How Big Data Became So Big
nytimes.com
nytimes.com
It probably does not really need to be repeated, but I guess it cannot hurt. Data being big rarely causes it to be much more interesting. There can be much more actionable information in a few hundred records than in billions, depending on context, proper experimental design, and so on.
Also, an often overlooked point is that precision of statistical estimators (e.g. width of confidence intervals) typically scales with the square root of sample size; yet the cost of processing an additional observation is typically constant (e.g. with distributed systems like hadoop). So in many cases there are decreasing returns to data size.
But - posts like these frequently jump to the top of hacker news, and there's clearly a feeling that access to new analyses and more data is going to change the world. I think this is probably right. I'd love to hear more discussion of how big data has already started this process.
Examples I can think of (and I'd love to hear more): - weather analysis for farmers (weatherbill / the climate corporation) - marketing (the target pregnancy example - http://www.nytimes.com/2012/02/19/magazine/shopping-habits.h...)
More examples?
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Not that it isn't an important thing, and certainly more and more data is becoming available. Now lets get back to work.