(SNOW) 2024 Q3 法說會逐字稿

Good afternoon. Thank you for attending today's Q3 FY 2024 Snowflake's Earnings Conference Call. My name is Tina, and I will be your moderator for today's call. (Operator Instructions) I would now like to pass the conference over to our host, Jimmy Sexton, Head of Investor Relations at Snowflake. You may go ahead.

午安.感謝您參加今天的 2024 財年第三季 Snowflake 收益電話會議。我叫蒂娜，我將擔任今天電話會議的主持人。 （操作員指示）我現在想將會議轉交給我們的東道主、Snowflake 投資者關係主管吉米·塞克斯頓 (Jimmy Sexton)。你可以繼續。

Good afternoon, and thanks for joining us on Snowflake's Q3 Fiscal 2024 Earnings Call. With me in Bozeman, Montana, are Frank Slootman, our Chairman and Chief Executive Officer; Mike Scarpelli, our Chief Financial Officer; and Christian Kleinerman, our Senior Vice President of Product, who will join us for the Q&A session.

下午好，感謝您參加 Snowflake 的 2024 年第三季財報電話會議。和我一起在蒙大拿州博茲曼的是我們的董事長兼執行長 Frank Slootman； Mike Scarpelli，我們的財務長；我們的產品資深副總裁 Christian Kleinerman 將參加我們的問答環節。

During today's call, we will review our financial results for the third quarter of fiscal 2024 and discuss our guidance for the fourth quarter and full year fiscal 2024. 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, our stock repurchase program and overall future prospects.

在今天的電話會議中，我們將回顧2024 財年第三季的財務業績，並討論我們對2024 財年第四季和全年的指導。在今天的電話會議中，我們將做出前瞻性聲明，包括與預期業績相關的聲明我們的業務、未來的財務表現、策略、產品和功能、長期成長、我們的股票回購計劃和整體未來前景。

These statements are subject to risks and uncertainties, which cause -- 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 fiscal quarter ended July 31, 2023, and the Form 10-Q for the quarter ended October 31, 2023 that we will file with the SEC.

這些陳述存在風險和不確定性，可能導致它們與實際結果有重大差異。有關這些風險的資訊可在今天收盤後發布的收益新聞稿和向SEC 提交的文件中找到，包括我們最近提交的截至2023 年7 月31 日的財政季度的10-Q 表格以及該季度的10- Q 表格截至 2023 年 10 月 31 日，我們將向 SEC 備案。

We cause (sic) [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.

我們要求您（原文如此）[警告]不要過度依賴前瞻性陳述，並且不承擔因新資訊、未來事件或我們的期望變化而更新任何前瞻性陳述的責任或義務。

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.

我們還想指出，在今天的電話會議上，我們將報告 GAAP 和非 GAAP 業績。我們在內部使用這些非公認會計原則財務指標用於財務和營運決策目的，並作為評估期間比較的手段。非公認會計原則財務指標是根據公認會計原則計算的財務指標的補充，而不是替代。若要查看這些非公認會計準則財務指標的調節表，請參閱我們今天稍早發布的收益新聞稿以及發佈在 Investors.snowflake.com 上的投資者簡報。今天電話會議的重播也將發佈在網站上。

With that, I would now like to turn the call over to Frank.

有了這個，我現在想把電話轉給弗蘭克。

Thanks, Jimmy. Welcome and good afternoon. Q3 product revenue grew 34% year-over-year to reach $698 million. Non-GAAP adjusted free cash flow was $111 million, representing 7% year-over-year growth. Results reflect strong execution in a broadly stabilizing macro environment. while Snowflake's global revenue mix is highly diverse in terms of industries and geographies, the company derives an ever larger revenue share from mainstream enterprises and institutions. This, as compared to a newer crowd of digital natives, have made up many of Snowflake's early adopters. We added 35 $1 million plus customers during the quarter, 9 of our top 10 customers grew sequentially.

謝謝，吉米。歡迎，下午好。第三季產品營收年增 34%，達到 6.98 億美元。非 GAAP 調整後自由現金流為 1.11 億美元，較去年同期成長 7%。結果反映出在整體穩定的宏觀環境下的強勁執行力。儘管Snowflake的全球收入結構在行業和地區方面高度多樣化，但該公司從主流企業和機構獲得的收入份額越來越大。與較新的數位原住民群體相比，Snowflake 的許多早期採用者都是這個群體。本季我們增加了 35 家價值 100 萬美元以上的客戶，前 10 名客戶中有 9 家連續成長。

Generative AI is at the forefront of customer conversations, which in turn drives renewed emphasis on data strategy in preparation of these new technologies. We said it many times, there's no AI strategy without a data strategy. The intelligence we're all aiming for resides in the data, hence the quality of that underpinning is critical.

生成式人工智慧處於客戶對話的最前沿，這反過來又推動了人們在準備這些新技術時重新重視資料策略。我們說過很多次，沒有數據策略就沒有人工智慧策略。我們所追求的情報都存在於數據中，因此基礎的品質至關重要。

Meanwhile, Snowflake has announced and showcased the plethora of new technologies that let customers mobilize AI. We've introduced Snowflake Cortex to leverage AI and machine learning on Snowflake. Cortex is a managed service for inferencing large language models. This opens up direct access to models and specialized operations by translation, sentiment and vector functions.

同時，Snowflake 宣布並展示了眾多可讓客戶利用人工智慧的新技術。我們引入了 Snowflake Cortex，以利用 Snowflake 上的人工智慧和機器學習。 Cortex 是用於推理大型語言模型的託管服務。這使得可以透過翻譯、情感和向量函數直接存取模型和專門操作。

Business analysts and data engineers can now use AI functionality without the fractured highly technical challenges of the AI landscape. Last summer, we introduced Snowpark Container Services, which also serves as the second pillar of our AI enablement strategy. Developers can access any language, any library and flexible hardware inside the governance boundary of Snowflake. More than 70 customers are already using container services in preview with many more waiting in line.

業務分析師和資料工程師現在可以使用人工智慧功能，而無需應對人工智慧領域的高技術挑戰。去年夏天，我們推出了 Snowpark 容器服務，也是我們人工智慧支援策略的第二個支柱。開發人員可以存取 Snowflake 治理邊界內的任何語言、任何程式庫和靈活的硬體。已有 70 多家顧客在預覽版中使用容器服務，還有更多顧客在排隊等待。

Snowflake makes the common AI use cases easy and the advanced use cases possible. We are well positioned for AI based on the scale and scope of our data cloud programmability and governance framework. There are hurdles challenging enterprise adoption of AI and ML. The first is broad access to quality data. Snowflake addresses this challenge through its data sharing architecture. 28% of all our customer share data, up from 22% a year ago and 73% of our $1 million-plus customers are data sharing up from 67% a year ago.

Snowflake 讓常見的人工智慧用例變得簡單，並使進階用例成為可能。基於我們的資料雲可程式性和治理框架的規模和範圍，我們在人工智慧方面處於有利地位。企業採用人工智慧和機器學習存在一些障礙。首先是廣泛獲取高品質數據。 Snowflake 透過其資料共享架構解決了這項挑戰。我們所有客戶中有 28% 共享數據，高於一年前的 22%；價值 100 萬美元以上的客戶中有 73% 共享數據，高於一年前的 67%。

AI models can only be as smart as data they are trained on. Security and governance present another challenge for enterprise adoption of AI and ML. Snowflake Horizon offers a unified security and governance solution built for AI. Horizon strictly and consistently enforces user privileges on data across use cases, including large language model applications, traditional ML models and ad hoc queries. As part of Horizon, we introduced universal search, which enables customers to search the data cloud. Customers can now discover data and metadata that exists across their accounts and in the Snowflake marketplace.

