Snowflake beats quarterly estimates on strong demand for data management services


The company logo for Snowflake Inc. is displayed on a banner to celebrate the companys IPO at the New York Stock Exchange NYSE in New York U.S. September 16 2020. REUTERSBrendan McDermidfile photo

The company logo for Snowflake Inc. is displayed on a banner to celebrate the company's IPO at the New York Stock Exchange (NYSE) in New York, U.S., September 16, 2020. REUTERS/Brendan McDermid/file photo

(Reuters) - Cloud data analytics company Snowflake beat second-quarter revenue and profit estimates on Wednesday, boosted by rising data management and storage needs of businesses amid a surge in the use of generative artificial intelligence.

Shares of the company rose more than 3% in trading after the bell.

Enterprises are increasingly moving their data and infrastructure to the cloud to improve efficiency, helping cloud-related services companies.

Snowflake offers products and services that clients can use to store, process and consolidate data that helps in producing business insights.

The Bozeman, Montana-based company's revenue rose about 36% to $674 million for the quarter ended July 31, above analysts' average estimate of $662.2 million, according to Refinitiv data.

Excluding items, the second-quarter adjusted profit per share was 22 cents, compared with analysts' average estimate of 10 cents.

Snowflake's second-quarter product revenue rose 37% to $640.2 million, above market estimates of $623 million.

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Snowflake is well-positioned to enable the growing interest in artificial intelligence or machine learning, CEO Frank Slootman said, adding that enterprises "cannot have an AI strategy without a data strategy".

The company forecast third-quarter product revenue in the range of $670 million to $675 million, compared with analysts' average estimate of $670.8 million, according to Refinitiv data.

Snowflake had announced a partnership in June with chip company Nvidia to allow customers ranging from financial institutions to healthcare and retail to build AI models using their own data.

(Reporting by Jaspreet Singh in Bengaluru; Editing by Krishna Chandra Eluri)

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