Snowflake Exploring AI For Data Warehousing Capabilities

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According to a recent report, the Global market for Cloud Data Warehouse is forecast to grow at 16% CAGR to reach $3.5 billion by 2025. San Mateo-based Snowflake (NYSE: SNOW) is a leading player in the market that is focusing on expanding its AI capabilities within the data warehouse space.

Snowflake’s Financials

Snowflake’s fourth quarter revenues grew 117% to $190.5 million. Product revenues grew 116% to $178.3 million. Remaining performance obligations grew 213% to $1.3 billion. Net revenue retention rate was 168%. For the quarter, Snowflake had 77 customers with a trailing twelve-month revenue of more than $1 million.

GAAP net loss of $198.9 million grew significantly compared to GAAP net loss of $83.3 million a year ago. Non-GAAP net loss per share was $0.70, compared to non-GAAP net loss per share of $1.67 a year ago.

For the full year, revenues grew from $264.7 million a year ago to $592 million. It ended the year with a net loss of $3.81 per share compared with a net loss of $7.77 per share a year ago.

For the first quarter of fiscal 2022, the company expects product revenues of $195-$200 million and product revenues of $1-$1.02 billion for the year.

Snowflake’s Product Enhancements

During the quarter, Snowflake announced a partnership with healthcare data integration and interoperability platform Abacus Insights to provide the healthcare industry with seamless access to data insights at scale. The partnership addresses the healthcare industry’s need for liberating valuable, siloed data as well as unlocking meaningful insights that are able to provide personalized care and improve health outcomes.

Abacus Insights will use Snowflake Data Cloud as the central hub for its data ecosystem, allowing health plan customers with the ability to access, analyze, and visualize their data on Snowflake’s platform. The integrated solution will allow healthcare organizations to achieve interoperability and unlock insights about their businesses and plan members as well as enable rapid access to high quality data.

Recently, Snowflake announced that it had invested an undisclosed amount in another data science platform provider Dataiku. Dataiku is already a strategic partner for Snowflake and the companies had earlier rolled out a joint offering that allows Dataiku customers to perform machine learning tasks in the Snowflake environment. Dataiku has been working to bring AI and machine learning into the enterprise computing world by developing software that manages and automates various aspects of the data science process.

Snowflake, like other cloud data warehouses, focuses on configuring and running a scale-out analytical database allowing customers to focus on their SQL queries. Snowflake offers data prep and engineering capabilities needed by data science teams but does not deliver advanced tools needed by the data analysts. The investment and the partnership will help Snowflake expand within the data science arena. Besides Dataiku, Snowflake also has tie-ups with DataRobot, H2O.ai, and Amazon SageMaker to accelerate machine learning and data analysis for its customers.

Snowflake’s data tools are witnessing a strong adoption rate. Earlier this year, the company announced that it saw more than 300% increase in the total number of data providers on its Data Marketplace since April 2020. Organizations are leveraging the Data Cloud to unlock insights faster with seamless access to data from open and commercial third-party data providers and SaaS vendors. Its data users have access to over 350 datasets from more than 120 data providers like Heap Analytics, Knoema, FactSet, Safegraph, and WeatherSource across 16 key categories.

Its stock is currently trading at $235.64 with a market capitalization of $68 billion. It hit a 52-week high of $429 in November last year and a 52-week low of $205.07 in March this year.

Disclosure: All investors should make their own assessments based on their own research, informed interpretations, and risk appetite. This article expresses my own opinions based on my own research of product-market fit, channel execution, and other factors. My primary interest is in product strategy. While this may have bearing on stock movements, my writings tend to focus on long-term implications. The information presented is illustrative and educational, but should not be regarded as a complete analysis nor recommendation to buy or sell the securities mentioned herein. I am not a registered investment adviser and I am not receiving compensation for this article.

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