Thanks for joining us. Really looking forward to have Mike here. Mike, to get everyone back on the same page, you guys had like—just, from your perspective, what were, what were the highlights? How did it play out for you? You know, we saw good performance, and it was very broad-based, from large customers to small customers. We talked about on the call that we really saw a stabilization in consumption patterns- Mm-hmm. Going back to a little bit more historical consumption patterns. We called out that September, after Labor Day, had some of our largest week-over-week growth within our consumption, within our customers. Continued to see strong consumption in October and November, and just before the holidays in November. I feel good about where we're sitting right now. I'm not saying this is a recovery, and you're gonna expect a lot of upside, but really, we've seen more stabilization. No big optimizations. I'm not hearing of any big optimizations. I will say, and I've said this so many times, though, optimizations will always happen. It's a normal cycle. Yeah. Like, I know two of our big customers that really started to ramp last quarter. Both of them ramped the last few, and they were doing big on-prem migrations. It is very typical that when a customer starts migrating a lot of work, the consumption spikes, and then they go into production, and it kind of moderates and comes back. Then they need more data, and it goes up. Yeah, yeah, yeah. You'll see those trends, but then that is a normal trend within our customer base. So, no, I feel good, and it's broad-based across industries. Financial services continues to do well. Healthcare continues to... Technology is doing well, telco. Yeah. I will tell you, the one area that has a lot of upside, there's little downside because it's such a small piece, is FedRAMP High. And literally, the PMO and the federal government has said, "We have our FedRAMP High, and it'll—you'll see it on our website." Literally, every day we're checking. Okay. That will open up a lot of new opportunities for us. Yeah, yeah, yeah. We have a healthy pipeline within the federal business that we've been working on for the last two years. They're just waiting for this. Yeah, yeah, yeah. Okay, that's interesting. And then we met in London last month. Well, it's actually over in October. October. Yeah, yeah. It's like, you just did the, you know, the big customer global tour event. Mm-hmm. I think you were in New York and London. What were the customer conversations like there? You know, so it was New York, London, and Stockholm. I would say New York and London were very much financial services. Yeah. You know, I actually did the dinner with a bunch of the Chief Data Officers at the big banks in New York. Their excitement around Snowflake was Streaming Tables- Yeah ... and Iceberg Tables. They all want Iceberg. Uh-huh. They all want to be able to have their data, and you can understand why, so that they don't have to pay for the cost of storage twice. It actually will make Snowflake cheaper for them, too, and they can do more work on Snowflake by having all of their data in an open format, Iceberg. Yeah. You know, nobody wants to get locked in on their data. Everyone wants to have their data in open file formats, that it's easy to move the data. It's easy to move the data in- Yeah ... and it's easy to move the data out. It makes it cheaper to run your queries on that. Yeah. I mean, did you notice quite a difference in terms of how far customers are down the adoption curve, if you think about Europe- Absolutely ... versus, Yeah. I would say the U.S. customers, in general, are further along in their adoption Snowflake across the enterprise. Yeah, yeah. I would say in Europe, it's more early. There are customers that are very well established there, but in general, I don't think I have a single European customer in my top 10 yet. Mm. I don't have a single Asian customer in my top ten yet. I have some, both, that will be close to getting in there- Right ... but they're not there yet. You'd expect to see at least a couple Asian and European ones- Yeah, yeah ... over the long term in there. Do you think it's just timing? Timing. Timing. Timing. Timing, yeah. Yeah. Is there... Do you notice when you were having the client conversation, is there differences on the demand there at the moment, or is like, you know, globally, it's, you know, tougher times, now everyone's kind of living in tougher times? Yeah, I would say the European customers and some Asian by region are a lot more concerned about data residency and sovereign clouds- Yeah ... because of their, you know, it's providing headache, and I was at ServiceNow, the whole company turning over all of their customer data to the US government- Yeah, yeah ... has been revived a bit lately. So, you know, we're working on strategies with different sovereign clouds. Yeah. So. Yeah, yeah, yeah. And you talked a little bit about the last quarter as well, about the shifting mix in the top customers, that were- Mm-hmm ... you have more established guys coming in here. Like, where are we on that journey? It's continuing. I will have at least one new big customer this quarter because they're just growing really fast. Yeah. Potentially, another one. It doesn't mean those other customers aren't doing good, they're... I'm just getting big- Yeah ... customers, and it's a lot more mature. If I look at our top customers, they're... you know, early on, we used to have the