Perhaps the biggest development in information technology in the 21st century has been the rise of big data. But our capacity for tracking and storing information has thus far generally outpaced our ability to effectively analyze and make use of it. We tend to think that more data is better, but when we’re tasked with answering a simple question—for example, what kind of product is most often purchased on what day of the week—the answer can be obscured rather than clarified by an excess of information concerning the variables of the time of day of purchase, the temperature, the weather conditions, the larger economic parameters, and so forth. Moreover, the human labor required to create the algorithms and systems architecture capable of crunching such vast sets of data has usually proved time-consuming and costly.