人工智慧模型的智慧程度取決於它們所訓練的資料。安全和治理為企業採用人工智慧和機器學習帶來了另一個挑戰。 Snowflake Horizo​​n 提供專為 AI 建置的統一安全和治理解決方案。 Horizo​​n 嚴格一致地跨用例強制執行使用者對資料的權限，包括大型語言模型應用程式、傳統的 ML 模型和即席查詢。作為 Horizo​​n 的一部分，我們引入了通用搜索，使客戶能夠搜尋資料雲。客戶現在可以發現其帳戶和 Snowflake 市場中存在的資料和元資料。

Snowflake continues to win new workloads outside of its traditional. Snowpark consumption grew 47% quarter-over-quarter. Consumption in October was up over 500% since last year. Over 30% of customers use Snowflake to process unstructured data in October. Consumption of unstructured data was up 17x year-over-year. Our newest streaming capability, Dynamic Tables entered public preview earlier this year. Approximately 1,500 customers are using the feature and initial adoption is outpacing expectations.

Snowflake 繼續贏得傳統以外的新工作負荷。滑雪場消費量較上季成長 47%。 10月份消費量較去年增長超過500%。 10 月份，超過 30% 的客戶使用 Snowflake 處理非結構化資料。非結構化資料的消耗量較去年同期成長 17 倍。我們最新的串流功能 Dynamic Tables 在今年稍早進入了公開預覽版。大約 1,500 名客戶正在使用該功能，初步採用率超出了預期。

We have a number of major new capabilities becoming broadly available in Q4. Our native apps framework will go GA, Unistore for transaction processing, Snowpark Container Services and Apache Iceberg Tables will all enter public preview. These products unlock substantial new workload expansion opportunities. We are campaigning globally to expand our audience. This fall, our Data Cloud World Tour traveled to 26 cities worldwide. In-person attendance at these events reached 23,000, nearly double from last year. Next up is our Build Developer Conference in early December, where we anticipate 35,000 registrations. Build is focused on building apps, data pipelines and AI/ML workflows. We hope to see you there.

我們有許多主要的新功能將在第四季度廣泛使用。我們的原生應用程式框架將正式發布，用於事務處理的 Unistore、Snowpark Container Services 和 Apache Iceberg Tables 將全部進入公開預覽版。這些產品釋放了大量新的工作負載擴展機會。我們正在全球開展活動以擴大我們的受眾。今年秋天，我們的資料雲世界巡迴足跡遍及全球 26 個城市。參加這些活動的人數達到 23,000 人，幾乎是去年的兩倍。接下來是 12 月初的構建開發者大會，預計將有 35,000 人註冊。 Build 專注於建立應用程式、資料管道和 AI/ML 工作流程。我們希望看到你在那裡。

With that, I will turn the call over to Mike.

這樣，我會將電話轉給麥克。

Thank you, Frank. In Q3, we saw strong consumption from a broad base of customers. Our performance was evenly split between large and small accounts. Our largest customer stabilized as expected. Migrations drove growth in Q3. Our 2 fastest-growing customers who are both migrating workloads from a legacy vendor. One of these accounts is in their second year on the platform, the other in their eighth year on the platform. We added 4 customers with more than $5 million and 2 customers with more than $10 million in trailing 12-month product revenue in the quarter.

謝謝你，弗蘭克。第三季度，我們看到廣大客戶的強勁消費。我們的業績在大客戶和小客戶之間平均分配。我們的最大客戶如預期穩定。遷移推動了第三季的成長。我們成長最快的 2 個客戶都在從傳統供應商遷移工作負載。其中一個帳戶是在該平台上的第二年，另一個是在該平台上的第八年。本季度，我們增加了 4 個過去 12 個月產品收入超過 500 萬美元的客戶和 2 個超過 1000 萬美元的客戶。

Growth in September exceeded expectations. For 3 weeks, consumption grew faster than any other period in the past 2 years. Consumption continued to grow in the month of October. Q3 represented a strong quarter for bookings execution. Remaining performance obligations grew 23% year-over-year to $3.7 billion. Of the $3.7 billion in RPO, we expect 57% to be recognized as revenue in the next 12 months. APJ and SMB drove growth in net new bookings. We are making significant progress in delivering margin expansion.

9月份的成長超乎預期。連續三週的消費成長速度超過了過去兩年中的任何其他時期。 10月份消費持續成長。第三季是預訂執行強勁的季度。剩餘履約義務年增 23%，達到 37 億美元。在 37 億美元的 RPO 中，我們預計 57% 將在未來 12 個月內確認為收入。亞太及日本地區和中小型企業推動了淨新預訂量的成長。我們在實現利潤率擴張方面取得了重大進展。

Non-GAAP product gross margin of 78% was up approximately 300 basis points year-over-year. Improved terms from the cloud service providers have contributed to margin expansion. We also benefit from increasing consumption of higher-priced additions of Snowflake. In Q3, price per credit increased 4% year-over-year.

非 GAAP 產品毛利率為 78%，較去年同期成長約 300 個基點。雲端服務提供者條款的改善有助於利潤率的擴大。我們也受惠於雪花高價添加劑消費量的增加。第三季度，每筆信貸的價格年增 4%。

Non-GAAP operating margin of 10% was ahead of expectations. Operating margin benefited from revenue outperformance and increased hiring scrutiny. Non-GAAP adjusted free cash flow margin was 15%, benefiting from favorable timing of collections.

10% 的非 GAAP 營運利潤率超出預期。營業利益率得益於收入表現優異和招募審查力度加大。受惠於有利的收款時機，非公認會計原則調整後的自由現金流率為 15%。

We ended the quarter with $4.5 billion in cash, cash equivalents and short-term and long-term investments. Our strong cash position allows us to opportunistically repurchase shares. In Q3, we used $400 million to repurchase 2.6 million shares. Year-to-date, we have used $592 million to repurchase 4 million shares at an average price of $147.5.

截至本季末，我們的現金、現金等價物以及短期和長期投資為 45 億美元。我們強大的現金狀況使我們能夠趁機回購股票。第三季度，我們用 4 億美元回購了 260 萬股股票。今年迄今為止，我們已使用 5.92 億美元以平均價格 147.5 美元回購了 400 萬股股票。

Now let's turn to guidance. For the fourth quarter, we expect product revenue between $716 million and $721 million, representing year-over-year growth between 29% and 30%. We're increasing our full year guidance to approximately $2.65 billion, representing 37% year-over-year growth. Consumption trends have improved. We are seeing stability in customer expansion patterns. Our guidance is based on observed patterns and assumes continued stability of consumption.

現在讓我們轉向指導。對於第四季度，我們預計產品收入在 7.16 億美元至 7.21 億美元之間，年增 29% 至 30%。我們將全年指引提高至約 26.5 億美元，年增 37%。消費趨勢有所改善。我們看到客戶擴張模式的穩定性。我們的指導是基於觀察到的模式，並假設消費持續穩定。

For the fourth quarter, we expect operating margin of 4% and 360 million diluted weighted average shares outstanding. For the full year, we are increasing our non-GAAP product gross margin guidance. We now expect non-GAAP gross margin of 77%. We still expect a product gross margin headwind in the fourth quarter associated with new products.

我們預計第四季的營業利益率為 4%，稀釋加權平均流通股數為 3.6 億股。對於全年，我們正在提高非公認會計準則產品毛利率指引。我們目前預期非 GAAP 毛利率為 77%。我們仍預期第四季產品毛利率將因新產品而出現阻力。

We are increasing our fiscal 2024 non-GAAP operating margin guidance. We now expect non-GAAP operating margin of 7%. We are increasing our fiscal 2024 non-GAAP adjusted free cash flow margin. We now expect non-GAAP adjusted free cash flow margin of 27%. For the full year, we expect diluted weighted average shares outstanding of 361 million. We are on track to add more than 1,000 employees this year, inclusive of M&A.

我們正在提高 2024 財年非 GAAP 營業利潤率指引。我們目前預期非 GAAP 營業利益率為 7%。我們正在提高 2024 財年非 GAAP 調整後的自由現金流量利潤率。我們目前預期非 GAAP 調整後自由現金流率為 27%。我們預計全年稀釋加權平均已發行股數為 3.61 億股。今年我們預計將增加 1,000 多名員工，其中包括併購。

With that, operator, you can now open up the line for questions.

接線員，現在可以撥打電話提問了。

(Operator Instructions) Our first question is from the line of Mark Murphy with JPMorgan.

