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FactSet Data Now Available in the DealCloud Platform Through DataCortex

The integration of FactSet’s financial data into DealCloud’s DataCortex product will allow capital markets clients to make more confident, data-driven investing decisions

DealCloud, the premier provider of deal, relationship, and firm management technology solutions, announced that it has integrated leading financial market data from FactSet into its DataCortex product.

“In order to be competitive in today’s modern deal-making landscape, capital markets professionals are orienting their key decision-making activity around a combination of both proprietary and third-party data,” says Ben Harrison, Chief Revenue Officer and Co-Founder of DealCloud. “We have developed this integration in response to our clients’ growing reliance on FactSet’s market-leading data, and we’re excited about the increased utility our private equity, investment banking, asset management, and other clients will realize from the platform as a result.”

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By integrating FactSet’s data into DealCloud DataCortex, capital markets professionals will be able to search and query FactSet’s data in real-time without ever leaving the DealCloud platform. The integration supports the modern dealmaker’s need to act quickly and confidently by allowing them to verify the accuracy of their own proprietary data by comparing it to FactSet’s information, all in one centralized place.

The integration reduces the administrative burden associated with data entry by enabling firms to automatically populate certain fields, reports, and dashboards with FactSet data.

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Thanks to the FactSet data integration, firms will gain access to data on public and private operating companies, fund managers, endowments, non-profits, and governments, as well as the firmographic, financial, and management and board details of each. As investment management, banking, and lending organizations look to scale their reach and operational efficiency, they can benefit from this data integration to supplement their proprietary data and to fuel their data analysis efforts.

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