 Hi everybody, welcome back to Caesars in Las Vegas. My name is Dave Vellante. We're here with the Chairman and CEO of Snowflake Frank Slutman. Good to see you again Frank, thanks for coming on. Yeah, you as well Dave, good to be with you. It's awesome to be, obviously everybody's excited to be back, you mentioned that 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. 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? Well, you know, when you are a data cloud and you have data, people want to 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 want to build businesses on it. So it goes on and on and on. So 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, sort of similar to what happened to Facebook in many ways, you know. There was some confusion, I think, and there still is in the community, particularly on Wall Street, about your quarter. The consumption model. I loved, on the earnings call, one of the analysts asked Mike, do you ever consider going to a subscription model and like cut them off and then let them finish? No, that would really defeat the purpose. And so there's also a narrative around, well, maybe Snowflake consumption's easier to dial down. Maybe it's more discretionary, but 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 with those cloud costs. And so unless you're selling it for more, it costs more than you're selling it for, you're going to dial that up. And that is the future of, I see this ecosystem in your company. Is that fair, you buy that? Yeah, it is fair. Obviously, the public cloud runs on a consumption model, so you start looking all the layers of the stack. Snowflake, we have to be a consumption model because we run on top of other people's consumption models, otherwise you don't have alignment. We have conversations with people that build on Snowflake. They have trouble with their financial model because they're not running a consumption model, so it's like square packing around whole. So we all have to align ourselves, so that when they pay a dollar, a portion goes to, let's say AWS, portion goes to Snowflake of that dollar and the portion goes to whatever the uplift is, application value, data value, whatever it is that goes on top of that. So the whole dollar gets allocated depending on whose value at it we're talking about. Yeah, but you sell value, so you're not a SaaS company. At least, I don't look at you that way. I've always felt like the SaaS pricing model is flawed because it's not aligned with customers, right? If you get stuck with orphaned licenses, too bad. Pay us. Yeah, we're obviously a SaaS model in the sense that they're 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 when you buy so many users from Salesforce and ServiceNow or whoever, you have just purchased the right for so many users to use that software for this period of time and the revenue gets recognized radically, one month at a time, the same amount. Now, we're not that different because we still do a contract the exact same way a SaaS 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's just not neatly organized in these monthly buckets. So what happens if they underspend one quarter? They have to catch up by the end of the term? Is that how it works or is that a negotiation? The spending is totally separate from the consumption itself, because how they pay for the contract, let's say they do a three-year contract, they will probably pay for that on an annual basis, that three-year contract. 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, all of that needs to get consumed or they expire. And it's the same way with Amazon. If I don't consume what I buy from Amazon, I still got to pay for it. I guess you could buy by the drink, but it's way, way more expensive than nobody really does that. Okay, phase one, better, simpler, cloud, enterprise data warehouse. Phase two, you introduced the data cloud and now we're seeing the rise of the data cloud. What does phase three look like? Phase three is all about applications. We've just learned from the beginning that people were trying to do this, but we weren't instrumental at all to do it. So people with ODBC, JDBC drivers just uses this as a database, right? So the entire application would happen outside of Snowflake. We're just a database. You connect to the database, you read or write data, you do data manipulations, and then the application processing all happens outside of Snowflake. Now there's issues with that because we start to exfiltrate data, meaning that we start to take data out of Snowflake and put it in other places. Now there's risk with that. There's operational risk, there's governance exposure, security issues, all this kind of stuff. And the other problem is data gets re-siloated, it proliferates, and then data scientists are like, well, I need that data to stay in one place. That's the whole idea behind the data cloud. We have very big infrastructure clouds. We have very big application clouds, and then data sort of became the victim there and became more proliferated and more segmented than it's ever been. So all we do is just send data to the work all day, and we said, no. We're going to enable the work to get to the data and the data that stays in one place. We don't have latency issue, we don't have data quality issues, we don't have lineage issues. So people have responded very, very well to the data cloud idea. It's like, yeah, as an enterprise or an institution, 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. For example, take an investment bank in New York City. They send data to Fidelity, they send data to BlackRock, they send data to Bank of New York, all the regulatory clearing houses on and on and on. Every night they're running thousands, tens of thousands of jobs pushing that data out there. They're all on Snowflake already, so it doesn't have to be this way, right? Yes, so I asked the guys before last week, hey, what would you ask, Frank? Now you might remember, you came on our program during COVID and I was asking you how you're dealing with it, turn off the news and that was cool. And I asked you at the time, will you ever go on-prem? 