（操作員說明）我們的第一個問題來自摩根大通的馬克墨菲。

I love the 11-minute earnings call, and congrats on a fantastic result. So Frank, we are hearing broadly that conversations are starting with generative AI and they're stopping at data, because they find their data estates aren't in good enough shape. Are you sensing more tangible uplift there around that concept that Snowflake might be on the front edge of AI projects and perhaps seeing that spill over into customer conversations or drive more pipeline for some of your other products like Snowpipes and Snowpark and data sharing?

我喜歡 11 分鐘的財報電話會議，並祝賀取得了出色的成果。弗蘭克，我們廣泛聽到，對話是從生成人工智慧開始的，他們停止在數據上，因為他們發現他們的數據資產狀況不夠好。您是否感覺到Snowflake 可能處於AI 專案前沿這一概念有更明顯的提升，並且可能會看到這一概念溢出到客戶對話中，或者為您的其他一些產品（如Snowpipes 和Snowpark 以及資料共享）推動更多管道？

Generally speaking, yes, one of the interesting things is that customers are now getting preoccupied with their data estates because they have to get them into shape where they can productively take advantage of the newer technologies, which we are now also showcasing and delivering where they can just turn it on and have well-governed frameworks to run them with all the things that they're used to from Snowflake. So it's definitely true that the frenzy and the high degree of interest in AI has a knock-on effect on the interest in data strategy, data platforms.

一般來說，是的，有趣的事情之一是，客戶現在開始關注他們的數據資產，因為他們必須將這些數據資產塑造成可以有效利用新技術的狀態，我們現在也在向他們展示和交付這些技術。只需打開它並擁有管理良好的框架即可使用他們習慣的 Snowflake 中的所有功能來運行它們。因此，對人工智慧的狂熱和高度興趣確實對數據策略、數據平台的興趣產生了連鎖反應。

And people are also not just looking at the quality of their data and the optimization, organization, curation of data but also what kind of data they need to be able to have access to. So people are taking a much broader view of their data estates as well in terms of what's in it and what should be in it.

人們不僅關注數據的品質以及數據的最佳化、組織和管理，還關注他們需要能夠存取什麼樣的數據。因此，人們對他們的數據資產以及其中包含什麼和應該包含什麼有了更廣泛的看法。

Our next question is from Keith Weiss with Morgan Stanley.

我們的下一個問題來自摩根士丹利的基斯‧韋斯。

This is Theo Thun on for Keith. Maybe just start off with a quick question on sort of you mentioned several times on the call, the stabilization that you are seeing with the new growth. And we've obviously heard that from sort of your hyperscaler peers as well. When you're looking at an account level, could you give us sort of an idea like how much of the stabilization is coming from cost optimization, scrutiny alleviating versus sort of existing customers who slow what migrations leaning in more versus customers leaning more into new products? Is there any way that you can kind of give us more color on what parts are playing out already and which are yet to come maybe into the next year?

我是西奧·圖恩 (Theo Thun) 替基思 (Keith) 發言。也許首先要問一個你在電話中多次提到的快速問題，也就是你看到的新成長的穩定性。我們顯然也從一些超大規模同行那裡聽到了這一點。當您考慮帳戶層級時，您能否給我們一些想法，例如穩定的程度有多少來自於成本優化、審查減輕以及減緩遷移的現有客戶與更多傾向於新客戶的客戶產品？有什麼辦法可以讓我們更了解哪些部分已經上演，哪些部分可能會在明年播出嗎？

Keith (sic) [Theo], one of the things -- this is Frank. What I mentioned is our customer base has evolved in recent years to include much larger enterprises and institutions who are typically not prone to over consumption and unbridled expansion that they then later have to reset and rationalize. Because of that, the exposure to these drastic resets and optimizations that we saw earlier in the year is getting less and less with each incremental quarter.

基斯（原文如此）[西奧]，其中之一——這是弗蘭克。我提到的是，我們的客戶群近年來已經發展到包括更大的企業和機構，這些企業和機構通常不容易過度消費和無節制的擴張，然後他們必須重新調整和合理化。正因為如此，我們在今年稍早看到的這些劇烈的重置和優化的風險隨著每個增量季度的增加而越來越少。

Secondly, people have really driven themselves through these processes and rationalized themselves and are now in a good place to move forward. You can only optimize and rationalize so much. At some point, it's diminishing returns. People get tired of us and they're moving on to things that are now new and interesting, namely preparing for enabling AI and ML technologies.

其次，人們確實透過這些過程驅動自己並使自己合理化，現在處於前進的良好位置。你只能優化和合理化這麼多。在某些時候，它的回報會遞減。人們厭倦了我們，他們開始轉向現在新的、有趣的事物，即為啟用人工智慧和機器學習技術做準備。

Yes, I'll add to that, too, that why we see that stabilization is 9 out of our top 10 customers all grew quarterly sequentially. And the other point I'll make is we are seeing a shift, as Frank mentioned. Our biggest customers are mature enterprises we're seeing now and mature enterprises have always scrutinized cost. They always will. And so there's nothing new there, and that will continue. And that's just the way anyone should run a business.

是的，我還要補充一點，這就是為什麼我們看到穩定的 10 個客戶中有 9 個都按季度連續成長。我要說的另一點是，正如弗蘭克提到的那樣，我們正在看到轉變。我們最大的客戶是我們現在看到的成熟企業，成熟企業一直在審查成本。他們總是會的。所以那裡沒有什麼新的東西，而且這種情況將會繼續下去。這正是任何人經營企業的方式。

Got it. That's helpful. And then maybe one quick question on your sales and marketing headcount. Obviously, we noticed it's basically flat quarter-over-quarter this quarter. But then again, it's only sort of 1 number. Can you shed some light in terms of like what regions are you maybe leaning more into versus getting more efficiencies or any sort of areas that you're investing in still? Because obviously, your growth seems pretty healthy. So just some color on where you're investing versus not would be helpful.

知道了。這很有幫助。然後可能會問一個關於您的銷售和行銷人員人數的快速問題。顯然，我們注意到本季環比基本持平。但話又說回來，這只是 1 個數字。您能否透露一些信息，例如您可能更傾向於哪些領域而不是提高效率或您仍在投資的任何領域？因為顯然，你的成長看起來相當健康。因此，只要對您正在投資和不投資的地方進行一些說明就會有所幫助。

Yes. So first of all, in general, with sales and marketing heads, most of those typically are added right at the end of Q4 or even more so at the beginning of Q1, so people can get involved in our sales kickoff. And what I would say is we are continuing to invest very heavily in our sales and marketing function, in particular, in Europe. We talked about 6 months ago or so, we added a new leader there. We have been changing out some people and investing, and we're continuing to, and we will continue to prune underperformers globally and invest more in the right people as we go forward. And APJ is another one that we continue to invest in.

是的。因此，首先，一般來說，對於銷售和行銷負責人來說，大多數人通常會在第四季度末甚至第一季初添加，這樣人們就可以參與我們的銷售啟動。我想說的是，我們將繼續大力投資我們的銷售和行銷職能，特別是在歐洲。我們大約在 6 個月前討論過，我們在那裡增加了一位新的領導者。我們一直在更換一些人員並進行投資，我們將繼續這樣做，隨著我們的前進，我們將繼續在全球範圍內裁減表現不佳的人員，並在合適的人員上進行更多投資。 APJ 是我們繼續投資的另一個項目。

Our next question is from the line of Raimo Lenschow with Barclays.

我們的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Congrats from me as well. Guys, you have like a crazy amount of new exciting products coming out. How do you think about the sales setup here now going forward? Because you're going to be able to address lots of different areas from like classic data to kind of more AI. Does that mean your sales approach needs to change, Frank, here going forward? And it doesn't sound like you are going to have a crazy sales force expansion here. Like how do you want to do that going forward and ensure that all these new products are actually finding the market?

我也表示祝賀。夥計們，你們有大量令人興奮的新產品問世。您如何看待這裡現在的銷售設定？因為你將能夠解決許多不同的領域，從經典數據到更多的人工智慧。弗蘭克，這是否意味著您的銷售方式需要改變？聽起來您不會在這裡進行瘋狂的銷售團隊擴張。例如，您未來想如何做到這一點並確保所有這些新產品真正找到市場？

Yes, that's actually an excellent observation. We have historically had sort of 1 dominant selling motion that we sort of deployed everywhere and anywhere. It has served us well. But as you correctly observed, the market has really changed. When you go back to 2015, Snowflake really swam in swim lanes that were very narrowly defined and very well understood. Now we're in the mega market, right?

