(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)