An Opinion:

Snowflake’s Data Marketplace: The Key To Unlocking The Potential Of Generative AI

What the company does for customers

Snowflake first emerged as an on-prem enterprise data warehouse, a data management system that stores and manages structured data within a customer’s own data center. The company eventually transformed into a data lake, a centralized repository of raw, unstructured, and semi-structured data in its native format. Unstructured data is information that is challenging to organize for a user to search effortlessly. It is nearly impossible to process and analyze using traditional data analysis tools. Some of unstructured data include the Internet of Things (“IoT”), video, audio, images, social media posts, and email data.

Snowflake later moved to the cloud and became a data lakehouse, a unified platform for storing, processing, and analyzing structured and unstructured data. More recently, the company started calling itself a Data Cloud, defined by Snowflake as “a single platform connecting businesses globally, at practically any scale to bring data and workloads together.”

The company’s strengths

Snowflake didn’t invent the concept of a data warehouse or data lake. Nevertheless, it was among the initial companies to bring the data warehouse concept to the cloud, giving it a first-mover advantage. It established itself as a market leader before Amazon’s (AMZN) Redshift, Alphabet’s (GOOGL) (GOOG) BigQuery, and SAP’s (SAP) Business Warehouse were able to gain serious traction. A key element of its success was enabling companies to exchange data, which later turned into its Data Marketplace. The more customers use its tools and exchange data on the platform, the more expensive it becomes to leave the platform for another solution. Thus, Snowflake has developed a robust switching cost moat and, to a lesser extent, a network effect moat.

High switching costs come from the time, effort, and cost of shifting company data from Snowflake’s platform to another data vendor’s platform. There is also the risk that a company could lose or corrupt data by extracting data from one system and adding that data to another. Last, all the time and expense that an organization uses to train employees on Snowflake’s platform is lost, and the company must spend money to train personnel on a new data system. Often, once a company joins Snowflake, it rarely leaves. You can measure the strength of this switching cost moat through the Net Revenue Retention Rate (“NRR”). A high NRR indicates a company successfully retaining its customers and generating recurring revenue. Snowflake recently reported that its third quarter NRR was at 135%, an excellent number.

Snowflake Third Quarter FY 2024 Presentation

The value of Snowflake’s platform drastically increases as the number of partners and customers increases. The more partners that join the platform, the more expertise and support will be available to customers, making them more likely to adopt and stick with it. On the other side of the network, as more customers use the platform, they create more data, making it more valuable for other customers to join. Customers covet Snowflake’s data-sharing capabilities, as they help them access and analyze data from other customers, providing deeper insights and a competitive advantage.

These competitive advantages prevent larger companies like Amazon from quickly crushing it. Additionally, you can view Snowflake as the Switzerland of Data Platforms, a cloud-agnostic architecture. Customers can host it on the top three cloud providers: AWS, Azure, and Google Cloud. In contrast, some data platforms have tight integration with one specific cloud platform. For instance, Amazon’s platform hosts Redshift. Snowflake’s multi-cloud flexibility appeals to customers who want to avoid vendor lock-in.

A consumption-based business in the age of Generative AI

Snowflake is a consumption-based business, meaning the company generates additional revenue the more customers use the platform’s computing resources, storage, and data transfer services. Since Generative AI vastly increases customers’ computing and data storage needs, demand for Snowflake’s services could go through the roof if the technology continues to proliferate and becomes more than a fad.

Snowflake Second Quarter FY 2023 Investor Presentation

Companies were already gravitating to Snowflake’s data cloud solutions before last year. Still, once OpenAI introduced generative AI to the market in late 2022, Snowflake’s solutions only became more important. Data is one of the most critical resources in generative AI, the “oil” that fuels powerful AI models. Those AI models run best on heavily refined “oil” and can create biases and incorrect answers when run on crude “oil,” which can be extraordinarily damaging to people’s lives. Snowflake is like a refinery that optimizes, cleans, and prepares data for advanced machine learning (“ML”) and AI models, which has become extremely valuable in the emerging age of generative AI.

Snowflake CEO Slootman said during the third quarter earnings call:

“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 results in the data, hence the quality of that underpinning is critical. Meanwhile, Snowflake has announced and showcased the plethora of new technologies that let customers mobilize AI.”

Snowflake 2023 Investor Day

The company has also recently been on the hunt for any company that can improve its ability to extract data or increase its AI capabilities for customers. Snowflake’s most recent acquisitions are Neeva, Streamlit, and Applica. Neeva is a search company that utilizes generative AI and other technologies to give users a more powerful search engine to discover hidden patterns and insights within data. Management plans to integrate this AI-powered search engine into its Data Cloud. Streamlit is a platform that developers can use to build generative AI apps. Applica is a Polish-based AI platform specializing in document understanding.

In a press release, Snowflake said about the company, “With this acquisition, Snowflake’s customers will be able to more easily leverage unstructured data in the Snowflake Data Cloud.” This acquisition should improve Data Cloud users’ ability to extract data from unstructured documents like PDFs, emails, and contracts. Investors should not be surprised if the company makes additional bolt-on acquisitions to increase its ability to support AI applications.

Source: Seeking Alpha and company information