是的，這實際上是一個很好的觀察。從歷史上看，我們有一種主導性的銷售行動，我們在任何地方都部署了這種行動。它為我們提供了很好的服務。但正如你所觀察到的，市場確實發生了變化。當你回到 2015 年時，Snowflake 確實在定義非常狹窄且非常容易理解的泳道中游泳。現在我們正處於龐大市場，對嗎？

These are very, very broad-based platforms that are incredibly capable in many directions. And we've been working very hard, as you've seen in recent years, in delivering just an absolute ton of capabilities to enable these platforms in all these different directions. I mean, our drive towards applications and the whole programmability framework, the onslaught of AI and ML capabilities, all of that is coming to fruition.

這些都是基礎非常非常廣泛的平台，在許多方面都具有令人難以置信的能力。正如您近年來所看到的，我們一直在非常努力地提供大量功能，以使這些平台能夠朝著所有這些不同的方向發展。我的意思是，我們對應用程式和整個可程式性框架的推動，人工智慧和機器學習能力的衝擊，所有這些都即將實現。

Now we have a ton of irons in the fire, and they're now all getting hot. So from a sales standpoint, we have much more specialization happening and that is going to literally going all over the world because it is impossible for a single person to be to be expert in all these technologies and all these disciplines. So we're going to have people that have general purpose capabilities, sort of core skills, if you will, and then we will have teams of specialists that will augment these groups wherever they're needed. So our basic selling motions and how they are supported will evolve rapidly in the coming year.

現在我們有大量的熨斗正在燃燒，它們現在都變熱了。因此，從銷售的角度來看，我們正在發生更專業化的事情，而這實際上將遍及世界各地，因為一個人不可能成為所有這些技術和所有這些學科的專家。因此，如果你願意的話，我們將擁有具有通用能力、核心技能的人員，然後我們將擁有專家團隊，在需要的地方增強這些團隊的能力。因此，我們的基本銷售舉措及其支援方式將在來年迅速發展。

Our next question is from the line of Kirk Materne with Evercore ISI.

我們的下一個問題來自 Evercore ISI 的 Kirk Materne。

Congrats on the quarter. I guess, Mike, could you just talk about the impact that some of these newer unstructured data workloads are having on consumption at all, meaning I assume it's still a very, very small part of overall consumption when you look at it, but is that helping with the stabilization? Can they turn into sort of catalyst for acceleration as we get into '24? Anything you did to sort of dimensionalize the impact that has as we think out to next year.

恭喜本季。我想，麥克，您能否談談其中一些較新的非結構化資料工作負載對消耗的影響，這意味著我認為當您查看它時，它仍然只佔總體消耗的非常非常小的一部分，但這是嗎？有助於穩定？當我們進入 24 世紀時，它們能否成為某種加速催化劑？您所做的任何事情都可以量化我們對明年的影響。

Well, they're definitely helping with stabilization. I can't quantify exactly what unstructured is doing, but it's not just that. It's also we're starting to see the effects more of Snowpark that's doing very well for us right now. Some of the new things we're already seeing very early uptick in streaming and Dynamic Tables. We really -- I would say, Streamlit is built into our forecast for next year. The other products because they're new, we really don't build much in for that because we need history before we can do that. And clearly, we think a lot of these new products that are just going into public preview now and GA next year will be a catalyst for growth for us in 2025.

嗯，他們肯定有助於穩定。我無法準確量化非結構化正在做什麼，但不僅僅是如此。我們也開始看到更多 Snowpark 的效果，目前它對我們來說效果很好。我們已經看到串流媒體和動態表中的一些新事物很早就出現了增長。我想說，Streamlit 已納入我們對明年的預測。其他產品因為它們是新產品，所以我們實際上並沒有為此做太多構建，因為我們需要歷史才能做到這一點。顯然，我們認為許多現在剛進入公開預覽版並於明年上市的新產品將成為我們 2025 年成長的催化劑。

One follow-on, Kirk. Document AI is a technology that we've been working on for quite a while, and it really was on the basis of an acquisition we did over a year ago. That is now going into preview. And it is incredibly popular out there and what Document AI does, returns to an unstructured document into a semi-structure document. So it can become a full participant in analytical processing.

後續作品之一，柯克。文件人工智慧是我們已經研究了很長一段時間的技術，它確實是基於我們一年多前進行的一項收購。現在正進入預覽階段。它在那裡非常受歡迎，Document AI 所做的就是將非結構化文件返回到半結構化文件。因此它可以成為分析處理的全面參與者。

There is a ton of interest in that. And so that really brings the entire estate of unstructured data, which is 80% of the world's data into the analytical sphere. So we do expect that to become very important, and especially because AI and LLMs are so heavily focused on unstructured data, textual data, at least today, this will be something that will be a driver in our business.

人們對此很感興趣。因此，這確實將整個非結構化資料（即世界上 80% 的資料）帶入了分析領域。因此，我們確實預計這將變得非常重要，特別是因為人工智慧和法學碩士非常關注非結構化數據、文字數據，至少在今天，這將成為我們業務的驅動力。

And Mike, can you just give us an update on where the federal sort of opportunity stands? I know you guys were waiting to hear back on FedRAMP. Any update on that?

麥克，您能給我們介紹一下聯邦機會的最新情況嗎？我知道你們正在等待 FedRAMP 的回覆。有更新嗎？

Federal is a huge opportunity, and I would say it's upside for us because it's such a small piece, but we should have our FedRAMP high authorization literally any day. I actually thought I might have had it today. So stay tuned. You'll see an announcement on that very soon.

聯邦是一個巨大的機會，我想說這對我們有好處，因為它很小，但我們實際上隨時都應該獲得 FedRAMP 的高度授權。我實際上以為我今天可能已經得到了它。所以請繼續關注。您很快就會看到相關公告。

our next question is from the line of Brad Reback with Stifel.

我們的下一個問題來自 Brad Reback 和 Stifel。

Just a quick technical question with Graviton 4 now being announced by Amazon, should we think of any potential headwinds there?

亞馬遜現在宣布推出 Graviton 4，這是一個簡單的技術問題，我們是否應該考慮其中潛在的阻力？

Well, as we told you before, every year, we count on a 5% headwind associated with software, hardware improvements. Graviton 4 was just announced recently. We really have not tested that and not all hardware improvements benefit our software. We expect there will be some, but we just don't know. It's too early, stay tuned and we'll update you when we have more information.

嗯，正如我們之前告訴過您的，每年我們預計會出現 5% 與軟體和硬體改進相關的阻力。 Graviton 4 最近剛發布。我們確實還沒有測試過這一點，並且並非所有硬體改進都有益於我們的軟體。我們預計會有一些，但我們只是不知道。現在還為時過早，請繼續關注，當我們有更多資訊時，我們會及時通知您。

Our next question is from the line of Alex Zukin with Wolfe Research.

我們的下一個問題來自 Wolfe Research 的 Alex Zukin。

This is Ethan Bruck on for Alex Zukin. Congrats on the nice quarter. My question is, if you're assuming the consumption trends persist through 4Q, and that's how you're guiding, I guess, what would be the biggest puts and takes to accelerate growth next year? And in the same vein, when we think about NRR, just given the stabilizing consumption trends, I guess, directionally, when should we think about when would we expect NRR to stabilize trough and around like what level would you expect?

我是伊森布魯克 (Ethan Bruck) 替補亞歷克斯祖金 (Alex Zukin)。恭喜這個美好的季度。我的問題是，如果您假設消費趨勢持續到第四季度，而這就是您的指導方式，我想，明年加速成長的最大投入和支出是什麼？同樣，當我們考慮 NRR 時，鑑於消費趨勢趨於穩定，我想，從方向上看，我們應該何時考慮 NRR 何時會穩定在谷底或附近，就像您期望的水平一樣？

So I'll start with -- I'm not going to guide to NRR. I do see it stabilizing. It could dip a little bit more. I do expect over time, NRR, as we've said, we'll converge with our revenue growth at the size we're at. And clearly, the biggest puts and takes for next year is going to be the -- to continue to see the stabilization we have we're seeing right now and what the impact of a lot of our new initiatives are going to be next year, and it's just too early to tell right now and to guide to that. So stay tuned for our February call when we give guidance for next year.

