We need more of the sponsors and the parents who are encouraging the kids and making the right decisions to help them get along that path. And we need more folks like Emma and more women that we can see, "Wow, look what she's doing in such a short time period. We want to be just like that." So you guys are, have both been fantastic. I thank you so much for joining me at the International. Women's Showcase, more power to your family. We need more folks like you guys, so great work. Keep it up. >> Thank you. >> Thanks Lisa. >> For Frank and Emma Arrigo, I'm Lisa Martin. You're watching theCUBE's coverage of International Women's Showcase 2022. (soothing music)

>>Hey, welcome to this continuing coverage of the H P E Aruba. Pensando announcement. I'm lisa martin. Hopefully you've seen by now the announcement from john and Antonio, we're going to get into some technical details. Now I've got two guests joining me. Please welcome Krishna Otopeni, the VP of engineering at Pensando and frank Reich stein, senior Director platform engineering from HP Aruba guys welcome to the program. >>Hi lisa. >>Hi lisa. Thanks for having us. >>Sure. So we're going to, we're going to dig in here. You guys are tasked with bringing these two worlds together, christian. Let's go ahead and start with you talk to me about the announcement why this is so significant and then we'll dig into the technical details. >>Yeah. So as you know, right, Pensando has been in the market for a couple of years right now. Um, and we heard a lot of success with the cloud providers and we're also working with be a million project Montreat. Um, so what we learned in the last couple of years, we're trying to take all the lessons and I was a little bit going to what, what we learned with the crop, your providers. So we took a dsC card, which is a B C, a form factor, the customer takes dsC card inserts into the, into server with various forces and hypervisors. So it's really exciting that the BSE is in production with some of the providers already and some of them were taking to production in this calendar quarter and we also have in connection with that first generation BSC cards a couple of years and some of the biggest banks and storage platform providers. So, so this is kind of a big deal for us because we are starting with what we call a D P U. Uh that Pensando is bailing which is the latest generation of it is called code named Alba which delivers the software in silicon program ability while matching the performance of hardware. So internally the DPU has the tight integration between special purpose processors that consent of what we call mps and a general purpose processor like arm course where we do the management and control software and with tied together with offload engines like encryption and compression. The key takeaway from this platform. Their consent of belt. It's it's programmable at all layers Either by Pensando or our customers whether it's in data plane using P four or control and management plane. All right. So what we learned while developing this platform and taking this production with the public cloud providers, we realize that the platform and architecture is not only very highly scalable with very high performance with respect to, you know, packets per second or stable connections per second or NBA me I ops but it's also adaptable like a very rapid paced. And another key lesson that we learn from our cloud partners is that the new devoPS model operations is as important as functionality. For example, the importance of creating the DPU pipeline the subsequent guarantees or providing Hatch uh first fateful connections so that in some cases the component fails, there is hardware or software customer doesn't have any disruption in his network or storage operations. So we took all the ski lessons that we learned over the last few years. And then we are building a new platform partnering with Aruba team which is very high scale with very high performance at the same time, tied with very good operations um that you know it comes the best of both both platforms from the pew side and from the Aruba side frank they want to add on the Aruba platform side. >>Sure, yeah. So the Aruba networking team has been building network switches for the past 25 years and we've been following all of the trends and evolutions over that time frame. And as we've gone through a few years ago we decided to make an evolution of our operating system to scale it up for the modern needs of the modern world. And this included doing things like designing with a micro services oriented architecture to provide for a high degree of resiliency throughout the product line. And then being able to extend that single network operating system from the core to the edge of the network. As we've been partnering with Pensando, it came very clear that the evolution of the network the next step was this form of a deep, you integrated into that top of rack switch to provide a deeper and richer feature set and what has traditionally been available in your top of rack switch. And so this partnership has enabled us to leapfrog but has been traditional top of rack functionality and add to it. Things that previously were not attainable in that layer of the network >>frank. Continuing on with you. Talk to me about some of the technology requirements and challenges of designing and engineering and delivering the industry's first distributed service switch. What were some of those? >>Sure, sure. So a lot of the challenges around integrating this type of solution come down to how to ensure that you have the highest performance possible and maintaining high speed of performance when you're now introducing an additional pay hop within the network topology inside of the switch, a lot of that came down to integrating the background and skill setting capabilities that come along with osc x that were made it quick for us to enable a new piece of functionality within the architecture and then a lot of credit has to go to the Pensando team for the richness of the feature setting capability set that they have within that DPU product as it stands >>christian, let's go ahead and dig through some of those core features and capabilities that are really going to be benefiting customers. >>Yeah, so basically right, uh taking a little bit of step back, we started with the dsc market from Pensando perspective where we wanted to put gPU in every survey and we obviously have success in enterprise customers and cloud customers that we discussed earlier. But we also learned a few lessons while deploying DSC and enterprise markets in the sense that enterprise markets do not need the performance of every DSC at 200 G full duplex network services for every survey. And also you know what makes historic key is that you know, there are a lot of brownfield service in current enterprise data centers where customers do not want to open up a server to put the DSC in. So we wanted to give a product with the form factor that frank is talking about and technology that's very familiar to every IT department given the Aruba Lois uh in a deployment in data centers. And also as I said earlier, what we lessons that we learned, we came up with this taking this production very deep you software and hardware which is deployed in public clouds. And combined with those features that that have been rapidly evolving uh through multiple Aruba releases into enterprise data centers in a switch form factors. So what we think is by doing this taking the best of both worlds. We're creating a new product category that is not that is for the features and capabilities are not available in the market from any vendor specifically providing state full services at every tour without the complexity of the service redirection because today's data centers if you want to install services. It's a it's a lot of effort operator to bring in those services. This obviously also has a great operational model, great TCO and the functionality that customers that you never see in tar before. For example, in the first release we are providing state full firewall with the visibility at every floor level that goes through the tower which never existed in the market before. >>New product category. That's a big deal christian. Talk to me a little bit about how long you guys have been at this, you were in stealth mode crack that open for us. >>I mean it has been a less than a year but of development that both teams have been doing and we work very closely together and we meet I mean for sure at least more than a week uh you know, more than once the once a week between uh frank's team and you know, and send it to them and there's a coordination between the sales team and the marketing team and the go to market team and then how we sell it and the manufacturing team, there's a lot goes on in building this product. I mean we believe this is the fastest uh tard new generational product that we built because because we could do that because the experience of both the teams trying they want anything more to this one. >>Yeah, I think that that really goes to the point here. The capabilities and maturity of the deep you solution that Pensando was bringing into the solution really allowed for a very fast and seamless integration on top of that Aruba, OsC X and the platform that we built there with automated Api generation and integration with our Aruba fabric composer orchestration layer really created the capability to make things go as fast as possible for this development effort And so to really take a new product and define a new product space within a 12 month time frame has been a really exciting and impressive feat by both teams. >>Very impressive considering the challenges and the dynamics in the market and the global market that we've had frank. How big of a lead do you think you have on incumbents here? >>I think we have a substantial lead on the incumbents here. I think what we're doing is a fundamentally different take on how you do a top of rack switch and the capabilities that we're bringing to bear at the top of rack are fundamentally new and differentiated from what the competition has been thinking about. So I believe we have a substantial lead on the competition. >>Excellent chris to talk to me about what's next? What's the future? I have some secret sources that tell me that john and Antonio are meeting regularly pushing you guys, what does the future hold. >>Yeah. So I mean obviously this is the start of an exciting journey. There's a first platform you're bringing to the market jointly and obviously we like a bunch of form factors without upcoming road map. So additionally I mean the software in silicon performance that with all the services that we deliver a software means that scope and scale of the state will services that we can deliver and evolve over time whether you talk about security or encryption or state flat or load balancing or d does all of the services and then you know hybrid connectivity. So obviously you know there's a lot that we can do with this platform that will be driven by with the partnership with our customers. We also see that you know the market of all where you know all the customers we'll have some customers will have deep us in the service and some customers will use the new platform that we're bringing together. So we won't have all the management start to make sure all of them can be managed uniformly and any time you know you this is a major step for a new category of platform and architecture we're developing jointly with the rubber and I believe this will be a huge opportunity for both the companies and our customers and this is exciting times ahead for us >>and talk to me both of your opinions here where can customers go to find more information, how can they get started frank will go ahead and start with you. >>Yeah you can jump straight to Aruba networks dot com and dig into the feature sets and packages that we have available with the Aruba 10-K product line direct from there. >>Fantastic christian anything to add >>that is correct actually. So we are treating it as one product coming from both the companies. All the documentation is where you know, frank pointed out in Aruba website, we put all the documentation at the same place and we're supporting it as one unified product from both the companies. >>Are you seeing any? We've seen so much change in the last year and a half. Last question. I'm just wondering if if either of the HPV riverside or the pence underside is seeing any industries that might be really prime to take advantage of knowing how many industries all have been affected by the events of the last year and a half christian any thoughts there? >>Yeah, I mean if you look at it right and obviously all of us are working from home and now everything happens, you know, mostly at the edge, right? You know, and we are in that this platform will help us get there where we get security to the edge and we get more visibility and more services to the edge. Right? So I mean that's what you know Pensando is all about and hoping that you know, this is uh this journey that we started with the D. P us, we go with this platform and it will ever all and it will help customers, our customers and our partners leverage all the functionality that, you know, Pensando and the rubber can bring together. >>Well guys, congratulations on an enormous feat accomplished in not just a 12 month time period, but a very challenging 12 month time period. We appreciate you guys breaking down the HP Aruba Pensando announcement and more technical detail. Those can go to learn more information and again, congratulations. >>Thank you. >>Thank you very much lisa >>for my guests. I'm lisa martin. You're watching this HP Aruba Pensando announcement. Thanks for watching. >>Mhm >>mm.

>> Welcome to this "Cube" conversation. I'm Lisa Martin. Pleased to welcome back Caitlin Gordon, Vice President of Product Management at Dell technologies. Caitlin it's great to see you again, though virtually. >> Yes, it's good to see you as well, Lisa. >> Tony Frank is here as well. Global client executive at Equinix, Tony, welcome to the program. >> Thank you, Lisa. Good to be here. >> We're going to be talking about some news. Caitlin let's go back. You and I, before we started filming, we were trying to remember, when did we last see each other? Of course it was virtual. So APEX was announced product APEX, October 2021. Just about a year ago. Released it in may, but just refresh the audience's memories with respect to the catalyst for Dell to go into this as a service offering. >> Yeah, I think we're all losing track of the virtual months here, (all laugh) so go back in time a little bit. Yeah, exactly right. So in the fall of last year, we had announced Project APEX. The first actual APEX offers really came to market in the spring in May with our APEX Data Storage Services. And at that time we actually had pre-announced what we're going to talk more about here today with our partnership with Equinix. But if we take a step back, you know, why did Dell talk about this as a project and is now really investing for the future? It really connects to a lot of the conversations you guys have here in "theCube", right? What's happening in IT? What's happening with our customers? Is that they're looking for outcomes. Yes, they're predominantly still buying products today, but they're really starting to look for outcomes. They want to be buying those outcomes. They want to have something that is an operating expense for them. Something that we can take, we as the technology, the infrastructure experts can take on the management, can take on the ownership of that equipment and really enable them to focus on their business. So really consumption-based, usage based infrastructure, all being elastic resources that Dell owns and manages, but customers can still operate. And of course, one of the first offers was APEX Data Storage Services, which we're extending here this fall. >> Talk to me a little bit, Caitlin, about outcomes. I just want to understand what Dell actually is focusing on for its customers, where outcomes are concerned. >> Yeah. And it's interesting as a company, it's a pretty big transformation for us. We have always been a product led company, but it's not really about a product. So when I talk about APEX Data Storage Services, you're not going to hear me mention a product name or anything. Because what it's about, it's about offering our customers what they're actually looking for. Which in the case of storage, they're all looking for, I want either block or file storage. I want a certain tier, so it is at a higher performance. I want a certain capacity of it, and I want to commit for some period of time. That's it. Those are the questions we ask. There's no product names and sizing and it's really, really simple. And that's what we're talking about. It's really the beginning of really trying to deliver customers an outcome versus a product. >> Got it. APEX Data Storage Services. This is Dell's efforts to supply managed file and block Storage as Services. Talk to me about that. Talk to me about some of the things, how does it enable the fast time to value as little as 14 days for your customers? >> Yeah, so there's a lot of really important things we're doing here. We're not just taking the products we had and kind of packaging it up in a new financial model. There's a lot of parts to this. It all centers around the APEX console. So the APEX console is where you start, begin really ongoing manage and experience these outcomes from Dell Technologies. And it starts with selecting the service you want. So if you select that you want APEX Data Storage Services, you pick your type, you pick your tier, you pick your time period, and you pick your size, right? And then you're off to the races. And we will be able to, what we're committing to do is delivering that in as few, and as little as 14 days time to value. And for us, you know, one of the benefits of being able to do this as Dell, we have always really thrived in our supply chain and the ability to have that predictability and being able to deliver things as a service, including storage, is really something that's just an extension of what we've been able to do there. And our partnerships with Equinix actually is going to enable us to even look at that further and see what we can do to really bring value to our customers as quickly as possible. >> That speed, that time to value, is even more important as we've lived through the last tumultuous 18 months. Let's break into the news now. You guys pre-announced the partnership with Equinix, but talk to me about, with respect to APEX Data Storage Services, what's being announced? Caitlin, we'll start with you and then Tony we'll bring you into the conversation. >> Yeah, absolutely. So again, we first released APEX Data Storage Services in the spring, and we're already enhancing that today. Couple exciting things. So geographic expansion, so expanding out into additional regions across Europe and Asia, who are expanding our support. So we talked about the fact that it's block and it's file. Well, actually on our file capability here, on our file outcome, we now will have the ability to support an S3 protocol. So you can do that app development and run your operations all off the same platform. So that's an exciting new expansion there. We're also enabling partners sell through. Our partners are really, really important, whether the resell partners or technology partners like Equinix. So partner sell through is another important piece. And of course the most important for our conversation today, is the exciting new announcement of the fact that we are going to offer APEX Data Storage Services available in Equinix facilities, all integrated into the APEX console. The fifth question is, now, where do you want your APEX Data Storage Services? You can select a Dell provided facility and you get the choice to select the different cities of Equinix locations. And we're going to provide that single bill and experience through Dell, but on the backend, we've worked with Tony and team for months to get this to be a very streamlined experience for our customers. >> Tony, talk to us about this from Equinix's perspective. >> Yeah, we're very excited. Caitlin, thank you very much and Lisa, thank you. Very excited to be part of what Dell's doing with APEX and enable enterprise customers to get delivered to them at Equinix facilities Storage as a Service, in addition to additional Equinix capabilities, really enabling agile enterprises to distribute their infrastructure across the world, leveraging Dell product, Dell management, and to get access to partners, to their other footprints, to cloud service providers, et cetera, all within the footprints of Equinix. >> So Caitlin, APEX Data Storage Service in secure colo facilities in conjunction with Equinix. Talk to me about what the reception has been from Dell customers. >> Yeah, it's been really fun. I mean, first of all, when we thought about data center providers are a critical part of us being able to deliver that outcome to customers. And when we looked at the ecosystem of partners, it was very clear who we were going to be partnering with. Equinix was really the best partner for us. We already had been working together in many different ways and we're just taking this partnership to the next level. And what we've already seen actually, all the way since earlier this year, we've had many, many customers coming to us, at first it was separately, but now it's actually jointly to say, I'm having a challenge and here's my challenge. And most of these conversations start in one way. I'm getting out of the data center business. And the nice thing for us is that between our two companies, we can solve that. Right, we have the combination of the right infrastructure, and with our partnership with Equinix, you partner that with the data center services, you can actually give that full outcome to a customer. And we were solving those separately, and now we're solving those together. >> Those folks wanting to get out of the data center, if we think about in the last year and a half, how inaccessible the data centers were, Tony, I want to get your perspective on the colo market, and as we look at IT today, the acceleration of it and digital and cloud adoption and getting out of the data center that we've seen in the last 18 months. Help me understand why the colo market is really key today for the future of IT. >> Absolutely Lisa. So, you know, focusing on outcomes as Caitlin outlined earlier, is a really important part of, really how IT has managed this pandemic and thinking about how do we solve for this vast distributed set of employees that we used to have aggregated in a single building or multiple buildings, but really spearheaded in a couple locations. And all of a sudden everything became, you know, out in rural America, out in rural Europe, out everywhere, employees were spread out and they needed a way as an IT team, to bring together the network, the security and the ability to be very agile and focus on an outcome as opposed to, how am I going to get this next piece of equipment, this next storage device, this next compute system in my data center and add the cooling and the power and all the things that they have to think about. And really it was an outcome. How do I give my employees the best experience possible? My partners, that access they need to my systems and the various ways that we interact together. So the colo market as a whole has been really changed dramatically through the whole pandemic. And if you didn't know Zoom two years ago, it's your best friend now, or it's your, you know, least favorite way to do business, but the only way we have to do business in the world that we're living in today. >> A lifeline, and here we are Zooming with each other right now. (Caitlin and Tony laugh) Tony, I want to stick with you. Let's talk about this partnership between Dell and Equinix. Why is this such a compelling partnership? Talk to me about that from Equinix's perspective. >> Yeah. We're so excited to be able to be partnered with the number one leader and provider of infrastructure and infrastructure services. We have really been a niche provider for the last 15 years. We're a 21, 22 year old company, and we focused on developing ecosystems and those were at first the internet. We brought the telecom providers together to make the internet work. And then on top of that started enabling things like digital trading. Also enabling all sorts of ad exchanges so that you see the banner ads that apply to you when you go to a website. And so we were well known within those ecosystems that we worked within, but getting out to the enterprise has been a big challenge. And Dell brings us those relationships. They bring that expertise, that trusted advisor kind of role. And so being able to extend our sales team and really leverage what Dell has done across small, medium, large and very large enterprise is a real win for us. And it allows us to achieve a scale that we wouldn't have been able to achieve by ourselves without breaking the bank trying to hire people, and trying to get them familiar with those customers. And so Dell brings us into that. We're able to complete what I call the three legged stool. The compute, the storage, and now the networking aspects can be dealt with in a single conversation around an outcome. And APEX gives us a chance to really be agilely available as Dell's customers define that for themselves and to deploy the infrastructure where they need it and to achieve those outcomes that they're trying to get to. >> So it's an ostensible value that Equinix is getting by the Dell partnership. You said, pulling us into the enterprise, facilitating that scale. Caitlin, talk to me about this from Dell's lens. What makes this partnership so compelling for Dell and the future of it as a service? >> I'm laughing as Tony's talking through that because it tees it up perfectly. From Dell's perspective, when we looked at data center providers, one of the challenges for us is we're a global IT provider. So we had to partner with someone who understood what it meant to operate and manage data centers at a global scale and locations all over the world. There's a very short list to choose from once you look at it from that lens, but more importantly, and what Tony you already hit on, the networking. The interconnects that we have in our partnership with Equinix are incredibly valuable. Cause ultimately, although customers start going to a colo facility because they want out of data center business, they don't want to be managing racks and power and cooling and all of that. Oftentimes actually the value they find once they get there and why they stay and grow is those interconnects. The ability to connect to other tenants in these facilities and the ability to connect into the hyper-scalers. And the richness of those interconnects with Equinix was truly unmatched, and that's why it's been such an important partnership for us. >> Tony, what's been some feedback from the Equinix customer base? >> Well, it's really funny. I spent half of my time trying to figure out with my team, how we're going to solve for Storage as a Service. The next geography, the next product. But the other half of the time is spent, who on the team is the right person to go pair up with the Dell team and get the Dell team brought into a discussion. And it's going bi-directionally right now. The volume is picking up. The velocity is picking up and it really seems to be like that snowball just going down the hill. It's just picking up speed and with every interaction we're gaining trust with each other, we're gaining competence in what the message is and how to solve for it. And we're working out the various ways, you know, in a predictive way, what are most people asking for? But the wonderful thing is, there's custom availability to figure out a solution for just about any problem that the IT or infrastructure focused teams in the enterprise are looking to solve for. >> Tony, sticking with you for a final question or two, in terms of the last, you know, few months, have you seen any industries in particular that are really readily adopting this? We've seen so much change across industries in the last 18 months. I'm just curious if you're seeing any industries that are particularly taking advantage of this capability and this partnership. >> Yeah. I would point to highly regulated industries. Thinking about financial, thinking about governments, and it's not just a US situation. This is a global situation and data sovereignty where that matters to a particular customer, is really important that they keep that data in the geography that it needs to stay in. It's defined by the different governments around the world. You know, you see, the financial industry has been a first mover towards electronic trading and really disrupted, thankfully, prior to the pandemic, the way trading was done. Because in-person trading wasn't going to happen anymore. And so in the highly regulated world, that healthcares, the financials. Those folks are definitely looking for a solution that has certifications across the board to help them say to their auditors, we've got this covered. That's something we were able to bring to the table for Dell. And then it also helps that the first movers sort of towards a digital infrastructure were insurance companies and others that saw the value of leveraging partnerships and bringing together things as quickly and fast as they could, without deploying huge global networks to try and make it all happen. They can instead virtually meet in the same room, leveraging our software defined network called Equinix Fabric. It's been a real win for the regulated industries, certainly. >> Got it. Thanks for that, Tony. Caitlin, last question for you. This is Dell managed, so single bill from Dell. Where can the viewers go to learn more information about this new partnership? >> Delltechnologies.com/apex. You'll learn more about all things APEX. Really, the APEX consoles, the experience, so you can learn more about it there. And then of course, your friendly neighborhood, Dell EMC rep, and or channel partner, now that we've got that partner enablement as well. >> Delltechnologies.com/apex. Caitlin and Tony, thank you so much for joining us today, sharing the exciting news about what's new with Dell and Equinix and what's in it for your customers and your partners. We appreciate your time. >> Thanks, Lisa. >> Thank you, Lisa. >> For Caitlin Gordon and Tony Frank, I'm Lisa Martin, you've been watching a "Cube" conversation. (soft music playing)

