(T) I found an interesting segmentation of the various types of analytics from an IBM’s article promoting its IBM Power Systems:

• “Descriptive analytics: This type determines what is happening based on existing data

• Diagnostic analytics: This type goes one step further to determine why a specific situation happened

• Predictive analytics: This type looks across a broader set of data perhaps over a longer period of time to see trends and examples and then uses that historical information to predict future occurrences

• Prescriptive analytics: This type goes beyond prediction to provide suggestions on how to best change future situations to meet your goals”

Out of those four classifications, most present applications of automated analytics using machine learning apply to predictive analytics. In most cases, descriptive, diagnostic and prescriptive analytics use a combination of human analyses and computer-generated analyses.

However, the scope of predictive analytics applications is moving very rapidly and considered even in new industries that have not a strong technology focus such as:

• The publishing industry: “Yes, Machine Learning Can Help Predict a Bestseller”

• The legal industry: “AI predicts outcome of human rights cases”

• Or the restaurant industry: “Predictive Analytics adopted by restaurant executives worldwide”

Note: The picture above is an untitled painting from Amy Sillman displayed at Stanford’s Cantor Arts Center Museum.

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