因此，我將首先——我不會指導 NRR。我確實看到它穩定下來。它可能會再下跌一點。我確實預計隨著時間的推移，NRR，正如我們所說，我們將與我們目前的規模的收入成長趨同。顯然，明年最大的投入和投入將是——繼續看到我們現在所看到的穩定情況，以及我們許多新舉措明年將產生的影響，現在判斷並指導這一點還為時過早。因此，請繼續關注我們二月份的電話會議，屆時我們將給予明年的指導。

Our next question is from the line of Brent Thill with Jefferies.

我們的下一個問題來自傑弗里斯的布倫特·希爾。

Mike, I think you mentioned there is a higher utilization on the higher tiers that you're offering. Can you just extrapolate what you're seeing there?

麥克，我想您提到過您提供的更高級別的利用率更高。你能推斷出你在那裡看到的情況嗎？

Well, typically, large enterprises are the ones using our business critical in BPS, and those guys are becoming bigger and bigger customers. And as a result, we do see more of our revenue being derived from these very large companies who are using our higher SKU, which has higher margin for us, and that's what we're seeing there.

嗯，通常情況下，大型企業是在 BPS 中使用我們的關鍵業務的企業，而這些企業正在成為越來越大的客戶。因此，我們確實看到更多的收入來自這些非常大的公司，他們使用我們更高的 SKU，這對我們來說有更高的利潤，這就是我們所看到的。

Okay. And quickly for Frank, when you think about just the overall AI impact, do you feel that this is a bigger tailwind in the back half of '24? Do you think you'll see it coming in early '24? How are your thought process in terms of adoption in this way helping you? When does that impact hit from a monetization perspective?

好的。對弗蘭克來說，當你考慮到人工智慧的整體影響時，你是否覺得這是 24 世紀後半段更大的推手？您認為您會在 24 年初看到它嗎？您在採用這種方式方面的思考過程對您有何幫助？從貨幣化的角度來看，這種影響何時會出現？

There's going to be a lot of nuances to how AI is going to unfold and translate itself into the effects into our business. It's not just like turning on the switch and all of a sudden, you see incremental consumption happening. As we said during the prepared remarks, we're already seeing that the interest in AI is also driving interest in the data strategy, which then has a knock-on effect on consumption.

人工智慧將如何展開並轉化為對我們業務的影響，將會有許多細微差別。這不僅僅是打開開關，突然之間，您會看到增量消耗的發生。正如我們在準備好的演講中所說，我們已經看到對人工智慧的興趣也在推動對數據策略的興趣，從而對消費產生連鎖反應。

It's also the expansion of the data universe that people are bringing in quality of the data initiatives. All of that is going to bring incremental workload utilization to Snowflake, even though you would normally not necessarily characterize that as AI, but these are things that are going to enable AI, and it might well be that a ton of the workload of AI is actually the proverbial iceberg where only the tip of it that sticking above the water is really AI, but everything that has to happen to support us is happening below the service then we're going to be a huge beneficiary of that.

人們帶來的數據空間的擴展也提高了數據計劃的品質。所有這些都將為 Snowflake 帶來增量的工作負載利用率，儘管您通常不一定將其描述為人工智慧，但這些都是將啟用人工智慧的東西，而且很可能人工智慧的大量工作負載是實際上，就像眾所周知的冰山一樣，只有冰山一角浮在水面上才是真正的人工智慧，但支援我們的一切都發生在服務下方，那麼我們將成為其中的巨大受益者。

We think that Snowflake is super well prepared because our data estates are in a very, very advanced state because our customers have spent years, years and years. And in some cases, literally decades from prior legacy platforms to building these estates and curing the data and organizing and optimizing for the data to be completely trusted and sanctioned in their environment, and that is a huge value when you start tackling AI and ML models.

我們認為 Snowflake 已經做好了充分的準備，因為我們的資料資產處於非常非常先進的狀態，因為我們的客戶已經花費了很多年。在某些情況下，從以前的遺留平台到構建這些資產、固化數據、組織和優化數據，使其在其環境中完全信任和認可，實際上需要數十年的時間，當您開始處理人工智慧和機器學習模型時，這是一個巨大的價值。

Our next question is from the line of Patrick Colville with Scotiabank.

我們的下一個問題來自豐業銀行的派崔克·科爾維爾。

In your prepared remarks, you talked of very strong consumption in September. Consumption continued to grow in October. We're now 29 days through November. Can you just talk about trends thus far this month?

在您準備好的發言中，您談到了 9 月的消費非常強勁。 10月份消費持續成長。距離 11 月還有 29 天。您能談談本月迄今的趨勢嗎？

What I would say is trends are good, but you have to remember, it also has a big holiday in the U.S. and the week of Thanksgiving is typically a slow week. With that said, I'm happy with the consumption we're seeing, and that's reflected in our guidance.

我想說的是，趨勢是好的，但你必須記住，美國也有一個大假期，感恩節這一周通常是緩慢的一周。話雖如此，我對我們所看到的消費感到滿意，這也反映在我們的指導中。

Our next question is from the line of Tyler Radke with Citi.

我們的下一個問題來自花旗銀行的泰勒拉德克 (Tyler Radke)。

I wanted to ask you about Container Services. So it sounds like you're seeing some good early momentum there, more than 70 customers in private preview. I'm curious how many of those are actually deploying large language models directly on the Snowflake data? And for those customers that are doing that, what type of uplift or how you kind of characterize that consumption when they do that?

我想向您詢問有關集裝箱服務的問題。聽起來您似乎看到了一些良好的早期勢頭，有 70 多個客戶在進行私人預覽。我很好奇其中有多少實際上直接在 Snowflake 資料上部署大型語言模型？對於那些正在這樣做的客戶，什麼類型的提升或當他們這樣做時你如何描述這種消費？

Yes. This is Christian. Yes, we have seen a variety of use cases, but a good number of those -- quite a few customers are leveraging GPU instances in Snowpark Container Services for use of large language models. So for sure, it's a meaningful part of the early adoption use cases and we've got lots of encouragement and excitement to continue the rollout of the preview.

是的。這是基督教的。是的，我們已經看到了各種各樣的用例，但其中有很多——相當多的客戶正在利用 Snowpark 容器服務中的 GPU 實例來使用大型語言模型。因此，可以肯定的是，這是早期採用用例中有意義的一部分，我們對繼續推出預覽版感到非常鼓勵和興奮。

Great. And just a question on go-to-market. So I think earlier this year, you talked about some execution issues and it seems like that's been partially resolved to get good results in APAC. I guess, do you feel like you have all the right key sales leaders in place at this point? Or are there still some roles you're looking for? And I guess, ultimately, do you feel like you've turned the corner on those execution issues as well?

偉大的。只是一個關於上市的問題。所以我認為今年早些時候，您談到了一些執行問題，似乎已經部分解決，以便在亞太地區取得良好的結果。我想，您覺得目前所有關鍵銷售領導者都已到位嗎？或者還有一些你正在尋找的角色嗎？我想，最終，您是否也覺得自己已經在這些執行問題上扭轉了局面？

Yes. It's Frank. Look, in a global sales organization that we're running and we're running all the way from an on-demand selling motion that's unattended, if you will, by salespeople to SMB, to an ISB to mid-range large and then the extremely large customers. The -- it's always a work in process. There's always opportunity for improvement. That's been true for as long as I've been here. That said, I feel we're getting incrementally better, stronger, deeper in terms of our ability to sell. We're becoming much more consistent and more and more productive every day.

是的。是弗蘭克。看，在我們正在運營的全球銷售組織中，我們一直在運行從無人值守的按需銷售活動（如果你願意的話），從銷售人員到中小型企業，再到 ISB 到中型大型企業，然後是非常大的客戶。這始終是一項正在進行中的工作。總是有改進的機會。自從我在這裡以來，情況一直如此。也就是說，我覺得我們的銷售能力逐漸變得更好、更強、更深。我們每天都變得更加一致、越來越有效率。

So a lot of stability and a lot of progress. But this is something that's never over. Anybody who's been in this business knows how this works. It's a very dynamic mix of things. But on the whole, we have to, as a company, a $3 billion or something of that order of magnitude run rate, we lean hard on our organization to show up and deliver those results every quarter. So it's becoming a formidable enterprise in terms of our go-to-market capability.

