Snowflake: The AI Opportunity

 

 

 

Artificial Intelligence has become the next big thing in the market. The launch of ChatGPT late last year was a watershed moment for AI as it made this technology a household name. Silicon Valley companies have been in a race ever since to highlight how they are planning to use AI or develop AI-related products/services to benefit from the growing adoption of the technology. While the market has rewarded big tech companies with customer-facing AI ambitions such as Microsoft Corporation (MSFT) and Meta Platforms, Inc. (META) – two stocks that I own – I feel Mr. Market has not been kind to the technological enablers of AI.

Snowflake Inc. (NYSE:SNOW) is a cloud-based data platform that enables users to store, analyze, and share large amounts of structured and unstructured data. Snowflake offers a scalable, secure, and flexible solution that can handle diverse data sources and workloads. One of the emerging trends in the data industry is the adoption of Artificial Intelligence and machine learning to enhance data-driven decision-making and innovation. AI and ML can help organizations extract valuable insights from their data, automate tasks, optimize processes, and create new products and services. Snowflake recently announced a flurry of advancements related to AI to leverage its strengths to capitalize on the AI wave.

The company already provides a robust and reliable data infrastructure for AI applications. Snowflake's architecture allows users to separate storage and compute resources, enabling them to scale up or down as needed. Snowflake also supports various data formats and integrations, making it easy to ingest and process data from different sources. Its security features ensure that data is protected and compliant with regulations. These capabilities can help Snowflake attract and retain customers who need a high-performance and cost-effective data platform for their AI projects.

In this analysis, I will focus on Snowflake's business – not valuation.

Snowflake Benefiting From The Evolving Telecommunications Sector

Snowflake is likely to reap the benefits of the deployment of AI in the telecommunications sector. In 2022, Snowflake announced a partnership with H2O.ai, a privately held AI cloud company, to bring automated machine learning to its Telecom Data Cloud. This collaboration aims to help telecommunications service providers accelerate digital transformation, enable superior customer experiences, and maximize operational efficiency.

Exhibit 1: Overview of Snowflake's and H2O's capabilities

 

H2O.ai presentation

 

By incorporating AI-based solutions into its Telecom Data Cloud, Snowflake can provide telecommunication service providers with near real-time data access, enriched with machine learning models, and the ability to share and analyze data to drive better decisions. This will assist telecommunication service providers in breaking down data silos within companies and across the ecosystem, allowing them to optimize their operations and stay ahead of the competition.

The incorporation of AI-based solutions also assists Snowflake's customers in minimizing customer churn and maximizing profitability through the use of machine learning predictions. Snowflake's partnership with H2O.ai is an example of how two leading companies can combine their expertise to address the needs of the industry. By leveraging the power of machine learning and big data analytics, Snowflake can provide its customers with the tools they need to succeed in the rapidly growing telecommunications sector.

The demand for AI-based solutions in the telecommunications sector is rapidly increasing since AI enables telecommunication businesses to quickly identify problems, making it easier to maintain their networks. The continued growth of IoT is also accelerating the incorporation of AI into this industry. The global AI in Telecommunications market segment is expected to reach $10 billion by 2028, growing at a compounded annual growth rate of 37.4%.

The deployment of AI-based solutions within the telecommunications sector will continue to be a driving force for growth and innovation. Snowflake's Telecom Data Cloud and partnership with H2O.ai will enable the company to remain at the forefront of this industry, providing its customers with the data they need to make better decisions and optimize their operations.

Strategic Partnerships to Offer 360-Degree Solutions

Snowflake's commitment to partnering with other AI providers and platforms continues to expand its market reach and create synergies. The company has already established partnerships with leading cloud providers such as AWS, Azure, and Google Cloud, which offer their own AI and ML services and tools. By collaborating with other AI vendors and startups, Snowflake can leverage its specialized expertise and resources to provide more comprehensive and customized solutions to its customers across a wide range of domains and use cases, such as healthcare, finance, retail, and marketing.

To further enhance its AI capabilities, Snowflake has also been making strategic acquisitions. The January acquisition of Myst AI, a time series forecasting platform provider, has given Snowflake's machine learning capabilities an instant boost, strengthening the company's strategy to integrate machine learning features into its data cloud.

Virtualitics, Inc., an artificial intelligence and data exploration company, recently launched its AI Platform on the Snowflake Data Cloud. This integration allows data analysts to use out-of-the-box AI to uncover hidden connections in their data and explore insights in immersive, rich 3D visuals, all while accessing data directly from Snowflake's single, integrated platform.

