Good afternoon. Thank you for attending today's Q2 FY 2023 Snowflake Earnings conference call. My name is Hannah, and I will be your moderator for today's call. All lines will be muted during the presentation portion of the call, with an opportunity for questions and answers at the end. If you would like to ask a question, please press star one on your telephone keypad. I would now like to pass the conference over to our host, Jimmy Sexton, Head of Investor Relations. Please go ahead. Good afternoon, and thank you for joining us on Snowflake's Q2 fiscal 2023 earnings call. With me in Bozeman, Montana, are Frank Slootman, our Chairman and Chief Executive Officer, Michael Scarpelli, our Chief Financial Officer, and Christian Kleinerman, our Senior Vice President of Product, who will join us for the Q&A session. During today's call, we will review our financial results for the second quarter fiscal 2023, and discuss our guidance for the third quarter and full year fiscal 2023. During today's call, we will make forward-looking statements, including statements related to the expected performance of our business, future financial results, strategy, products, and features, long-term growth, and overall future prospects. These statements are subject to risks and uncertainties, which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after market close today, and in our SEC filings, including our most recently filed Form 10-Q for the first quarter ended April 30, 2022, and the Form 10-Q for the quarter ended July 31, 2022 that we will file with the SEC. We caution you to not place undue reliance on forward-looking statements, and undertake no duty or obligation to update any forward-looking statements as a result of new information, future events, or changes in our expectations. We'd also like to point out that on today's call, we will report both GAAP and non-GAAP results. We use these non-GAAP financial measures internally for financial and operational decision-making purposes, and as a means to evaluate period-to-period comparisons. Non-GAAP financial measures are presented in addition to, and not as a substitute for, financial measures calculated in accordance with GAAP. To see the reconciliations of these non-GAAP financial measures, please refer to our earnings press release distributed earlier today, and our investor presentation, which are posted at investors.snowflake.com. A replay of today's call will also be posted on the website. With that, I would now like to turn the call over to Frank. Thanks, Jimmy, and good afternoon, everybody. Product revenue grew 83% year-over-year to $466 million. Remaining performance obligations grew 78% year-over-year to $2.7 billion. In the quarter, we added 12 global 2,000 customers. Our net revenue retention rate exceeded 170%, and Snowflake leads the industry with a net promoter score of 72. Snowflake is delivering high growth and operating leverage. Non-GAAP product gross margin exceeded 75%, and we continue to generate non-GAAP operating income and free cash flow. Our success is fueled by broad-based workload enablement. The core idea behind the Snowflake Data Cloud is to enable work to come to the data and prevent data from having to be moved to the work. Previously, data was copied, transferred, and replicated to be used wherever it was processed. That led to massive operational complexity, costs, and governance risks. The Snowflake Data Cloud promises to bring that regrettable legacy to an end. Starting in 2014, Snowflake's cloud-native architecture removed the scale, performance, and economic bottlenecks that held back data analytics at scale for generations. The impact was immediate, and led to a major expansion of workloads and use cases. Initially, organizations used Snowflake to drastically improve overnight analytical processes so that fresh, up-to-date data about the business was reliably available first thing. Checking that box, customers move on to using data for predictive insights and prescriptive solutions. This is what has driven Snowflake's massive platform expansion in terms of workload types, user types, and data types. Snowflake's data sharing solves the challenge of data access and enrichment. In Q2, the number of Snowflake data sharing relationships measured with what we call stable edges grew 112% year-on-year. 21% of our growing customer base has at least one stable edge, up from 15% a year ago. Among customers over $1 million in product revenue, 65% have at least one stable edge. Across sectors, we are meeting customers with solutions pertinent to their vertical industries. For example, supply chain management relies on Snowflake's combination of execution and access. We hear how supply chain management is failing at many levels because of dislocations such as the pandemic and spiking inflation. This is in large part a data problem. The data originates in different places, which is why it has such a challenging time coming together. When the world is stable and changing marginally day-to-day, this has been somewhat tolerable. Now, with massive disruption, the status quo must change. Our next frontier of innovation is aimed at reinventing cloud application development. Our ambition is far-reaching. Our aim is to transform how cloud applications are built, deployed, sold, and transacted. To help achieve this, we launched our Powered by Snowflake program. Today, we have 590 Powered by Snowflake registrants, representing 35% quarter-over-quarter growth. We announced a number of significant product innovations at our Snowflake Summit in June, which saw an approximate five-fold increase in attendance from 2019. These announcements are foundational for that vision. Unistore allows developers to bridge transactional and analytical workloads in a single dataset. This saves users time and effort associated with moving and transforming data across systems. Snowpark for Python is now in public preview. This capability brings more optionality to a technical audience of application developers, data engineers, and data scientists. Our integration with the recently acquired Streamlit is tracking well against plan. Streamlit bridges the gap between data scientists and business users, accelerating time to insight by enabling developers to build applications using their favorite tools. Finally, we announced support for Apache Iceberg table formats in private preview. Iceberg is the emerging standard for data lake architectures. With this offering, we bring the performance and governance benefits