Big data use cases in the public sector often present unique data challenges, especially within health care related policy. Data from various sources is needed in order to solve important, high impact problems such as the spread of infectious diseases and the creation of new healthcare programs. In order to solve these problems, government organizations need a platform approach that allows them to not only solve the problem at hand using the latest in machine learning, but have an audit trail of what analyses were done to get to an impactful result.
Leidos (formerly Lockheed Martin) utilizes Chorus as a part of its CAADS Platform (Collaborative Advanced Analytics & Data Sharing) to help healthcare agencies analyze their data across a broad variety of use cases. Chorus provides Leidos and its customers with the ability to create complex, repeatable data science workflows without hiring additional specialists. Users are able to build workflows based on their industry expertise, without having to worry about the underlying complexity of various big data technologies.
“As data science drives more and more decision making at Leidos, the Collaborative Advanced Analytics & Data Sharing (CAADS) platform has become a tentpole of the organization. Chorus is a key component of the CAADS analytic stack and it’s very cool to see how it’s changing workflows and driving decision making in their organization.”