likes of Lacework, and Instacart, and Coinbase... early adopters of Snowflake in our top ten. Now I just have, Instacart is still in my top ten, they continue to grow. Yeah. There's that big six months ago that everyone. Those guys continue to grow with us. Yeah, yeah. It's just I have more mature... I got a telco that's moved up in there, so I have two telcos in there, more banks in there, large banks. Yeah, yeah, yeah. And then the, if you think about it, then, what does it mean from a visibility perspective? You know, like, obviously earlier this year, in fact, you know, like- Yeah ... you know, those virtual natives having to, kind of, do almost like emergency, kind of, thinking about their stuff. What, what I like about large enterprises that are more mature- Yeah ... is they've always been conscious. Yeah. It is more predictable, their business. They're also a lot more methodical in how they do their migrations, and they share that with us. So I know, like, I talked about next quarter, I'll have a bank move into my top ten. We have a roadmap over the next three years. We've been working with them on migrating data, and they have hundreds of on-prem data warehouses. Yeah. And from your perspective to visibility, like, I'm more now, kind of, going more, like, to your CFO is like, is it on track with it, or is it, kind of, more like you talk about a roadmap and- Well, the roadmap I'm talking about is on the technical level. Yeah ... with our PS people and our sales engineers with the customer on the migration. There are contracts with these customers, which is their commitment they're making with Snowflake. Yeah. Yeah, yeah. Um, so. Okay. And then the, if you think about it, like, where, like, you know, I would agree with you, there's this, like, data mart, data warehouse is still inside. Like, the one question I get a lot is like: "Oh, like, Teradata was never that big, so why Snowflake?" So kind of, where are these workloads coming from? And, and- Yeah ... Are there any new workloads in there as well, that- Yes, yes. So, you know, a lot of people think we just replaced Teradata. When we're doing a Teradata migration, we're generally replacing a lot of Hadoop, a lot of SQL Server- Yeah ... a lot of different things. And then there's a lot more new use cases the customers determined. I talked about this one telco that's been around for. They've been a customer for almost eight years now, I think for six years. It's before my time. They were never. They never started with an on-prem migration. They started doing some new use cases in the cloud. Yeah. In the last six months, they've decided to do a Teradata migration. It's, it's all over the board. Yeah, yeah, yeah. Okay. Okay, perfect. Yeah, because, like, that's the thing, man. I used to cover them, like, I think Teradata was only, like, a number four in the market. Like, if you, because, yeah, they were high-end, but everyone knew them, but, like, there's so much Oracle, Microsoft- It's kind of like when I was at ServiceNow. It really is very similar, the analogy that everyone who was just at ServiceNow was the helpdesk market. Yeah. $1.6 billion market. Look how big it is today. Yeah, yeah, yeah. It's clearly, they're more- The one was all- There's a lot more, we're much broader. Data warehouse is just one workload. Right. Data sharing is one of the key differentiators of Snowflake, and I think people do not appreciate that. You- Us, like financial services and the financial service providers, think of BNY Mellon, State Street, Fidelity, BlackRock, DTCC, are all standardizing on Snowflake and doing data sharing with everyone. It's a huge network effect to get new customers because of that. Yeah, yeah, yeah. It was funny, four years ago, we were trying to get Bloomberg data into Snowflake and get Bloomberg in. Now, it took so long, but now Bloomberg data, the data, not all of it yet, we're working on that- Yeah ... is available for customers to use data sharing and get it in Snowflake. That's the thing, like, yeah, data sharing is, like, the one thing that, you know, everyone underappreciates. Yeah. Okay, yeah, makes sense. And then the, shifting gear a little bit, like, so there, there's the Snowflake, now we have, like, Snowpark. Like, how do you... Like, maybe where are you on— What are you trying to achieve in Snowpark, and where are you on that maturity curve? I think we're still very much in the early phases of Snowpark. Now it's available in multiple languages to work with now that we have Python. There's still more of them. There's still big versions of Python. You know, Snowpark's about a $70 million run rate now, as today, so it's starting to get meaningful. Really, what we're, our salespeople have been focused on is Spark migrations. And more, I would say it's almost a low-hanging fruit because we can see the workloads customers are running in Snowflake. They're using open source Spark, Databricks, EMR, and those are the ones that we've gone after in doing migrations. As Snowpark Container Services comes out next year, it'll be used more heavily in app development for people. You got to understand, with Snowpark and more, there's a migration involved, and that takes time, so we can quickly go in and win a POC, and then you need a customer to get lined up to do the migration. Yeah. Some of those migrations take months and months to do, depending on how complex the system is, so it takes time. Yeah. We're now starting to see some of those things come