 From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. Hi everybody, this is Dave Vellante and welcome to the special CUBE Conversation. I first met Frank Slutman in 2007 when he was the CEO of Data Domain. Back then he was a CEO of a disruptive company and still is. Data Domain, believe it 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 a hundred plus million dollars. Frank and his team took that company to 1.2 billion and Gartner at the time of the 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 of billion dollars. The vision of Slutman 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, reimagining data. Well, last year, Frank Slutman joined Snowflake, another disruptive company. And he's here today to talk about how Snowflake is really participating in this COVID-19 crisis and really want to share some of Frank's insights and leadership principles. Frank, great to see you. Thanks for coming on. Yes, 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 kind of, 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 next week in the next month and so on. All of a sudden, that's out of the window. 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, you know, 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. Yeah, so it's not that different than what it was before. It sounds very Bill Belichickian, you know, to focus on those things at which you can control. When you were running service now, I really learned from you and of course, Mike Scarpelli, you're 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, you know, sort of the running into people here, there and everywhere. So we have to be much more purposeful about communications. Now, for example, I mean, I sent an email out to the entire company on Monday morning, you know, and it's kind of a bunch of anecdotes. Just to bring the connection back, the normalcy, you know, it just helps people, you know, get connected back to the mothership and like, well, you know, things are still going on, you know, we're still talking in the way we always used to be. That really helps. And I also, you know, 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. I mean, 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? You know, I've said, there's no layoffs on our radar. Number one, number two, we are hiring. And number three is, you know, 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, you know, I prioritize the roles that are closest to the direct train of the business, right? It's kind of common sense, but you know, 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 and engineering without any reservation because that is the long-term, you know, strategic interest of the company. On the sales side, I want to know that sales leaders, you know, know how to convert to yield, right? That we're not just sort of, you know, bringing capacity online and the leadership, you know, is not convinced or confident that they can convert to yield. So there's a little bit, you know, finer level of scrutiny on the hiring, but by and large, you know, it's not that different. There's this saying out there that, you know, we should suspend all non-essential spending and hiring. I'm like, you should always do that, right? I mean, what's different today? If it's non-essential, why do it, right? So all of this comes back to, you know, this is how we probably should operate anyways. You know. 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, you know, I'm not trying to bait CEOs into, you know, ambulance chasing, that's not what this is 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 a while, if you guys bring up that first slide, that, you know, the innovation in the industry is really no longer about Moore's law. You know, it's really shifted. There's a new, what we call innovation cocktail in the business. We've collected all this data over the last 10 years, you know, with Hadoop and other distributed data. Now we have edge data, et cetera. There's this huge trove of data. 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, you know, clouds 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 order of magnitude faster than they ever could before. And that introduces concepts like the time value of data. The faster you get it, the more impactful and powerful it is. I do agree. I view AI sort of next generation of analytics. You know, instead of using data to inform people, you know, we're using data to drive processes and business directly, right? So I'm agreeing with obviously with these trends because we're the principal beneficiaries and drivers of these platforms. Well, when we talked about earlier this year about a 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. 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 that we wrote is essentially for our audience, Redshift was based on ParXL. 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 the early January when I saw this, you know, COVID come out, somebody texted me this and it's the John Hopkins data set, it's awesome. It shows you that, you know, around the map, you can follow it, it's pretty close to real time and it's quite good. But the problem is, I 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 on the top left here. And basically it was a CSV and notice what it says is 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 is a data company and essentially you guys made the notion that, look, the John Hopkins data set is great as it is, it's not 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 felt, you know, about Snowflake is what we call the data sharing architecture, what that really means is that, you know, Vue and I both have Snowflake accounts even though we work for different institutions, you know, we can, you know, share data objects, tables, schema, whatever they are with each other and you can process against that in place as if they are residing in their local to your own platform. We have taken that concept from private also to public so that data providers like Star Schema, you know, can list their data sets 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, you know, our Snowflake users can just combine this data with supply chain, with economic data, with internal operating data and so on. We got a very strong reaction from our customer base because they're like, man, you're saving as weeks if not months, just getting prepared to start to do an L, let alone doing it, right? Because the data is analytics ready and they have to do literally nothing. I mean, in other words, if they ask us forward in the morning, in the afternoon, they'll be running workloads against it, right? And combining it with their own data. Yeah, so I just point out that New York Times GitHub data set that I showed you, it's a couple of days behind. We're talking here about near real time or as close as real time as you can get, is that right? Yeah, it's every day gets updated. So the other thing, one of the things we've been reporting, and Frank, I wonder if you can comment on this, is this new emerging workloads in the cloud. We've been reporting on this for a couple of years. You know, the first generation of cloud was IAS. It 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 real time or near real time 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. You know, 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 into those infrastructure clouds as well. We've been familiar for 10, 20 years now with application clouds, you know, notably Salesforce, but obviously, you know, Workbase Service Now, SAP and so on. They also have data in them, right? But now you're seeing that, you know, people are un-siloing the data. This is super important because as long as the data is locked in these infrastructure cloud, in these application cloud, we can do the things that we need to do with it, right? We have to un-silo it to allow the scale of querying and execution against that data. And you don't see that any more clearly than 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. 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 burned the ship behind us, okay? We're not doing this endless hedging that people have done for 20 years, you know, sort of keeping, you know, 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, the excuses are running out at this point. You know, we think that 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 a private cloud, it just diminishes the potential and the value that we bring. So as I 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 these events who used to be physical and now we're doing, you know, the cube digital. And so everybody talks about digital transformation. CEOs get up, they talk about how they're helping their customers, you know, move to digital. But the reality is when you actually talk to businesses, there was a lot of complacency. Hey, you know, 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 with the P and L managers who have a nut date. 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 sort of, you're seeing it obviously in retail play out and the number of other industries, supply chains are, you know, this is wreak 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 Rich Bernstein is obviously an enormous catalyst for digital transformation and everything that that entails and what that means. I think we, you know, as an industry, we're just victims of inertia, right? I mean, I haven't understood for 20 years why education, both K through 12 but also higher at, you know, why you're so brick and mortar bound, you know, on the way they're doing things, right? We could massively scale and drop the cost of education, you know, by going digital and 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, you know, the economic imperative hasn't really set in, but it is now. So these are all great things. You know, having said that, you know, there are also limits to digital transformation and I'm sort of experiencing that right now, you know, being on video calls all day and oftentimes the people that 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 and I want to sort of over rotate on this concept. And they're like, okay, I'm here on out, you know, we're all going to be on the wire. That's not the way it will be. Yeah, be balanced. So earlier you made a comment that hook, we should never be spending on non-essential items. And so you've seen, you know, back in 2008, you saw, you know, the rest in peace, good times. You've seen, you know, 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 with regard to investments? You know, will investments continue? Will we continue to feed innovation? What's your sense of that? Well, this is another wake-up call, you know, 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, you know, a lot of things get funded and the execution is either, you know, no good or it's just not a valid opportunity. And when you go through a downturn like this, you know, you're finding out that, you know, those businesses are not going to make it. I mean, when the tide is running out, you know, only the strongest players, you know, are going to survive that. It's almost a, you know, a natural, you know, selection, you know, 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 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 know, you could have 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, really appreciate it. I hope you to do it. Thanks, Dave. All right, and thank you for watching everybody. Dave Vellante for theCUBE. We will see you next time.