Snowflake Inc.

Good afternoon. Thank you for attending today's Q2 FY23 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 1 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 the Q2 fiscal 2023 earnings call. With me in Bozeman, Montana, are Frank Slootman, our Chairman and Chief Executive Officer, Mike Scarpelli, our Chief Financial Officer, and Christian Kleinemann, 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-definition, 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-on-year to $466 million. Maining performance obligations grew 78% year-on-year. to $2.7 billion, and 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 growth 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. 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 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 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 the 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 Summit Users Conference 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 data set to save 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 plant. 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. And with that, I will turn the call over to Mike.