on production. I'm glad you were here because, like, kind of, me out of the room. Like, container services, like, why is that so interesting? Like, you know, I should know that, but- Yeah, you know, the big thing about Container Services is it will enable people in your container to bring your own application to Snowflake to run neatly in Snowflake. Yeah. You don't have to worry about all the security and that noise, because we provide all that security and giving it a very simple form. Yeah, It also will enable, and I'm not a technologist either, I'm an accountant. You can also bring your own large language model of choice into Snowflake to be able to fine-tune a model on your data. Yeah. That's what's really exciting, and we talked about Cortex coming out, which makes it easier for the average analyst to be able to do that. If you're a hardcore data scientist, you'll use Snowpark direct or Container Services to do that directly. Yeah. But it will also enable new applications to be developed very easily in Snowflake. So Frank always talked about, it's about bringing the applications to the data versus the data to the application. And that way, you know, the data stay in a secure government environment. Yeah. And you have Streamlit as well, which kind of helps you kind of build- Streamlit will enable people to develop applications. It also gives you a visualization layer. You know, within my finance department, there's a lot of dashboards that I look at on a daily basis. But it's more than just a dashboard, it's dynamic. But I used to do everything in Tableau, now I've switched everything over to Streamlit. That's the first thing I do every day when I wake up, is I go into my Streamlit dashboard, and I look at my revenue for the prior day, and then I look at all of our customers, the forecast. Yeah. I can drill down into anything. I can see how many Snowpark credits were consumed yesterday, how many streaming dynamic table credits were consumed. Yeah. And on that note, I wanted to ask that later, but I might as well just squeeze it in now. Like, if you think about the forecasting and, you know, the maturity of your forecasting, I appreciate it's tough because consumption trends, so you can't predict them. Mm-hmm. Like, how does that, you know, like, forecasting cadence kind of change for you over the last couple of years? Yeah. You know, we've developed an in-house model for doing our forecasting, and your model is based upon historical data. Yeah. If your model has never seen a downturn, it's hard for it to predict that. Yeah. So over the last actually 9-12 months, we knew our model had outgrown, our business had outgrown our model, and we developed a new model that we just went live beginning of Q3. I guess it was the end of Q2. We were running it in parallel, and live with it at the beginning of Q3, which was the theory. We call it our Ensemble Model. It's a different model, looking at the different cohorts to predict our business, and it seems to be a much more accurate model at the specific customer level than what our old model was. Yeah. And then the, but- Now we have all the data around the downturn, so you can, like, predict- Yeah, yeah. When you see a customer slowing down, what's happening? But will it ever be like- No model is ever going to be- Yeah, yeah, but, like, like you never know what, what's coming next, yeah. Yeah. Okay, yeah. But, and- And by the way- Yeah ... you still have to have human intervention in the model. Even when we had our model before, we were doing something I never believed, and we would make top-side adjustments. Yeah. I would say with our Ensemble Model, I make a lot more adjustments. Okay, yeah, yeah, yeah. Okay. Because, like, it's like... So in the downturn, you kind of put another layer of model on in that way? Is that kind of the way to think about it, yeah. I would just say it's more of a detailed model that better splits out our business. Yeah. I will say, as we become bigger, it becomes easier to predict. If, like, one customer coming down, it's like- Yes, one customer is not gonna have as big of an impact today- Yeah, yeah ... as it did two years ago. Yeah, yeah, yeah. Fair enough. I wanted to just get a little bit, so if you think about new products, there's a lot of stuff coming out from your perspective. You mentioned some of that already. Like, if you kind of... I don't wanna, you know, it's like picking a favorite child, but, like, if you kind of think what's coming out there, what's kind of the one that we should be most interested in? You know, in the next 12 months, in the last 3 months, is probably the most new product feature releases that we've ever had in this industry. Mm. We now have Streamlit, went GA a few weeks ago. Streaming Dynamic Tables is in a public preview. You have, Iceberg Tables is in private preview. You have Container Services is private preview. Uh. Unistore is going to private preview or public preview. We actually have 10 customers that are actually using Unistore in a production environment. Yeah. Iceberg Tables will be... A lot of those things will be GA by Summit next year in June, is what our goal is. Yeah. I think the one that I'm the most. I continue to be bullish on Snowpark and what it can do for us longer term. Container Services is a big one because, as we talked about, that's gonna enable both native app developers on Snowflake to easier develop. And we have, by the way, a lot of customers that are replatforming their business