Join the data renaissance in healthcare and life sciences

How HLS organizations are revolutionizing patient care and operations


Globally, commerce is at the dawn of a data renaissance, and Healthcare and Life Sciences (HLS) organizations aren’t sitting by on idle hands. HLS organizations are investing in technology across the patient care journey and, most importantly, extracting insights from the growing volume of health data. 

Data silos and data regulations have traditionally been unmovable blockers in creating scalable high-value use of all the data.  Researchers can’t always access data on hospital outcomes due to privacy restrictions imposed by laws and policies regulating medical information release. Data fragmentation and the lack of uniform digitization impede efficiency, with significant amounts of data overlooked because it’s stuck in silos. The siloes also create issues with inconsistent information across the organization, an inability to grow or scale processes, and redundancies between departments. 

In this ebook, we explore how leading HLS organizations, including Sophia Genetics, EMIS Health, Assurance, Novant Health, Bamboo Health, Genus, and many more are unleashing their data to improve patient care and operations by:

  • Taking the fastest path from data to decisions with out-of-the-box data discovery, cataloging, access management, and data sharing, allowing data teams to focus on delivering critical insights for the business and care providers —not managing analytics infrastructure.  
  • Building future-proof data architectures with a single point of access for distributed data to access disparate and new data sources as needs change, ensuring productivity and creativity are never limited by what a data analytics platform can access.
  • Operating efficiently and reliably at internet scale to gain complete control over how data is stored, managed, and consumed, empowering HLS organizations to optimize their analytics environment for the perfect balance of performance and cost as they grow.
  • Gaining optionality with interoperability with nearly any data environment so HLS organizations can use the architecture that meets their specific business needs and change it when new needs emerge. 

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