How data-centric laboratory information systems create new value, using your laboratory’s own data
Today, enterprises want to capitalise on complex, data-intensive AI/ML and advanced analytics workloads that involve petabytes of data. To accomplish that, they are reprioritising data as an organizational asset and reestablishing their enterprise information architecture around data models that are designed to generate reliable, structured data.
This relatively recent paradigm shift of positioning data at the center of enterprise architectures is known as data-centric computing1 Let’s look at how laboratories are taking this kind of data-centric computing approach, using their clinical laboratory information system (LIS) or analytical laboratory information management system (LIMS) to better manage and derive value from data as assets.
1 Agerwala,T. Data Centric Systems: The Next Paradigm in Computing. IBM Research. (2014). https://hosting.cs.vt.edu/icpp-conf/2014/agerwala.html