>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Hey, welcome to theCUBE's coverage of IBM Think 2021. I'm Lisa Martin. I have two IBM alumni with me here today. Please welcome Briana Frank, the Director of Product Management at IBM and Jason McGee is here as well, IBM Fellow, VP and CTO of the,IBM Cloud Platform. Brianna and Jason. Welcome back to theCUBE. >> Thanks Lisa. >> Thank you so much for having us. >> You guys were here a couple of months ago but I know there's been a whole bunch of things going on. So Brianna, we'll start with you. What's new? what's new with IBM Cloud? >> We--it's just, it's been such a rush of announcements lately, but one of my favorite announcements is the IBM Cloud Satellite product. We went GA back in March and this has been one of the most fun projects to work on as a product manager. Because it's all about our clients coming to us and saying, "Hey, look, we're having, these are the problems that we're really facing with as we move to cloud and our journey to cloud and can you help us solve them?" And I think this has been just an exciting place to be in terms of distributed cloud. This new category that's really emerging where we've taken the IBM Cloud but we've distributed into lots of different locations on-prem, at the edge and on other public clouds. And it's been a really fun journey and it's such a great fulfilling thing to see it come to life and see clients using it and getting feedback from analysts and the industry. So it's been a great a few months. >> That's good. Lots of excitement going on. Jason talk to me a little bit about, kind of unpack the cloud satellite from your seat which is flashing in Jason's background as an IBM Cloud Satellite neon sign I love that. But talk to me a little bit about the genesis of it. What were some of the things that customers were asking for? >> Yeah, absolutely. So okay I think as we've talked about a lot at IBM as people have gone on their journey to cloud and moving workloads in the cloud over the last few years. Not all workloads have moved, maybe 20% of workloads have moved to the cloud and that remaining 80%, sometimes the thing that's inhibiting that is regulation, compliance, data latency, where my data lives. And so people have been kind of struggling with how do I get the kind of benefits and speed and agility to public cloud, but apply it to all of these applications that maybe need to live in my data center or need to live on the edge of the network, close to my users or need to live where the data is being generated or in a certain country. And so the genesis of satellite was really to take our hybrid strategy and combine it with the public cloud consumption model and really allow you to have public cloud anywhere you needed it. Bring those public cloud services into your data center or bring them to the edge of the network where your data is being generated and let you get the best of both. And we think that really will unlock the next wave of applications to be able to get the advantages of as a service kind of public cloud consumption while retaining the flexibility to run wherever you need. >> Curious station. Did you see any particular industries in the last year of I don't want to say mayhem, but mayhem taking the lead and the edge in wanting to work with you guys to understand how to really facilitate digital business transformation because we saw a lot of acceleration going on last year. >> Yeah, absolutely. I mean, it's interesting cloud is fundamentally a pretty horizontal technology. It applies to lots of industries. But I think this past year especially with COVID and lockdowns and changes in how we all work have accelerated massively clients adoption of cloud. And they've been looking for ways to apply those benefits across more of what they do. And I think there's different drivers there's security compliance drivers maybe in places like the financial services industry but there's also industries like manufacturing and retail that have, they have a geographic footprint like where things run matters to them. And so they're like, "Well, how do I get that kind of remote cloud benefit in all those places too? And so, I've seen some acceleration in those areas. >> And one of the interesting things that I thought has emerged from industry focus is this concept of our FS cloud control. So we have specific control and compliance built into the IBM Cloud. And one of the most prevalent questions I get from clients is "When can I get those FS cloud controls in satellite, in all of these different locations?" And so we've built that in that's coming later this year but I was really surprised to hear every industry. And I guess I shouldn't be surprised I mean, every industry is trading money. So it's important to keep things secure but those FS cloud controls being extended into the satellite location is something I hear it constantly as a need no matter the industry, whether it's retail or insurance et cetera. So I think that the security concerns and being able to offload the burden and chores of security is huge. >> One of the things we saw a lot last year and along the security lines was ransomware. Booming ransomware as a service ransomware getting more personal. I talked to a lot of customers and to your point in different industries that are really focused on, it's not if we get hit by ransomware, it's when. so I'm wondering if that, if some of the things that we saw last year, or maybe why you're seeing this being so such a pervasive need across industries. What do you think? >> Absolutely. I think that it's something that you really have to concentrate on full time and it has to be something you're just maniacally focused on. And we have all kinds of frameworks and actually groups where we're looking at shaping regulation and compliance and it's really something that we study. So if, when we can pass on that expertise to our clients. And again, offload them. So not everyone can be an expert in these areas. I find that relieving. Our clients have these operational and security chores allows them to get back to what they want to do. Which is actually just keep inventing and building better technology for their business. >> I think that's such a-- I think that's such an important point that Briana is bringing it up too that was like part of the value of something like satellite is that we can run these technology platforms as a service. And well, what does as a service means? It means you can tap into a team of people who are the industry's best at building and operating that technology platform. Like maybe you've decided that Kubernetes and OpenShift is your go-forward platform as a business. But do you have the team and skills that you need to operate that yourself? You want to use AI. You probably don't want to become an expert in how to run like whatever the latest and greatest AI framework is. You want to actually like figure out how to apply that to your business. And so we think that part of what's really attracting people to solutions like satellite, especially now with with like the threats you described is that they can tap into this expertise by consuming things as a service instead of figuring out how to run it all themselves. >> Yeah. To that point. A lot of times we see really talented developers. I really like talking to incubation teams where they're building new and they're just trying to figure out how to create the next new thing. And it's not that they're not talented enough. They could do whatever they put their mind to. It's just that they don't have enough time. And they, then it just becomes, comes down to what do you really want to spend your time doing? Is it security and operational chores or is it inventing the next the big thing for your business? And I think that that's where we're seeing the market really shift is that, it's not efficient or a great idea and no one really wants to do that. So if we can offload those chores then that becomes really powerful. >> It does. Resource allocation is key to let those businesses to your point. We're going to focus on their core competencies innovating new products, new services, meeting customers where they are as customers like us become more and more demanding of things they are readily available. I do want to understand a little bit, Jason, help me understand. How this service is differentiated from some of the competitors in the market? >> Yeah. It's a totally fair question. So I would answer that in a couple of ways. First off, anytime you're talking about extending a cloud into some other environment you obviously need some infrastructure for that application to run. And whether that infrastructure is in your data center or at the edge or somewhere else. And one of the things that we've been able to do is by leveraging our hybrid cloud platform by leveraging things like OpenShift and Linux, we've been able to build satellite in a way where you can bring almost any-- infrastructure to the table and use it to run satellite. So we don't require you to buy a certain rack of hardware or a particular gear from us. You don't have to replace all your infrastructure. You can kind of use what you have and extend the cloud. And that to me is all about, if the goal is to help people build things more quickly and consume cloud, like you don't want step one to be like wheel in a whole new data center full hardware before you can get started. The second thing I would say is, we have built our whole cloud on this containerized technology on Kubernetes and OpenShift which means that we're able to deliver more of our portfolio through satellite. We can deliver application platforms and databases and Dev tools and AI and security functions all as a service via satellite. And so the breadth of cloud capability that we think we can deliver in this model is much higher than what I think our competitors are going to be able to do. And then finally, I would say the tie to kind of IBM's view of enterprise and regulated industries, the work Briana mentioned around things like FS cloud the work we're doing in telco. Like we spend a lot of our energy on like, how do we help enterprises regulated industries take advantage of cloud. And we're extending all of that work outside of our cloud data centers with satellite to all these other places. And so you really can move those mission critical applications into a cloud environment when you do it with us. >> Let's talk about some successes. Brianna, tell me about some of the customers that are getting some pretty big business outcomes. And this is a new service. And talk to me about how it's being used, consumed and the benefits. >> Absolutely. What I find a trend that I'm seeing is really the cloud being distributed to the edge. And there are so many interesting use cases I hear every single day about how to really use machine learning and AI at the edge. And so, maybe it's something as simple as a worker safety app or you're making sure that workers are safe using video cameras in an office building and alerting someone if they're going into a construction area and you're using the AI and all of the images that's coming, they're coming in through the security cameras you're doing some analysis and saying, all right this person is wearing a hard hat or not and warning them. But those use cases can be changed so quickly. And we've seen that. And I think I've talked about it before with COVID you changed that to masks. You could change that you could hook up the application of thermal devices. We've seen situations where machine learning is used at the manufacturing edge. So you can determine if there's an issue with your production of in a factory we're seeing as use cases in hospitals in terms of keeping the waiting room sanitized because of over usage. So there's all kinds of just really interesting solutions. And I think this is kind of the next area where we're really able to, and even partner with folks that have extraordinary vertical expertise in a specific area and bringing that to life at the edge and being able to really process that data at the edge so that there's very little latency. And then also you're able to change those use cases so quickly because you're really consuming cloud native best practices in cloud. Cloud services at the edge. So you're not having to install and manage and operate those services at the edge it's done for you. >> I'd mentioned changing the ability to change use cases so quickly in a year that plus that we've seen so much dynamics and pivoting is really key for businesses in any industry Brianna. >> I agree. And that's the thing. There hasn't been one particular industry. I think of course we do see a lot in the financial services industry, just probably cause we're IBM, but in every industry, we see retail, it's interesting to see sporting goods companies want to have pop-up shops at a specific sporting events. And how do you have a van that is a sporting good shop but it's just there temporarily. And how do you have a satellite location in the van? So there's really interesting use cases that have emerge just over time due to the need to have this capability at the edge. >> Yeah. Necessity is the mother of invention, as they say right? Well, thank you both so much for stopping by and sharing what's going on with IBM Cloud Satellite, the new service, the new offerings, the opportunities in it for customers. I'm sure it's going to be another exciting year for IBM cause you clearly have been very busy. Thank you both for stopping by the program. >> Thank you. >> Thanks so much Lisa. >> For Briana Frank and Jason McGee. I'm Lisa Martin. You're watching theCUBE. Live coverage of IBM Think. (upbeat music) (upbeat music)

>>from >>around the globe, it's the cube with digital coverage of IBM Think >>2021 >>brought to you by IBM. >>Hey, welcome to the cubes coverage of IBM Think 2021. I'm lisa martin, I have to IBM alumni with me here today please welcome Brianna frank the director of product management at IBM and Jason McGee is here as well. IBM fellow VP and Cto of the IBM cloud platform, Brianna and Jason welcome back to the cube. >>Thank you so much for having us, >>you guys were here a couple months ago, but I know there's been a whole bunch of things going on. So Brianna, we'll start with you, what's new, what's new with IBM cloud? >>We are, it's just, it's been such a rush of announcements lately, but one of my favorite announcements uh, is the IBM cloud satellite product. We went g a back in March and you know, this has been one of the most fun projects to work on as a product manager because you know, it's all about our clients coming to us and saying, hey look, we're having these are the problems that we're really facing with as we, as we move to cloud in our journey to cloud and can you help us solve them? And I think this has been just an exciting place to be in terms of distributed cloud, this new category that's really emerging where we've taken the IBM cloud, but we've distributed into lots of different locations on prem at the edge and on other public clouds. And it's been a really fun journey and it's such a great fulfilling thing to see it come to life and see clients using it and getting feedback from analysts and um in the industry. So it's been a, it's been a great, you know, a few months. >>That's good. Lots of excitement going on. Jason talk to me a little bit about kind of unpack uh, the cloud satellite from, you see what flashing in Jason's background is an IBM cloud satellite. Me, I'm sorry, I love that. You talk to me a little bit about the genesis of it. What were some of the things that customers were asking for? >>Yeah, absolutely. I mean, so, so look, I think as we've talked about a lot of IBM, you know, as as people have gone on their journey to cloud and been moving workloads in the cloud over the last few years, um, you know, not all workloads have moved right. Maybe 20 of workloads have moved to the cloud and that remaining 80% sometimes that thing that's inhibiting that is regulation compliance data late and see where my data lives. And so people have been kind of struggling with, how do I get the kind of benefits and speed and agility to public cloud, But apply it to all these applications that maybe need to live in my data center or need to live on the edge of the network close to my users or need to live where the data is being generated or in a certain country. And so the genesis of satellite was really to take our hybrid strategy and combine it with the public cloud consumption model and really allow you to have public cloud anywhere you needed it, bring those public cloud services into your data center or bring them to the edge of the network where your data is being generated and let you get the best of both. And we think that really will unlock, you know, the next wave of applications to be able to get the advantages of as a service kind of public consumption um, while retaining the flexibility to run wherever you need, >>curious station, did you see any particular industries in the last year of, I don't want to say mayhem, but you know, mayhem taking really the lead and the edge in wanting to work with you guys to understand how to really facilitate digital business transformation, because we saw a lot of acceleration going on last year. >>Yeah, absolutely. I mean, it's interesting. Cloud is fundamentally pretty horizontal technology. It applies to lots of industries, but I think the past year, especially, um, with, you know, Covid and lockdowns and changes in how we all work have accelerated massively, um, clients adoption of cloud. Um, and they've they've been looking for ways to apply those benefits across more of what they do. All right. And, and I think there's different drivers, you know, there's, you know, security compliance drivers, maybe in, in places like the financial services industry, but there's also the industries like manufacturing and retail that have, you know, they have a geographic footprint, like where things run matters to them. And so they're like, well, how do I get that kind of remote cloud benefit in all those places too. And so I've seen some acceleration in those areas. >>And one of the interesting things that I thought has emerged from an industry focus is this concept of RFs file control. So we have specific control and compliance built into the IBM cloud and one of the most prevalent questions I get from clients, you know, when can I get this FSL controls in satellite, you know, in all of these different locations. And so we built that in that's coming later this year. But I was really surprised to hear every industry and I guess it shouldn't be surprised. I mean every, every industry is trading money so it's important to keep things secure. But those fs cloud controls being extended into the satellite location is something I hear constantly as a need no matter the industry, whether it's, you know, retail or insurance, you know, etcetera. So I think that the security concerns and being able to offload the burden and chores of security is, is huge. >>One of the things we saw a lot last year, Brianna along the security lines is was ransomware booming, ransomware is a service, ransomware getting more personal. Talk to a lot of customers and to your point in different industries that are really focused on, it's not if we get hit by ransomware, it's when. So I'm wondering if that if some of the things that we saw last year or maybe why you're saying this being so such a pervasive need across industries, what do you think? >>Absolutely. I think that it's something that you really have to concentrate on full time and you know, it has to be something you're just maniacally focused on. And we have all kinds of frameworks and actually, uh, groups where we're looking at shaping regulation and compliance and it's really something that we study. Um, so if when we can pass on that expertise to our clients and again offload them. So, you know, not everyone can be an expert in these areas. I find that, you know, relieving, you know, our clients of these operational security tours allows them to get back to what they want to do, which is actually just keep inventing and building better technology for their business. >>I think that's such a, I think that's such an important point that brand is bringing up to those like part of the value of something like satellite is that we can we can run these technology platforms as a service. Right. And well, what does that? The service means? It means you can tap into a team of people who are the industry's best at building and operating that technology platform, right? Like maybe you've decided that, you know, kubernetes and open shift is your go for or platform as a business, but do you have the team and the skills that you need to operate that yourself? You know, you want to use a I you probably don't want to become an expert in how to run like whatever the latest and greatest ai framework is, you want to actually like figure out how to apply that to your business. And so we think that part of what's really attracting people to solutions like satellite, especially now with the threat you described is that they can tap into this expertise by consuming things as a service instead of figuring out how to round all themselves >>to that point. A lot of times we see really talented developers, I really like talking to incubation teams where there, you know, they're building new and they're just trying to figure out how to create, you know, the next new thing and um, it's not that they're not talented enough, they could do whatever they put their mind to, it's just that they don't have enough time and they, you know, then it just becomes too, comes down to, you know, what do you really want to spend your time doing? Is it, you know, security and operational chores, or is it inventing the next big thing for your business? And I think that that's where we're seeing the market really shift, is that, you know, it's not efficient or you know, um you know, a great idea and really no one wants to do that, you know, so we can over, if we can offload those chores, then that becomes really powerful. >>It does resource allocation is key to let those businesses to your point, we're gonna focus on their core competencies, innovating new products, new services, meeting customers where they are as customers like us become more and more demanding of things being readily available. I do want to understand a little bit, Jason, help me understand how this service is differentiated from some of the competitors in the market. >>Yeah, it's a it's a totally fair question. Um so I would answer that in a couple of ways. Um first off, you know, anytime you're talking about extending a cloud into some other environment, you obviously need some infrastructure for that application to run on whether the infrastructure is in your data center or at the edge or somewhere else. And one of the things that we've been able to is by leveraging our hybrid cloud platform by leveraging things like open shift and Lennox, we've been able to build satellite in a way where you can bring almost any clinics infrastructure to the table and use it to run satellite. So we don't require you to buy a certain lack of hardware or particular gear from us. You don't have to replace all your infrastructure. You can kind of use what you have and extend the cloud and that to me is all about, you know, if the goal is to help people build things more quickly and consume cloud, like you don't want step one to be like wheel in a whole new data center full of hardware before you get started. Um the second thing I would say is we have built our whole cloud um on this, this containerized technology, on kubernetes and open ship, which means that we're able to deliver more of our portfolio through satellite. We can deliver application platforms and databases and Deb tools and ai and security functions all as a service via satellite. So the breath of cloud capability that we think we can deliver in this model is much higher than what I think our competitors are going to be able to do. And then finally, I would say the tide to kind of IBM view of enterprise and regulated industries, you know, the work brand I mentioned around things like FS cloud, the work we're doing in telco, like we spent a lot of our energy, I'm like, how do we help, you know, enterprises regulated industries take advantage of cut and we're extending all of that work outside of our cloud data centers with satellite to all these other places. And so you really can move those mission critical applications into a cot environment when you do it with us. >>Let's talk about some successes Brianna tell me about some of the customers that are getting some pretty big business outcomes and this is a new service to talk to me about how it's being used consumed in the benefits. >>Absolutely. You know what I I find a trend that I'm seeing is really uh the cloud being distributed to the edge and there's so many interesting use cases I hear every single day about how to really use machine learning and ai at the edge. And so you know, maybe it's something as simple as, you know, a worker safety app or you're you know, making sure that workers are safe using video cameras in an office building and alerting someone if they're going into a construction area and you're using the Ai and although the the images that's coming, they're coming in through the security cameras, you're doing some analysis and saying this person is wearing a hard hat or not and warning them, but that those use cases can be changed so quickly. And you know, we've we've seen that, I think I've talked about it before with Covid you change that to masks. Um you could change that. You could hook up the application of thermal devices. We've seen situations where you know, um machine learning is used at the manufacturing edge. So you can determine if there's an issue with your um production of, you know, in a factory there's we're seeing uh edge use cases and hospitals in terms of, you know, keeping the waiting room sanitized because of, you know, over usage. So there's all kinds of just really interesting solutions and I think this is kind of the next area where we're really able to um and even partner with folks that have extraordinary vertical expertise in a specific area and you know, bringing that to life at the edge and being able to really process that data at the edge. So there's very little latency and then also you're able to change those use cases so quickly because you're really consuming cloud native best practices in cloud cloud services at the end. So you're not having to install and and manage and operate those services at the edge. It's done for you >>imagine changing the ability to change use cases so quickly in a year that plus that we've seen so much dynamics and pivoting is really key for businesses in any industry Brianna. >>I agree. And that's the thing. You know, there hasn't been one particular industry I think, you know, of course we do see a lot in the financial services industry just probably because we're IBM, but in every industry, you know, we see, you know retail, it's interesting to see sporting goods companies want to have pop up shops in a specific sporting events and how do you, you know, have a van that is a sporting goods shop, but it's just there temporarily. And how do you have a satellite location at, in the van? So there's really interesting use cases that, you know, have emerged, um, you know, just over time due to, um, you know, the need to have this capability at the edge. >>Yeah, it's necessity is the mother of invention as they say, right, well thank you both so much for stopping by sharing what's going on with IBM Cloud Satellite, the new service, the new offerings, the opportunities in it for customers. I'm sure it's going to be another exciting year for IBM because you clearly have been very busy. Thank you both for stopping by the program. >>Thanks. Thanks so much lisa >>for Brianna frank and Jason McGee. I'm lisa martin. You're watching the cube live coverage of IBM, think. >>Mm