of Snowflake to externally stored data. We are pleased to announce our intent to acquire Applica. Applica mobilizes unstructured data for advanced analytics and machine learning. Applica's team and best-in-class technology will create opportunities for customers and partners to get more value from all data types. We believe our strategy and underlying market trends position us for success. We look forward to executing against this growing opportunity. With that, I will turn the call over to Mike. Thank you, Frank. Q2 product revenues were $466 million, representing 83% year-over-year growth. Our remaining performance obligations grew 78% year-over-year, totaling $2.7 billion. Of the $2.7 billion in RPO, we expect approximately 57% to be recognized as revenue in the next twelve months. This represents a 79% increase compared to our estimate as of the same quarter last year. Our net revenue retention rate of 171% includes 15 new customers with $1 million in trailing-twelve-month product revenue, and it reflects durable growth among our largest customers. We continue to pursue a vertical sales strategy. Our core verticals are financial services, advertising, media, and entertainment, retail and CPG, technology, and healthcare and life sciences. While all verticals are growing rapidly, financial services drove the most product revenue growth sequentially. Advertising, media, and entertainment, and technology verticals grew in line with the overall company. Driving this growth is our continual move upmarket. In the quarter, we added 12 new Global 2000 customers. Our average trailing 12-month product revenue from these customers grew 14% quarter-over-quarter to $1.2 million. We believe these accounts will grow to become our largest customers. A Global 2000 technology company is now a top 10 product revenue customer less than 2 years after signing their initial deal. Last quarter, we called out customers that were negatively impacted by headwinds specific to their businesses. The Q2 results from these customers were mixed. Some saw the weakness we expected, while others outperformed. We are monitoring our key business metrics, which we believe are leading indicators of the macro economy impacting our business. We are not seeing these metrics soften across the customer base. For example, our corporate sales team that addresses small and medium-sized businesses outperformed their net new bookings goal for the quarter. Our EMEA sales team contributed 4 of our top 10 new customer wins in the quarter. As mentioned earlier, the largest organizations in the world continue to increase their use of Snowflake. These indicate that companies globally are prioritizing Snowflake right now. Foreign currency exposure has been a relevant topic recently. However, less than 5% of our revenue is invoiced in currencies other than the U.S. dollar. So at the moment, we do not evaluate our business on a constant currency basis given the immateriality. Now turning to margins on a non-GAAP basis. Our product gross margin was 75%. Scale in our public data cloud, public cloud data centers, and enterprise customer success contribute to the year-over-year gross margin improvement. Operating margin was 4%, benefiting from revenue outperformance. Our adjusted free cash flow margin was 12%, positively impacted by strong collections. We collected a $33 million invoice in Q2 from a customer who had paid its invoices in Q3 in prior years. We ended the quarter in a strong cash position with approximately $5 billion in cash equivalents, and short-term and long-term investments. Now let's turn to our guidance. For the third quarter, we expect product revenue between $500-$505 million, representing year-over-year growth between 60%-62%. I would like to remind everyone that in Q3 last year, we saw unusual seasonality due to re-accelerated product revenue growth. Turning to margins, we expect on a non-GAAP basis 2% operating margin, and we expect 358 million diluted weighted average shares outstanding. In Q3, we expect $4 million of expenses associated with our Data Cloud World Tour. The 21 events will take place around the world and showcase our latest innovations. For the full year fiscal 2023, we expect product revenues between $1.905 billion and $1.915 billion, representing year-over-year growth between 67% and 68%. Turning to profitability for the full year fiscal 2023, we expect on a non-GAAP basis approximately 75% product gross margin, 2% operating margin, and 17% adjusted free cash flow margin, and we expect 358 million diluted weighted average shares outstanding. The full-year outlook includes operating expenses related to the acquisition of Applica. We are adding headcount to support our growth initiatives. Year to date, we have added almost 1,000 net new employees. We view the current hiring market as favorable for Snowflake and have not altered our hiring plans for the year. Our long-term opportunity is stronger than it has ever been, and we look forward to executing. With that, operator, you can now open up the line for questions. Finally, if you would like to ask a question, please press star followed by one on your telephone keypad. If for any reason you would like to remove that question, please press star followed by two. Again, to ask a question, press star one. We kindly ask that participants limit themselves to one question today. As a reminder, if you're using a speakerphone, please remember to pick up your handset before asking your question. The first question is from the line of Mark Murphy with J.P. Morgan. Please proceed. Yes. Thank you very much. I'm looking at the sequential growth in the product revenue, which is very strong. It's almost twice as strong as it was in Q1. So I'm curious first if you think analytics and data-intensive projects might be an insulated area of activity during an economic slowdown. Just relatedly, are you seeing many customers consume at higher levels to try to analyze the changing macro, maybe looking at FX sensitivity or interest rate sensitivity, et cetera? Hey, Mark. It's Frank. You know, in general, you know, I would say that, you know, Snowflake gets prioritized fairly high inside the enterprise. The reason is, you know, we're sitting right on the intersection, you know, of cloud computing, artificial intelligence, machine learning, advanced analytics. You know, customers are. You know, they have picked up the scent of the opportunity that is in front of them, and they're investing, they're hiring, they're buying, because