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 think I know the answer, but I want to hear from you. Did a customer come to you and say, get in a headlock and say, you got to do this? It didn't happen that way. It started with a conversation I had with Michael Dell. It was supposed to be just a friendly chat. Hey, how's it going? And I mean, obviously Dell is the owner of Data Domain, our first company. But it wasn't easy 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 cloth company. And it's like, what do we have in common here? What can we talk about? But Michael's a very smart, engaging guy, always looking for opportunity. And of course, he decides, we're going to hook up our CTOs, our product teams, and explore somebody's ideas. And yeah, we had some starts and restarts and all of that because it's just naturally, not an easy thing to conceive of, but in the end, it was like, you know what? It makes a lot of sense. We can virtualize Dell object storage as if it's an S3 storage from Amazon and then Snowflake in its analytical processing will just reference that data because to us it just looks like a file that's sitting on an S3. And we have such a thing, it's called an external table. That's how we basically, it projects a Snowflake semantic and structural model on an external object and we process against it exactly the same way as if it was an internal table. So we just extended that with our storage partners like Dell and Pure Storage for it to happen across a network to an on-premise place. So it's very elegant and it becomes an enterprise architecture rather than just a cloud architecture. And 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. You just can't go anywhere because they process against it where it originates. But there are analytical processes that want to reference attributes off that data. Well, this is what will do that. Yeah, it's interesting. I'm going to ask Dell, if I were them, I'd be talking to you about, hey, I'm going to try to separate compute from storage on-prem and maybe do some of the work there. I don't even know if it's technically feasible. I'll ask Benoit. But to me, that's an example of your extending your ecosystem. 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 there yet. But as you've said before, there's no lack of market for you. Yeah, I mean, obviously it's no flake. It's genesis was reinventing database management in a cloud computing environment which is so different from a machine environment or a cluster environment. So that's why we're not a fit for a machine-centric environment, sort of defeats the purpose of how we were built. We are truly a native solution. Most products in the cloud are actually not cloud native. They originated in machine environments and you still see that. 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. 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, yeah, we're in the cloud, too. And you basically get, you just shift it. It didn't make sense. Well, they throw it in the container and run it. Yeah, okay, that's cool. But what does that get you? That doesn't change your operational model. So coming back to software development and what you're doing in that regard, it's one of the things we said about super cloud is in order to have a super cloud, you got to have an ecosystem. You got to have optionality. Hence, you're doing things like Apache Iceberg. You know, you said today, well, we're not sure where it's going to go, but we're offering options. But my question is, as it pertains to software development specifically, how do you, so one of the things we said, sorry, lost my train there. One of the things we said is you have to have a super pass in order to have a super cloud. The ecosystem, pass layer, that's essentially what you've introduced here is it not a platform for application development? Yeah, I mean, what happens today? I mean, how do you enable a developer on Snowflake without the developer reading the files out of Snowflake processing against that data wherever they are and then putting the results that God knows where, right? And that's what happens today. It's the Wild West. It's completely ungoverned, right? And that's the reason why lots of enterprises will not allow Python anywhere near their enterprise data. We just know that. We also know it from Streamlit or the acquisition, large acquisition that we made this year because they said, look, we have a lot of demand in the Python community, but that's the Wild West. That's not the enterprise-grade, high-trust corporate environment. They are strictly segregated today. Now, do these things sometimes dribble up in the enterprise? Yes, they do, and it's actually intolerable. The risk that enterprises take with things being ungoverned. I mean, the whole Snowflake strategy and promise is that, you're in Snowflake, it is an absolute enterprise-grade environment experience, and it's really hard to do. It takes enormous investment, but that is what you buy from us. Just having Python is not particularly hard. We can do that in a week. This has taken us years to get it to this level of governance, security, and 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 everything that may not have been understood or foreseen. So there are trade-offs of going into the Snowflake. You get all this great functionality. Some people might think it's a walled garden. How would you respond to that? Yeah, and it's true. When you have a Snowflake object, like a Snowflake table, only Snowflake runs that table, and that is, it's a very high function. It's sort of analogous to what Apple did. They have very high functioning, but you do have to accept the fact that it's not, other things than Apple cannot get at these objects. So this is the reason why we introduce an open file format, like Iceberg, because what Iceberg effectively does is it allows any tool to access that particular object. We do it in such a way that a lot of the functionality of Snowflake will address the Iceberg format, which is great because you're going to get much more function out of our Iceberg implementation than you would get from Iceberg on its own. So we do it in a very high value added manner, but other tools can still access the same object in a read-write manner. So it really sort of delivers the original 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, so you get the best of both worlds for the most part. I mean, it reminds me a little bit of VMware. I mean, VMware is a software mainframe. It's just better than doing it on your own. One of the other hallmarks of a cloud company, and you guys clearly are a cloud company, is startups and innovation. Now, of course, you see that in the ecosystem, and maybe that's the answer to my question, but you guys are kind of whale hunters. Your customers tend to be bigger. Is the innovation now, the extension of that, the ecosystem? Is that by design? You know, we have an enormous ISV following, and we're going to have a whole separate conference, like this part of the way, just for developers. I hope you guys will show up there too, yeah. The reason that the ISV strategy is very important for many reasons, but 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 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 going to run infrastructure, database operations, security, compliance, scalability, economics? How do you do that as a software company where really you only have your domain expertise that you want to deliver on a platform? You don't want to do all these things. First of all, you don't know how to do it, how to do it well, so it is much easier, much faster when there is a ready platform to actually build done. In the world of cloud, that just doesn't exist. And then beyond that, okay, fine, building it to sort of step one, now I got to sell it. I got to market it. So how do we do that? Well, in the Snowflake community, you have a ready market. There's thousands and thousands of customers that are also on Snowflake, okay? So their ability to consume that service that you just built, they can search it, they can try it, they can test it, and decide whether they want to consume it. And then we can monetize