>> Announcer: From the theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE coming to you from our Palo Alto studios. Today we're going to have a CUBE conversation really about this kind of ongoing evolution of cloud, and it was a huge deal, and AWS came on the scene and really launched kind of the public cloud evolution, which not only was a different technology stack, but really a different way to think about things, a different way to think about workloads. And that has evolved to hybrid cloud and multicloud, and it just continues to evolve over time. So we're going to get some of the experts in from IBM to talk about their perspective and what they're doing all about it. So we're excited to invite our next guest. She is Briana Frank. She's the director of product management for IBM. Briana, good to see you. Where are you joining us from today? >> I am joining you from Wake Forest, North Carolina. And as you can see, I'm from my home office, but always busy working and fun doing things in the cloud and thinking about new technologies even when we're at home. >> Excellent. And also joining us, many-time CUBE alumni Jason McGee, IBM fellow, vice president and CTO of IBM Cloud Platform. Jason, great to see you again. I looked it up before we turned on the cameras. I think you've been on, like, eight times. So you're definitely a VIP in the CUBE alumni world. Where are you joining us from today? >> Yeah, I mean, I'm in Apex, which is outside of Raleigh, and great to be here again. It's always fun to talk to you guys. It's been a little while, but great to be back. >> Yeah, so let's just jump into it, right? You've all seen the memes revolving around what's driving your digital transformation. Is it the CEO, the CIO, or COVID? And we all know the answer to the question. It's really been an interesting time, right? It was kind of a light switch moment in mid-March. And then people are saying, you know, years and years of digital transformation kind of suddenly compressed into this light switch moment. But now we're months and months and months later, we're in October, and it's clear that this is not just a a one-time fix and wait till we all go back to work. This is going to continue for a while. And cloud is such a huge enabler. Had this happened five years ago, 10 years ago, 15 years ago, the ability for information workers, like the businesses that we're in, would've been much more difficult. So acknowledging that there's still a lot of people hurting, a lot, hospitality industry, restaurant industry, sports places that aggregate people, concerts. We're fortunate we're in the information industry. And I'd just love to get your perspective, Jason, on cloud as an enabling platform and really an enabling way of thinking about things that have made this transition a little bit less painful than it otherwise would've been. >> Yeah, that's a great point, Jeff, and I think on one hand it's been pretty amazing to see how much our industry in technology and IT has been able to kind of adapt to COVID, adapt to working at home, adapt to these kinds of changing models. But what's been really interesting is as someone who spends all their time thinking about cloud every day, it's been really incredible to see how much it's accelerated people's adoption of cloud. Like, obviously everyone was leveraging cloud. They had plans to move more and more workloads to cloud. But I think over the last six months we've really seen a massive acceleration, and I also think kind of a mindset shift that maybe before there was some hesitation and conversation about what things move to cloud and what things don't, and that seems to have kind of gone away, and everyone's like, this is the model that not only will carry us through moments like this, but we have newfound confidence that it's the right model for us to move the majority of our businesses to. >> Right. >> So really massive acceleration. >> Massive acceleration. And Briana, get your take, 'cause you're a product manager, so you're in the weeds on the speeds and feeds and the features and functions. Cloud as a concept sounds kind of simple, but the execution is not so simple. And we've seen kind of this morphing from moving your test dev maybe to a public cloud, IBM has a cloud, to there's some stuff that just can't go on the cloud or shouldn't go to the cloud or I'm not sure if it should go in the cloud. So now we're hearing talk of hybrid cloud and multicloud, and we're hearing pieces of public cloud in my own data center and pieces of my own data center in a public cloud. It's a pretty complicated space. I wonder if you can kind of share your perspective as this thing morphs from kind of a simple concept and a beautiful little icon to a much more complex execution in the real world. >> Well, great question and insights. And I think, building off of what Jason said, I think the most important shift I've seen is really a mind shift, a mindset shift. And there's so much more empathy that I'm seeing across the board, whether it's children running in the background or cats and pets, there's a lot more tolerance for work-life balance and a lot more empathy for how people are getting through this really challenging pandemic. And what I think is interesting is that kind of carries over into the technology. And so now where some of our clients were solving problems like keeping their workforce safe by using video analytics to see if someone's using or wearing maybe a hard hat in a construction zone. Now that use case has sort of shifted, and now it's is someone wearing a mask? Do they have a temperature? How do we make sure that the office areas are sanitized and clean so that when people go back to work, they'll be working in a safe environment? So I think that the mindset shift is really driving a lot of these technology innovations. And then of course you need cloud to make those real. So I think that's the kind of aha moment I've seen is that people are leading with empathy and that's driving kind of the next wave of innovation that I'm seeing. >> I have to say I've been doing these many, many years, and Briana, I don't think anyone has brought up empathy at the at the head end of the open. And I love that 'cause I think that's a way to think about it, right? 'Cause these are people trying to execute business activities, and it's not easy. And that's a really great take. Jason, I want to go back to you and talk about one of the things we talked about the cloud, but really it's about enabling applications, right? And really, the application now has become this first class citizen where it's, this is the app I want. Cloud enables me to use whatever infrastructure I need versus this is the infrastructure I have. Hm, what can I put on this app? So I'd love to get your take. As you said, you think about cloud all the time, but really, cloud is an app enabler. And how has, as that capability has been gifted to people, how has that made the the cloud execution a lot more complex? >> Yeah, you know, it's interesting. I think you're hitting on a really key transformation that's happened in cloud over the last few years, which is that it's gone from infrastructure kind of cost optimization to an application delivery accelerator. And what I think that's caused is everyone's starting to kind of move their thinking up the stack in cloud, and you see the rise of technologies like Kubernetes and OpenShift as a platform that enables application developers to build applications and deliver them more quickly. I think the acceleration that we've been talking about here has cemented that. At the end of the day, we're all trying to figure out in our businesses how to adapt to change. We have some new changes this year that maybe we didn't predict we would have last year. We're trying to figure out how to adapt to those to deliver new capabilities, to maybe build a digital experience for something that we didn't have a digital experience for before, 'cause now nobody is face to face. And that requires cloud to be much more application-centric. It requires cloud, you alluded to this kind of evolution. I think it's starting to drive cloud into more places. Cloud isn't about just getting into some big cloud data center somewhere. Cloud is about a style of working and a set of technologies that I want to be able to consume wherever I need them. So that kind of application-centric capability and the rise of cloud-native technologies I think go hand in hand. >> Right, so it got to us from a simple dev swiping a credit card to do a little project on Amazon to now enterprising having very complex ecosystems, right? Very complex situation because they've got lots of different clouds and lots of different apps running on lots of different clouds, and the application and the control of those is now much more complicated than probably when you just had it all in your own data center or if you're some cloud data organization and you grew up on the public cloud and you really are kind of a single app that happens to be a big one in hyperscale. So I'm curious, Briana, you guys have a ton of customers. What are they telling you about what they're doing with hybrid cloud, managing hybrid cloud, trying to get back to some of the simplicity and kind of the simplistic vision and execution when what's happening is probably increasing complexity as different apps are running on different clouds, different places. >> Yeah, great question. You know, I think that what we're hearing from our clients is really a couple of things. One is that they have to find ways to unburden their teams. They only have limited resources and the sky's the limit in terms of what's possible. So they need to be able to innovate faster, but they have to unburden the team. So the rise of "as a service" I think is really coming into its own because teams don't have time to manage things like Kubernetes. They have to go higher in the stack and really start to build and innovate for their own business differentiation. But another I think really important thing that we're hearing from our clients is that we have to meet them where they are in their journey. So what you said was great. A lot of our clients are using five to nine different clouds today, and that's extraordinarily fragmented, and being able to manage and have one way to see what workload is running where and what is running on that workload is really important. And having kind of one single pane of glass where they can manage everything is one of the single most important features that I hear that is needed. And I think the other thing that I hear a lot from clients is they need flexibility. They need flexibility for, you know, where they are in their journey. Some folks, they need to be able to deploy to existing infrastructure that they have in their data center, and others need to be able to deploy to another public cloud. And having the flexibility to run anywhere is one of the more common themes that I'm seeing. >> Right, so, and you guys built something to help with that, right? It's the IBM cloud satellite. So you just basically outlined the customer challenge, so what did you have to do to enable them to have a single pane of glass, to have more control across these disparate projects running in disparate clouds. >> Well, so one of the things that we found is our clients really, all of the agility that they need to adopt cloud data best practices, really comes from the public cloud. The public cloud services, DevOps, all the tools that allow you to really run and move faster and innovate faster, but they needed that ability to consume those public cloud services anywhere. So at the edge, on another public cloud, or in their existing infrastructure. And of course there's tons of infrastructure options. We have infrastructure for our clients that they can use. We have turnkey appliances. But really having that public cloud, cloud-native agility, but really bringing that anywhere that our clients want to run it is the key to satellite. >> Right, right. So it's not kind of what would be typically thought of as a hybrid cloud solution per se, but it's really almost kind of a level up, if I'm hearing you correctly, in controlling all the different kind of instances or instantiations of your cloud execution. That'd be accurate, Jason? >> Yeah, well, or maybe another way to think about it is it's a way of consuming hybrid, right? It's a way of consuming these hybrid cloud capabilities. Hybrid starts with a common platform, and this idea that we are using things like OpenShift as that common technology platform that enables customers to build applications once and run them anywhere. What satellite brings to the table is it takes that base technology platform and it delivers it as a cloud service, and a cloud service that's flexible enough to be anywhere. And so you kind of combine the best of both. You combine a common technology approach and you combine the as a service API-based consumption model of public cloud to get a hybrid strategy that's super flexible, right? And now really lets customers focus on the work that they're doing going faster. And at IBM, we've been pretty clear that we think the future of hybrid cloud computing is rooted in technologies like Kubernetes and OpenShift, that that's the platform of the future. The acquisition of Red Hat was motivated by that strategy. Our public cloud for the last three-plus years has been built internally on top of the same technologies. And so what we've done with satellite from a technology perspective is we've taken the things that we do in our cloud and we've used the power of of Kubernetes and OpenShift to deliver those anywhere, right? And to give customers that same experience on their infrastructure or on some other public cloud. >> Right. I love it because it's kind of cloud on cloud, if you will, but it really supports this notion of the customer experience, and even more importantly in some ways, the developer experience to make sure that your developers inside the house are feeling good, have a great productive environment so they can do a better job with what they're working on. And that that sounds like something they would really, really enjoy and be native to the way they're used to working already. >> It's interesting too, one of the kind of interesting, I don't know, adoption trends we're starting to see with approaches like satellite is if you think about cloud, I'll oversimplify, but you could say there's kind of two big transformations. One is move my workload to a public cloud, and the other is change how my team works, right? Adopt cloud-native, agile best practices. And often to get to the culture change of the team, you had to start with moving the app, but that's hard, especially for the kind of 80% of workloads that we're seeing move to cloud now where they're complex. They have lots of ties into data that you have in your data center. So it's hard to move them sometimes. So with approaches like satellite, you can kind of flip the order. You can bring the cloud in house, if you will. You can start to adopt self-service and API-based consumption and DevOps and change how your teams work and make them more efficient without moving the applications. And then later, if it makes sense to move them, you can, right? And I think that's really powerful. >> Right, right. Briana, I want to go back to you on kind of the nuts and bolts. 'Cause I don't know if you've read "Innovator's Dilemma" by Christian Clayton. You should if you haven't. But one of the things is how do you prioritize what you're building? How do you prioritize your feature stack? Because you have to, right? You have to put one in front of the other, and it's going to drive your design decisions and what you ultimately ship. So as you were thinking about satellite, what were kind of your top-level design priorities that you're really building this towards that you wanted to make sure you really nailed? >> Oh, what a great question. I love that question. I'm so passionate about product and design and I think we take it very seriously at IBM, and it's, we have an amazing design department, if you will, at IBM. And one of the things we do is just relentlessly interview our clients, and we really try to understand what their main issues are. And one of the first use cases that we we looked at was actually in the financial industry, which was, in the financial services industry, the differentiation is really all about the technology itself, and so they're constantly having to innovate at a faster pace so they can bring new features and functions to their clients but they have this dilemma where they have to, in some cases, in many cases, keep the data on-prem in a specific location. And that starts to get really interesting, because sometimes the regulations, it could be country, it could be a compliance thing, but for whatever reason, there is a specific requirement, and sometimes that comes with a fine if that data doesn't reside in that location. So having the ability to move at an incredibly fast pace and keep innovating, but keep that data on-prem and offload the management of Kubernetes and the services that allow them to move fast. That was one of the first use cases that we tackled. And I think that's a pretty important one, because if you can get that right, that starts to permeate all other industries, because you want to, you have to be secure. You have to make sure that the data resides and is on-prem and in a specific location and that it's auditable. So I think that was one of our first use cases, and that has served us really well. We also, one of the things that we do inside of IBM is that we co-develop using our own internal workloads. And so we use the data and AI team within IBM will GA with us when we GA IBM Cloud Satellite, and so their workloads are running on top of satellite. And I think that's a great way to come to market because when you're delivering an MVP, but if you can deliver an MVP that's already running a really complex AI workload, that's a pretty impressive MVP, if you ask me. So we try to do that whenever we release new products, and I think that has served us very well because it really forces us to solve the really hard problems first. We don't have a choice. We have to be able to make some pretty strategic choices upfront to be able to deliver something like that. >> That's great. Jason, I want to go back to you and talk about a little bit beyond the cloud, but things that are really interesting and happening, right? You already talked about this big enabler with containers and Kubernetes, but this next thing that's coming, right, is just edge, which is an extension of the cloud, an outpost to the cloud, but this whole concept of getting outside of the data center but actually now starting to bring the compute to the devices that generate the data as well as need that. How do you see that kind of impacting your cloud thoughts? I love that you're thinking cloud all the time. And the other piece, keying off of what Briana just said, is applied AI, right? I mean, I think we all would agree that AI and machine learning as kind of a standard, generic thing is okay, but really the application of the AI and the machine learning for specific use cases is where we're seeing huge, huge benefit. And I would imagine there's many, many kind of areas within cloud execution that AI and machine learning can start to add even more and more and more efficiencies and automation. >> Sure, sure. So maybe a couple comments. I mean, I think the edge thing is so interesting because if you really kind of step back and think about what we were talking about with cloud, what is a cloud is becoming much more diverse. Started as it's these three regions and it's becoming everybody's data centers plus on-prem, and then it's becoming edge, large edge locations, and then it's becoming devices. So clouds are becoming pervasive as a concept across all IT consumption models. And there's core technologies, even, like containers that we think apply at all those levels. They apply in the core cloud, in the data center, at the edge, in a device. And so things like satellite certainly give us a mechanism to push that boundary, to push closer to the end user. And there's a ton of scenarios motivating that. 5G telecommunications and high-speed networking for mobile devices is necessitating pushing closer to where the data's getting generated. IoT, same thing. If you think about the IoT edge case, that's massive data generation. You don't necessarily want to backhaul that all the way back to a central cloud. You want to be able to do AI and training and inferencing on that data close to where it lives. And so you need this whole idea of cloud to kind of expand, and if it doesn't, then what happens is all of these different use cases become like different technology stacks or different operational models and you get tons of complexity. So it's this really interesting intersection, and I think we're getting much more complex in how we deploy, but we're trying to put common ideas over the top of it to simplify, and I think that's pretty interesting. On the AI question, you're right, there's tons of places where AI, applied AI will come into the picture. At IBM, we're doing a ton of work on AI for IT operations and how do we apply AI modeling to monitoring, to resiliency, even to workload placement. I mean, just think about the world we just described. As a customer, maybe I have IBM cloud and I have 20 satellite locations in all our fun places in the world, and now I have to make decisions about what runs where and where should I deploy my workloads and what's the most efficient way to place workloads to get availability or better performance, and AI plays a role there. So I see a really bright future as we build out this infrastructure to then use AI as a mechanism to further simplify the customer's consumption of cloud. >> Yeah, that's great. So I want to give you both the last word before we sign off, and that was a good summary, Jason. Cloud's been around for a while and it gets tossed around, and again, now we have hybrid and multi and all these different flavors. You guys are in the weeds and you're seeing down the road a little bit. What is it about cloud that most people probably aren't talking about when you kind of look in your crystal ball, obviously don't share any secrets that you can't share, that gets you excited and makes you think, wow, we're still really, hard to believe, but really in the early days of what this really, the kind of opportunities that this opens up. And I'll go with you first, Briana. >> Well, that's a great question. I think we're already starting to see that with the example of all of the work that we're seeing in the COVID space. It just feels like whatever challenge that might lie ahead in our future, we have an ability to quickly iterate and change and adapt. It's so interesting to see how fast we can roll out new technologies and new ideas. Things that would take years to put together you can kind of put together in a week or so with a quick POC. And that's really an exciting kind of place to be that you can adapt and change so quickly. So I think that's one. And I do think your point about edge is really an important one. There's more and more opportunities to distribute workloads closer to, compute goes closer to where the users are, so therefore you're reducing latency, so you're getting instant feedback. And I think that's really going to be interesting. And then I think the third element, again, is like security and compliance. How do you know exactly that your data stays exactly where you want it to, and you can have proof and you can audit that data. I think that's really where the future's headed. >> Yeah, that's great. And Jason, to you, what's getting you up in the morning today? >> Oh, you don't want to know what gets me up today. But if we talk about what's coming, so for me, my whole career, I've really been thinking about applications. And I think one of the kind of macro trends that everyone doesn't always see that's going on in cloud is we're switching from an IT infrastructure-centric view of computing to an application-centric view. And all of these things we've been talking about are kind of steps along that journey. We're getting to a point where I can build applications, I can build them in a consistent way, I can deploy them anywhere in the world on this incredibly diverse infrastructure. As a developer, I have simple, immediate access to world-class capabilities, to specialized hardware. We are really in the midst of a transformation on how we build computing technology and really a democratization of that technology that 10 or 15 years ago you wouldn't have had the, most people would not have had the funds to stand up the technology they needed to build these things. And that's what really gets me excited, because I think about, well, then what's all the innovation that's going to come from that? As more and more developers have access to this powerful infrastructure in these diverse ways, what are they going to create? And that's what's, I think, going on under the covers. I think we're in the middle of a generational transformation of technology that will result in things we can't predict today because we'll open up so many people's ability to leverage that platform. >> What a great thought to close on, Jason, 'cause I think we hear that consistently all the time. What's the key to innovation? Give more people the access to the tools, give more people access to the data and more people the power to do something with it and create. And we hear all the time about the disadvantaged classes of people that just didn't get the opportunity, and if all those people had the same school, the same education, and now the same basically infinite compute power at their disposal, what are they going to invent? And I think it's an exciting future, and I think that's a great place to close. So we'll leave it at that. I want to thank you both for checking in. Briana, great to meet you, and Jason, always good to see you, as well. >> Yeah, nice to meet you. >> Yeah, great to be here, thank you. >> All right, thanks a lot and have a great day. >> Thank you. >> All right, that was Briana and Jason. I'm Jeff. You're watching theCUBE. Thanks for watching. We'll see you next time. (bright music)