these things are going to change, you know, big changes for their industry. Whole industries are gonna get redefined in healthcare, in pharma, in financial services. This is not a business as usual, you know, let's try to hit the brakes. There is a very high urgency, you know, around advancing towards cloud computing environments and then having an opportunity to really pursue the promise that that brings. Now we're looking at a very exciting time, you know, where things are becoming possible that we couldn't even dream of just a few short years ago. This is why we feel that this is not one of those expenses that people are gonna casually cut back on because it's strategically compelling and important. Yeah. I'll also add, Mark, just to remind, this is a consumption model, not a SaaS model. Even if we sign up a customer, it takes them months before they go into production. As I mentioned, there was a global 2,000 technology company we signed in the last two years that's now one of our top 10 customers. That customer didn't start really ramping until the end of last year, and they're gonna continue to ramp, and there's many more that started ramping this quarter that we would've signed last quarter. You can't just do a quarter-over-quarter. Because it is a consumption model, we do see patterns. Some customers do go down consumption based upon specific projects. By and large, most of our customers are still ramping, moving workloads to us, and we think that is going to continue on average with our customers. Wonderful. Thank you very much. Thank you. The next question is from the line of Keith Weiss with Morgan Stanley. Please proceed. Thank you for taking the question. This is Sanjit Singh for Keith. Very impressive Q2. Mike, I wanna talk to—I wanted to ask you a little bit about the Q3 guide. From a seasonal perspective, you know, the high end sort of implies 8% growth. Understanding that last year was an abnormally strong seasonal quarter, if I look back historically, the guidance does seem more conservative than usual, and I wonder if you could provide any context in terms of what you're assuming going into Q3, just conservatism or extrapolating any sort of trends that you may have seen in July. Nothing has changed in our guidance philosophy since the time we went public. What I would say is Q3 of last year was unusually high, so it's not a good year-over-year comparison. As I said, there is uncertainties in the macro environment right now, and I think the guidance is prudent that we put out. Understood. Thanks, Mike. Thank you. The next question is from the line of Simon Leopold with Raymond James. Please proceed. Thanks for taking the question. I wanted to see what your take is on your suppliers of public cloud capacity and whether or not you're seeing any changes in how they work with you and your pricing, and really what is the criteria to pick one over another, AWS versus Google versus Azure? Thank you. This is Frank. You know, I think that most enterprises, you know, typically, you know, decide first on their public cloud platform strategy, and, you know, oftentimes it's a multi-cloud posture, and then over time, that can also change. You know, then they sort of, you know, decide on, okay, you know, where is Snowflake going to run? That can also change, you know, over time. You know, we've seen customers, you know, also deploy Snowflake on more than one cloud. That's sort of, you know, how it works. Obviously, you know, our pricing does vary. I mean, Snowflake is more expensive on one cloud than another. Obviously, our most aggressive pricing is on our top cloud providers where we have the heaviest concentration, you know, of deployment. It obviously matters to our customers. It all translates to dollars and cents. But the reality is, Snowflake is Snowflake. There's really no change in the experience depending on what cloud you're running on. You would think that it is strictly an economic trade-off, but it's usually, you know, predicated by, you know, why they picked one public cloud platform over another. With that said, the majority of our customers, 80+%, run in AWS, and about 18% is Azure, and 2% is GCP. Thank you very much for that detail. Thank you. The next question is from the line of Alex Zukin with Wolfe Research. Please proceed. Hey guys. Thanks for taking the question. I guess maybe just a high level mixed with a tactical financial question. If I look at the environment, right, a lot of investors, a lot of customers are wondering about optimizations. I think on the call, Mike, in your script, you mentioned that you actually increased the prediction of how much will be consumed in reference to your CRPO metric over the next 12 months. It feels like there's some massive differential in terms of expectations versus what you're seeing and delivering. I just wanted to better understand what's driving that increased conviction around consumption. Have you seen a meaningful wave of optimizations that have rebased and now, you know, you're kinda off to the races in those workloads? You know, do you not anticipate that occurring? I guess how is that like, what were the dynamics that made you change those assumptions that you saw in the quarter? Well, I didn't change any assumptions in the quarter. It's the same that we've had for quite some time. Optimizations are not something that's new. We just started talking to you about them and showing the impact about them. We have always done optimizations. We will continue to do optimizations. They're good for our customers because when they see if we can help make them use Snowflake more efficiently, we become cheaper, they move more workloads to us. I showed you guys at our Investor Day real data with two customers around that. With regards to the CRPO, that 57% of the total RPO, that is more of a function that we have a lot of our contracts that are starting to get burned down that were multi-year, that we do expect in Q4 there will be a number of renewals of those contracts. I do think the current CRPO as a percent of the total in Q4 will come down more in line with that, into the low 50s where it historically has been. That's really a function of think of our largest customer. They signed a 3-year contract, in I think it was September 2020. They're gonna burn through that contract in advance, and there'll be a big renewal with them. Whether they do it one-year or multi-year, that's up to them. That will happen in our Q4, and then you'll see that as well. We have a number of