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NTT Data, Oracle Collaborate to Bring Healthcare Big Data to the Cloud

by HITC Staff 02/20/2017 Leave a Comment

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7 Essential Steps for Safely Moving Patient Data to the Cloud

NTT DATA, Inc. announced the expansion of its existing relationship with Oracle to include end-to-end cloud capabilities for Oracle’s Healthcare Foundation, a unified healthcare analytics platform. The platform provides data integration and warehousing of clinical, financial, administrative and -omics modules in a cloud solution to customers worldwide. The healthcare cloud offering will provide organizations the ability to easily unify, grow or replace their existing healthcare data warehouse and data aggregation solutions. 

 

NTT DATA and Oracle will provide a comprehensive, end-to-end offering that includes consulting and implementation, as well as maintenance and IT services. The solution provides healthcare organizations with the flexibility to replace aging systems with an enterprise data warehouse or to maintain their existing investments with an on-site solution, which will be transferred to an enterprise data warehouse.

Combined with Oracle Healthcare Foundation, NTT DATA’s comprehensive portfolio of analytic capabilities for population health, regulatory requirements, quality measure and clinical research will enable organizations to enhance business agility.

 

“With the evolution of population health, precision medicine and value-based care, healthcare organizations are being driven to find new ways of aggregating and managing structured and unstructured data from a variety of systems. The expanded relationship between NTT DATA and Oracle Health Sciences will provide healthcare businesses with a data integration, warehousing and analytics solution, now available in the cloud,” said Steve Rosenberg, general manager, Oracle Health Sciences.

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Tagged With: big data, clinical research, cloud, Data Integration, Enterprise Data Warehouse, healthcare analytics, healthcare big data, healthcare cloud, Healthcare Data, HIMSS17, Oracle, Population Health, Precision Medicine, unstructured data, Value-Based Care

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