>> Announcer: From around the globe. It's theCUBE. With digital coverage of AWS re-invent 2020 sponsored by Intel, AWS, and our community partners. >> Hi, welcome to theCUBE virtual and our coverage of AWS reinvent 2020. We are theCUBE virtual and I'm your host Keith Townsend. Today I'm joined with Melanie Frank who is managing VP of technology at Capital One. Welcome to theCUBE Melanie >> Thanks for having me glad to be here. >> So first time on theCUBE, but you guys have done something big at Capital One. So we're not going to take it easy on you. This is, this has been hitting the news cycles. You guys have closed down your last data center. What spurred the, the initiative for Capital One to exit to private data center. >> Oh, there's so many cool technology, you think that we'll talk about, but you know, if you want to talk about why that is not tech for the sake of tech in this case, this is about working back from, from what our customer needs are. So I think of how the digital world has transformed our expectations as consumers, right. I, I actually was, I use a digital assistant a lot in the kitchen. And so the other day I was cooking and, you know, I update a shopping list to set a timer. I'm just used to doing those things. And the other day I actually asked my digital assistant to set my stove to 350 degrees, which I do not have a smart stove. It's not integrated with my digital assistant, nothing in my home has that capability right now, but it really kind of struck me as a wow, this whole, like this, this interaction has changed my expectations now for my entire kitchen. And I think that those types of experiences now are what we've come to expect as consumers. And that really was the center of it for us, our shift to cloud and exit of the data centers was all about our ability to provide our customers with experiences that are real-time and intelligent that you just can't do, if you're running on outdated technology in a data center. >> So I absolutely understand the benefits of when you're there. The other day, I was bringing up another circuit in our data center and I'm thinking our virtual data center and I'm thinking, wow, man, this is so easy. I can just issue a command software defined. And now the data centers has redundant connectivity, but getting there is a process can you talk to us about the process and how long it took for Capital One to actually reach that goal. >> Yeah, you know, you're so right. Like it is so nice once you're there, but it is not to be underestimated the, the transformational aspect of this, so this was a part of a massive eight year technology transformation, really. That was about modernizing the way in which we worked as well as the tech infrastructure itself. So our goal was to get to this destination where we were faster and more nimble, like you described with those new capabilities for those customers. But we're talking about this eight year transformation where we transformed our talent. We had to hire product managers, data scientists, designers. We shifted our developer skill sets. We're now sitting at an 11,000 person tech organization with 85% of that being, you know, engineers, we shifted the way we work to agile, is it is just much more conducive to that rapid delivery of value. And then of course, on the tech side, really since about 2014, we've closed eight data centers and rebuilt thousands of applications to take full advantage of the cloud technology and capabilities. >> Cool. So it goes without saying, you guys won the world's biggest financial organizations and you've highlighted the non-technical part of the journey. Can you provide a little bit of insight for us on the, kind of the, your partners within the bank, not just technologists in the technology organization, how was this not necessarily disruptive, but changing, you know, groups like audit your financial services. You're constantly worried about audit. How did audit embraced this change? >> Well, I think there was a huge learning for the entire organization to think about what, what parts of what we do need to be done differently. In some ways there were a lot of benefits if I think about our business partners in the finance team where, you know, you had a data center running with massive amounts of technology infrastructure, perhaps you had to size that technology infrastructure for your peak loads, for us during, you know, holiday shopping periods and things like that. And now we're at a position where we can much more nimbly control the tech. We can audit scale up, we can audit scale down that is much more cost-effective for us, for our business. And then from a financial perspective, you just take that use case for the finance department it's, you know, adjusting so that we can directly show that cost to the line of business and allow them to make the changes that they need, which makes sense for their business and their customers. >> So let's talk about more of that process and the journey from a technology perspective, as we look at something as mature as a bank's infrastructure, not all of those applications can be migrated easily and re-platformed easily. How did you guys deal with those tough last to move application, you know, that last 20%? >> Yeah. I think, you know, it early with that, for us with a declaration that, you know, kind of I'll say the easier part, anything new gets built into the cloud. And as you point out that is way easier than tackling some of those things that you you've probably been dealing with and tackling for a very, very long time, from an application standpoint. We knew early on that it would be better if we could modernize the applications themselves as we moved them to the cloud to really kind of unlock the advantages because there's one part of the advantages of the cloud infrastructure. There is a second part of what it forced was a application modernization and a tech modernization for us. And so those two things together were super powerful. We had a few stubborn ones that we said, okay, can we containerize this? Can we lift and shift this over it's, to me, it was likening to, you know, moving from one house to another and you've, you're kind of cleaning out your attic and you're trying to figure out, ideally, you don't take anything to the new house that you don't need and you do all this cleanup. And at some point you say, well, this I'm going to put in this box and I will deal with it kind of at the new house. And ideally you do that before you put it right back in the attic. So we had a few of those, but in large part, you know, 85%, I think that's, that's part of why it took us so long was let's, let's do this right. And let's get, get this so that these applications can run effectively and take full advantage of the cloud. >> So let's talk about some of the potential benefits and the past eight to nine months. My relationship with my commercial banker, with my private banker have really changed due to the pandemic. Talk to me about some of the advantages or capabilities the bank has gained as a result of moving all almost all. Well now totally to the public cloud. >> Yeah. Yeah. It's a good question. I think I'll start with one that is a little bit more technically oriented then talk about the capabilities. So, you mentioned the pandemic and we had, you know massive amounts of planning as we were kind of taking in the full impact of what was about to happen for our associates and our customers, you know and trying to think through how will customer behavior change during a pandemic? We didn't have a whole lot of indicators as to what that might look like. You know, how is their activity going to change from a transactions, for example, or, you know, are they going to change the frequency with which they're logging in online or paying the cloud gave us the flexibility. As you mentioned earlier to scale rapidly in case the projections that we were making were wrong about consumer behavior. And so we could keep the platforms up and running and recover them much quicker, more resilient infrastructure to make sure that it's up because we really we're in unprecedented times, trying to think through how, how behaviors and needs of customers would change. Secondly, you know, from a capability standpoint, we talked about the need for those real time intelligent experiences that only cloud can give you only modern applications can give you things like, you know Eno, our digital assistant, which is built on a streaming architecture, it can identify unusual charges, 40% tip and alert me in real time. You know, these days 40% tip, I'm trying to help local businesses, that's, that's exactly true. But the fact that Eno is out there kind of looking out and watching my back and saying, this is unusual is, is this you you're transacting a lot online who knows what the fraudsters are looking for. It's those types of experiences that, that you can't build. If you are posting transactions to a mainframe that, you know, runs a batch process overnight, it doesn't help me if you tell me the next day. >> So let's talk about this talent transformation a little bit too, because one of the most difficult things I've witnessed with any type of, of massive transformation like this is recruitment and retention of talent, not the industry hasn't quite built up the talent pool to support such massive transformations. How is this impacting your talent and recruitment processes? >> Yeah. So, massively. And the good news is, you know, given the amount of time we've been on this transformation, we had some time to allow that to adjust, you know, when we started and knowing that, that we were focused largely on AWS, we said, we'd be great if we could go find it, you know thousands of engineers who are, you know, deep experts in AWS, and they didn't necessarily exist at the time given that there, there aren't a whole lot of companies doing what we were doing at the time besides perhaps, you know, AWS themselves and Netflix and they're good partners to us. So we don't need to, to steal everybody's talent. And so we started early on with training and re-skilling our engineers, generally speaking, I find that engineers love using new things. And they in particular love learning newer technologies. I haven't found one yet who's kind of resistant and, you know, wanting to go back and learn COBOL or Fortran like I had to. And I was in college. So, you know, the fact that, that they could, could learn some of these modern tech help evolve and develop them, you know, really kind of push on, on some of the capabilities and, and partner with partners like AWS to enhance the capabilities that are out there. And that's, that's an engineer's dream. The fact that they had, we had plenty of time. We made the declaration that we were going to go all in on cloud. Well, before we targeted getting it done probably before we even knew how in the world we were going to get there, it gave folks plenty of time to think through the training. We provided massive amounts of, of access to learning and training certifications of, for, for everyone to develop the skills that they needed. And I think it's just been great and super fun from a talent perspective. >> I love that you mentioned Netflix, they've been another company that's been extremely public with their journey to the cloud. We kind of think of Netflix is just born in the cloud company and they weren't, and they had a journey to the cloud you share your journey to the cloud. What are some of the pieces of advice, the best practices you can give other companies looking to take that similar journey? >> I will say to, you know, not underestimate the transformative part, for us I think I've said it before. I'll I will say it again. This was not just a tech transformation, you know, this started with our customer needs. It started with a business strategy. It was transformative to our culture for how we, how we think about building and delivering capabilities, as well as the software, then that underlies and supports them. And so I think, you know, starting from a place of where are you trying to go and why? And giving yourself really the fortitude and commitment to achieve it, because you mentioned it, it is not necessarily easy. If you run on a yearly budget cycle, you if, unless you are, you know, running on very few applications at this point, you know, you will not get this done in kind of one year budget cycle, this is a multi-year journey. And ideally you're changing the technology itself, but also how software gets delivered. And therefore then as we just talked about the talent required to do so. >> So Melanie, we've been watching your journey for the past couple of years and we so appreciate you sharing your journey with theCUBE. More importantly, you're now a CUBE alum, and you get all the benefits of the CUBE alum, which has a great headshot that the team has shared, but we really appreciate you sharing a builder's journey at this builder's show. Stay tuned for more coverage of AWS re-invent 2020 via that you.. virtual. Thanks for joining us. (gentle upbeat music)

>>Hi, I'm Frank's Luqman CEO of Snowflake. And welcome to the Snowflake Data Cloud Summit. I'd like to take the next few minutes to introduce you to >>the data cloud on why it matters to the modern enterprise. As an industry, we have struggled to mobilize our data, meaning that has been hard to put data into service of our enterprises. We're not living in a data economy and for most data central how we run our lives, our businesses and our institutions, every single interaction we have now, whether it's in social media, e commerce or any other service, engagement generates critical data. You multiply this out with the number of actors and transactions. The volume is overwhelming, growing in leaps and bounds every day. There was a time when data operations focused mostly on running reports and populating dashboards to inform people in the enterprise of what had happened on what was going on. And we still do a ton of that. But the emphasis is shifting to data driving operations from just data informing people. There is such a thing as the time value off data meaning that the faster data becomes available, the more impactful and valuable it ISS. As data ages, it loses much of its actionable value. Digital transformation is an overused term in our industry, but the snowflake it means the end to end automation of business processes, from selling to transacting to supporting to servicing customers. Digital processes are entirely disinter mediated in terms of people. Involvement in are driven into end by data. Of course, many businesses have both physical and digital processes, and they are >>intertwined. Think of retail, logistics, delivery services and so on. So a data centric operating discipline is no longer optional data operations Air now the beating heart >>of the modern enterprise that requires a massively scalable data platform talented data engineering and data science teams to fully exploit the technology that now is becoming available. Enter snowflake. Chances are that, you know, snowflake as a >>world class execution platform for a diverse set of workloads. Among them data warehousing, data engineering, data, lakes, data, science, data applications and data sharing. Snowflake was architected from scratch for cloud scale computing. No legacy technology was carried forward in the process. Snowflake reimagined many aspects of data management data operations. The result was a cloud data platform with massive scale, blistering performance, superior economics and world class data governance. Snowflake innovated on a number of vectors that wants to deliver this breakthrough. First scale and performance. Snowflake is completely designed for cloud scale computing, both in terms of data volume, computational performance and concurrent workload. Execution snowflake features numerous distinct innovations in this category, but none stands up more than the multi cluster shared stories. Architectural Removing the control plane from the individual cluster led to a dramatically different approach that has yielded tremendous benefits. But our customers love about Snowflake is to spin up new workloads without limitation and provisioned these workloads with his little or as much compute as they see fit. No longer do they fear hidden capacity limits or encroaching on other workloads. Customers can have also scale storage and compute independent of each other, something that was not possible before second utility and elasticity. Not only can snowflake customer spin up much capacity for as long as they deem necessary. Three. Utility model in church, they only get charged for what they consumed by the machine. Second, highly granular measurement of utilization. Ah, lot of the economic impact of snowflake comes from the fact that customers no longer manage capacity. What they do now is focused on consumption. In snowflake is managing the capacity. Performance and economics now go hand in hand because faster is now also cheaper. Snowflake contracts with the public cloud vendors for capacity at considerable scale, which then translates to a good economic value at the retail level is, well, third ease of use and simplicity. Snowflake is a platform that scales from the smallest workloads to the largest data estates in the world. It is unusual in this offer industry to have a platform that controversy the entire spectrum of scale, a database technology snowflake is dramatically simple fire. To compare to previous generations, our founders were bent on making snowflake, a self managing platform that didn't require expert knowledge to run. The role of the Deba has evolved into snowflake world, more focused on data model insights and business value, not tuning and keeping the infrastructure up and running. This has expanded the marketplace to nearly any scale. No job too small or too large. Fourth, multi cloud and Cross Cloud or snowflake was first available on AWS. It now also runs very successfully on mark yourself. Azure and Google Cloud Snowflake is a cloud agnostic platform, meaning that it doesn't know what it's running on. Snowflake completely abstracts the underlying cloud platform. The user doesn't need to see or touch it directly and also does not receive a separate bill from the cloud vendor for capacity consumed by snowflake. Being multi cloud capable customers have a choice and also the flexibility to change over time snowflakes. Relationships with Amazon and Microsoft also allow customers to transact through their marketplaces and burned down their cloud commit with their snowflakes. Spend Snowflake is also capable of replicating across cloud regions and cloud platforms. It's not unusual to see >>the same snowflake data on more than one public cloud at the time. Also, for disaster recovery purposes, it is desirable to have access to snowflake on a completely different public cloud >>platform. Fifth, data Security and privacy, security and privacy are commonly grouped under the moniker of data governance. As a highly managed cloud data platform, snowflake designed and deploys a comprehensive and coherent security model. While privacy requirements are newer and still emerging in many areas, snowflake as a platform is evolving to help customers steer clear from costly violations. Our data sharing model has already enabled many customers to exchange data without surrendering custody of data. Key privacy concerns There's no doubt that the strong governance and compliance framework is critical to extracting you analytical value of data directly following the session. Police Stay tuned to hear from Anita Lynch at Disney Streaming services about how >>to date a cloud enables data governance at Disney. The world beat a >>path to our door snowflake unleashed to move from UN promised data centers to the public cloud platforms, notably AWS, Azure and Google Cloud. Snowflake now has thousands of enterprise customers averaging over 500 million queries >>today across all customer accounts, and it's one of the fastest growing enterprise software companies in a generation. Our recent listing on the New York Stock Exchange was built is the largest software AIPO in history. But the data cloth conversation is bigger. There is another frontier workload. Execution is a huge part of it, but it's not the entire story. There is another elephant in the room, and that is that The world's data is incredibly fragmented in siloed, across clouds of old sorts and data centers all over the place. Basically, data lives in a million places, and it's incredibly hard to analyze data across the silos. Most intelligence analytics and learning models deploy on single data sets because it has been next to impossible to analyze data across sources. Until now, Snowflake Data Cloud is a data platform shared by all snowflake users. If you are on snowflake, you are already plugged into it. It's like being part of a Global Data Federation data orbit, if you will, where all other data can now be part of your scope. Historically, technology limitations led us to build systems and services that siloed the data behind systems, software and network perimeters. To analyze data across silos, we resorted to building special purpose data warehouses force fed by multiple data sources empowered by expensive proprietary hardware. The scale limitations lead to even more silos. The onslaught of the public cloud opened the gateway to unleashing the world's data for access for sharing a monetization. But it didn't happen. Pretty soon they were new silos, different public clouds, regions within the and a huge collection of SAS applications hoarding their data all in their own formats on the East NC ations whole industries exist just to move data from A to B customer behavior precipitated the silo ing of data with what we call a war clothes at a time mentality. Customers focused on the applications in isolation of one another and then deploy data platforms for their workload characteristics and not much else, thereby throwing up new rules between data. Pretty soon, we don't just have our old Silas, but new wants to content with as well. Meanwhile, the promise of data science remains elusive. With all this silo ing and bunkering of data workload performance is necessary but not sufficient to enable the promise of data science. We must think about unfettered data access with ease, zero agency and zero friction. There's no doubt that the needs of data science and data engineering should be leading, not an afterthought. And those needs air centered on accessing and analyzing data across sources. It is now more the norm than the exception that data patterns transcend data sources. Data silos have no meaning to data science. They are just remnants of legacy computing. Architectures doesn't make sense to evaluate strictly on the basis of existing workloads. The world changes, and it changes quickly. So how does the data cloud enabled unfettered data access? It's not just a function of being in the public cloud. Public Cloud is an enabler, no doubt about it. But it introduces new silos recommendation by cloud, platform by cloud region by Data Lake and by data format, it once again triggered technical grandstands and a lot of programming to bring a single analytical perspective to a diversity of data. Data was not analytics ready, not optimized for performance or efficiency and clearly lacking on data governance. Snowflake, address these limitations, thereby combining great execution with great data >>access. But, snowflake, we can have the best of both. So how does it all work when you join Snowflake and have your snowflake account? You don't just >>avail yourself of unlimited stories. And compute resource is along with a world class execution platform. You also plug into the snowflake data cloud, meaning that old snowflake accounts across clouds, regions and geography are part of a single snowflake data universe. That is the data clouds. It is based on our global data sharing architectures. Any snowflake data can be exposed and access by any other snowflake user. It's seamless and frictionless data is generally not copied. Her moves but access in place, subject to the same snowflake governance model. Accessing the data cloth can be a tactical one on one sharing relationship. For example, imagine how retailer would share data with a consumer back. It's good company, but then it easily proliferate from 1 to 1. Too many too many. The data cloud has become a beehive of data supply and demand. It has attracted hundreds of professional data listings to the Snowflake Data Marketplace, which fuels the data cloud with a rich supply of options. For example, our partner Star Schema, listed a very detailed covert 19 incident and fatality data set on the Snowflake Data Marketplace. It became an instant hit with snowflake customers. Scar schema is not raw data. It is also platform optimize, meaning that it was analytics ready for all snowflake accounts. Snowflake users were accessing, joining and overlaying this new data within a short time of it becoming available. That is the power of platform in financial services. It's common to see snowflake users access data from snowflake marketplace listings like fax set and Standard and Poor's on, then messed it up against for example. Salesforce data There are now over 100 suppliers of data listings on the snowflake marketplace That is, in addition to thousands of enterprise and institutional snowflake users with their own data sets. Best part of the snowflake data cloud is this. You don't need to do or buy anything different. If your own snowflake you're already plugged into the data clouds. A whole world data access options awaits you on data silos. Become a thing of the past, enjoy today's presentations. By the end of it, you should have a better sense in a bigger context for your choices of data platforms. Thank you for joining us.