所以很多穩定和很多進步。但這是永遠不會結束的事。任何從事過這個行業的人都知道這是如何運作的。這是一個非常動態的事物組合。但總的來說，作為一家公司，我們必須以 30 億美元或類似數量級的運作率，我們努力依靠我們的組織每季展示並交付這些結果。因此，就我們的市場進入能力而言，它正在成為一家強大的企業。

Our next question is from the line of Brent Bracelin with Piper Sandler.

我們的下一個問題來自 Brent Bracelin 和 Piper Sandler。

Frank, we'll start with you here. I think last quarter, unstructured data was mentioned twice. You've called it out here more than a dozen times. You talked about October trends being up, I think, 17x increase year-over-year. How much of a game changer is this, particularly as we think about Document AI and Snowpark Containers coming out next year? Clearly, a focus here. It certainly hasn't been an area you supported in the past, but it feels like there's a sea change movement here. How much of a game changer is unstructured data support relative to the growth opportunity going forward?

法蘭克，我們就從你這裡開始。我認為上個季度，非結構化資料被提到了兩次。你已經在這裡喊過十幾次了。您談到了 10 月的趨勢，我認為同比增長了 17 倍。這對遊戲規則有多大的改變，特別是當我們考慮明年推出的 Document AI 和 Snowpark Containers 時？顯然，這裡是一個焦點。這當然不是您過去支持的領域，但感覺這裡正在發生翻天覆地的變化。相對於未來的成長機會，非結構化資料支援在多大程度上改變了遊戲規則？

Look, unstructured data, as I said earlier, is the majority of the world's data. And until relatively recently, it's been borderline unusable for analytical purposes, because it is unstructured and you can't reference it in analytical workloads.

看，正如我之前所說，非結構化資料是世界資料的大部分。直到最近，它一直無法用於分析目的，因為它是非結構化的，您無法在分析工作負載中引用它。

It's ironic that both through the on slide of large language models that is also extraordinarily of dealing with textual data as well as things just Document AI that Snowflake developed, and it's bringing to the market that this data is going to become a full participant in these types of workloads. It's super exciting because it's going to really enrich and really unlock insights and outcomes and all of that we haven't had before. So this is going to be a driver of our world as we know it in terms of this type of computing.

諷刺的是，透過幻燈片上的大型語言模型，它也非常處理文字資料以及 Snowflake 開發的文檔人工智慧，並將這些資料推向市場，這些資料將成為這些領域的全面參與者。工作負載類型。這非常令人興奮，因為它將真正豐富並真正釋放見解和成果以及我們以前從未有過的所有內容。因此，正如我們所知，就此類計算而言，這將成為我們世界的驅動力。

That's helpful. And Mike, if I look at average consumption revenue per customer, those metrics improved on a growth perspective, slightly year-over-year for the first time in over a year. What are the driving factors there? How much of this is just the optimization headwinds now starting to ease versus net new workloads coming on the platform?

這很有幫助。麥克，如果我看看每個客戶的平均消費收入，這些指標從成長的角度來看有所改善，一年多來首次同比略有改善。其中的驅動因素是什麼？其中有多少只是與平台上出現的淨新工作負載相比現在開始緩解的最佳化阻力？

Well, what I would say, and I'll repeat what I've said at numerous times to investors, optimizations are part of our life. They've been happening at Snowflake from day 1, they will continue to happen. Nothing is new with optimization. I don't see any big ones happening now, but that's not to say they won't happen in the future, because history has shown they happen all the time.

好吧，我想說的是，我會重複我多次向投資者說過的話，而優化是我們生活的一部分。從第一天起，這些事情就在 Snowflake 發生，並將繼續發生。優化並不是什麼新鮮事。我現在沒有看到任何重大事件發生，但這並不是說它們將來不會發生，因為歷史表明它們一直在發生。

Most of the growth that we're seeing within our customers is we talked about 2 of our biggest growth customers was on-prem legacy migrations into Snowflake. So there's initial migrations, but we're also seeing new workload expansion within existing customers as well, too.

我們在客戶中看到的大部分成長是我們談到的兩個最大的成長客戶是將本地舊版遷移到 Snowflake。因此，存在最初的遷移，但我們也看到現有客戶中新的工作負載擴展。

So it's -- there's no one thing that's driving it. It's just general consumption we're seeing. And I will say Snowpark is starting to kick in for us. Still not 10% of our revenue. That's a long ways to get there, but it's still meaningful for us.

所以，沒有任何一件事在推動它。這只是我們看到的一般消費。我想說的是，Snowpark 已經開始為我們服務了。仍然不到我們收入的 10%。雖然還有很長的路要走，但對我們來說仍然很有意義。

Our next question is from the line of Derrick Wood with TD Cowen.

我們的下一個問題來自 Derrick Wood 和 TD Cowen。

I guess I wanted to dovetail off of that on-premise legacy migrations. And I guess for Frank, I mean, when we saw the macro hit, I think it did cause a slowdown in customers looking to re-platform from on-prem to cloud. Just curious, I mean, I know you guys are kind of highlighting the consumption trends improving here. But wondering what you're seeing in the pipeline for new Global 2000 accounts? And if you're seeing legacy replatforming initiatives start to kick back up now that the macro environment has gotten a little bit more stable?

我想我想與本地遺留遷移相吻合。我想對於弗蘭克來說，當我們看到宏觀打擊時，我認為這確實導致了客戶尋求從本地到雲端重新建構平台的速度放緩。只是好奇，我的意思是，我知道你們有點強調這裡的消費趨勢正在改善。但想知道您在全球 2000 強新帳戶中看到了什麼？既然宏觀環境變得更加穩定，您是否發現傳統的平台重組計劃開始復甦？

Well, I mean, there's no doubt that the legacy replatforming is sort of the hardcore of our business. And almost surprisingly there is just an enormous amount of workloads still sitting on-premise that is still waiting to get migrated to the cloud. So I expect this to continue for a very long period of time. But as what Mike said is very important. Once you get those data estates into the cloud, our new architectures and our new technologies are now enabling opportunities that people haven't had before. And so that drives workload expansion.

嗯，我的意思是，毫無疑問，遺留平台重組是我們業務的核心。幾乎令人驚訝的是，仍有大量工作負載仍在本地等待遷移到雲端。所以我預計這種情況會持續很長一段時間。但正如麥克所說，這一點非常重要。一旦將這些資料資產轉移到雲端中，我們的新架構和新技術就會為人們帶來前所未有的機會。這推動了工作負載的擴展。

So it's not just like, okay, we're going to be doing in the cloud what we used to be doing on-premise, and that's the foundation of the business. It is definitely foundational but the opportunity is really what grows from that. That's been the Snowflake story from day 1. Because of what's now possible, we don't have the capacity constraints and people can run unlimited numbers of workloads.

所以這不僅僅是，好吧，我們將在雲端做我們過去在本地做的事情，這是業務的基礎。這絕對是基礎，但機會確實是從中產生的。這就是雪花從第一天開始的故事。由於現在的可能性，我們沒有容量限制，人們可以運行無限數量的工作負載。

And now with all the new technologies in terms of programmability, AI and ML, the sky is the limit. I mean, in our conversation with customers, I was telling us is that your problem is no longer the technology. Your problem is your imagination and your budget, right? Not that those are easy things, but technology is not holding us back anymore. It's our ability to harness the technology. And then, of course, you have to pay for it as well.

現在，隨著可編程性、人工智慧和機器學習方面的所有新技術的出現，天空是極限。我的意思是，在與客戶的對話中，我告訴我們，您的問題不再是技術。你的問題是你的想像和預算，對吧？並不是說這些都是容易的事情，但科技不再是我們的阻礙。這是我們利用科技的能力。當然，你也必須為此付出代價。

Yes. I'll just add to that, Derrick, too, on your question about Global 2000. Yes, we added 2 Global 2000 last quarter. And as I've said many times before, selling into a Global 2000 as a campaign, it's a 1 to 2, sometimes 3-year sales cycle. With that said, we have a number of Global 2000 in our pipeline for Q4.

