Refinitiv's Quantitative Data Now Available on Snowflake's Financial Services Data Cloud

Refinitiv, an LSEG business, yesterday announced an agreement that allows for its comprehensive suite of quantitative data to now be made available on Snowflake's Financial Services Data Cloud.

Today's financial services industry is challenged with quickly adapting to a digital economy built on efficiency and cost-savings solutions that meet the growing needs of its customer base. Asset managers and hedge funds can now access Refinitiv quant data alongside existing Snowflake vendor and proprietary data on Snowflake's Data Cloud, which is configurable to run across numerous AWS and Azure cloud regions.

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Making Refinitiv quant data available via Snowflake means that quant researchers are freed from the burden of managing data infrastructure and can spend more time developing and testing investment strategies, optimizing portfolios, managing risk, and accessing and onboarding new datasets. This is accomplished while leveraging Snowflake data sharing capabilities to drive collaboration between teams, partners and customers, who now have quicker on-boarding, faster delivery of updates, the removal of cost associated with servers and database maintenance, and a scalable solution to meet their performance requirements. The platform integrates and delivers a wide range of global market and referential data in one standardized database with a unified symbology – all with the flexibility and security of a single cloud platform. 

Matt Glickman, Financial Services Industry Principal for Snowflake, said: "The Snowflake Data Cloud enables financial services customers to seamlessly discover, access and collaborate with data without the traditional data movement challenges resulting in faster insights and decision making. We are extremely pleased to be partnering with Refinitiv to improve the workflows of quantitative researchers who now have the flexibility to integrate, join and query across their own portfolio data, Refinitiv's financial forecast, fundamental and market data, topical ESG content as well as new alternative datasets."