Predictive Analytics in Action

A handful of the world’s companies have cracked the code on embedding analytics into every layer of their organizations.

Data science is a rapidly evolving discipline that leverages an ever-widening array of tools and capabilities to learn and exploit. Because of such inherent complexities surrounding adoption, integration and support, the work of the data scientist can be daunting. That complexity is one of the reasons IBM several years ago set out to bring clarity and uniformity to the otherwise disparate data discovery and analytics process. The goal: create a solution that leveraged the best capabilities available, in an integrated, collaborative platform that was easy to access and use. With it, everyone from data scientists to business analysts would be able to not only tackle the discipline, but conquer it. Along the way, we learned a lot about the role of data scientists; their challenges, their tools of choice, and how they valued certain processes and functionalities over others. But, first a little background. Up until the time IBM rolled out the popular Data Science Experience, if someone…