it. So all they have to do is cast a check. So the net effect of it is we drastically lowered the barriers to entry into the world of software. Two men or two women and a dog in a handful of files can build something that then can be sold. Sort of tick-tock for software developers. I wrote a piece, 2012, after the first re-invent, and I put a big gorilla on the front page and said, how do you compete with the Amazon gorilla? And one of my answers was, you build the data ecosystems and you verticalize, and that's what you're doing here. Yeah, there are certainly verticals that are farther along than others, obviously, but for example, in financial, which is our largest vertical, I mean, the data ecosystem is really developing hardcore now, and that's because they so rely on those relationships between all the big financial institutions and entities, regulatory clearinghouses, investment bankers, retail banks, all this kind of stuff. So they're like, it becomes a no-brainer. The network effects 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 networking connection between us, I mean, it would take forever to get our lawyers to agree that, yeah, it's okay. Right. Now it's like a matter of minutes to set it up if we're both on snowflake. It's like procurement, do you have an MSA? Yeah. And it just sails right through versus back and forth and endless negotiations. So 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. Correct. Again, you know, you weren't the first to come up with that notion, but you are applying it here. I want to switch topics a little bit. When I read your press releases, I laugh every time, because it says no HQ Boseman. And so, where do you, I think I know where you land on hybrid work and remote work, but what are your thoughts on that? You see Elon the other day said you can't work for us unless you come to the office. Where do you stand? Yeah, well, the first aspect is we really wanted to 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 decisions that whole way of thinking, you know, it's obsolete. I mean, I am where I need to be. And it's many different places. It's not like I sit in this incredible place, you know, and 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 regional headquarters for sales, obviously, we have in Malaysia, we have in Europe, you know. So I want to get rid of this headquarters designation. And the other issue, obviously, is that, you know, we were obviously in California, but California is no longer the dominant place of where we are resident. I mean, 40% of our engineering people are now in Bellevue, Washington. You know, we have hundreds of people in Poland where people, you know, we are going to have a very special location in Toronto. You know, obviously our customers are everywhere, right? So this idea that, you know, everything is happening in one state is just, you know, not correct. So we wanted to go to no headquarters. Of course, the SEC doesn't let you do that because they want you to have a street address where the government can send you mail. And that becomes a question as well, what's an acceptable location? Well, it has to be a place where the CEO and the CFO have residency. By hook or by crook, that happened to be in Bozeman, Montana because Mike and I are both, and it was not by design. We just did that because we were required to, you know, comply with government requirements, which of course we do. But that's why it says what it says. Now, on the topic of, you know, where do we work? We are super situational about it. It's not like, hey, you know, everybody in the office or everybody is remote, we're not categorical about it. Depends on the function, depends on the location. But everybody is tethered to an office. Okay, in other words, everybody has a relationship with an office. There's almost nobody, there are a few exceptions of people that are completely remote. 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 a 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. And we're now into hoteling, right? So you don't have a fixed place, you know. You're talking to your keynote a lot about, last question, I'll let you go, customer alignment is 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 shake your head and say, well, 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. So that's a whole different conversation. And I wonder if you could sort of close on how that's different. I mean, at service now you transformed IT. You know, I get that, you know, the data domain was, okay, tape, blow it out. But this feels like a whole new vector wave of growth. Yeah, you know, monetizing data becomes sort of, you know, a byproduct of having a data cloud. You all of a sudden become aware of the fact that hey, I have data and be, that data might actually be quite valuable to parties and then see, you know, it's really easy to then, you know, sell that and monetize that because it was hard to 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. I just want to reference one attribute, two attributes of what you have. By the way, you know, Edge funds have been into this sort of thing for a long time because they procure data from hundreds and hundreds of sources, right? Because they are the original data scientists. But the bigger thing with data is that a lot of, you know, digital transformation 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 run a supply chain? You know, how do we run, you know, healthcare? All these things are becoming, how do we run cybersecurity? They're being redefined as data problems and data challenges and they have data solutions. So that's why data strategies are insanely important because, you know, if the solution is through data, then you need to have, you know, a data strategy. You know, 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 saying, you know, data science is going to 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 have conversations with hospital executives that are like, I got generations of data, you know, clinical, diagnostic, demographic, genomic, and then I am envisioning these predictive outcomes over here. I want to be able to predict, you know, once somebody's going to get what disease and, you know, what I have to do about it, how do I do that? Right, there you go from, you know, I have a lot of data too, I have these outcomes and then do me a miracle in the middle somewhere. Well, that's where we come in. We're going to organize ourselves and then unpack that, you know, and then we work through training models, you know, we can start delivering some of these insights, but the promise is extraordinary. We can change whole industries like pharma and healthcare, you know, through the effects of data, the economics will change and, you know, the societal outcomes, you know, quality of life, disease, longevity of life, it's quite extraordinary. Supply chain management, it'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 opportunity's enormous. You're not slowing down. You're amping it up, you know, pun intended. So Frank Slutman, thanks so much for coming to theCUBE. 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 theCUBE.