>> Hello everybody. And welcome back to, theCUBE coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the Chairman and CEO of Snowflake and Anita Lynch, the Vice President of data governance at Disney streaming services. Folks Welcome. >> Thank you >> Thanks for having us Dave. >> Anita Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar movie soul. I haven't gotten it to the Mandalorian yet, your favorite. But really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the Data Cloud, because I never liked the term enterprise data warehouse. What you're doing is so different from the sort of that legacy world that I've known all these years. But start with why the Data Cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah, you know, we have a, we've come a long way in terms of workload execution. Right? In terms of scale and performance, and concurrent execution. We've really taken the lid off, sort of the physical constraints that have existed on these type of operations. But there's one problem that we're not yet solving, and that is the siloing and bunkering of data. And essentially, data is locked in applications, it's locked in data centers, it's locked in cloud, cloud regions. Incredibly hard for data science teams to really unlock the true value of data, when you can't address patterns that exist across data sets. So where we perpetuate a status we've had for forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, "Look folks, we have to start on siloing and unlocking the data, and bring it into a place, where we can access it across all these perimeters, and boundaries that have historically existed. It's very much a step level function. Like the customers have always looked at things, one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita, it was great hearing your role at Disney and in your keynote, and the work you're doing, the governance work. and you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. Maybe you can expand on some of these initiatives here, and share what you're seeing as some of the biggest challenges to success, and of course, the opportunities that you're unlocking. >> Sure. In my role leading data governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them. They can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture simply because you often have different teams at different periods and time trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders. There are time constraints and quite often, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos is allow individuals to see upfront how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I'm a copy Creek because it'd be the silent killer. Frank I followed you for a number of years, you're a big thinker, you and I have had a lot of conversations about the near-term, mid-term and long-term, I wonder if you could talk about, in your keynote you're talking about eliminating silos and connecting across data sources. Which is really powerful concept but really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to, Salesforce, you know, they had discovered that we were a top three destination of Salesforce data and they were wondering why that was, and the reason is of course, that people take Salesforce data push it to snowflake because they want to overlay it with what data outside of Salesforce. Whether it's Adobe or any other marketing dataset. And then they want to run very highly scaled processes on it. But the reflexes in the world of SaaS is always like no, we're an Island, we're a planet down to ourselves. Everybody needs to come with us, as opposed to we go to a different platform to run these types of processes. It's no different for the public cloud vendor. They didn't only, they have massive moats around their storage to really prevent data from leaving their orbit. So there is natural friction in terms for this to happen. But on the other hand there is an enormous need. We can't deliver on the power and potential of data unless we allow it to come together. Snowflake is the platform that allows that to happen. We were pleased with our relationship with Salesforce because they did appreciate why this was important and why this was necessary. And we think, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come, right. When people are recognizing why this matters now. It's not going to happen overnight. It is a step while will function a very big change in mentality and orientation. >> Yeah. It's almost as though the the SaaS suffocation of our industry sort of repeated some of the application silos and you build a hardened top around it, all the processes are hardened around it and okay, here we go. And you're really trying to break that, aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so it's so important. It's the first role in your title and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean, we saw this in the early days of big data where governance was just afterthought. It was like bolted on the kind of wild wild West. I'm interested in your governance journey. And maybe you can share a little bit about what role snowflake has played there in terms of supporting that agenda and kind of what's next on that journey. >> Sure. Well, I've led data teams in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance and what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about at least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera. You've taken care of all that it's sort of transparent to them. Is that right?| >> Yea That's right absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring that we're able to do this. we don't do it alone. But governance includes not just the compliance and the privacy, it's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these are really important components of our strategy. >> I got a...So I have a question maybe each of you can answer. I sort of see this, our industry moving from products, to then, to platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing but maybe Frank, you can start, Anita you can add on to Frank's answer. You're obviously both passionate about the use of data and trying to do so in a responsible way. That's critical but it's also going to have business impact. Frank, where's this passion come from on your side. And how are you putting into action in your own organization? >> Well, you know I'm really going to date myself here, but many, many years ago, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data warehouses and business. All these terms didn't exist. People just knew that they wanted to have a more flexible in way of reporting and being able to pivot data dimensionally and all these kinds of things. And I just bought whatever this predates windows 3.1, which really, set off the whole sort of graphical, way of dealing with systems which there's now a whole generations of people that don't know any different right? So I've lived the pain of this problem and sort of had a front row seat to watching this transpire over a very long period of time. And that's one of the reasons, why I'm here, because I finally seen, a glimpse of, I also, as an industry fully, fully just unleashing and unlocking to potential. We're now in a place where the technology is ahead of people's ability to harness it. Which we've never been there before. It was always like, we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just, their heads are spinning with what's now possible, which is why you see markets evolve, very rapidly right now we were talking earlier about how you can't take past definitions and concepts and apply them to what's going on in the world. because the world's changing right in front of your eyes right now. >> So Anita maybe you could add on to what Frank just said and share some of the business impacts and outcomes that are notable since you've really applied your your love of data and maybe, maybe touch on, on culture. Data culture, any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah sure. I think for me, I fell in love with technology first and then I fell in love with data. And I fell in love with data because of the impact that data can have on both the business and the technology strategy. And so it's sort of that nexus, between all three. And in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud, before, well, how do I say that. Before the cloud actually became so prevalent and such a common part of the strategy that's required it was so difficult, you know, so painful. It took so many hours to actually be able to calculate the volumes of data that we had. Now we have that accessibility, and then on top of it, with the snowflake Data Cloud it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate. And really, truly understand our customer's interests and their preferences and then tailor the experiences that they really want and deserve for them. It's, been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you this. So in your spare time you decided to write a book, I'm loving it. I don't have a signed copy so I'm going to have to send it back and have you sign it. But, and you're, I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons, obviously we thought of as an interesting tale to tell for anybody, who is interested in what's going on, how did this come about? Who are the characters behind the scenes and all this stuff. But from a business standpoint because this is such a step function it's so non incremental, we felt like, we really needed quite a bit of real estate to really lay out what the full narrative and context is. And, we thought, the books titled the "Rise of the Data Cloud." That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy because all of us, I think as an industry, were at risk of, persisting, perpetuating where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for a look. There's an enormous opportunity out there but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank, I know you and I are going to talk again Anita, I hope we have a chance to meet face to face and talk in theCUBE live someday. You're phenomenal guests and what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the, Snowflake Data Cloud Summit, on theCUBE.

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around >>the world. This is a cute conversation high, but this is Day Volonte. And as you know, we've been tracking the next generation of clouds. Sometimes we call it Cloud to two point. Frank's Lukman is here to really unpack this with me. Frank. Great to see you. Thanks for coming on. >>Yeah, you as well. They could see it >>s o obviously hot off your AIPO A lot of buzz around that. Uh, that's fine. We could we could talk about that, but I really want to talk about the future. What? Before we get off the I p o. That was something you told me when you're CEO service. Now you said, hey, we're priced to perfection, so it looks like snowflakes gonna be priced to perfection. It's a marathon, though. You You made that clear. I presume it's not any different here for you. Yeah, >>well, I think you know the service now. Journey was different in the sense that we were kind of under the underdogs, and people sort of discovered over the years the full potential of the company and I think there's stuff like they pretty much discovered a day. One. It's a little bit more, More sometimes it's nice to be an underdog. Were a bit of an over dog in this, uh, this particular scenario, but, you know, it is what it is, Andre. You know, it's all about execution delivering the results, delivering on our vision, Uh, you know, being great with our customers. And, uh, hopefully the chips will fall where they where they may. At that point, >>yeah, you're you're You're a poorly kept secret at this point, Frank. After a while, I wanted, you know, I've got some excerpts of your book that that I've been reading. And, of course, I've been following your career since the two thousands. You're off sailing. You mentioned in your book that you were kind of retired. You were done, and then you get sucked back in now. Why? I mean, are you in this for the sport? What's the story here? >>Uh, actually, that that's not a bad way of characterizing it. I think I am in that, uh, you know, for the sport, uh, you know the only way to become the best version of yourself is to be to be under the gun and, uh, you know, every single day. And that's that's certainly what we are. It sort of has its own rewards building great products, building great companies, regardless off you know what the spoils. Maybe it has its own rewards. And I It's hard for people like us to get off the field and, you know, hang it up. So here we are. >>You know, you're putting forth this vision now the data cloud, which obviously it's good marketing, but I'm really happy because I don't like the term Enterprise Data Warehouse. I don't think it reflects what you're trying to accomplish. E D. W. It's slow on Lee. A few people really know how to use it. The time value of data is gone by the time you know, your business is moving faster than the data in the D. W. And it really became a savior because of Sarbanes Oxley. That's really what it came a reporting mechanism. So I've never seen What you guys are doing is is e d w. So I want you to talk about the data cloud. I want to get into the to the vision a little bit and maybe challenge you on a couple things so our audience can better understand it. Yes. So >>the notion of a data cloud is is actually, uh, you know, type of cloud that we haven't had. I mean, data has been been fragmented and locked up in a million different places in different clouds. Different cloud regions, obviously on premise, um, And for data science teams, you know, they're trying thio drive analysis across datasets, which is incredibly hard, Which is why you know, a lot of this resorts to, you know, programming on bond things of that sort of. ITT's hardly scalable because the data is not optimized. The economics are not optimized. There's no governance model and so on. But a data cloud is actually the ability thio loosely couple and lightly Federated uh, data, regardless of where it is. So it doesn't have scale limitations or performance limitations. Uh, the way traditional data warehouses have had it. So we really have a fighting chance off really killing the silos and unlocking the bunkers and allowing the full promise of data sciences and ml On day I thio really happen. I mean, a lot of lot of the analysis that happens on data is on the single data set because it's just too damn hard, you know, to drive analysis across multiple data sets. And, you know, when we talk to our customers, they have very precise designs on what they're trying to do. They say, Look, we are trying to discover, you know, through through through deep learning You know what the patterns are that lead to transactions. You know, whether it's if you're streaming company. Maybe it's that you're signing up for a channel or you're buying a movie or whatever it is. What is the pattern you know, of data points that leads us to that desired outcome. Once you have a very accurate description of the data relationships, you know that results in that outcome, you can then search for it and scale it, you know, tens of million times over. That's what digital enterprises do, right? So in order to discover these patterns enriched the data to the point where the patterns become incredibly predictive. Uh, that's that's what snowflake is formed, right? But it requires a completely Federated Data mo because you're not gonna find a data pattern in the in the single data set per se right? So that's that's what it's all about. I mean, the outcomes of a data cloud are very, very closely related to the business outcomes that the user is seeking, right? It's not some infrastructure process. It has a very remote relationship with business outcome. This is very, very closely related. >>So it doesn't take a brain surgeon to look at the Trillion Years Club. And so I could see that I could see the big you know, trillion dollars apple $2 trillion market cap companies. They got data at the core, whereas most companies most incumbents. Yeah, it might be a bottling plant that the core, some manufacturing or some other processes they put, they put data around it in these silos. It seems like you're trying toe really? Bring that innovation and put data at the core. And you've got an architecture to do that. You talk about your multi cluster shared storage architecture. You mentioned you mentioned data sharing it. Will this, in your opinion, enable, for instance, incumbents to do what a lot of the startups were able to do with the cloud days? I mean they got access to data centers, which they they couldn't have before the cloud you're trying to do with something similar with data. >>Yeah, so So, you know, obviously there's no doubt that the cloud is a critical enabler. This wouldn't be happening. Uh, you know what? I was at the same time, the trails that have been blessed by the likes of Facebook and Google. Uh, e the reason those enterprises are so extraordinary valuable is is because of what they know. Uh, you know, through data and how they can monetize what they know through data. But that is now because that power is now becoming available, you know, to every single enterprise out there. Right, Because the data platform, the underlying cloud capabilities, we are now delivering that to anybody who wants it. Now, you still need to have strong date engineering data science capabilities. It's not like falling off a log, but fundamentally, those capabilities are now, you know, broadly accessible in the marketplace. >>So we're talking upfront about some of the differences between what you've done earlier in your career. Like I said, you're the worst kept secret, you know, Data domain. I would say it was sort of somewhat of a niche market. You you blew it up until it was very disruptive, but it was somewhat limited in what could be done. Uh, and and maybe some of that limitation, you know, wouldn't have occurred if you stay the price, uh, independent company service. Now you mop the table up because you really had no competition there, Not the case here. You you've got some of the biggest competitors in the world, so talk about that. And what gives you confidence that you can continue to dominate, >>But, you know, it's actually interesting that you bring up these companies. I mean, data. The man was a scenario where we were constrained on market and literally we were a data backup company. As you recall, we needed to move into backup software. Need to move the primary storage. While we knew it, we couldn't execute on it because it took tremendous resource is which, back in the day, it was much harder than one of this right now. So we ended up selling the company to E M. C and and now part of Dell. But way short, uh, we're left with some trauma from that experience, Uh, that, you know, why couldn't we, you know, execute on that transformation? So coming to service now, we were extremely. I'm certainly need personally, extremely attuned to the challenges that we have endured in our prior company. One of the reasons why you saw service now break out at scale at tremendous growth rights is because of what we have learned from the prior journey. We're not gonna ever get caught again in a situation where we could not sustain our markets and sustain our growth. So if service I was very much the execution model was very much a reaction to what we had encountered in the prior company. Now coming into snowflake totally different deal. Because not only is there's a large market, this is a developing market. I think you've pointed out in some of your broadcasting that this market is very much in flux on the reason is that you know, technology is now capable of doing things for for people and enterprises that they could never do before. So people are spending way mawr resource is than they ever thought possible on these new capability. So you can't think in terms of static markets and static data definitions, it means nothing. Okay, These things are so in transition right now, it's very difficult for people you know to to scope that the scale of this opportunity. >>Yeah. I wanna understand you're thinking around and, you know, I've written about the TAM, and can Snowflake grow into its valuation and the way I drew it, I said, Okay, you got data Lakes and you got Enterprise Data Warehouse. That's pretty well understood. But I called it data as a service to cover the closest analogy to your data cloud. And then even beyond that, when you start bringing in the edge and real time data, uh, talk about how you're thinking about that, Tam. And what what you have to do to participate. You have toe, you know, bring adjacent capabilities, ISAT this read data sharing that will get you there. In other words, you're not like a transaction system. You hear people talking about converge databases, you hear? Talk about real time inference at the edge that today anyway, isn't what snowflake is about. Does that vision of data sharing and the data cloud does that allow you to participate in that massive, multi $100 billion tam that that I laid out and probably others as well. >>Yeah, well, it is always difficult. Thio defined markets based on historical concept that probably not gonna apply whole lot for much longer. I mean, the way we think of it is that data is the beating heart of the digital enterprise on, uh, you know, digital enterprises today. What do you look at? People against the car door dash or so on. Um, they were built from the ground up to be digital on the prices and data Is the beating heart off their operation Data operations is their manufacturing, if you will, um, every other enterprise out there is is working very hard to become digital or part digital and is going to learn to develop data platforms like what we're talking about here to data Cloud Azaz. Well, as the expertise in terms of data engineering and data scientist to really fully become a digital enterprise, right. So, you know, we view data as driving operations off the digital enterprise. That's really what it iss right data, and it's completely data driven. And there's no people involved. People are developing and supporting the process. But in the execution, it is end to end. Data driven. Being that data is the is the signal that initiates the process is technol assess. Their there being a detective, and then they fully execute the entire machinery probe Problematic machinery, if you will, um, you know, of the processes that have been designed, for example, you know, I may fit a certain pattern. You know, that that leads to some transactional context. But I've not fully completed that pattern until I click on some Lincoln. And all of a sudden proof I have become, you know, a prime prospect system, the text that in the real time and then unleashes Oh, it's outreach and capabilities to get me to transact me. You and I are experiencing this every day. You know, when we're when we're online, you just may not fully re election. That's what's happening behind the scenes. That's really what this is all about. So and so to me, this is sort of the new online transaction processing is enter and, uh, you know, data digital. Uh, no process that is continually acquiring, analyzing and acting on data. >>Well, you've talked about the time time value of of data. It loses value over time. And to the extent that you can actually affect decisions, maybe before you lose the customer before you lose the patient even even more importantly or before you lose the battle. Uh, there's all kinds of, you know, mental models that you can apply this. So automation is a key part of that. And then again, I think a lot of people like you said, if you just try to look at historical markets, you can't really squint through those and apply them. You really have toe open up your mind and think about the new possibilities. And so I could see your your component of automation. I I see what's happening in the r P. A space and and I could see See these this massive opportunities Thio really change society, change business, your last thoughts. >>There's just there's just no scenario that I can envision where data is not completely core in central to a digital enterprise, period. >>Yeah, I think I really do think, Frank, your your your Your vision is misunderstood somewhat. I think people say Okay. Hey, we'll bet on salute men Scarpelli the team. That's great to do that. But I think this is gonna unfold in a way that people may be having predicted that maybe you guys, yourselves and your founders, you know, haven't have aren't able to predict as well. But you've got that good, strong architectural philosophy that you're pursuing and it just kind of feels right, doesn't it? >>You know, I mean, one of the 100 conversations and, uh, you know, things is the one of the reasons why we also wrote our book. You know, the rights of the data cloud is to convey to the marketplace that this is not an incremental evolution, that this is not sort of building on the past. There is a real step function here on the way to think about it is that typically enterprises and institutions will look at a platform like snowflakes from a workload context. In other words, I have this business. I have this workload. This is very much historically defined, by the way. And then they benchmark us, you know, against what they're what they're already doing on some legacy platform. And they decided, like, Yeah, this is a good fit. We're gonna put Snowflake here. Maybe there, but it's still very workload centric, which means that we are essentially perpetuating the mentality off the past. Right? We were doing it. Wanna work, load of the time We're creating the new silos and the new bunkers of data in the process. And we're really not approaching this with level of vision that the data science is really required to drive maximum benefit from data. So our arguments and this is this is not an easy arguments is to say, toc IOS on any other sea level person that wants to listen to that look, you know, just thinking about, you know, operational context and operational. Excellent. It's like we have toe have a platform that allows us unfettered access to the data that, you know, we may need to, you know, bring the analytical power to right. If you have to bring in political power to a diversity of data sets, how are we going to do that right? The data lives in, like, 500 different places. It's just not possible, right, other than with insane amounts of programming and complexity, and then we don't have the performance, and we don't have to economics, and we don't have the governance and so on. So you really want to set yourself up with a data cloud so that you can unleash your data science, uh, capabilities, your machine learning your deep learning capabilities, aan den, you really get the full throttle advantage. You know of what the technology can do if you're going to perpetuate the silo and bunkering of data by doing it won't work. Load of the time. You know, 5, 10 years from now, we're having the same conversation we've been having over the last 40 years, you know? >>Yeah. Operationalize ing your data is gonna require busting down those those silos, and it's gonna require something like the data cloud to really power that to the next decade and beyond. Frank's movement Thanks so much for coming in. The Cuban helping us do a preview here of what's to come. >>You bet, Dave. Thanks. >>All right. Thank you for watching. Everybody says Dave Volonte for the Cube will see you next time

>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah. You know, we have We've come a long way in terms of workload, execution, right? In terms of scale and performance and concurrent execution. We really taking the lid off. Sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data essentially in the data is locked in applications. It's locked in data centers. It's locked in cloud cloud regions incredibly hard for for data science teams to really unlock the true value of data when you when you can address patterns that that exists across data set. So we're perpetuate, uh, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data club mentality as well as a workload orientation towards towards managing data. >>Anita is great here in your role at Disney and you're in your keynote and the work you're doing the governance work and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure, I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're gonna be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale, the use cases that they're focused on their no longer required Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I've followed you for a number of years. Your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah, natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering why that was. And the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data? Outside of Salesforce, you know, whether it's adobe or any other marketing data set and then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, No, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Better day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in, uh, in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. Uh, you know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? Uh, people are recognizing, you know, why does this matter now? It's not gonna happen overnight. There's a step global function of very big change in mentality and orientation. >>Yeah. It's almost as though the SAS ification of our industry sort of repeated some of the application silos and you build a hardened top around it. All the processes are hard around. OK, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey. And maybe you could share a little bit about what role snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about. At least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that were ableto do this. We don't we don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products toe, then two platforms and platforms, even involving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, uh, many, many years ago, uh, I saw the first glimpse off, uh, multidimensional databases that were used for reporting really on IBM mainframes on git was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and all these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which really set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different, Right? So I I've lived the pain off. This problem on sort of had a front row seat to watching this this transpire over a very long period of time. And that's that's one of the reasons you know why I'm here. Because I finally seen a glimpse off. You know, I also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. We were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that are notable since you're really applied your your love of data and maybe maybe touch on culture, data, culture, any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud you know before. Well, how do I say that before the cloud actually became, you know, so prevalent and such a common part of the strategy that's required It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's it's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time. You decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But your love, the inside baseball, it's just awesome. Eso really appreciate that. So but why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, uh, we thought it was an interesting tale to tell for anybody who's interested in, you know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative in context is on. Do you know, we thought books titled The Rise of the Data Cloud. That's exactly what it iss. And we're trying to make the case for that mindset, that mentality, that strategy. Uh, because all of us, you know, I think it's an industry were risk off, you know, persisting, perpetuating. Uh, you know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, there's an enormous opportunity out there. The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal guests. And what a great story. Thank you both for coming on. Thank you. All right, you're welcome. And keep it right there, buddy. We'll be back for the next guest right after this short break and we're clear. All right. Not bad.