customers like that. One of the things that we're seeing more and more is customers, because they're consuming faster than their annual amount in their actual contract term, they're doing what we're calling co-term, where they're bridging to their annual renewal, and a lot of those annual renewals are really moving towards Q4 for us. Got it. That's why the billings versus CRPO delta is a little bit higher? Well, I have to tell you, I don't even look at billings because it's a meaningless thing for our business, 'cause we're not a SaaS company. I really focus more on cash flow and revenue consumption by our customers. Perfect. Thank you, guys. Thank you. The next question is from the line of Raimo Lenschow with Barclays. Please proceed. Thank you. Quick question. I'm sure Frank and Mike, you heard all the concerns from investors this quarter about consumption models and, you know, how in lower economic activities there's less. I'm also seeing like the 12 new global customers. What are you seeing in your customer conversations about consumption models in terms of like it gives customers more flexibility to pay for what they're using, et cetera? That almost in tougher times should be an incentive to go that way rather than having these massive upfront commitments. Like, maybe talk a little bit of what you're seeing in the field. Thank you. Raimo, it's Frank. We sort of invert that whole way of thinking because it's actually quite attractive for customers to have a consumption model because they can sign a contract with us, but then they can throttle up and down how much they wanna use. You can't do that in a SaaS model. You're gonna pay no matter what, whether you're using it or not. This gives customers actually more confidence to contract with us, knowing that they can throttle up and down. We actually think it's an advantage in the type of times that we're living in, as opposed to a negative, which is what it has been portrayed on the sell side and in the media. Yeah. I'll add to that too, Raimo. As a reminder, new customers, when we land them, they generally start very small, and it takes them nine months to really start to consume, so it's very low risk to come on. Once we have an existing customer that is looking to buy more, they already have a path for what they wanna do workloads, and they wanna do that on Snowflake because we will save them money from what they're doing. The other thing I wanna remind you too is we have many different models. You can sign a one-year commitment, you can sign a three-year commitment, or you can go onto on-demand as a customer if you're not comfortable making a big commitment up front. We do see customers, I think last quarter about $7.2 million of our revenue was actually on-demand. These are new customers that are just trying us out before they sign a capacity deal. That's most of our capacity deals start from being on-demand to go to that. Okay. Perfect. Thank you. Well done. Thank you. The next question is from the line of Kirk Materne with Evercore. Please proceed. Yeah. Thanks for taking the question. It's Frank. I was wondering if you could talk a little bit about some of the feedback you got from partners, both GSIs and ISVs coming away from your user conference. And kind of what are they asking you about in terms of, you know, making or telling you about, rather, in terms of making bigger investments in Snowflake, and maybe some of the takeaways you've had in terms of, you know, as you set up your own go-to-market, you know, not only for the remainder of the year, but into next year. Thanks. You know, I think the conference was an extraordinary display of our ecosystem. I mean, we had a partner pavilion that was the size of multiple football fields and, you know, I think we're punching way above our weight, you know, in terms of, you know, how vibrant and how large and how active, you know, our ecosystem is. It's a very purposeful choice on our part to run the company that way. You know, we're not trying to create, you know, a single, you know, vertically integrated stack where you have to buy all things Snowflake. We do quite the opposite. You know, we try to create maximum choice and innovation on our platform. We really become market and channel, if you will, you know, for, you know, for system integrators. You know, the reality in the world of system integrators is, you know, Snowflake's presence in the marketplace is obviously, you know, forcing their hand because, you know, our customers are their customers, and vice versa. We intersect in the marketplace, and their customers are expecting them to be able to step up and then deliver, you know, highly, you know, high value, high impactful capabilities, on Snowflake. They're growing in leaps and bounds. You know, sometimes they're more following than leading. That's why Snowflake is always leading, and the rest of the world is following. You know? Just to give you a little data around the GSI network. In the first half of this year, the GSIs have done north of $550 million in services around Snowflake. Our top five GSIs represented more than $320 million of that work. These are real practices within these GSIs now. Just on another thing, because I know there's been some chatter about resellers and other things, I just wanna make it very clear, 1% of our bookings in Q2 went through the resale channel. 2% of our product revenue goes through resellers. Resellers is not a significant amount of our direct business. The GSIs are very helpful in doing the services work to get customers to consume on Snowflake. Super. Thank you all. Thank you. The next question is from the line of Brad Reback with Stifel. Please proceed. Great. Thanks very much. Mike, I know you mentioned the 3Q consumption comp. You also have a really difficult 4Q RPO comp. Given your commentary, should we expect a, you know, healthy end to the year given that renewal pool? Thanks. Yes. We expect- Great Q4 will have a big increase in RPO, but I'm not guiding to it. You'll have to wait and see. I'm never gonna guide to RPO. Understood. Thanks very much. Thank you. The next question is from the line of Brent Bracelin with Piper Sandler. Please proceed. Good afternoon. Wanted to drill down into Europe. That's been an area where we saw large deal delays with other large software companies. It sounds like the opportunity for you closed several large deals. Maybe if you could just talk about the demand environment in Europe right now, and what's driving some of the momentum for you