October 13, 2014
Big-Data Doubts
As you may have noticed, Big
Data is, well, big. Very BIG. So big it’s becoming boring, a bandwagon
term that everyone needs to talk about to show that they can play the
game, keep up with the gossip, or do contemporary small talk. Many
observers once thought the craze would go away, and some wish it had.
But the hype keeps growing through data streams and dreams.
The term itself is quite phenomenal. Its capacity to morph into so
many forms and functions is akin to a powerful shape-shifter, taking on
new meaning amid a new data-driven grammar. Put any noun in front of the
term, and you have just named an area of life that Big Data is going to
somehow transform: health, finance, education, marketing and retail,
sports, environment and climate, housing and cities. Put an adjective in
front of it—gloopy, colored, short, fat, thin—and you’ll see it catch
on, at least in some circles, for at least a short time.
But mostly the grammar of Big Data is about verbs and what we can do
with it: predict; steer, shape; harvest, harness, mine; sort, store,
synthesize; track and trace; innovate and transform; optimize, maximize,
visualize; and so on. So many of those verbs are about maximizing the
capacity to model human behavior: intervening, faster and more
efficiently than ever before, now, in real time—or as quickly as
possible, so we can shift from forecasting to "now-casting" and prevent traffic hot spots, epidemics, riots, and civil unrest. Read more...
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