>> Narrator: From "theCUBE" studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is "theCUBE" conversation. >> Hi everybody, this is Dave Vellante. and as you know, we've been tracking the next generation of cloud. Sometimes we call it cloud 2.0, Frank Slootman is here to really unpack this with me. Frank, great to see you. Thanks for coming on. >> Yeah, you as well Dave, good to see you. >> Yeah so, obviously hot off your IPO, a lot of buzz around that, that's fine. We could talk about that, but I really want to talk about the future. What, before we get off the IPO though, was something you told me when you were CEO of ServiceNow. You said, "Hey, we're priced to perfection." So it looks like Snowflake is going to be priced to perfection, it's a marathon though. You made that clear. I presume it's not any different here for you. >> Well, I think, you know, the ServiceNow journey was different in the sense that we were kind of underdogs and people sort of discovered over the years, the full potential of the company. And, I think with Snowflake, they pretty much just discovered it day one (laughs). It's a little bit more, sometimes it's nice to be an underdog or a bit of an overdog in this particular scenario, but yeah, it is what it is. And, it's all about execution, delivering the results, being great with our customers and, hopefully the (indistinct) where they may at that point. >> Yeah, you're a poorly kept secret at this point, Frank, after a while. I've got some excerpts of your book that I've been reading and of course I've been following your career since the 2000's. You're off sailing. You mentioned in your book that you were kind of retired, you were done, and then you got sucked back in. Now, why? Are you in this for the sport? What's the story here? >> Actually, that's not a bad way of characterizing it. I think I am in it, for the sport, the only way to become the best version of yourself is to be under the gun, every single day. And that's certainly what we are. It sort of has its own rewards, building great products, building great companies, regardless of what the spoils may be, it has its own reward. It's hard for people like us to get off the field and hang it up, so here we are. >> You're putting forth this vision now, the data cloud, which obviously it's good marketing, but I'm really happy because I don't like the term enterprise data warehouse. I don't think it reflects, what you're trying to accomplish. EDW, it's slow, only a few people really know how to use it, the time value of data is gone by the time, your business is moving faster than the data in EDW. And it really became, as the savior because of Sarbanes-Oxley, that's really, what became of a reporting mechanism. So I have never seen what you guys are doing as EDW. So I want you to talk about the data cloud, I want to get into the vision a little bit and maybe challenge you on a couple things so our audience can better understand it. >> Yeah, so the notion of a data cloud is actually a type of cloud that we haven't had. Data has been fragmented and locked up in a million different places, in different clouds, different cloud regions, obviously, on premise. And for data science teams, they're trying to drive analysis across datasets, which is incredibly hard, which is why a lot of this resorts to programming and things of that sort. It's hardly scalable because the data is not optimized, the economics are not optimized, there's no governance model and so on. But the data cloud is actually the ability to loosely couple and lightly federate data, regardless of where it is, so it doesn't have scale limitations or performance limitations the way traditional data warehouses have had it. So we really have a fighting chance of really killing the silos and unlocking the bunkers and allowing the full promise of data sciences and ML and AI to really happen. A` lot of the analysis that happens on data is on a single dataset because it's just too damn hard to drive analysis across multiple datasets. When we talk to our customers, they have very precise designs on what they're trying to do. They say, "Look, we are trying to discover through deep learning what the patterns are that lead to transactions, whether it's... If you're a streaming company, maybe it's that you're signing up for a channel or you're buying a movie or whatever it is. What is the pattern of datapoints that leads us to that desired outcome?" Once you have a very accurate description of the data relationships that result in that outcome, you can then search for it and scale it tens of million times over. That's what digital enterprises do, right? So in order to discover these patterns, enrich the data to the point where the patterns become incredibly predictive, that's what Snowflake is for, right? But it requires a completely federated data model because you're not going to find a data pattern in a single dataset, per se, right? So that's what it's all about. The outcomes of a data cloud are very, very closely related to the business outcomes that the user is seeking, right? It's not some infrastructure process. that has a very remote relationship with business outcome. This is very, very closely related. >> So it doesn't take a brain surgeon to look at the trillionaires' club. (chuckles) So I can see that. I can see the big trillion dollars, Apple, $2 trillion market cap companies, they get data at the core. Whereas most companies, most incumbents, it might be a bottling plant at the core or some manufacturing or some of the process, and they put data rounded in these silos. It seems like you're trying to really bring that innovation and put data at the core and you've got an architecture to do that. You're talking about your multi cluster shared storage architecture. You mentioned data sharing. Will this, in your opinion enable, for instance, incumbents to do what a lot of the startups were able to do with the cloud days. hey got access to data centers which they couldn't have before the cloud. Are you trying to do something similar with data? >> Yeah, so obviously there's no doubt that the cloud is a critical enabler. This wouldn't be happening without it. At the same time, the trails that have been blazed by Alexa, Facebook and Google. The reason that those enterprises are so extraordinarily valuable is because of what they know through data and how they can monetize what they know through data. But that power is now becoming available to every single enterprise out there, right. Because the data platforms and the underlying cloud capabilities, we are now delivering that to anybody who wants it. Now you still need to have strong data engineering, data science capabilities. It's not like falling off of a log, but fundamentally those capabilities are now broadly accessible in the marketplace. >> So we talking up front about some of the differences between what you've done early in your career, like I said, you're the worst kept secret, Data Domain I would say it was somewhat of a niche market. You blew it up until it was very disruptive, but it was somewhat limited in what could be done. And maybe some of that limitation, you know, wouldn't have occurred if you stayed an independent company. ServiceNow, you mopped the table up 'cause you really had no competition there. Not the case here. You've got some of the biggest competitors in the world. So talk about that and what gives you confidence that you can continue to dominate? >> It's actually interesting that you bring up these companies. Data Domain, it was a scenario where we were constrained on market and we were a data backup company as you recall, we needed to move into backup software, needed to move into primary storage. While we knew it, we couldn't execute on it because it took tremendous resources which, back in the day, it was much harder than what it is right now. So we ended up selling the company to EMC and now part of Dell, but we're left with some trauma from that experience in the sense that, why couldn't we execute on that transformation? So coming to ServiceNow, we were extremely, and certainly me personally, extremely attuned to the challenges that we had endured in our prior company, and one of the reasons why you saw ServiceNow break out at scale, at tremendous growth rates is because of what we learned from the prior journey. We were not going to ever get caught again in the situation where we could not sustain our markets and sustain our growth. So ServiceNow is very much, the execution model, very much a reaction to what we had encountered in the prior company. Now coming into Snowflake a totally different deal because not only is this a large market this is a developing market. I think you've pointed out in some of your broadcasting, that this market is very much influx. And the reason is that technology is now capable of doing things for people and enterprises that they could never do before. So people are spending way more resources than they ever thought possible on these new capabilities. So you can't think in terms of static markets and static data definitions, it means nothing. Okay, these things are so in transition right now. It's very difficult for people to scope the scale of this opportunity. >> Yeah, I want to understand your thinking around and, you know, I've written about the TAM and can Snowflake grow into it's valuation and the way I drew it, I said, okay, I've got data lakes and you've got an enterprise data warehouse, that's pretty well understood but I called it data as a service company the closest analogy to your data cloud. And then even beyond that when you start bringing in the Edge and real time data. Talk about how you're thinking about that TAM what you have to do to participate. Do you have to bring adjacent capabilities? Or is it this read data sharing that will get you there? In other words, you're not like a transaction system. You hear people talking about converged databases. You're going to talk about real time inference at the Edge that today anyway, isn't what Snowflake is about. Does that vision of data sharing in the data cloud, does that allow you to participate in that massive multi hundred billion dollar TAM that I laid out and probably others as well? >> Yeah, well, it's always difficult to define markets based on historical concept that probably not going to apply a whole lot or for much longer. I mean the way we think of it is that data is the beating heart of the digital enterprise and digital enterprises today, what are you looking at people like the car door dash or so on. They were built from the ground up to be digital enterprises. And data is the beating heart of their operation, data operations is their manufacturing if you will. Every other enterprise out there is working very hard to become digital or part digital and is going to learn to develop a data platform like what we're talking about here to data cloud as well as the expertise in terms of data engineering and data sciences to really fully become a digital enterprise, right? So we view data as driving operations, all the all the digital enterprise, that's really what it is, right? And it's completely data driven end-to-end. There's no people involved and the people are developing and supporting the process but in the execution, it is end-to-end data driven. Meaning that data is the signal that initiates the process he's taking, but as they're, as they're being detected, and then they fully execute the entire machinery, programmatic machinery if you will, all of the processes have been designed. Now for example, I may fit a certain pattern, that leads to some transactional law context, but that's not fully completed, that pattern until I click on some link and all of a sudden, poof, I have become a prime prospect. System detects that in the real time and then unleashes all its outreach and capabilities to get me to transact. You and I are experiencing this every day. When we're, when we're online, you just may not fully realize (laughs) that that's what's happening behind the scenes. That's really what this is all about. So to me, this is sort of the new online transaction processing is an end to end data digital process that is continually acquiring, analyzing and acting on data. >> Well, you've talked about the time, time value of, of data. It loses value over time. And to the extent that you can actually affect decisions, maybe prior, before you lose the customer, before you lose the patient, even even more importantly, or before you lose the battle. There's all kinds of mental models that you can apply this. So automation is a key part of that and then again, I think a lot of people, like you said, if you just try to look at historical markets, you can't really squint through those and apply them. You really have to open up your mind and think about the new possibilities. And so I could see >> Exactly. >> Your component of automation. I see what's happening in the RPA space, and I could see these just massive opportunities to really change society, change business. Your last thoughts. >> While there's just no scenario that I can envision where data is not completely core and central to a digital enterprise period. >> Yeah, I think I really do think Frank, your vision is misunderstood somewhat. I think people say, "Okay hey, we'll bet on Slootman, "Scott Pelley, the team." That's great to do that, but I think this is going to unfold in a way that people maybe haven't predicted and maybe you guys yourselves and your founders you know haven't, aren't able to predict as well, but you've got that good, strong architectural philosophy that you're pursuing and it just kind of feels right, doesn't it? >> One of the harder conversations and the this is one of the reasons why we also wrote our book "The Rise of the Data Cloud" is to convey to the marketplace that this is not an incremental evolution. It is just not sort of building on the past. There is a real step function here. And the way to think about it is that typically enterprises and institutions will look at a platform like Snowflake from a workload context. In other words, I have this business, I have this workload, which is very much historically defined by the way, and then they benchmark us against what they're already doing on some legacy platform and they decide, "Yeah, this is a good fit, we're going to put Snowflake here, maybe there." But, it's still very workload centric which means that we are, essentially, perpetuating the mentality of the past. We were doing it one workload at a time, we're creating the new silos and the new bunkers of data in the process. And we're really not approaching this with the level of vision that the data scientists really require to drive maximum benefit from data. So our argument, and this is not an easy argument, is to say to CIOs and any other C-level person that wants to listen and say, "Look, just thinking about operational context and operational excellence, it's like we have to have a platform that allows use unfettered access to the data that we may need to bring the analytical power to." If you have to bring analytical power to a diversity of datasets, how are we going to do that? The data lives in 500 different places, it's just not possible, other than with insane amounts of programming and complexity and then we don't have the performance and we don't have the economics and we don't have the governance and so on. So you really want to set yourself up with a data cloud so that you can unleash your data science capabilities, your machine learning, your deep learning capabilities and then really get the full throttle advantage of what the technology can do. If you going to perpetuate the silo-ing and bunkering of data by doing it one workload at a time, five, 10 years from now, we're having the same conversations we've been having over the last 40 years. >> Yeah, operationalizing your data is going to require busting down those silos and it's going to require something like the data cloud to really power that to the next decade and beyond. Frank Slootman, thanks so much for coming to "theCUBE" and helping us do a preview here of what's to come. >> You bet Dave, thanks. >> All right, thank you for watching everybody. This is Dave Vellante from the "theCUBE". We'll see you next time.

>> Hello everybody and welcome back to the cubes coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the chairman and CEO of Snowflake and Anita Lynch, the vice president of Data Governance at Disney Streaming Services. Folks, welcome. >> Thank you Thanks for having us, Dave, >> I need a Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar Movie saw, I haven't gotten into the Mandalorian yet, your favorite, but, (woman laughing) really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud, because I never liked the term Enterprise Data Warehouse, what you're doing is so different from the sort of that legacy world that I've known all these years, but start with why the Data Cloud, what problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah I know, you know we've come a long way in terms of workload execution, right? In terms of scale and performance, you know, concurrent execution, we really taken the lid off sort of the physical constraints that have existed on these types of operations. But there's one problem, that we're not yet solving. And that is the siloing and bunkering of data. And especially in a data is locked in application it is locked data centers, is locked in cloud regions, incredibly hard for data science teams to really, you know, unlock the true value of data. When you can address patterns that exist across a data set. So we're perpetuate, a status we've had forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, look folks, you know, we have to start unsiloing and unlocking the data, and bring it into a place, you know, where we can access it, you know, across all these parameters and boundaries that have historically existed. It's very much a step level function. Now the customers have always looked at things one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita was great hearing your role at Disney, and your keynote, and the work you're doing, the governance work, and you're serving a great number of stakeholders, enabling things like data sharing, you got really laser focused on trust, compliance, privacy. Is this idea of a data clean room is really interesting. You maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And of course, the opportunities that you're unlocking. >> Sure. I mean, in my role, leading Data Governance, it's really critical to make sure that all of our stakeholders, not only know what data is available and accessible to them, they can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so, that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually, is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos, and obviously you can relate to that, having been in the data business for awhile, but wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture, simply because you often have different teams at different periods in time, trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that, is, due to the different needs of specific stakeholders. There are time constraints, and quite often it's not always clear, how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos, is, allow individuals to see upfront how much value they're going to get from the data, by knowing that it's trustworthy right away . By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I mean copy creek, cause it'd be the silent killer. Frank I followed you for a number of years. You're a big thinker. You and I have had a lot of conversations about the near term, mid term and long term. I wonder if you could talk about, you know, when your keynote, you talked about eliminating silos, and connecting across data sources, which really powerful concept, but it really only, if people are willing and able to connect and collaborate, where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to Salesforce, you know, they had, discovered that we were a top three destination of Salesforce data and they were wondering, you know, why that was? And the reason is of course that people take Salesforce data, push it to Snowflake, because they want to overlay it with data outside of Salesforce. You know what it is Adobe or any 6other marketing dataset. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS, is always like, no, we're an Island, we're a planet onto ourselves. Everybody needs to come with us as opposed to, we go to a different platform to run these types of processes. It's no different for thee public cloud vendor. They did only, they have, you know, massive moats around, you know, their storage to, you know, to really prevent data from leaving their orbit. So there is natural friction in terms of for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on the power and potential of data, unless we allow it to come together. Snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate, you know, why this was important and why this was necessary. And we think, you know, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come. Right, people are recognizing, you know, why does this matters now. It's not going to happen overnight. It is a step what will function a very big change in mentality and orientation. You know? >> Yeah. It's almost as though the sussification of our industry sort of repeated some of the application silos, and build a heart on to and all the processes of(mummers) Okay, here we go. And you're really trying to break that aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so important. It's the first rule in your title, and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean we saw this in the early days of big data where governance was this afterthought. It was like bolted on kind of wild west. I'm interested in your governance journey. And maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda, and kind of what's next on that journey. >> Sure. Well, you know, I've led data teams, in numerous ways over my career, this is the first time, that I've actually had the opportunity to focus on governance. And what it's done, is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about, at least my inference in your talk, was really that the business folks didn't have to care about, your wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera, you've taken care of all that. It's sort of transparent to them. >> Yeah, that's right. Absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical, to ensuring you know, that we're able to do this. We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access. And it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data, we focus on the infrastructure, and making sure that we've architected for scale , and all of these are really important components of our strategy. >> So I have a question maybe each of you can answer it. I sort of see this, our industry moving from products to then, to the platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, but, but maybe Frank, you can start and Anita you can add onto Frank's answer. You obviously both passionate about the use of data and trying to do so in a responsible way, that's critical, but it's also going to have business impact. Frank, where's this passion come from on your side? And how are you putting into action in your own organization? >> Well, you know, I'm really going to date myself here, but you know many years ago, you know, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and business, all these terms didn't exist. People just knew that they want to have a more flexible way of reporting and being able to pivot data, dimensionally, all these kinds of things. And I just by whatever this predates, you know, windows 3.1, which really, you know, set off the whole sort of graphical, you know, way of dealing with systems, which there's not whole generations of people that don't know any different. Right? So I've lived the pain of this problem, and sort of had a front row seat, to watching this transpire over a very long period of time. And that's one of the reasons, you know, why I'm here because I finally seen, you know, a glimpse of, you know, I also, as an industry fully, just unleashing and unlocking the potential. We're not at a place where the technology is ahead of people's ability to harness it. Right. Which we'd never been there before. Right. It was always like we wanted to do things and technology wouldn't let us, it's different now. I mean, people are just, heads are spinning with what's now possible, which is why you see Marcus evolve, you know, very rapidly right now, we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on in the world. The world's changing right in front of your eyes right now, >> So Anita maybe you could add on to what Frank just said and share some of the business impacts, and outcomes that are notable since you've really applied your love of data and maybe touch culture, data culture. Any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah Sure. I think for me, I fell in love with technology first, and then I fell in love with data and I fell in love with data because of the impact that data can have, on both the business, and the technology strategy. And so it's sort of that nexus between all three. And in terms of my career journey and some of the impacts that I've seen. I think with the advent of the Cloud, you know, before, well, how do I say this? Before the cloud actually became so prevalent and such a common part of the strategy that's required, it was so difficult, you know, so painful. It took so many hours to actually, be able to calculate, you know, the volumes of data that we had. Now we have that accessibility. And then on top of it, with the Snowflake Data Cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think, moving beyond some of the traditional mechanisms for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate and really, truly understand our customer's interests and their preferences, and then tailor the experiences that they really want and deserve for them. It's been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you to do so in your spare time you decided to write a book am loving it. I have a signed copy, so I'm going to have to send it back and have you sign it. But, and I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons. Obviously we thought it was an interesting tale to tell for anybody, you know, who is interested in, you know, what's going on? How did this come about? You know, or the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, you know, because this is such a step function, it's so non incremental, we felt like we really needed quite a bit of real estate to really lay out, what the full narrative and context is. And, you know, we thought, you know, books titled the rise of the Data Cloud. That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy, because all of us, you know, I think as an industry we're at risk of, you know, persisting, perpetuating, you know, where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for look, you know, there's an enormous opportunity out there, but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank. I know you and I are going to talk again, Anita, I hope we have a chance to meet face to face and in the cube live someday, your phenomenal guest and what a great story. Thank you both for coming on. Thanks Dave, >> Thank you >> You're welcome to keep it right there, buddy. We'll be back with the next guest right after this short break. (upbeat music)

