In math, multiplying two negative numbers together yields a positive number. In the world of data, multiplying a huge number of negative data points, worthless in isolation, can yield highly positive insights, according to new research published by Flemish researchers in the Big Data journal.
As the authors conclude, “when predictive models are built from sparse, fine-grained data—such as data on low-level human behavior—we continue to see marginal increases in predictive performance even to very large scale.”
The trick is figuring out the right questions to ask and finding the right people to interpret the data. This turns out to be a big hurdle.