Snowflake continues to expand its in-house capabilities with the acquisition of automation tools as well. In January, the company announced a definitive agreement to acquire SnowConvert from Mobilize.net. SnowConvert offers a suite of tools designed to efficiently migrate databases to Snowflake's Data Cloud and has become a preferred solution for migrating customer workloads to Snowflake. With over 1.5 billion lines of code already converted using SnowConvert, the toolkit has been proven to significantly reduce migration effort and improve the speed of migrating legacy databases to Snowflake. One of the main challenges with platform migrations is the code conversion required to ensure that all legacy database functionality can be moved to the cloud with minimal time and effort. SnowConvert uses sophisticated automation techniques that reduce the need for manual coding and help ensure successful migration projects. The toolkit also has built-in analysis capabilities at a data-type and procedure level, as well as matching to Snowflake native types, making it easier to transfer code to Snowflake's Snowpark developer environment.

The acquisition of SnowConvert is expected to further enhance Snowflake's capabilities in data migration, enabling its customers to easily and efficiently migrate their data to Snowflake's Data Cloud. In Q4, Snowpark for Python reached general availability status, with early traction showing promising results – 20% of customers have already tried Snowpark, which is initially focused on the adoption and migration of Spark workloads for data engineering and machine learning.

Snowpark allows for a cheaper and faster running of Spark jobs on Snowflake, with added benefits of superior governance and operational simplicity. Benchmark results have shown superior comparative results, with customers seeing significant cost savings and improved performance. For instance, a financial services customer was able to run workloads 8x faster at 30% of the cost after migrating from Spark to Snowpark.

Additionally, Snowflake has entered private preview status with Streamlit in Snowflake. Streamlit is a popular application development framework for the Python developer community, especially for those focused on machine learning applications.

These partnerships and acquisitions showcase Snowflake's commitment to providing its customers with innovative and cutting-edge AI solutions. By expanding its AI capabilities through collaboration with other providers, Snowflake is able to offer a more complete suite of services that help its customers unlock the full potential of their data.

Snowflake already caters to customers from many different business sectors and with these recent partnerships, the company is well-positioned to expand its scope further.

Exhibit 2: Snowflake's major customers based on industry

 

Earnings presentation

 

Generative AI to Further Accelerate Snowflake's Growth

The growing prevalence of generative AI and large language models is creating new opportunities for Snowflake to grow. Generative AI and large language models rely heavily on data to function effectively. These technologies can analyze and learn from vast amounts of data to generate new insights, ideas, and even entire pieces of content. Snowflake's cloud-based data warehousing platform is designed to handle enormous amounts of data and enable users to store, manage, and analyze it with ease. From a technical standpoint, AI models need to be fed raw, unstructured data, which are usually stored in data lakes. The demand for data lakes is likely to grow in multiples in the next few years, and as one of the leading data lake solutions providers in the world, Snowflake will benefit from this growth.

As AI technologies continue to evolve, the ability to analyze and draw insights from complex data sets is becoming increasingly important. Snowflake's platform is built to integrate with various AI and machine learning tools, providing a robust foundation for the development of advanced analytical solutions. Furthermore, Snowflake's cloud-based architecture makes it an ideal platform for the development of large language models, which require massive computing power to train and run. With Snowflake's scalable infrastructure, developers can easily build and deploy these models, enabling organizations to derive even more value from their data.

According to Precedence Research, the global generative AI market is projected to grow at a compounded annual growth rate of 27% through 2032, reaching a market value of around $118 billion.

Exhibit 3: Generative AI market size

 

Precedence Research

 

The U.S. generative AI market alone was valued at $2.7 billion in 2022. The exponential growth of the adoption of generative AI presents a significant opportunity for Snowflake to leverage its data capabilities and drive growth.

Takeaway

 

As the world continues to generate and accumulate massive amounts of data while investing billions of dollars to embrace AI, Snowflake, a cloud-based data platform, is well-positioned to grow. The company has the right characteristics to emerge as a leading AI infrastructure solutions provider thanks to its scalable infrastructure and compatibility with various AI and machine learning tools. By combining Snowflake's extensive data resources with other data sources, customers can unlock new insights and gain a deeper understanding of their data, which will not be a luxury but a necessity in the coming years. Considering all of the above, I have no doubt about Snowflake's ability to continue to grow. The next important consideration is Snowflake's current valuation, which I am planning to discuss in a separate analysis.