on Snowflake. Yeah. Think of, like, Blue Yonder, and there's a bunch of others. They all want Container Services. We also have a number of customers that want to be able to fine-tune their large language models on their Snowflake data in Snowflake. Mm. Container Services will allow, enable that to happen easily in a secure, governed way, where you know your data is never leaving Snowflake. How does that... If you think about the new products, you're kind of broadening your addressable market by quite a bit. Like, do you think about— Do you still like think like in the old IT world?... my tab? Or like, is it, you know, like, do you try to put numbers on it or? Yeah. You know, we, we laid it out at our investor day. There are $200 billion market opportunity we're going after and growing it, and- Yeah ... There's gonna be many, many winners in this space. It's not one person take them all, but data continues to grow, and if you want to get the benefits of generative AI, you're not gonna do that on-prem, you're gonna do it in the cloud. And so you're gonna have to have your data in the cloud, and in order to get good results out of your large language models, you have to make sure you have clean data you're running it on, and we think Snowflake is the ideal place for that to be done. Yeah. Will it be the only place? Absolutely not. Mm. But we think it will be the prime choice for customers to do. Yeah. I mean, how do you think about, like, if you, We had worked a ServiceNow on Snowflake, on, Salesforce, on, downstairs on- Yeah Other stage as well. You know, they always pride themselves because they have these systems of record with a lot of data in there. Mm-hmm. Then, kind of see that as like a good starting point toward doing AI. Like, in a way, you know, you could be a consolidator of data. Like, how do you see that playing out for you? The reality is most customers do use CRM, Salesforce, they use ServiceNow, they use ERPs, whether it's Workday, Oracle, SAP- Yeah All of those people are putting their data in Snowflake. Because when you're gonna run any type of model, you generally are gonna want to look at a lot of different data from different sources. Yeah. Yeah. Snowflake, you know, customers will choose what the right place is, and we see them choosing Snowflake. You know, we already have a lot of Snowflake ServiceNow data and putting it into Snowflake. CRM data, the most common type of data going into Snowflake is CRM data. Mm. We have a lot of large customers that want to have all of their SAP data. Big German companies are really pushing to have all of their data, SAP data, in Snowflake. Yeah. Wouldn't be HANA? Okay, yeah. Yeah. It's funny, actually, ServiceNow, that's their... And I remember I was the one that made the decision to go with HANA there, HANA database now in Snowflake. Okay, that's funny. Yeah, okay. And then, how does it change the competitive, like, or how do you see that playing out over time, the competitive landscape then? Because it does feel like everyone a little bit comes together because data is the gravity. It's funny, all of those, as you mentioned, their customers use Snowflake too. Yeah, yeah. You know, as I said, I think there's going to be many winners in this. It's not one person and, you can do a lot of coopetition- Mm ... happening. Just like today, how we compete with AWS, Azure, and Google, yet we partner really well with AWS and Azure. Actually, I think we just went AWS re:Invent. We just won their Partner of the Year for their year. Yeah. So we clearly partner, and we'll work with. We partner well. At the end of the day, I think all of those people are gonna wanna do what's in the best interest of their customers, and if their customers want that, we'll work together. We work very well with all of those companies. Yeah. Yeah, yeah. Okay. And then you mentioned AI already a little bit. Like, how do you-how do you see that playing out for you, or just are you kind of seeing this, like, as the... You're the vehicle to consolidate the data, and then AI gets driven off that, or are there other initiatives for you guys? There are other initiatives that we're working on. Yeah. Some we're not talking about, and I won't. But there's a lot of, you know, at the end of the day, the value of what you get out of your models is gonna be based upon how good a data you have. Yeah. We think Snowflake is the right place for that. We are working on offering an on-demand GPU model, where even though I have to do it through reservation, it's 30 days, I'm working on structuring that. I think that'll be an attractive thing, and, because people do struggle, especially small companies, getting access to GPUs. You know, with AI, most customers, when you talk to them, still are trying to figure out their API strategy. Yeah. But they realize that they have to have their data in the cloud to really get the benefit of it. You know, everyone talks about Copilot. We announced the Copilot six months ago, too. Everyone has one. Yeah, yeah. Those are simple things with AI, but wouldn't it be nice to... And we have a vision, where a business analyst can just ask a question, Snowflake, in plain, plain English- Yeah and be able to get an answer? That's the type of stuff we're working on. Yeah. I mean, follow up question here. You've always been like a very sober CFO. How do you think about the monetization, especially around these Copilots? Because there's like... There are some firms that go like, "Oh, I