We can live with many of the uncertainties of big data for now, with the hope that its benefits will outweigh its harms, but we shouldn't blind ourselves to the possible irreversibility of changes—whether good or bad—to society.

It's no secret that both private enterprise and government seek greater insights into people's behaviors and sentiments. Organizations use various analytical techniques—from crowdsourcing to genetic algorithms to neural networks to sentiment analysis—to study both structured and unstructured forms of data that can aid product and process discovery, productivity, and policy-making. This data is collected from numerous sources including sensor networks, government data holdings, company market lead databases, and public profiles on social networking sites. Although data mining in one form or another has occurred since people started to maintain records in the modern era, so-called big data brings together not only large amounts of data but also various data types that previously never would have been considered together. These data streams require ever-increasing processing speeds, yet must be stored economically and fed back into business-process life cycles in a timely manner.