TMT Series #7: Snowflake, a long-term aggressive bet on the future of the data cloud (1/2)
2022 has been one of the toughest years for stocks so far. With the FED raising rates to combat sky high inflation, many investors have steered away from fast-growing technology stocks which sent the prices crashing down.
Snowflake (NYSE:SNOW), was no exception. The share price is now a little less than 70% off its peak. Could this represent the right moment to scoop some Snowflake shares? Let’s find out!
Sections
a. What should you know about Snowflake
b. Products
c. How does Snowflake make money? (no, it’s not a SaaS model)
d. Go-to-market and sales execution
e. Datacloud market overview
f. Competitive landscape
g. How big is Snowflake’s lead on competitors?
h. What are Snowflake’s moats
i. Profitability model looking ahead
j. Impact of SBCs
k. Key investment risks
l. Conclusion: is Snowflake a good long-term buy?
a. What Should You Know About Snowflake?
Founded in 2012, Snowflake (SNOW) is a cloud native data platform provider. Snowflake’s highly scalable, Cloud Data Platform helps customers break down data silos and enhance data governance while leveraging the scalability, elasticity, and performance of the public cloud. Through Snowflake’s platform, customers are able to unify data and create a single source of truth to drive meaningful analytics, enhanced business insights, build data driven applications and share data within and across organizations. Leveraging 22 regional deployments across the three major Cloud Service Providers (CSPs), Snowflake provides customers massive scalability to store and analyze diverse types of data through an easy to use and manage cloud-native platform delivering a consistent user experience across clouds and regions.
Snowflake’s Cloud Data Platform provides a holistic, end-to-end solution delivering faster data transformations, superior data insights, and enhanced data sharing. The platform supports a wide variety of use cases, including Data Engineering, Data Lake, Data Warehouse, Data Science, Data Applications, and Data Exchange (more below) through three independently scalable layers. The centralized storage layer provides support for both structured and semi-structured data and can be scaled independently of compute resources providing enhanced elasticity and scalability. The multi-cluster compute layer allows customers to spin up or down compute clusters in seconds allowing multiple concurrent users to operate queries on a single copy of data with optimized price-performance. The cloud services layer performs a variety of tasks, including query optimization and security operations, ensuring a user-friendly and consistent experience across the platform.
Conversations I had with clients point to ease of use and maintenance, elasticity and scalability, the ability to support global multi-cloud deployments, and the ability to facilitate data sharing as key differentiators of Snowflake’s Cloud Data Platform relative to the competition. Additionally, the platform benefits from network effects as more customers adopt the platform and move large volumes of data to the cloud, more data can be exchanged on the platform, enhancing the value of the platform to all users, in turn attracting more customers and data to the platform.