From SABR member Dick Cramer at the University of Nebraska Press on May 2, 2019:
The world we live in is mostly uncertain and unpredictable. Yet each and every one of our ancestors, all the way back to the primordial archaea, is one of the few organisms in each generation who survived and reproduced, in part because they better predicted (though far more often lucked into!) what would happen next and took appropriate action. A drive for better prediction has been baked into our genes.
Okay. But where do predictions come from? If you think about it a little, the only possible basis for any prediction is previous experience, by oneself or (especially for humans) as reported by others. Prediction then is a recognition, consciously or unconsciously, that some pattern among past experiences makes some future event more likely to occur. And such patterns are more likely to be recognized whenever experiences have been recorded and somehow organized. For example, recognizing that weather tends to repeat itself in 365-day patterns depended on someone counting sunrises and associating each day’s weather with the pattern of the stars—over many years. Using that prediction to decide when to hunt animals or plant crops worked much better than simply sowing on the next warm moist day, because nice days occur as often in October as in April. And it worked almost as well before it was discovered that the earth actually went around the sun, rather than the other way around.
The term big data vaguely summarizes the immense collections of organized past experiences made possible by the latest information technologies. These collections are foundations for our expectations of personalized medicine or self-driving cars, and already, by empowering Facebook or Google, they quietly but significantly impact our lives. Within big data, searching for predictive patterns requires specialized and increasingly complex statistical methodologies, for which analytics has become something of a buzzword.
Read the full article here: https://unpblog.com/2019/05/02/excerpt-when-big-data-was-small/
Originally published: May 3, 2019. Last Updated: May 3, 2019.