that perhaps is a little different than some of the peers. Thanks. Yeah. Brent, Frank. We've really shifted gears in Europe in terms of, you know, not so much moving away, but sort of, you know, really emphasizing the large iconic accounts in key verticals and key and obviously in the top regions and countries. That's really how you win markets over there. That redirection, you know, has taken us a little bit of time. This last quarter that we just reported on, we've seen some significant impact. You know, we made, you know, one comment, you know, during the prepared remarks about how they contributed some very large customers to the overall, you know, portfolio, so to the overall roster. We're actually, you know, feeling good about the progress we're making in Europe, in the large names in the key verticals. I think it's going good. You know, the macro commentary, you know, it's probably you know, we're not really, you know, feeling a lot of, you know, sort of headwinds, if you will, in Europe. Obviously, there are pockets that are weak. You know, the farther east you go, you know, the more you feel it. But that's really not where we were to begin with, so it's not really a factor. We're not negative on Europe at all. Great to see. Thank you. Thank you. The next question is from the line of Gregg Moskowitz with Mizuho. Please proceed. Okay. Thank you for taking the question. Another software vendor that primarily has a consumption-based model recently made the comment that their NRR for customers below the 130% threshold has been unchanged, but those above 130 have been slowing their consumption growth since it deviates a lot from what had been budgeted or committed. Now, your overall NRR this quarter again was quite strong, guys, but I'm curious if you've seen any of this dynamic with your bigger enterprise customers. Thank you. No. You know, obviously there are some of our top 10, and we talked about last quarter with some specific things to their business where they have slowed down, and that's been in our guidance, but overall, our top customers continue to grow. I haven't seen that slowing down the NRR. Got it. Thanks very much. Thank you. The next question is from the line of Pat Walravens with JMP Securities. Please proceed. Oh, great. Thank you. Let me offer my congratulations on this quarter. Frank, can you take a minute to differentiate Snowflake's approach to the market from that of Databricks and their Lakehouse approach? You know, I mean, one of the ways, you know, we characterize it is, you know, sorta, you know, historically, you know, Snowflake, you know, has been, you know, a data lake with its own platform, its own proprietary file formats, you know, and so on. You know, whereas, you know, Databricks has taken the approach that they're just another tool, you know, in the lake, and you can use many, including them. We were a far more strategic choice, you know, customers to commit to, than a much more tactical choice of just being a tool in the lake. You know, over the years, you know, we have really, you know, converged, because, you know, for example, we made mention in the prepared remarks, you know, of our support of the Iceberg Open table formats, you know, which, you know, allows, Snowflake, files to be used by non-Snowflake tools, for example, right? It really, you know, puts us completely on par or better, if you will, in terms of functionality and performance, you know, in a, in a pure data, lake configuration. Customers can also use this, you know, in the, in the, in the conventional, traditional, highly optimized, you know, Snowflake proprietary format, that most people are using. You know, I think that's one aspect of it. You know, the other aspect of it is, you know, we come from different places. You know, our DNA, our culture as a company is as a database platform, you know, and obviously, you know, Databricks comes from a totally different type of background. We also have different user types. You know, we have a very much high-level approach. We very much democratize access to the sophistication of a platform like Snowflake. You know, whereas, you know, Databricks, you know, coming from a world that's much more, you know, roll your own, and very, very deep technical, very skilled demanding type of environment. There's a market for that, as well. There's different user types, you know, different workloads, you know, that whereas, you know, people will use different type of tools. The last thing I will say about it is that de facto, you know, Databricks and Snowflake have lived side by side for many years, playing different roles, you know, in the setups and the type of workloads that they perform. Is there anything you want to say about that, Christian? Yes. One quick comment on top of everything Frank said. We hear very consistently from customers that our approach to simplicity and ease of use is one of the reasons why well, you see the results that you're seeing today and the net promoter score that Frank mentioned, because we help customers focus on solving data problems, getting value out of the data, and not dealing with infrastructure. Great. Thank you both. Thank you. The next question is from the line of Kamil Mielczarek with William Blair. Please proceed. Thank you. Congrats on the solid quarter. The headcount growth in your sales and marketing organization has exceeded 50% in the first half of this year, which is comfortably above the growth rates achieved in both fiscal 2021 and 2022. Can you provide more detail on where you've been focusing these new investments? Given the macro uncertainty, how do you think about the time to ramp? How long should it take for the new hires to be fully reflected in revenue? Thank you. Well, the first half of the year is always the biggest hiring, and that tends to be we wanna get people on board for our sales kickoff. It's also when we like to onboard a lot of our junior SDRs, so we can train them all together in the year. The people we're adding are principally in direct sales and sales engineers, and we continue to open up new countries around the world. We're going a lot deeper within North America as well too because there still is a lot of accounts that aren't being covered today. It takes, depending on where they are on the corporate sales team, which is more of an inside sales, it's about a six-month period to ramp. It's a little bit longer on the enterprise and the verticals, the real large verticals we go after. Those guys could take a year to ramp 