是的。 Derrick，我也想補充您關於 Global 2000 的問題。是的，我們上季度添加了 2 個 Global 2000。正如我之前多次說過的，向全球 2000 強企業進行銷售作為一項活動，是一個 1 到 2 年，有時是 3 年的銷售週期。話雖如此，我們在第四季準備了許多全球 2000 強公司。

And what I also want to see, too, is not every Global 2000 starts with an on-prem migration. Many of them start with a first-gen cloud solution they had purchased to migrate to Snowflake. Yes, almost all of them have an on-prem estate, but that doesn't always happen at first. It really varies by customer. But with that said, we still see a lot of on-prem migration to be done over the coming years, and it's going to be for many, many years.

我還想看到的是，並非所有全球 2000 大企業都從本地遷移開始。他們中的許多人從購買的第一代雲端解決方案開始遷移到 Snowflake。是的，幾乎所有的公司都擁有本地資產，但一開始並不總是如此。這確實因客戶而異。但話雖如此，我們仍然看到未來幾年需要進行大量本地遷移，而且這種情況將會持續很多很多年。

Got it. And Mike, a follow-on for you, really around RPO. And we've heard of more companies looking to take a pay-as-you-go approach. So could you speak to what extent customers are shifting to that approach versus annual or multiyear commits and how that may play into your RPO growth trends looking forward?

知道了。麥克（Mike）是您的後續人員，主要圍繞 RPO 進行工作。我們聽說越來越多的公司希望採取即用即付的方式。那麼，您能否談談與年度或多年承諾相比，客戶在多大程度上轉向這種方法，以及這對您未來的 RPO 成長趨勢有何影響？

No. I don't see that, that much. The only time you see pay-as-you-go are ones who had signed a 3-year contract and then they run out of capacity. And then they just pay as they go. Actually, one of our top 10 customers is like that. They have until April to continue before they have to do another contract, if they want to get the same pricing that they have. I actually expect Q4 is going to be a pretty significant bookings quarter with a number of renewals that are up or customers are going to do something. And we continue to push for 3-year contracts with our customers.

不，我不這麼認為。唯一看到現收現付的情況是那些簽訂了 3 年合約的人，然後他們的能力就用完了。然後他們就隨用隨付。事實上，我們的十大客戶之一就是這樣的。如果他們想獲得與現有價格相同的價格，他們必須在四月之前繼續簽訂另一份合約。實際上，我預計第四季度將是一個相當重要的預訂季度，大量續訂活動將會增加，或者客戶將採取一些行動。我們繼續推動與客戶簽訂三年合約。

Payment terms, I do expect though that is one of the things I'd rather give up on payment terms and discount to price per credit. And that's really, I've said it all along, I anticipate longer term, customers will want to do more monthly in arrears payment terms, and that is available to customers. It all comes down to what price you want to pay per credit. And to date, most people want the lower price per credit and are willing to pay annual in advance.

付款條件，我確實希望這是我寧願放棄付款條件和每信用價格折扣的事情之一。事實上，我一直在說，我預計從長遠來看，客戶會希望按月支付更多的欠款，而這對客戶來說是可行的。這一切都取決於您想要為每個積分支付的價格。迄今為止，大多數人希望每個信用的價格較低，並且願意提前支付年度費用。

Our next question is from the line of Joel Fishbein with Truist.

我們的下一個問題來自 Joel Fishbein 與 Truist 的對話。

Congrats on the great quarter. I guess, Frank, this one is for you. At Snowflake Summit, you announced an expanded partnership with Microsoft. And I'm just curious how that partnership is going, and you also announced some joint product integration. So I'd love to get an update how that's going and how you feel about that going forward?

恭喜這個偉大的季度。我想，法蘭克，這個是給你的。在 Snowflake Summit 上，您宣布擴大與 Microsoft 的合作關係。我只是好奇這種合作關係進展如何，你們也宣布了一些聯合產品整合。所以我很想了解最新進展以及您對未來有何看法？

This is Frank. Yes, we actually saw quite a bit of energy coming from the Azure platform this quarter. The things that we worked on in the renewed relationship with Microsoft is really much better alignment in the field from a compensation standpoint that is just super, super important in our world. And we're seeing the effects of that.

這是弗蘭克.是的，本季我們實際上看到了來自 Azure 平台的大量能量。從薪酬的角度來看，我們在與微軟重新建立關係時所做的工作確實在該領域取得了更好的一致性，這在我們的世界中非常非常重要。我們正在看到其影響。

And the Microsoft platform really upticked during the quarter. I don't know the exact numbers at hand, but it measurably ticked up. So we're encouraged by the behavior we're seeing in the field, and we're encouraged in the overall sentiment that's developing in the field. So it's definitely healthier than the relationship with Microsoft has been historically. So we're pleased and optimistic about it.

微軟平台在本季確實有所提升。我不知道手頭上的確切數字，但它明顯增加了。因此，我們對在該領域看到的行為感到鼓舞，並且對該領域正在發展的整體情緒感到鼓舞。因此，這絕對比歷史上與微軟的關係更健康。所以我們對此感到高興和樂觀。

Any milestones we should be looking for there from the partnership?

我們應該從合作關係中尋找任何里程碑？

Not really.

並不真地。

Our next question is from the line of Mike Cikos with Needham.

我們的下一個問題來自 Mike Cikos 和 Needham。

And good to hear some of the earlier comments around Snowpark, which is consistent with some of the growing momentum we've heard in some of our checks. I think the question is probably more for maybe Mike or Christian. But is there enough empirical data or a sizable enough customer base yet for Snowpark to start talking about how these Snowpark customers, I guess, what adoption of Snowpark does for consumption versus non-Snowpark customers? Or maybe how we should think about usage building over time as Snowpark becomes a larger part of those customers' workflows?

很高興聽到一些早期關於 Snowpark 的評論，這與我們在一些檢查中聽到的一些成長勢頭是一致的。我認為這個問題可能更適合麥克或克里斯蒂安。但是，是否有足夠的經驗數據或足夠大的客戶群讓 Snowpark 開始談論這些 Snowpark 客戶（我猜），與非 Snowpark 客戶相比，Snowpark 的採用對消費有何影響？或者，隨著 Snowpark 成為這些客戶工作流程的重要組成部分，我們應該如何考慮隨著時間的推移而建立的使用量？

I think it's still too early to tell. I will say we have 1 customer doing a significant migration, which will increase their consumption on Snowflake to roughly $1.5 million a year. And there are a number of those that we've identified in POCs, but we haven't done the migrations. I see that 1 customer going into production right now, which, by the way, has saved them significantly on their legacy vendor. So clearly, the -- with some customers, it's quite meaningful, the consumption we're starting to see, and we expect that trend will continue into next year.

我認為現在下結論還為時過早。我想說的是，我們有 1 位客戶正在進行重大遷移，這將使他們在 Snowflake 上的消費增加到每年約 150 萬美元。我們已經在 POC 中確定了其中的許多內容，但我們尚未完成遷移。我看到 1 個客戶現在正在投入生產，順便說一下，這大大節省了他們對傳統供應商的依賴。很明顯，對於一些客戶來說，這是非常有意義的，我們開始看到這種消費，我們預計這種趨勢將持續到明年。

Our next question is from Patrick Walravens with JMP.

我們的下一個問題來自 JMP 的 Patrick Walravens。

This is Owen Hobbs on for Pat. Congrats on the strong quarter. So starting off, I guess, how much consumption comes from the different hyperscalers? Is there 1 that kind of -- is it split evenly between the 3 or does kind of have the more -- majority of compute share there?

這是帕特的歐文·霍布斯。恭喜季度表現強勁。因此，我想，首先，有多少消耗來自不同的超大規模企業？是否有 1 種 - 是在 3 種之間平均分配還是有更多 - 大部分計算共享在那裡？

No. AWS by far is our biggest, followed by Azure and then GCP. GCP is up to 3% right now. Microsoft Azure is the fastest-growing one, but AWS is still 76% of our business with Microsoft being 21%. As I said, GCP is 3%. And I will tell you, one of the reasons why GCP is not as big as just so much more expensive for our customers to operate in GCP than it is in AWS and Azure. And as a result, our salespeople are really not inclined to do much in GCP.