(upbeat music) >> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. >> Hi everyone, welcome back to theCUBE's coverage of AWS Public Sector Partner Awards Show. I'm John Furrier, host of theCUBE. We're here in Paolo Alto, California but during COVID, we're doin' all the remote interviews and gettin' the stories and celebrating the awards for the Partner Awards Show. And the award here is most customer-obsessed mission-based win in the federal area. We've got two great guests, Greg Siegel Senior Manager at Accenture and Frank Urbano Program Manager with the FBI Federal Bureau of Investigation. Gentlemen, thank you for joining me and congratulations on the win. >> Thank you. >> Thank you. >> So let's break this down. So you're federal, big category, a lot of intelligence agencies been using the gov cloud and Amazon. What's the mission win? What's the award for? Tell us. >> So I guess the award is the Bureau was shutting down our data centers and we needed to move to an infrastructure that would support our application. That was the first problem that we were trying to actually solve. But also, we know we were always seeing a performance hit on our infrastructure, and we always suspected that by moving to the gov cloud, we'll see an increase in performance because once we went live in our current, in or old environment seven years ago, performance was always an issue, our end users were always complaining and then we moved to our VMs four years after that. We saw an increase in performance a little bit but then once we moved over to the cloud, the FBI secret cloud, we heard crickets. The end users haven't been complaining. Greg and I were actually talking about that the other day how, you know, there's minimal complaints as far as performance. That's going to be one of the themes you hear throughout is performance, performance, performance. >> Got to love the no complaints, that means it's workin', people are doin' their job, gettin' the job done. Greg, I want to get your thoughts on this because Accenture, we've had many conversations with you guys over there about being agile and now you're a partner. You know, the FBI, I saw a presentation in person at Reinvent, I think last year where the FBI was like, "Lookit, our workloads "are increasing and budget isn't increasing "at the same rate." So it's kind of like, you know, "I need more power." It's like that scene in Star Trek, "Scotty, more power," you need to get that power. Take us through that transformation because one, you got a good user experience. That means people are doin' their job. But the cases get bigger, the more workload is there, but the budget's got to be increased or leveraged better. What's your thoughts? How do you tackle that problem because it's do more with less, classic do more with less. >> That's right. Yeah, so as Frank said, I think the system had been live for about seven years and you see over that time in the traditional data centers how the performance requirements increase but as you said, are kind of there on hardware and not easily able to adapt and overcome those. So, you know, when it became clear that the cloud move was a serious consideration we were able to pull on a few other experiences that the firm has had moving similar technologies to the cloud and then kind of combined that with the experience implementing technology at the FBI. And those two components kind of together were able to get us on a path to successfully move to the cloud and be, you know, kind of one of the first big systems at the FBI to make that transition. So that was our approach. >> Frank, I'd like to ask, you mentioned crickets. That means, that's good, actually. No one's complaining. What was it like before when you had the data center? What were some of the complaints? What were some of the challenges that you were dealing with? >> So (chuckling) so some of the challenges we were dealing with was, to give an example, when we went live seven years ago, we actually deployed our application on hardware that was already end of life. And so immediately we saw challenges there. And so by moving to the cloud, it gave us a lot of architectural flexibility. And what I mean by that is that we control, now, our own destiny, meaning that in the past, we would have to put in change requests to have firewall configuration changes. Now that responsibility is with us. Our DBAs had limited access to actually do some type of performance tuning on the backend to our databases. Now we have full control of that. I guess a couple of examples, or one example that I would give is that we're in the COVID era, as you mentioned, right? We have a space where we, prior to COVID, we had about 70 people on staff, both government and at Accenture. And all of our development is done on the secret side. And we have major deliverables due at the end of September. Well, COVID hits, we now have to social distance and come up with a plan, and we have to have reduce our staff of 70, both functional developers down to anywhere between 10 people or less on-site. So that, right there, you know, we were talking major hit in our development effort and in cost, I guess, also. While we're doing our social distancing plan Greg came up to me and said, "Hey, why don't we move "our development environment and our test environment "to the gov cloud and scramble the data. "We'll be able to have our developers remote access in "and continue with our development efforts?" And I told Greg, "Great, put a plan together. "Let's talk to our information security officer." I said, "If he signs off on it, let's get off and running." We met with him, he signed off on them, and within two weeks that dev and test environment was up and running. And now, we're still on-track to meet our deliverable dates in September. >> That's a great example, well, that's awesome insight. Greg, expand on that because this is an example of agility. You talk about readiness, I mean it's unforecasted disruption, there's all kinds of use cases. "Oh, we have a hurricane," or whatever, you know. This is unforeseen and unique. Take us through-- >> Yeah, that's absolutely right. >> The agility piece here, on how you got deployed, time frame, and solution. >> Yeah, definitely. So yeah, it can't be overstated how much of a benefit it was that we had already gone through the process of refactoring a lot of our applications into the cloud and using some of those services available and, you know, able to containerize and take some of those application from where they were, as Frank mentioned, scramble the data, and then able to quickly use the cloud experience that we had to stand up an environment in gov cloud where it was more accessible for development that didn't need to take place on-site, was, essentially, the saving grace. We would have had major slowdowns in delivery, as Frank mentioned and a lot of cost implications there, so it really can't be overstated how much that experience having gone through it and being in a spot where we had that flexibility to quickly replicate our architecture, went a long way towards keeping the mission going as the world deals with the pandemic. >> Yeah, this is just a striking example. You know, first of all, I'm a cloud-biased person. I'm very much a, I lean heavily towards pro-cloud so I'll just say this as total bias. There are companies that have gone cloud and took advantage of that refactoring or reinvention and are in a position not only to hit the deadlines but also be in a position of growth strategy, or in this case, a mission-based expansion for the FBI, as Frank was alluding to. Could you imagine, Frank, if you had the data center challenge and you weren't in the cloud? And the you had to go to Greg, or somebody, and say, "Hey, what do you do?" So imagine you had the data center, and then COVID hits. A lot of people are on that side of the street, right now, goin', "What do we do?" >> Yeah, yeah we would have been dead in the water as Greg mentioned. You know, all of our work streams would have been forced out to the left. I couldn't even imagine, you know, the timelines that we would have had to come up with because we would have had to have come up with some rotation plan to develop, you know, team one can only come in on Mondays and Tuesdays and then team two would come in on Wednesdays and Thursdays which would have pushed out our delivery dates and as Greg mentioned also, cost goes up. Time is money, money's time. >> Yeah, I totally, and people goin' out of business because of it and, or settin' their mission back you know, decades. Greg, talk about what goes on next because obviously, congratulations on being a customer success, it's a great mission win here, but you got to get through this. So how are you guys huddling on this point? What are the conversations? What are you thinking? >> Yeah, so now we're at a point where I think, as I'd mentioned, when we first moved to the cloud, the primary mission was getting there securely, getting there within policy, and getting operational so we were making trade-off decisions on where to lift and shift, and where to refactor. Got through all of that successfully. Got through the initial challenge of COVID which definitely threw some of the plans for a loop as we shifted our operations and focused on getting operational in gov cloud. And now we are at a point where we've stabilized delivery again, and we're re-picking up where we left off on the cloud journey which is really focused now, on continuing to look at the investments that AWS is making in the technologies that are coming next. And it really enables us to get ahead of the trends, easily analyze some of these services, available, and then we enter into conversations with Frank and others and start making those trade-off decisions of when it's time to refactor, retire another part of our application and start to look to go cloud-native. So that's where we are now, is looking for ways to maximize and use those services to, again, save costs, improve performance, all of those things that go along with getting more and more mature in the cloud. >> You know, one of the things, Frank, I want to hear your thoughts on just as while I got you guys here is you think about old school, old guard, as Andy Jassy would say, or Teresa talk about. You got silos and you got all these things: legacy. Okay, got that. But as you guys look at your mission have secure data, catch the bad guys, and protect citizens, right? So (chuckling) I mean, I'm over-simplifying but generally, that's it. Data's critical, right? I mean, speed to the edge of the network which is the field and the people doing the job, is critical. Cloud has an opportunity to make that development cycle faster, and ultimately, the workloads and the impact. Could you share your thoughts on how the cloud and Amazon are bringin' that to the table because havin' the right data at the right time could mean the difference between life or death. >> Yeah, so Greg and I experienced this, and again, it's all about having that architectural flexibility, right? So back in February, we had a requirement where we had to expose a large amount of data to employees about themselves, but not only about themselves, but also to their managers. And so, you know, we went through the basic you know, develop it, and then put it into our test environment, however the problem that we had was that we couldn't assimilate the large amount of data that we're exposing to 40,000 FBI employees. Because when we tested out, everything seemed to go fine, but as luck would have it, once we went operational, the application crashed. Our two main engineers come in my office and within 30 minutes, they identified the problem, they had the solution, and we already implemented the solution. Within 30 minutes. You know, going back in the past, like seven years, like you were mentioning, back in the old days, I would have to go around, beg for funding, buy hardware, then I would have to submit a requisition. It would have to go through the approval process. We then would have to procure the hardware, receive the hardware, install it, test it out, load the application, test it again, and then go into Ops. You know, you're lookin' anywhere from a three month to a nine month delay right then and there that our engineers were able to solve within 30 minutes. >> I mean, again, I'm back to my bias again. I'm old enough to remember when I was in college. I mean, I never programmed on punch cards, so that's kind of dates me, (chuckling) but so I'm post punch card generation. I used to look at the guys runnin' the mainframes sayin', "Look at those old relics over there," and "huggin' the mainframe." But what they did was that the smart people repurposed and got into mini-computers, they got into networking, LANs and PCs. This is kind of the cloud moment where if you're going to hold onto that old way you're going to have that operating model, it's just not effective in any way. I just don't see any benefit, other than have a preserved workload that needs the certain data, or you put containers around it and you can bring that in, but there are those corner cases. But generally speaking, you got to move to the new model. >> Mm-hmm. >> Guys, react to that. What's your thoughts? >> Yeah. >> Evermore. Yeah. >> Yeah, I agree, I mean It can't really be overstated, just the flexibility that exists. I think a lot of times, people get hung up on the you know, most efficient way to move to the cloud or you have to use X amount of cloud services. But it can't be overstated, regardless of the approach that you take to making that migration, that once you are there, the kind of intangibles that you get, the ease to take an idea and test it out, flip the switch on, flip the switch off if you like it or not. It's really just opened the door for the team to take some of the more innovative ideas and we have regular conversations with Frank and others that I think are fun for all of us where we get to look at some of these things and we can actually think about and envision how to get them in without, to Frank's point, "putting in requisitions," doing major activities that are going to derail our other schedules to pilot some of these new ideas. >> Frank, you got to attract some, it's a personnel challenge, too. You want to attract young minds, smart, young people. They want what's contemporary and they want state-of-the-art, they want to be in the right positions, drivin' the right, fastest car they can, and being successful. There's a staff component. What's your thoughts on that? Because, you know, if a young person comes in it's like, "Hey, I want to rock and roll with this new stuff, "not the old stuff I see there." >> Right. >> And so Greg put together an innovation team where we have these great, young minds, right? And you know, they're always bringing different ideas, different services that we can utilize on AWS, and sometimes Greg and I have to pull the reins on 'em, like, "Okay, we'll do that, but we have "major applications that we got to develop and deploy." But it's always refreshing and great to see young people with their innovative ideas that they bring to the table. >> Well, final question for you guys, while I got ya here. You know, I've been reporting, we've been saying on these CUBE interviews, trying to make sense of this COVID environment, what's goin' on and what it exposes. And you can see the obvious things. But it generally exposes this great IoT experiment. We're all IoT devices at this point. You've got work places which are not home and office, workforces which are remote, workloads and workflows that are changing, new things are happening. How do you guys see this? Because it ultimately opens up the fact that the architecture has to support multiple endpoints, edge of the network, new connections, new workflows. How are you guys looking at this? What's your vision on this? >> So Greg, I'll take a first crack at it from a Bureau employee being with the Bureau for 31 years. I would never have thought in my wildest dreams that we'd actually have people workin' from home and being able to remote in, and actually do development. And we did it all within two weeks. It's just incredible the obstacles that the team overcome, but also the flexibility of the FBI leadership, knowing that this had to happen in order to, for continuity of operations. >> Great point, great insight. Greg, your thoughts. >> Yeah, I agree with everything that Frank said. It's been a great partnership and I think that the nice thing that surprised us all was when it got down to it, the security controls and requirements were there and able to be met with the tools at our disposal. So I think the great fear that everybody had to Frank's point, it just wasn't something that was normal to this point. But as we were all forced to reevaluate what we had to do, the fear was, "Well, what accommodations are we "going to have to make from a security standpoint?" And the answer was being able to operate again without exposing any of that data, the risk was really extremely low, to zero. All the folks from security we're able to work closely with in partnership, and make this happen again so we can keep delivering the mission. So I think that partnership and getting through it together and all feeling really comfortable that we're doing it in a secure way was really what enabled us to be successful. >> That's a great point. Frank, he brings up something I didn't bring up which is super important. You mentioned in the old way you got to get all these requisitions in purchase. Security is the same kind of new dynamic which is like, "Okay, you got to get "everything tested," but it goes faster when you have the cloud 'cause that's also another criteria, you got to still got to get the approvals whether you're working with another vendor or integrating with another app. That's still now the new issue. So that's got to be approved faster, so that's also now a bottleneck. How does cloud help make those security reviews go faster? >> Right, so so we were the first ones on the cloud. So or security team was still defining the ATO process for us. However, what we did was we aligned ourselves with that team so that we could meet all the security requirements, but also app out all the security controls. And so from the time that we actually had the design till we went into deployment onto the SC2S or the cloud, and we went through the ATO process, it only took us eight months which really, in the past, that effort could have took anywhere from a year and a half to two years just because of the old ATO process. >> Awesome. Well, Greg and Frank, congratulations on a great award, Amazon Public Sector Partner Awards Show, most customer-obsessed mission-based win in the federal category. Congratulations. >> Thank you. >> Thank you. >> Okay, theCUBE's coverage of AWS Public Sector Partner Awards Show, I'm John Furrier, your host of theCUBE. Thanks for watching. (soft electronic melody music)

(upbeat music) >> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. >> Hi everyone, welcome back to theCUBE's coverage of AWS Public Sector Partner Awards Show. I'm John Furrier, host of theCUBE. We're here in Paolo Alto, California but during COVID, we're doin' all the remote interviews and gettin' the stories and celebrating the awards for the Partner Awards Show. And the award here is most customer-obsessed mission-based win in the federal area. We've got two great guests, Greg Siegel Senior Manager at Accenture and Frank Urbano Program Manager with the FBI Federal Bureau of Investigation. Gentlemen, thank you for joining me and congratulations on the win. >> Thank you. >> Thank you. >> So let's break this down. So you're federal, big category, a lot of intelligence agencies been using the gov cloud and Amazon. What's the mission win? What's the award for? Tell us. >> So I guess the award is the Bureau was shutting down our data centers and we needed to move to an infrastructure that would support our application. That was the first problem that we were trying to actually solve. But also, we know we were always seeing a performance hit on our infrastructure, and we always suspected that by moving to the gov cloud, we'll see an increase in performance because once we went live in our current, in or old environment seven years ago, performance was always an issue, our end users were always complaining and then we moved to our VMs four years after that. We saw an increase in performance a little bit but then once we moved over to the cloud, the FBI secret cloud, we heard crickets. The end users haven't been complaining. Greg and I were actually talking about that the other day how, you know, there's minimal complaints as far as performance. That's going to be one of the themes you hear throughout is performance, performance, performance. >> Got to love the no complaints, that means it's workin', people are doin' their job, gettin' the job done. Greg, I want to get your thoughts on this because Accenture, we've had many conversations with you guys over there about being agile and now you're a partner. You know, the FBI, I saw a presentation in person at Reinvent, I think last year where the FBI was like, "Lookit, our workloads "are increasing and budget isn't increasing "at the same rate." So it's kind of like, you know, "I need more power." It's like that scene in Star Trek, "Scotty, more power," you need to get that power. Take us through that transformation because one, you got a good user experience. That means people are doin' their job. But the cases get bigger, the more workload is there, but the budget's got to be increased or leveraged better. What's your thoughts? How do you tackle that problem because it's do more with less, classic do more with less. >> That's right. Yeah, so as Frank said, I think the system had been live for about seven years and you see over that time in the traditional data centers how the performance requirements increase but as you said, are kind of there on hardware and not easily able to adapt and overcome those. So, you know, when it became clear that the cloud move was a serious consideration we were able to pull on a few other experiences that the firm has had moving similar technologies to the cloud and then kind of combined that with the experience implementing technology at the FBI. And those two components kind of together were able to get us on a path to successfully move to the cloud and be, you know, kind of one of the first big systems at the FBI to make that transition. So that was our approach. >> Frank, I'd like to ask, you mentioned crickets. That means, that's good, actually. No one's complaining. What was it like before when you had the data center? What were some of the complaints? What were some of the challenges that you were dealing with? >> So (chuckling) so some of the challenges we were dealing with was, to give an example, when we went live seven years ago, we actually deployed our application on hardware that was already end of life. And so immediately we saw challenges there. And so by moving to the cloud, it gave us a lot of architectural flexibility. And what I mean by that is that we control, now, our own destiny, meaning that in the past, we would have to put in change requests to have firewall configuration changes. Now that responsibility is with us. Our DBAs had limited access to actually do some type of performance tuning on the backend to our databases. Now we have full control of that. I guess a couple of examples, or one example that I would give is that we're in the COVID era, as you mentioned, right? We have a space where we, prior to COVID, we had about 70 people on staff, both government and at Accenture. And all of our development is done on the secret side. And we have major deliverables due at the end of September. Well, COVID hits, we now have to social distance and come up with a plan, and we have to have reduce our staff of 70, both functional developers down to anywhere between 10 people or less on-site. So that, right there, you know, we were talking major hit in our development effort and in cost, I guess, also. While we're doing our social distancing plan Greg came up to me and said, "Hey, why don't we move "our development environment and our test environment "to the gov cloud and scramble the data. "We'll be able to have our developers remote access in "and continue with our development efforts?" And I told Greg, "Great, put a plan together. "Let's talk to our information security officer." I said, "If he signs off on it, let's get off and running." We met with him, he signed off on them, and within two weeks that dev and test environment was up and running. And now, we're still on-track to meet our deliverable dates in September. >> That's a great example, well, that's awesome insight. Greg, expand on that because this is an example of agility. You talk about readiness, I mean it's unforecasted disruption, there's all kinds of use cases. "Oh, we have a hurricane," or whatever, you know. This is unforeseen and unique. Take us through-- >> Yeah, that's absolutely right. >> The agility piece here, on how you got deployed, time frame, and solution. >> Yeah, definitely. So yeah, it can't be overstated how much of a benefit it was that we had already gone through the process of refactoring a lot of our applications into the cloud and using some of those services available and, you know, able to containerize and take some of those application from where they were, as Frank mentioned, scramble the data, and then able to quickly use the cloud experience that we had to stand up an environment in gov cloud where it was more accessible for development that didn't need to take place on-site, was, essentially, the saving grace. We would have had major slowdowns in delivery, as Frank mentioned and a lot of cost implications there, so it really can't be overstated how much that experience having gone through it and being in a spot where we had that flexibility to quickly replicate our architecture, went a long way towards keeping the mission going as the world deals with the pandemic. >> Yeah, this is just a striking example. You know, first of all, I'm a cloud-biased person. I'm very much a, I lean heavily towards pro-cloud so I'll just say this as total bias. There are companies that have gone cloud and took advantage of that refactoring or reinvention and are in a position not only to hit the deadlines but also be in a position of growth strategy, or in this case, a mission-based expansion for the FBI, as Frank was alluding to. Could you imagine, Frank, if you had the data center challenge and you weren't in the cloud? And the you had to go to Greg, or somebody, and say, "Hey, what do you do?" So imagine you had the data center, and then COVID hits. A lot of people are on that side of the street, right now, goin', "What do we do?" >> Yeah, yeah we would have been dead in the water as Greg mentioned. You know, all of our work streams would have been forced out to the left. I couldn't even imagine, you know, the timelines that we would have had to come up with because we would have had to have come up with some rotation plan to develop, you know, team one can only come in on Mondays and Tuesdays and then team two would come in on Wednesdays and Thursdays which would have pushed out our delivery dates and as Greg mentioned also, cost goes up. Time is money, money's time. >> Yeah, I totally, and people goin' out of business because of it and, or settin' their mission back you know, decades. Greg, talk about what goes on next because obviously, congratulations on being a customer success, it's a great mission win here, but you got to get through this. So how are you guys huddling on this point? What are the conversations? What are you thinking? >> Yeah, so now we're at a point where I think, as I'd mentioned, when we first moved to the cloud, the primary mission was getting there securely, getting there within policy, and getting operational so we were making trade-off decisions on where to lift and shift, and where to refactor. Got through all of that successfully. Got through the initial challenge of COVID which definitely threw some of the plans for a loop as we shifted our operations and focused on getting operational in gov cloud. And now we are at a point where we've stabilized delivery again, and we're re-picking up where we left off on the cloud journey which is really focused now, on continuing to look at the investments that AWS is making in the technologies that are coming next. And it really enables us to get ahead of the trends, easily analyze some of these services, available, and then we enter into conversations with Frank and others and start making those trade-off decisions of when it's time to refactor, retire another part of our application and start to look to go cloud-native. So that's where we are now, is looking for ways to maximize and use those services to, again, save costs, improve performance, all of those things that go along with getting more and more mature in the cloud. >> You know, one of the things, Frank, I want to hear your thoughts on just as while I got you guys here is you think about old school, old guard, as Andy Jassy would say, or Teresa talk about. You got silos and you got all these things: legacy. Okay, got that. But as you guys look at your mission have secure data, catch the bad guys, and protect citizens, right? So (chuckling) I mean, I'm over-simplifying but generally, that's it. Data's critical, right? I mean, speed to the edge of the network which is the field and the people doing the job, is critical. Cloud has an opportunity to make that development cycle faster, and ultimately, the workloads and the impact. Could you share your thoughts on how the cloud and Amazon are bringin' that to the table because havin' the right data at the right time could mean the difference between life or death. >> Yeah, so Greg and I experienced this, and again, it's all about having that architectural flexibility, right? So back in February, we had a requirement where we had to expose a large amount of data to employees about themselves, but not only about themselves, but also to their managers. And so, you know, we went through the basic you know, develop it, and then put it into our test environment, however the problem that we had was that we couldn't assimilate the large amount of data that we're exposing to 40,000 FBI employees. Because when we tested out, everything seemed to go fine, but as luck would have it, once we went operational, the application crashed. Our two main engineers come in my office and within 30 minutes, they identified the problem, they had the solution, and we already implemented the solution. Within 30 minutes. You know, going back in the past, like seven years, like you were mentioning, back in the old days, I would have to go around, beg for funding, buy hardware, then I would have to submit a requisition. It would have to go through the approval process. We then would have to procure the hardware, receive the hardware, install it, test it out, load the application, test it again, and then go into Ops. You know, you're lookin' anywhere from a three month to a nine month delay right then and there that our engineers were able to solve within 30 minutes. >> I mean, again, I'm back to my bias again. I'm old enough to remember when I was in college. I mean, I never programmed on punch cards, so that's kind of dates me, (chuckling) but so I'm post punch card generation. I used to look at the guys runnin' the mainframes sayin', "Look at those old relics over there," and "huggin' the mainframe." But what they did was that the smart people repurposed and got into mini-computers, they got into networking, LANs and PCs. This is kind of the cloud moment where if you're going to hold onto that old way you're going to have that operating model, it's just not effective in any way. I just don't see any benefit, other than have a preserved workload that needs the certain data, or you put containers around it and you can bring that in, but there are those corner cases. But generally speaking, you got to move to the new model. >> Mm-hmm. >> Guys, react to that. What's your thoughts? >> Yeah. >> Evermore. Yeah. >> Yeah, I agree, I mean It can't really be overstated, just the flexibility that exists. I think a lot of times, people get hung up on the you know, most efficient way to move to the cloud or you have to use X amount of cloud services. But it can't be overstated, regardless of the approach that you take to making that migration, that once you are there, the kind of intangibles that you get, the ease to take an idea and test it out, flip the switch on, flip the switch off if you like it or not. It's really just opened the door for the team to take some of the more innovative ideas and we have regular conversations with Frank and others that I think are fun for all of us where we get to look at some of these things and we can actually think about and envision how to get them in without, to Frank's point, "putting in requisitions," doing major activities that are going to derail our other schedules to pilot some of these new ideas. >> Frank, you got to attract some, it's a personnel challenge, too. You want to attract young minds, smart, young people. They want what's contemporary and they want state-of-the-art, they want to be in the right positions, drivin' the right, fastest car they can, and being successful. There's a staff component. What's your thoughts on that? Because, you know, if a young person comes in it's like, "Hey, I want to rock and roll with this new stuff, "not the old stuff I see there." >> Right. >> And so Greg put together an innovation team where we have these great, young minds, right? And you know, they're always bringing different ideas, different services that we can utilize on AWS, and sometimes Greg and I have to pull the reins on 'em, like, "Okay, we'll do that, but we have "major applications that we got to develop and deploy." But it's always refreshing and great to see young people with their innovative ideas that they bring to the table. >> Well, final question for you guys, while I got ya here. You know, I've been reporting, we've been saying on these CUBE interviews, trying to make sense of this COVID environment, what's goin' on and what it exposes. And you can see the obvious things. But it generally exposes this great IoT experiment. We're all IoT devices at this point. You've got work places which are not home and office, workforces which are remote, workloads and workflows that are changing, new things are happening. How do you guys see this? Because it ultimately opens up the fact that the architecture has to support multiple endpoints, edge of the network, new connections, new workflows. How are you guys looking at this? What's your vision on this? >> So Greg, I'll take a first crack at it from a Bureau employee being with the Bureau for 31 years. I would never have thought in my wildest dreams that we'd actually have people workin' from home and being able to remote in, and actually do development. And we did it all within two weeks. It's just incredible the obstacles that the team overcome, but also the flexibility of the FBI leadership, knowing that this had to happen in order to, for continuity of operations. >> Great point, great insight. Greg, your thoughts. >> Yeah, I agree with everything that Frank said. It's been a great partnership and I think that the nice thing that surprised us all was when it got down to it, the security controls and requirements were there and able to be met with the tools at our disposal. So I think the great fear that everybody had to Frank's point, it just wasn't something that was normal to this point. But as we were all forced to reevaluate what we had to do, the fear was, "Well, what accommodations are we "going to have to make from a security standpoint?" And the answer was being able to operate again without exposing any of that data, the risk was really extremely low, to zero. All the folks from security we're able to work closely with in partnership, and make this happen again so we can keep delivering the mission. So I think that partnership and getting through it together and all feeling really comfortable that we're doing it in a secure way was really what enabled us to be successful. >> That's a great point. Frank, he brings up something I didn't bring up which is super important. You mentioned in the old way you got to get all these requisitions in purchase. Security is the same kind of new dynamic which is like, "Okay, you got to get "everything tested," but it goes faster when you have the cloud 'cause that's also another criteria, you got to still got to get the approvals whether you're working with another vendor or integrating with another app. That's still now the new issue. So that's got to be approved faster, so that's also now a bottleneck. How does cloud help make those security reviews go faster? >> Right, so so we were the first ones on the cloud. So or security team was still defining the ATO process for us. However, what we did was we aligned ourselves with that team so that we could meet all the security requirements, but also app out all the security controls. And so from the time that we actually had the design till we went into deployment onto the SC2S or the cloud, and we went through the ATO process, it only took us eight months which really, in the past, that effort could have took anywhere from a year and a half to two years just because of the old ATO process. >> Awesome. Well, Greg and Frank, congratulations on a great award, Amazon Public Sector Partner Awards Show, most customer-obsessed mission-based win in the federal category. Congratulations. >> Thank you. >> Thank you. >> Okay, theCUBE's coverage of AWS Public Sector Partner Awards Show, I'm John Furrier, your host of theCUBE. Thanks for watching. (soft electronic melody music)

