Ray Dalio’s Top 10 Growth Stock Picks with 30+% Revenue Growth

6. Snowflake Inc. (NYSE:SNOW)

Number of Hedge Fund Investors  in Q1 2024: 73

1 Yr Revenue Growth: 40%

Bridgewater Associates’ Q1 2024 Stake: $17.9 million

Snowflake Inc. (NYSE:SNOW) is a cloud computing company that enables businesses to consolidate their data under a single roof to generate insights and run analysis. The data warehousing industry is one of the hottest in America right now, especially due to the proliferation of enterprise computing and particularly due to AI’s reliance on large amounts of data for model training. On this front, Snowflake Inc. (NYSE:SNOW) is one of the top companies in its industry, with estimates showing that it commands a 22% share of the data warehousing market. As software as a service (SaaS) stock, the keys to Snowflake Inc. (NYSE:SNOW)’s hypothesis are its revenue growth, its recurring revenue, and its margins. It has to perform on all three fronts to maintain the current valuation, which has seen analysts value Snowflake Inc. (NYSE:SNOW) at a whopping 238 times its forward earnings. This valuation also makes the stock quite vulnerable to any revenue slowdown, which is typically the case for SaaS stocks in an economy constrained by high interest rates and inflation.

To counter a potential slowdown, Snowflake Inc. (NYSE:SNOW) has to ensure it brings more customers to its platform no matter how the economy is doing. Here’s what management had to say on this front during the Q1 2025 earnings call:

“I’ve had conversations with over 100 customers for the past several months, and I’m very optimistic. Snowflake is a beloved platform, and the value we bring comes through in every customer conversation I have.

We are critical in helping our customers run their businesses. For example, one of the largest US telcos relies on us to help them close their books every month. We also help a global financial service customer from their counterparty credit risk process. The art of the possible on Snowflake is really incredible. It’s also probably no surprise that AI is top of mind for our customers as well. They want to make all business data in Snowflake available to everyone, not just the business analyst. They want us to help drive clarity, value creation, and reliability as they enter this new frontier. Over the last quarter, my time spent with our go-to-market teams has been focused on driving execution and alignment. Internally, we emphasize consumption and new customer acquisition.

And we’re developing an end-to-end cadence for both priorities. This includes developing sales motions in specific workloads, such as AI and data engineering. We have more to gain as we standardize our consumption mindset and effectively execute. We expect that this efficiency will contribute to further revenue growth. Those of you who know me know that I have a relentless focus on product innovation and delivery. Teams across the company are building and delivering at an incredible pace. Earlier this month, we announced that Cortex, our AI layer, is generally available. Iceberg, Snowpark Container Services, and Hybrid Tables will all be generally available later this year. We’re investing in AI and machine learning, and our pace of progress in a short amount of time has been fantastic.

What is resonating most with our customers is that we are bringing differentiation to the market. Snowflake delivers enterprise AI that is easy, efficient, and trusted. We’ve seen an impressive ramp in Cortex AI customer adoption since going generally available. As of last week, over 750 customers are using these capabilities. Cortex can increase productivity by reducing time consuming tasks. For example, Sigma Computing uses Cortex language models to summarize and categorize customer communications from their CRM. In the quarter, we also announced Arctic, our own language model. Arctic outperformed leading open models such as LLaMA-2-70B and Mixtral 8x7B in various benchmarks. We developed Arctic in less than three months at one-eighth the training cost of peer models.”