Healthcare

CASE STUDY

Major American Healthcare Firm Enriches their Data Quality Deploying The Modern Data Company’s DataOS

Leveraging DataOS enabled Modern Data’s healthcare client to keep up with major challenges like changing compliance regulations and advanced treatment options that combined to create a large influx of data that had to be appropriately accessed, stored, and managed.

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CASE STUDY

Billion-dollar Pharmaceutical Giant Accomplishes Faster Data Insights using The Modern Data Company’s DataOS

Discover how, within six weeks, Modern Data helped one of the largest multinational pharmaceutical organizations in the world integrate data from multiple data sources, automate data quality and audit trails, and enable researchers to efficiently find and analyze drug development data.

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How Data Fabrics Breathe Life into Healthcare
INFOGRAPHIC

How Data Fabrics Breathe Life into Healthcare

Healthcare organizations face the constant challenge of improving operational efficiency and maintaining the highest standards of patient care. From aging and growing populations to the expanding prevalence of chronic diseases and rapid, but costly, innovations in tools and tech—these are just a few of the developments that are increasing care demand and cost.

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The multitude of incredible advances in healthcare and life sciences has delivered astonishing improvements across a wide range of applications. However these advances also create enormous amounts of structured and unstructured data. While this can be a nightmare for scientists, IT professionals, and business stakeholders, it also presents the opportunity to uncover cures and improvements to quality of life and care for decades to come.

Healthcare and life science organizations are often at the forefront when it comes to using data strategically to achieve critical goals. However, even these organizations cannot fully realize the value of all of their data given its expansion beyond the limits of current IT systems. Artificial intelligence, or more specifically deep learning algorithms when it comes to healthcare and life sciences, can mine and leverage this data but users often simply can't access data tied to them due largely to data management complexity.

This, among a number of equally big challenges, are why healthcare and life sciences organizations are actively looking for new ways to enable their teams to access and use digital data.

See how a data fabric have become essential for these organizations.

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