(upbeat music) >> Narrator: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE Coversation. >> All right everybody, this is Dave Vellante and welcome to this special CUBE Conversation. I first met Frank Slootman in 2007 when he was the CEO of Data Domain. Back then he was the CEO of a disruptive company and still is. Data Domain, believe or not back then, was actually replacing tape drives as the primary mechanism for backup. Yes, believe it or not, it used to be tape. Fast forward several years later, I met Frank again at VMworld when he had become the CEO of ServiceNow. At the time ServiceNow was a small company, about 100 plus million dollars. Frank and his team took that company to 1.2 billion. And Gartner, at the time of IPO said "you know, this doesn't make sense. "It's a small market, it's a very narrow help desk market, "it's maybe a couple billion dollars." The vision of Slootman and his team was to really expand the total available market and execute like a laser. Which they did and today, ServiceNow a very, very successful company. Snowflake first came into my line of sight in 2015 when SiliconANGLE wrote an article, "Why Snowflake is Better "Than Amazon Redshift, Re-imagining Data". Well last year Frank Slootman joined Snowflake, another disruptive company. And he's here today to talk about how Snowflake is really participating in this COVID-19 crisis. And I really want to share some of Frank's insights and leadership principles, Frank great to see you, thanks for coming on. >> Yeah, thanks for having us Dave. >> So when I first reported earlier this year on Snowflake and shared some data with the community, you reached back out to me and said "Dave, I want to just share with you. "I am not a playbook CEO, I am a situational CEO. "This is what I learned in the military." So Frank, this COVID-19 situation was thrown at you, it's a black swan, what was your first move as a leader? >> Well, my first move is let's not overreact. Take a deep breath. Let's really examine what we know. Let's not jump to conclusions, let's not try to project things that we're not capable of projecting. That's hard because we tend to have sort of levels of certainty about what's going to happen in the week, in the next month and so on and all of a sudden that's out of the window. It creates enormous anxiety with people. So in other words you got to sort of reset to okay, what do we know, what can we do, what do we control? And not let our minds sort of go out of control. So I talk to our people all the time about maintain a sense of normalcy, focus on the work, stay in the moment and by the way, turn the newsfeed off, right, because the hysteria you get fed through the media is really not helpful, right? So just cool down and focus on what we still can do. And then I think then everybody takes a deep breath and we just go back to work. I mean, we're in this mode now for three weeks and I can tell you, I'm on teleconferencing calls, whatever, eight, nine hours a day. Prospects, customers, all over the world. Pretty much what I was doing before except I'm not traveling right now. So it's not, >> Yeah, so it sounds clear-- >> Not that different than what it was before. (laughs) >> It sounds very Bill Belichickian, you know? >> Yeah. >> Focus on those things of which you can control. When you were running ServiceNow I really learned it from you and of course Mike Scarpelli, your then and current CFO about the importance of transparency. And I'm interested in how you're communicating, it sounds like you're doing some very similar things but have you changed the way in which you've communicated to your team, your internal employees at all? >> We're communicating much more. Because we can no longer rely on sort of running into people here, there and everywhere. So we have to be much more purposeful about communications. For example, I mean I send an email out to the entire company on Monday morning. And it's kind of a bunch of anecdotes. Just to bring the connection back, the normalcy. It just helps people get connected back to the mothership and like well, things are still going on. We're still talking in the way we always used to be. And that really helps and I also, I check in with people a lot more, I ask all of our leadership to constantly check in with people because you can't assume that everybody is okay, you can't be out of sight, out of mind. So we need to be more purposeful in reaching out and communicating with people than we were previously. >> And a lot of people obviously concerned about their jobs. Have you sort of communicated, what have you communicated to employees about layoffs? I mean, you guys just did a large raise just before all this, your timing was kind of impeccable. But what have you communicated in that regard? >> I've said, there's no layoffs on our radar, number one. Number two, we are hiring. And number three is we have a higher level of scrutiny on the hires that we're making. And I am very transparent. In other words I tell people look, I prioritize the roles that are closest to the direct train of the business. Right, it's kind of common sense. But I wanted to make sure that this is how we're thinking about it. There are some roles that are more postponable than others. I'm hiring in engineering without any reservation because that is the long term strategic interest of the company. One the sales side, I want to know that sales leaders know how to convert to yields, that we're not just sort of bringing capacity online. And the leadership is not convinced or confident that they can convert to yield. So there's a little bit finer level of scrutiny on the hiring. But by and large, it's not that different. There's this saying out there that we should suspend all non-essential spending and hiring, I'm like you should always do that. Right? I mean what's different today? (both laugh) If it's non-essential, why do it, right? So all of this comes back to this is probably how we should operate anyways, yep. >> I want to talk a little bit about the tech behind Snowflake. I'm very sensitive when CEOs come on my program to make sure that we're not, I'm not trying to bait CEOs into ambulance chasing, that's not what it's about. But I do want to share with our community kind of what's new, what's changed and how companies like Snowflake are participating in this crisis. And in particular, we've been reporting for awhile, if you guys bring up that first slide. That the innovation in the industry is really no longer about Moore's Law. It's really shifted. There's a new, what we call an innovation cocktail in the business and we've collected all this data over the last 10 years. With Hadoop and other distributed data and now we have Edge Data, et cetera, there's this huge trove of data. And now AI is becoming real, it's becoming much more economical. So applying machine intelligence to this data and then the Cloud allows us to do this at scale. It allows us to bring in more data sources. It brings an agility in. So I wonder if you could talk about sort of this premise and how you guys fit. >> Yeah, I would start off by reordering the sequence and saying Cloud's number one. That is foundational. That helps us bring scale to data that we never had to number two, it helps us bring computational power to data at levels we've never had before. And that just means that queries and workloads can complete orders of magnitude faster than they ever could before. And that introduces concepts like the time value of data, right? The faster you get it, the more impactful and powerful it is. I do agree, I view AI as sort of the next generation of analytics. Instead of using data to inform people, we're using data to drive processes and businesses directly, right? So I'm agreeing obviously with these strengths because we're the principal beneficiaries and drivers of these platforms. >> Well when we talked about earlier this year about Snowflake, we really brought up the notion that you guys were one of the first if not the first. And guys, bring back Frank, I got to see him. (Frank chuckles) One of the first to really sort of separate the notion of being able to scale, compute independent of storage. And that brought not only economics but it brought flexibility. So you've got this Cloud-native database. Again, what caught my attention in that Redshift article we wrote is essentially for our audience, Redshift was based on ParAccel. Amazon did a great job of really sort of making that a Cloud database but it really wasn't born in the Cloud and that's sort of the advantage of Snowflake. So that architectural approach is starting to really take hold. So I want to give an example. Guys if you bring up the next chart. This is an example of a system that I've been using since early January when I saw this COVID come out. Somebody texted me this. And it's the Johns Hopkins dataset, it's awesome. It shows you, go around the map, you can follow it, it's pretty close to real time. And it's quite good. But the problem is, all right thank you guys. The problem is that when I started to look at, I wanted to get into sort of a more granular view of the counties. And I couldn't do that. So guys bring up the next slide if you would. So what I did was I searched around and I found a New York Times GitHub data instance. And you can see it in the top left here. And basically it was a CSV. And notice what it says, it says we can't make this file beautiful and searchable because it's essentially too big. And then I ran into what you guys are doing with Star Schema, Star Schema's a data company. And essentially you guys made the notion that look, the Johns Hopkins dataset as great as it is it's not sort of ready for analytics, it's got to be cleaned, et cetera. And so I want you to talk about that a little bit. Guys, if you could bring Frank back. And share with us what you guys have done with Star Schema and how that's helping understand COVID-19 and its progression. >> Yeah, one of the really cool concepts I've felt about Snowflake is what we call the data sharing architecture. And what that really means is that if you and I both have Snowflake accounts, even though we work for different institutions, we can share data optics, tables, schema, whatever they are with each other. And you can process against that in place if they are residing in a local, to your own platform. We have taken that concept from private also to public. So that data providers like Star Schema can list their datasets, because they're a data company, so obviously it's in their business interest to allow this data to be profiled and to be accessible by the Snowflake community. And this data is what we call analytics ready. It is instantly accessible. It is also continually updated, you have to do nothing. It's augmented with incremental data and then our Snowflake users can just combine this data with supply chain, with economic data, with internal operating data and so on. And we got a very strong reaction from our customer base because they're like "man, you're saving us weeks "if not months just getting prepared to start to do an al, let alone doing them." Right? Because the data is analytics ready and they have to do literally nothing. I mean in other words if they ask us for it in the morning, in the afternoon they'll be running workloads again. Right, and then combining it with their own data. >> Yeah, so I should point out that that New York Times GitHub dataset that I showed you, it's a couple of days behind. We're talking here about near realtime, or as close as realtime as you can get, is that right? >> Yep. Yeah, every day it gets updated. >> So the other thing, one of the things we've been reporting, and Frank I wondered if you could comment on this, is this new emerging workloads in the Cloud. We've been reporting on this for a couple of years. The first generation of Cloud was IS, was really about compute, storage, some database infrastructure. But really now what we're seeing is these analytic data stores where the valuable data is sitting and much of it is in the Cloud and bringing machine intelligence and data science capabilities to that, to allow for this realtime or near realtime analysis. And that is a new, emerging workload that is really gaining a lot of steam as these companies try to go to this so-called digital transformation. Your comments on that. >> Yeah, we refer to that as the emergence or the rise of the data Cloud. If you look at the Cloud landscape, we're all very familiar with the infrastructure clouds. AWS and Azure and GCP and so on, it's just massive storage and servers. And obviously there's data locked in to those infrastructure clouds as well. We've been familiar for it for 10, 20 years now with application clouds, notably Salesforce but obviously Workday, ServiceNow, SAP and so on, they also have data in them, right? But now you're seeing that people are unsiloing the data. This is super important. Because as long as the data is locked in these infrastructure clouds, in these application clouds, we can't do the things that we need to do with it, right? We have to unsilo it to allow the scale of querying and execution against that data. And you don't see that any more clear that you do right now during this meltdown that we're experiencing. >> Okay so I learned long ago Frank not to argue with you but I want to push you on something. (Frank laughs) So I'm not trying to be argumentative. But one of those silos is on-prem. I've heard you talk about "look, we're a Cloud company. "We're Cloud first, we're Cloud only. "We're not going to do an on-prem version." But some of that data lives on-prem. There are companies out there that are saying "hey, we separate compute and storage too, "we run in the Cloud. "But we also run on-prem, that's our big differentiator." Your thoughts on that. >> Yeah, we burnt the ship behind us. Okay, we're not doing this endless hedging that people have done for 20 years, sort of keeping a leg in both worlds. Forget it, this will only work in the public Cloud. Because this is how the utility model works, right? I think everybody is coming to this realization, right? I mean excuses are running out at this point. We think that it'll, people will come to the public Cloud a lot sooner than we will ever come to the private Cloud. It's not that we can't run on a private cloud, it just diminishes the potential and the value that we bring. >> So as sort of mentioned in my intro, you have always been at the forefront of disruption. And you think about digital transformation. You know Frank we go to all of these events, it used to be physical and now we're doing theCUBE digital. And so everybody talks about digital transformation. CEOs get up, they talk about how they're helping their customers move to digital. But the reality is is when you actually talk to businesses, there was a lot of complacency. "Hey, this isn't really going to happen in my lifetime" or "we're doing pretty well." Or maybe the CEO might be committed but it doesn't necessarily trickle down to the P&L managers who have an update. One of the things that we've been talking about is COVID-19 is going to accelerate that digital transformation and make it a mandate. You're seeing it obviously in retail play out and a number of other industries, supply chains are, this has wreaked havoc on supply chains. And so there's going to be a rethinking. What are your thoughts on the acceleration of digital transformation? >> Well obviously the crisis that we're experiencing is obviously an enormous catalyst for digital transformation and everything that that entails. And what that means and I think as a industry we're just victims of inertia. Right, I mean haven't understood for 20 years why education, both K through 12 but also higher ed, why they're so brick and mortar bound and the way they're doing things, right? And we could massively scale and drop the cost of education by going digital. Now we're forced into it and everybody's like "wow, "this is not bad." You're right, it isn't, right but we haven't so the economics, the economic imperative hasn't really set in but it is now. So these are all great things. Having said that, there are also limits to digital transformation. And I'm sort of experiencing that right now, being on video calls all day. And oftentimes people I've never met before, right? There's still a barrier there, right? It's not like digital can replace absolutely everything. And that is just not true, right? I mean there's some level of filter that just doesn't happen when you're digital. So there's still a need for people to be in the same place. I don't want to sort of over rotate on this concept, that like okay, from here on out we're all going to be on the wires, that's not the way it will be. >> Yeah, be balanced. So earlier you made a comment, that "we should never "be spending on non-essential items". And so you've seen (Frank laughs) back in 2008 you saw the Rest in Peace good times, you've seen the black swan memos that go out. I assume that, I mean you're a very successful investor as well, you've done a couple of stints in the VC community. What are you seeing in the Valley in regard to investments, will investments continue, will we continue to feed innovation, what's your sense of that? Well this is another wake up call. Because in Silicon Valley there's way too much money. There's certainly a lot of ideas but there's not a lot of people that can execute on it. So what happens is a lot of things get funded and the execution is either no good or it's just not a valid opportunity. And when you go through a downturn like this you're finding out that those businesses are not going to make it. I mean when the tide is running out, only the strongest players are going to survive that. It's almost a natural selection process that happens from time to time. It's not necessarily a bad thing because people get reallocated. I mean Silicon Valley is basically one giant beehive, right? I mean we're constantly repurposing money and people and talent and so on. And that's actually good because if an idea is not worth in investing in, let's not do it. Let's repurpose those resources in places where it has merit, where it has viability. >> Well Frank, I want to thank you for coming on. Look, I mean you don't have to do this. You could've retired long, long ago but having leaders like you in place in these times of crisis, but even when in good times to lead companies, inspire people. And we really appreciate what you do for companies, for your employees, for your customers and certainly for our community, so thanks again, I really appreciate it. >> Happy to do it, thanks Dave. >> All right and thank you for watching everybody, Dave Vellante for theCUBE, we will see you next time. (upbeat music)