On the way to active analytics for business, we have to answer two big questions: What must happen to data before running machine learning algorithms, and how should machine learning output be used to generate actual business value? Jean-François Puget demonstrates the vital role of human context in answering those questions.
The history of data analytics has been marked by an environment of scarcity. The way we approach data analytics is only just catching up. Tom Grey explains why we are on the cusp of a golden age of analytics and machine learning.