The problem, however, is that most people will never even know that a device ID exists for them.
'Big Data' Analysis Infers a Lot From a Little
So-called Big Data is one of the few big concepts that will define technology and culture in the first part of the 21st century. The term refers to the capture, storage, and analysis of large amounts of data. This can mean any kind of data, but the term often refers to the collection and analysis of personal data.
Running deep analysis of terabytes of data was perhaps pioneered by Google, but Big Data practices are now in place at all kinds of organizations, from law enforcement to dating sites to UPS to Major League Baseball. IDC (owned by the same parent company as PCWorld) says that the $3.2 billion that companies spent on Big Data in 2010 will grow to $16.9 billion in 2015.
Among people involved in the personal data economy in one way or another, one anecdote comes up over and over again, and beautifully demonstrates both the possibilities and the dangers of Big Data.
A story by Charles Duhigg in the New York Times Magazine in February described how analysts in the predictive data department of Target developed a way to use the company's customer data to predict the pregnancies (and future baby product needs) of its female customers, sometimes even before the woman's family knew she was pregnant.
This was an extremely important discovery for Target because it allowed the company to show the women ads for various baby products timed to each phase of the pregnancy. There was an even bigger bonus. During the stressful months of pregnancy, future moms' and dads' normal buying habits frequently go out the window, and they look for the most convenient place to buy everything. If Target could get the women into its stores to buy baby products, it might become their go-to source for all sorts of products.
The Target analysts got their breakthrough by looking at the buying histories of women who had signed up for new baby registries at Target. The analysts noticed that pregnant women often bought large amounts of unscented lotion around the start of their second trimester, and that sometime during the first 20 weeks of their pregnancies they bought lots of supplements like calcium, magnesium, and zinc.
The analysts then searched for these same "markers" in all females of childbearing age, found the likely moms-to-be, and sent them offers and coupons for baby products carefully timed to the various stages of pregnancy. Ka-ching.
This is a relatively simple example, and one that happened to be reported in the media. But, as the Duhigg article points out, most large companies in America now have "predictive analysis" departments and are learning to look for the kind of markers that Target discovered hidden in its data.