99% of analysis carried out by analysts involves a cross tab - analyzing one piece of data through the lens of another.
The cross tab is the de facto standard tool and while it has limitations from an analytical perspective, the cross tab is produces human readable outputs. The challenge lies in the fact that the cross tab produces linear results but not definitive results. They tell a story but often not a satisfactory one. For instance, if we look at how people voted in the 2016 Presidential Election in the USA using this data we can see a weak story appear. While many commentators wanted to label Trump supporters as white, poor and uneducated, these labels are only partially true. They are not definitive. Were we to use just these simple descriptors to predict who voted for Trump (or Clinton) and provide a definitive story then the story would be much more convoluted to relay, since it would rely on non-linear transformation of these descriptors.
The challenge for analytics is to find the right blend of Linear Analytics and Non-Linear Analytics that combines predictive power and retains human-readability.
