Wikibon conducted in-depth interviews with organizations that had achieved big data success and high rates of returns. These interviews determined an important generality: that big data winners focused on operationalizing and automating their big data projects.
They used inline analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems of record. These algorithms were usually developed and supported by data tables derived using deep data analytics from big data Hadoop systems and/or data warehouses. This white paper describes how, instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
Sponsored by IBM
Individual, Student, and Team memberships available.