can jack up the price by 60%," and off you go for running more queries or creating more queries. How do you think about that monetization? Well, you know, the beautiful thing about Snowflake, we really have one with four different layers: Enterprise, or Standard, Enterprise, Business Critical, and VPS. Most customers are on Business Critical. And every new feature we have, you don't get charged for. It's the consumption, the compute that it's using, those different features, is how we monetize. Right. And so, you know, the more queries you run, the more times you refresh your queries, the more often you want your data updated using Streaming and Dynamic Tables, it's gonna use more compute, you have to pay for that. And so it's truly a Consumption Model, and the more features we have, the more that customers use those, is going to drive revenue. It's not about. We're not gonna increase prices. And by the way, if you buy more, you commit more, you'll get better pricing on your price per credit. We now have tiered storage pricing, that if you make a bigger commitment, we'll give you a better price on storage. We're gonna protect the price per credit, but the storage pricing, we get a better price on. Yeah. Actually, I only have a few minutes left, so I need to kind of get a couple of questions. Like, you mentioned consumption. I don't answer questions. So that's why I do it. Yeah. If you think about consumption, like, how sensitive do you think you guys will be if the economy gets better? Because like, you know, what we've seen so far is, like, people were thinking about optimization, or maybe I have less data in Snowflake, and then save me a little bit of money. If it gets better again, like, how sensitive do you think you will be? You know, in a consumption model and what Snowflake has, customers can really ramp very quickly, but they can also slow down if they choose. Yeah. I think a lot of new products we have coming out next year could be a re-acceleration in our business. I am not forecasting that right now, and I need more time to see how these things play out before I look at changing any guidance or anything. I will say, a lot of these new things that we have coming out next year will be headwind through product margin expansion. Yeah. And there's a number of things from Unistore. The economics on that are not as good as our core product, because the way the system works to get the performance, there's having to store the data twice. Perhaps we need to take a. We'll get there, but it's gonna take about 6 months. GPUs, trying to do an on-demand model is more challenging and will be an economic headwind, but I think we have to have the GPUs to offer to people because we wanna be early to the game on that to get people- Yeah -on Snowflake. There's a lot of things happening with certain customers around the world with Sovereign clouds that are headwind to, margin expansion as we're opening up new deployments. It takes time before you can get those to scale- Yeah -to get to your ideal contribution rate. And then, since we're all in margins, like, so that's, that's more on a gross margin level. Yeah. Like, how do you think about the OPEX spending, and then, you know, operating margin part of that? Ram, how many years have I known you? 12, 13 years? Yeah. Every year, I always show operating margin. Yeah, you did it. We will continue to show our operating margin expansion. You know, it doesn't mean we're not gonna invest in the business, but we're gonna invest efficiently, and every year we're gonna show operating margin expansion. I've, I've said that in investor days, and we're very, I think we can grow this business very fast without sacrificing growth, continue to show leverage. Yeah. The one piece where we're not gonna see any individual item—we have a lot of R&D investments we're making next year- Mm-hmm ... and continuing to make with these products, a lot of the stuff around AI, what we're doing. We've got another $31 million dollar into R&D next year, just with what we're doing on GPUs internally. Yeah. Okay. And then last question on cash. Like, you know, you're nicely cash flow positive. You had a very strong cash flow. Like, how do you think about use of your cash? You know, we talked about last February, beginning of March, the board authorized the $2 billion buyback. We bought back just under $600 million, was it $580 million? Today, at $147. We will continue to opportunistically repurchase shares. As I said, we're gonna try to match it to our cash flow. Does that mean I'm gonna use all of the cash, or there may be quarters where I go over, but over the period of time? Yeah. Yeah. You know, a lot of companies say they're gonna do buybacks, but they never do them. I always like to do what we say we're going to do. Yeah. Yeah. So we're gonna continue to do that. You know, we continue to look at M&A, but all of the M&A continues to be the smaller M&A, and it's more teams of people- Yeah -that we can bring on. And I would say Neeva was an amazing acquisition for us with the talent we got out of that, Yeah ... really, really strong talent there. I mean, I mean, you're in a good position. You're growing organically really well, and there's nothing to buy. Like, what do you wanna buy? Yeah, and we don't need to buy a revenue stream. Yeah. Literally, any company that has revenue, I really don't want it. Yeah, yeah. Perfect. I think, you know, time's up, Mike. Thanks, I really enjoyed our conversation. Thank you.