'cause those are long sales cycles. Helpful. Thank you. Thank you. The next question is from the line of Derrick Wood with TD Cowen. Please proceed. Great. Thanks, and congrats on a great quarter. Hey, Derrick, we can't hear you very well. You're cutting in and out. Could you repeat that maybe? Is this better? Yes. Can you hear me now? Yeah. Yes. I wanted to ask about just the activity of migrating customers from legacy on-prem systems. I think you've shown stats that close to 60% of your new customers come from that environment. You know, given the macro out there, you know, some would argue you'd see acceleration because of operational efficiencies. Some would argue maybe there's a lot of change management and companies would wanna hold off. Just curious, you know, what you're seeing out of your pipeline in terms of the prospects' priority to migrate off of on-prem systems. I'll make one comment. I mean, I will tell you that just in the last week I've heard some, you know, two very iconic names in two different industries that were staunch on-premise people who would never, ever, you know, go cloud and that are now going. I just feel that the resistance is completely breaking, and people are going cloud. You know, I'm sure they have their own reasons, but a lot of it is what you said as well, is that they're gonna get left behind. You can't take advantage of innovations that are only available on the cloud. If anything, you know, I get to agree with you that we're gonna see acceleration out of this as opposed to people holding back. Thank you. Thank you. The next question is from the line of Brad Zelnick with Deutsche Bank. Please proceed. Excellent. Congrats guys on a really strong quarter and navigating a crazy environment out there. My question for you guys, maybe for Frank, is, I mean, if we think about just Data Cloud as the holy grail and data sharing being a really important element of that, and I look to the metric on stable edges, number of customers with at least one stable edge, I think it was 20% you said, versus 15% a year ago, which I think is unchanged from what you'd also said in Q1. Can you just give us a sense of, you know, how you would expect to see that progress? You know, when we look back one day, maybe, you know, where might the peak be? Thanks. Yeah, I think you know there's a natural progression in these things, you know. As you said, you know, lots of people are you know preoccupied with the migration. That takes a lot of time. There's a lot of risk. So people wanna get their core capabilities you know in place. They wanna deal with their backlog, you know, all the things that they need to do you know before they sort of move on to you know more aggressive, more ambitious you know projects where they're really starting to execute on their strategies and the vision that they have for themselves. I think that the data cloud is an incredibly important positioning element, you know, for us, but also for our customers, because if you don't adopt that posture, you will end up, you know, re-siloing your environment in the cloud, and you will basically load up on the same set of problems that we historically have had. It's a much bigger problem now because, you know, data science and the promise of data science, the ability to generate, you know, predictive insights and prescriptive solutions really depends on your ability to join and blend and overlay data regardless of data types, data source, or where it's coming from. You can't predict, so it's really, really important that you don't throw up new barriers between data sources because you will not only frustrate your data science teams, you will literally not be able to realize the potential that is now there. We draw a line in the sand on that. If you're gonna go, you know, silo by silo, then, you know, you will be on the cloud, but you will not have set yourself up for the promise that is now, that's now in front of us. Excellent. Thank you so much. Thank you. The next question is from the line of Will Power with Baird. Please proceed. Great. Thanks for taking the question and again, yeah, congratulations on the strong numbers. It looked like really strong upmarket success. I think a record number of billion-dollar or at least new billion-dollar customers. I'd just love to get more color if there are any common variables helping drive that upmarket success. It sounds like there's a correlation with data sharing, the percentage of those customers that are deploying stable edges. Any further color on that front would be great too. Yes. Frank again. You know, I think what Mike said earlier, I mean, a lot of these million-dollar accounts, you know, can be years in the making, and a lot of the work that we've done in previous years is now culminating, and it's becoming, you know, visible in this particular manner. It's not an overnight, you know, success. These things, you know, take time. Data sharing is incredibly important. You know, every industry and sub-industry has its own unique data networks and their own reasons and use cases, really, you know why they need to share data. I know financial services, for example, which is of course an industry that you're all very familiar with. I mean, a need for sharing is extremely pronounced and it's a daily preoccupation between institutions that need to share data. You know, Snowflake has really become a de facto platform for financial institutions on how to share data. So that becomes a very powerful thing. We feel the network effect from data sharing in certain verticals that are really, you know, more advanced, more mature in terms of the adoption of data sharing than some others that are taking more time to get into that. Yeah. What I will add too is, you know, we have 510 Global 2000 customers. The average revenue from them today is $1.2 million. That's up from $1.05 million last quarter, and that will continue to grow. Those large customers are what is driving those million-dollar-plus customers for us, and we don't see that slowing down. Great. Thank you. Thank you. The next question is from the line of DJ Hynes with Canaccord. Please proceed. Hey, guys. Thanks for taking the question. Mike, I wanted to ask you about the margin trajectory of the business. I mean. Continue to impress with the cash flow operating leverage you're showing. You know, you raised the guidance to 17% this year. Given the trajectory, we're not miles off from that, you know, longer term 25% target. What's the philosophy from here? Like, do