Episode 2: How Data is Empowering Life Sciences and Healthcare

Technology is changing how healthcare and life sciences organizations operate.  With more information and analytics to find the “meaning” from the data resource, these organizations are making breakthroughs in therapies, discoveries, and patient outcomes.  This blog details the key points from a recent podcast with Richard Kramer, Chief Strategist Healthcare and Life Sciences at Informatica.  The podcast detailed best practices and strategies for building a data layer in these vertical industries.

First and foremost, organizations are making substantial investments in managing data as an asset. Executives are focused on ensuring that the business has trustworthy fit-for-purpose data, and employees can make it useful. In addition, master data management and governance are necessary to reduce data friction. The idea of master data governance is all about getting accurate and useful data in place so that it can be used across the enterprise.

Some examples provide excellent illustrations of these goals.  Anthem is investing in an enterprise data catalog. They understand it is very difficult to manage data as an asset if they don’t know where it is, where it’s going, or what happens in between. Transparency and trust are mandatory.   Eli Lilly is investing in a data marketplace, a central place for data assets to be discoverable and consumable across a large, complex enterprise.

The benefits of these initiatives are substantial. The goal is to use data to break down silos.  Data becomes the common “language” in a global company, and it has tremendous value by providing consistency and coordination across the business.  Data is also essential to smoothing the processes between different entities, like providers and insurance carriers. With trustworthy, fit-for-purpose data, federated business processes work more effectively.  The data platform is an essential resource for every healthcare and life sciences organization. It will provide the foundation for modern operations that run on facts, not guesswork.

Data Engineering