If you've perused a technology news site or two recently, it's hard to miss the big deal people are making about Big Data. The possibilities for innovation in work and play presented by data analytics continue to grow more awe-inspiring by the day. For example, Big Data can actually draw and paint artwork, as the RealBrush program from Princeton University recently showed.
Michael Rappa, founder and executive director of North Carolina State University's Institute for Advanced Analytics, traces today's fascination with data analytics back through a series of innovations that began in the 1940s and 1950s. "There's a lot of excitement around it right now, but it's part of a longer evolution," he says.
- 1940s and 1950s — People begin using electronic computing to make high-speed calculations.
- 1960s and 1970s — Programs and data computations can be stored, not just on tapes but in solid-state forms. Data can be warehoused more cheaply.
- 1960s through 1980s — Increasing amounts of data are generated and stored by corporations and government.
- 1990s — The Internet ties globally distributed data repositories together, allowing data to flow, while generating reams of new data.
- Early 2000s — Internet-based businesses leverage the tight feedback loops made possible by large amounts of data to improve services for users.
- 2007 — NC State establishes the Institute for Advanced Analytics, offering America's first Master of Science in Analytics degree.
- 2011 — McKinsey Global Institute releases a report on Big Data, predicting a major shortfall of people with analytics skills in the U.S. by 2018.
- 2012 — Harvard Business Review calls data scientist "the sexiest job of the 21st century."
- 2013 — The democratization of data begins. With smartphones, tablets and Wi-Fi, data is generated by everyone at prodigious rates. More individuals access large volumes of public data and put data to creative use.
For more on Big Data's impact on higher education, check out EdTech's "Big Data 101" feature.