we reinvest the growth and the upside that we're seeing into the business to drive, you know, sales productivity and, you know, accelerated investment there? Or does some of that flow through the bottom line and, you know, maybe that 25% margin target is achievable ahead of schedule? Well, we're gonna get to that number before we even think about changing it. With regards to investing in the business, we are continuing to invest in the business. You can see the headcount we're adding. Principally, headcount is the main investment we're doing in the business because that's what drives R&D, and that's what drives sales. We're very thoughtful about where we invest those dollars and how quickly we do, and we think we're investing at the adequate pace, and we will continue with that. Thank you. Nothing has changed our philosophy. We will continue to show leverage year after year. Thank you. Our next question is from the line of Brent Thill with Jefferies. Please proceed. Thanks. Frank, Mike, hope you're well. On verticals, were there some standouts this quarter? We've heard energy has been a hot topic, you know, just as an example. Any other big verticals you'd call out that you saw a particular strength that you were excited by? Yeah. You know, energy is not a very big vertical for it. Yes, we have some good customers, but they're not huge consumers of Snowflake. Really, financial services is the number one vertical. It's about, if you look at it from a revenue perspective, about 20-21% of our revenue is from the financial services vertical, and then closely behind that is the media and entertainment, and then technology is right after that as well, about the same. Those are our three biggest. Healthcare is pretty big, but it can grow a lot bigger. Retail CPG. Retail CPG is a meaningful segment as well. Financial services is very large, and those are very large, stable edges, the data sharing that goes on in financial services. When we talk about big accounts, we landed in Europe, a big telco, we landed a big bank, we landed a big insurance company, and we continue to land big accounts in these verticals. Okay. One quick follow-up. Just on tonight, you've seen Salesforce.com take down guidance, Splunk take down guidance. Everyone's asking, you know, it seems like the industry is taking that guidance down, but you're seeing incredible strength and no stretch of deals or duration. What do you think is going on? Are you just taking share? Is it just early on? How would you characterize what you're seeing versus Well, I would say. What seems to be impact? Yeah, I would say most SaaS companies, when they land an account, they typically license most of the users in an account. When we land, we land small, and they go workload by workload, and they just keep moving stuff over to Snowflake. That drives that, and it's a multi-year journey within our customers. I don't see any of our customers that are fully saturated. Where I think some SaaS Thank you. Companies may be saturated. Very clear. Thanks. Thank you. The next question is from the line of Steve Koenig with SMBC. Please proceed. Hey, guys. This is Owen Hayward on for Steve. Thanks for taking the question. Two quick related questions from us. First, can you describe the near-term opportunity in analytics beyond your core data warehouse use case? And which of these other workloads would you expect to become most prevalent in the near term? As a second, I'm wondering if you can talk through the plans to break into the operational use cases, and how many times bigger is that market opportunity in the near term compared to that heritage EDW market? Thank you. Frank, I'll make one comment, and I'll give Christian maybe some time to think about some additional, you know, comments. You know, we started out in this, in this business, with what I've referred to as a workload modernization, where, you know, we're taking existing workloads, we're moving to the cloud. You know, we're running them much faster, you know, because of, you know, all the architectural innovations that Snowflake has represented. This really helps customers, and I mentioned this in the prepared remarks, really helps customers, you know, a 24-hour cycle to very reliably, you know, deliver data to their business users. That's been a long time coming. The customers have struggled with that enormously. Then we hear about it, you know, every single day. That's just reporting yesterday's news. You know, these days, I will tell you that, you know, nine out of ten conversations I have with customers are not about that, okay? They are about very specific, you know, industry challenges and industry opportunities. You know, for example, you know, we have pharma customers that are seeing opportunities to reduce their their clinical trials. It takes on average, you know, 12 years to bring a drug to market. You got 5 years left to monetize it. They can take a whole year off of that. You redefine the economics of an entire industry. You know, healthcare is trying to go to an entirely predictive model. Instead of treating people for disease, they're trying to predict, you know, who is going to get sick, and, you know, what preventative protocols they can put in place to help people then, you know, steer clear of that. These are very different conversations than what we're doing in advertising, for example, with clean room technologies. You know, we're doing totally different, you know, things now, and we're enabling these industries, you know, to navigate, you know, all the issues around privacy and compliance and so on. To characterize us as a data warehousing company, I've said this a million times, but, you know, that is probably five years out of date by now. You can keep doing that, but that doesn't make it the reality of our business because it's not anymore, you know? Yeah. Sorry, I'll add that we see broadening of the personas within a company that we speak to. It's not just the traditional data analyst team, but data engineering team are engaged with us, data scientists are engaged with us. Streamlit has a really strong relationship with many of the data science teams, and we see that part of it. We announced at a user conference in June, cybersecurity is a workflow that is doing very well for us. Probably the largest announcement was around Snowflake for data applications and for being an application platform. That's where the opportunity for the operational database capabilities fit into, and we see tremendous interest from both customers