The amount of data we are creating as society has exploded over the last decade. Consider this fact: Each day, we create more than 70 times the amount of information in the Library of Congress. Or this one: Approximately 2.5 billion Internet users generate 2.5 quintillion (2,500,000,000,000,000,000) bytes of data every day. Why are we producing so much data? Because we can.

Bandwidth, computer memory, and computer-processing capabilities have improved exponentially over the last decade. By 2016, it is estimated that the gigabyte equivalent of all movies ever made will cross global IP networks every 3 minutes. The average smartphone now has more computing power than NASA did when Neil Armstrong landed on the moon. At the same time, each one of us is a walking content generator. Our use of the Internet, social media, and mobile devices is creating a tsunami of electronic data. And, as mobile devices get smaller, faster, and more powerful, they will enable us to generate even more bytes of “likes” every year.

While the mere existence of so much data is interesting on a phenomenological level, it is not, in economic terms, worth much. The key development of big data analytics is our growing ability to turn this data into valuable information. In order to understand these analytics, it is helpful to have a little background in the history of data management and analysis.