The bigger the data, the more profitable and productive predictive analytics can be. But that’s conventional wisdom. Innovators more intent on inventing the future than predicting it should look hard at how cutting-edge scientists now computationally massage their big data.
As The Economist recently observed: “More than 90 groups of scientists are now developing hypothesis-generation software. They hope to use it not on recipe books but on the vast corpus of scientific literature (by one tally at least 50m scientific papers) that has piled up in public databases.” In other words, data-driven scientists worldwide recognize that petabytes and exabytes can make computation as creative and imaginative as imagination for hypothesis generation. They’re investing accordingly.
Author: Michael Schrage