and partners. Yeah. Just a quick follow-up. You know, Snowflake has become de facto a cloud application development and a runtime, you know, platform. People are building and deploying applications on Snowflake. I mean, we have customers like Western Union who are starting whole businesses on top of Snowflake. Those are the conversations, you know, that we are having with customers. Workload modernization, we'll be doing that till the end of times, but that's no longer the reality that dominates our daily existence. Super helpful. Thank you, guys. Thank you. The next question is from the line of Ittai Kidron with Oppenheimer. Please proceed. Thanks, nice quarter. Mike, I wanted to piggyback on a comment you made earlier that it takes months for customers to get into production even after they sign up with you. I guess with that being the case in the current environment being what it is, what is the risk that 6-12 months from now we'll see a little bit of a lull in your growth as whatever slowdown in activity that's happening with them right now translates into a smaller number of workload transitions into the cloud? How much visibility do you have into the prep work customers are doing with respect to the workload transition? Well, we have a lot of that. You can see in the number of customers that we landed last quarter, it was north of 600. All of those customers, they signed up on Snowflake to move workloads to us. We know based upon discussions we have with many of our top customers, their plans, what they're planning on doing. As an example, we have a number of our customers that are just chomping at the bit for Snowpark to go into GA with Python because they wanna do more on Snowflake. That's what gives us the confidence. We spend a lot of time looking, engaging with our reps. We're talking to our customers to get a feel for what is consumption going to be like over the next three months, six months with our customers. Just a quick follow-up. I actually think that the dynamic that you're describing, and we're gonna see the exact opposite of that. You know, we think people, because of the nervousness that they may have about the macro, they're going to accelerate to a cloud computing platform. The reason is these are elastic models. These are consumption models, right? It's much better to be in an elastic model where you only pay for what you use, and you can run on demand than when you have to make large upfront, you know, commitments to a vendor. If anything, I think people are gonna get a move on instead of hold off. Very good. Thank you. Thank you. The next question is from the line of Ari Kezerian with Cleveland Research. Please proceed. Thank you for taking the question, and congrats on the great results. You alluded to earlier, Frank, on Snowpark and Python support. I was just hoping, you know, if you could provide a little bit more color on, you know, the feedback you're getting from customers around Python for Snowpark, as well as the announcements you made around Apache at the user conference. Curious, you know, when you think those could start to, you know, drive consumption for the platform, you know, when you're expecting contribution and what types of projects that you're currently not involved in, what kind of use cases it could open up for you. Thank you. Yeah. I'll start. Maybe, you know, Christian can finish. But, you know, Snowpark for Python is red hot, and people are chomping at the bit, you know, for us to declare it GA, you know, which is something, and we have customers that are really wanting us to let them use it in production now, some of the largest customers that we have. The pressure is on because the demand is there. You know, the thing about the Iceberg open table formats that really, you know, completely opens Snowflake up for Snowflake tables to be used by anybody and everybody that can support that format. You know, we're seeing incredible results in terms of performance, you know, of Snowflake executing against that file format. So these are all very promising, you know, developments for us. I think the pressure is on for us to declare these things generally available because people are trying to rip them out of our hands right now. Yeah. As we said at our summit conference, we expect those to be GA by the end of this year, so meaningful contribution to consumption will happen next year. That's right. Qualitatively, the feedback is extremely positive, which is why, as Frank said, we get these many requests to go production, go GA as soon as we can. Excellent. Thank you. Final question will come from the line of Tyler Radke with Citi. Please proceed. Thank you. We made it almost a full hour without talking about Graviton. I actually just wanted to ask you how you're thinking about new projects or new workloads in response to some of the optimizations, you know, any change to your assumptions. I think you'd talked about kind of $60 million of net new spend coming online. Just curious how that's tracking in your expectations for the second half of the year. Thank you. No changes to our assumptions there, and we always expect that the biggest impact is in the second half of the year on those. Christian. Yeah. We're always continuously looking at how to deliver price performance advantage to our customers. Graviton happened to be one of the more significant changes, but any quarter, we have tens of changes that go and improve performance for different workloads. We're also constantly evaluating hardware advancements, and our commitment to our customers is to do that research on their behalf and deliver best price performance. If I could sneak in a quick follow-up, I guess just what type of workloads are you seeing customers bring on, you know, with those lower price points? Is it kind of new workloads that you weren't able to handle in the past? Just any way to characterize that. Thank you. Yeah. We're seeing a lot of lower latency, higher concurrency use cases like slicing and dicing with data migration from Druid, which is very low latency use cases recently, in part because of the better economics, but in part because of the performance, and they're obviously tightly correlated. We're also seeing a lot of data engineering, data transformation, Spark migrations coming on to Snowflake, all because of the price performance that we offer. Thank you. Thank you. That concludes the question and answer session, as well as today's call. Thank you for your participation. You may now disconnect your lines.