不會。到目前為止，AWS 是我們最大的，其次是 Azure，然後是 GCP。 GCP現在高達3%。 Microsoft Azure 是成長最快的，但 AWS 仍占我們業務的 76%，而 Microsoft 佔 21%。正如我所說，GCP 是 3%。我會告訴你，GCP 規模沒有那麼大的原因之一是我們的客戶在 GCP 中營運的成本比在 AWS 和 Azure 中營運的成本高得多。因此，我們的銷售人員實際上不太願意在 GCP 中做太多事情。

And then going bigger picture, maybe this is a question for Christian as well. How is the role of the data scientist you sort of kind of changed as we move through the era of big data, machine learning and now into AI? And I guess where do you see that going in the future?

從更大的角度來看，也許這也是克里斯蒂安的問題。隨著我們進入大數據、機器學習時代以及現在的人工智慧時代，資料科學家的角色發生了什麼樣的變化？我猜你認為未來會發生什麼事？

Yes. We see actually interest on both the traditional data science and ML platform. And we've had a number of announcements at Snowflake Summit for those such use cases, but we obviously see lots of interest on generative AI and large language models where we have also expanded Snowflake's capability to do both hosting via Snowpark Container Services, but more seamless inferencing via the new Snowflake Cortex. So we see strong demand from our broad customer base for both types of use cases.

是的。我們實際上看到了人們對傳統數據科學和機器學習平台的興趣。我們在 Snowflake 高峰會上針對此類用例發布了許多公告，但我們顯然看到了人們對生成式 AI 和大型語言模型的濃厚興趣，我們也擴展了 Snowflake 的能力，透過 Snowpark 容器服務進行託管，但更多透過新的雪花皮層進行無縫推理。因此，我們看到廣泛的客戶群對這兩種類型的用例都有強烈的需求。

Our next question is from the line of Gregg Moskowitz with Mizuho.

我們的下一個問題來自格雷格·莫斯科維茨（Gregg Moskowitz）和瑞穗銀行（Mizuho）。

Frank, since you speak with a lot of large company execs, I'm curious to hear any thoughts you have on IT budgets next year as well as whether there will be incremental budget dollars approved for AI in calendar '24 or if the AI spend will primarily or maybe even entirely come from other areas of IT?

Frank，由於您與許多大公司高管交談過，我很想听聽您對明年 IT 預算的任何想法，以及是否會在 24 日曆年批准用於 AI 的增量預算資金，或者 AI 是否支出主要或甚至完全來自IT 的其他領域？

I don't even hear the words AI and budget in the same sentence. In other words, they're going to make resources available to enable it. But if anything is holding them back is really understanding how to do it. It takes time in tech to mature and evolve deployment architectures where everybody involved is fully confident and comfortable that these are the right ways to do it.

我甚至沒有在同一句話中聽到人工智慧和預算這兩個詞。換句話說，他們將提供可用資源來實現這一目標。但如果有什麼阻礙他們的話，那就是真正了解如何做。技術需要時間來成熟和發展部署架構，每個參與其中的人都完全有信心和放心，這些是正確的方法。

So you see a lot of benchmark and compare and contrast experimentation, testing all these kinds of things. And they're going to go through many, many iterations of that. We will as well. And I think that the field will become very proliferated with large foundational models and many, many, many subsector specialized models that are very, very, very deep, but also are very, very narrow in purpose.

所以你會看到很多基準測試、比較和對比實驗，測試所有這些類型的東西。他們將經歷很多很多的迭代。我們也會的。我認為，隨著大型基礎模型和許多、許多、許多分部門專業模型的出現，該領域將變得非常廣泛，這些模型非常非常深，但目的也非常非常狹窄。

So it is going to become an enormous field. I will tell you that when you talk to the C-suite in large enterprises, people are looking for a reset of economics, like, for example, in contact centers, pricing optimization, supply chain management, I mean, really very, very big impact opportunities. These are not sort of marginal incremental things and that has the attention. Data has always had that promise, but it's really on steroids now under the influence of the newer technologies that we're all excited about.

所以它將成為一個巨大的領域。我會告訴你，當你與大型企業的最高管理層交談時，人們正在尋找經濟學的重置，例如在聯絡中心、定價優化、供應鏈管理中，我的意思是，真的非常非常大影響機會。這些不是邊際增量的事情，而是引起人們的注意。數據一直都有這樣的希望，但現在在我們都興奮的新技術的影響下，它確實變得更加強大。

Very helpful. And then for Mike, really encouraging, of course, to hear that for 3 weeks, consumption grew faster than any other period over the past 2 years. Over which 3 weeks though, did you see that particularly strong consumption? Was that post Labor Day? Or did it span a different time period?

很有幫助。然後，對麥克來說，聽到連續三週的消費成長速度比過去兩年中的任何其他時期都快，這確實令人鼓舞。不過，在哪 3 週內，您是否看到消費特別強勁？那是勞動節後嗎？還是跨越了不同的時段？

Post Labor Day.

勞動節後。

Our last question is from the line of Will Power with Baird.

我們的最後一個問題來自貝爾德的《意志力》系列。

Mike, you referenced that 9 of your top 10 customers, it sounds like grew nicely quarter-over-quarter. I guess I wonder, were there any common use cases or products or common threads kind of driving that? Any other color behind the strength there.

麥克，您提到了您的前 10 位客戶中的 9 位，聽起來季度環比增長良好。我想我想知道，是否有任何常見的用例或產品或常見的線程來驅動它？任何其他顏色背後的力量都有。

No, these are just all very large customers with massive data estates that continue to -- one was doing a big migration, but the others are just continuing to move workloads to Snowflake.

不，這些只是擁有大量資料資產的非常大的客戶，其中一個正在大規模遷移，但其他客戶只是繼續將工作負載轉移到 Snowflake。

Very industry-specific as well.

也非常具有行業特定性。

Okay. And maybe just a quick question on product gross margins. Last couple of quarters, you're kind of already at your longer-term target, I think. It sounds like there may be a couple of headwinds there in Q4, but is this kind of the general level to expect going forward? And maybe any color on kind of the upside surprise, I guess, if you will, given it seems like you've gotten there faster than you might have expected?

好的。也許只是一個關於產品毛利率的簡單問題。我認為，過去幾個季度，您已經達到了長期目標。聽起來第四季可能會遇到一些阻力，但這是否是未來預期的總體水平？我想，如果你願意的話，也許有任何關於上行驚喜的顏色，因為你似乎比你預期的更快到達了那裡？

Yes. I don't really see a lot of upside in our long-term guidance and for a number of reasons. The big headwind that we're seeing this quarter to our margin is with all these new products, that are going into public preview. We have to start to amortize the costs associated with the software development costs that we're required to capitalize under GAAP that are now going to start to be amortized on top of that.

是的。出於多種原因，我並沒有真正看到我們的長期指導有太多好處。本季我們看到的利潤率面臨的巨大阻力來自所有這些即將進入公開預覽的新產品。我們必須開始攤銷與軟體開發成本相關的成本，根據公認會計原則，我們需要將這些成本資本化，而這些成本現在將開始攤提。

In particular, something like Unistore, a lot of times when we introduce new products, many times, we actually have negative contribution margins until it takes us usually up to half a year to 9 months to actually fine-tune the software to get the -- to take costs out of operating those new features. And so we just have so many new products that are coming out this quarter that is going to have a headwind on the margin.

特別是像Unistore這樣的東西，很多時候我們推出新產品時，很多時候，我們的邊際貢獻實際上是負的，直到我們通常需要半年到9個月的時間來實際微調軟體以獲得—— - 降低營運這些新功能的成本。因此，本季我們推出瞭如此多的新產品，這將在利潤率方面遇到阻力。

That concludes the question-and-answer session as well as today's call. Thank you for your participation. You may now disconnect your lines.

問答環節和今天的電話會議到此結束。感謝您的參與。現在您可以斷開線路。