From the print edition of The Economist:
The data deluge
Feb 25th 2010
Businesses, governments and society are only starting to tap its vast potential
EIGHTEEN months ago, Li & Fung, a firm that manages supply chains for retailers, saw 100 gigabytes of information flow through its network each day. Now the amount has increased tenfold. During 2009, American drone aircraft flying over Iraq and Afghanistan sent back around 24 years’ worth of video footage. New models being deployed this year will produce ten times as many data streams as their predecessors, and those in 2011 will produce 30 times as many.
Everywhere you look, the quantity of information in the world is soaring. According to one estimate, mankind created 150 exabytes (billion gigabytes) of data in 2005. This year, it will create 1,200 exabytes. Merely keeping up with this flood, and storing the bits that might be useful, is difficult enough. Analysing it, to spot patterns and extract useful information, is harder still. Even so, the data deluge is already starting to transform business, government, science and everyday life (see our special report in this issue). It has great potential for good—as long as consumers, companies and governments make the right choices about when to restrict the flow of data, and when to encourage it.
A few industries have led the way in their ability to gather and exploit data. Credit-card companies monitor every purchase and can identify fraudulent ones with a high degree of accuracy, using rules derived by crunching through billions of transactions. Stolen credit cards are more likely to be used to buy hard liquor than wine, for example, because it is easier to fence. Insurance firms are also good at combining clues to spot suspicious claims: fraudulent claims are more likely to be made on a Monday than a Tuesday, since policyholders who stage accidents tend to assemble friends as false witnesses over the weekend. By combining many such rules, it is possible to work out which cards are likeliest to have been stolen, and which claims are dodgy.
Mobile-phone operators, meanwhile, analyse subscribers’ calling patterns to determine, for example, whether most of their frequent contacts are on a rival network. If that rival network is offering an attractive promotion that might cause the subscriber to defect, he or she can then be offered an incentive to stay. Older industries crunch data with just as much enthusiasm as new ones these days. Retailers, offline as well as online, are masters of data mining (or “business intelligence”, as it is now known). By analysing “basket data”, supermarkets can tailor promotions to particular customers’ preferences. The oil industry uses supercomputers to trawl seismic data before drilling wells. And astronomers are just as likely to point a software query-tool at a digital sky survey as to point a telescope at the stars.
There’s much further to go. Despite years of effort, law-enforcement and intelligence agencies’ databases are not, by and large, linked. In health care, the digitisation of records would make it much easier to spot and monitor health trends and evaluate the effectiveness of different treatments. But large-scale efforts to computerise health records tend to run into bureaucratic, technical and ethical problems. Online advertising is already far more accurately targeted than the offline sort, but there is scope for even greater personalisation. Advertisers would then be willing to pay more, which would in turn mean that consumers prepared to opt into such things could be offered a richer and broader range of free online services. And governments are belatedly coming around to the idea of putting more information—such as crime figures, maps, details of government contracts or statistics about the performance of public services—into the public domain. People can then reuse this information in novel ways to build businesses and hold elected officials to account. Companies that grasp these new opportunities, or provide the tools for others to do so, will prosper. Business intelligence is one of the fastest-growing parts of the software industry.
But the data deluge also poses risks. Examples abound of databases being stolen: disks full of social-security data go missing, laptops loaded with tax records are left in taxis, credit-card numbers are stolen from online retailers. The result is privacy breaches, identity theft and fraud. Privacy infringements are also possible even without such foul play: witness the periodic fusses when Facebook or Google unexpectedly change the privacy settings on their online social networks, causing members to reveal personal information unwittingly. A more sinister threat comes from Big Brotherishness of various kinds, particularly when governments compel companies to hand over personal information about their customers. Rather than owning and controlling their own personal data, people very often find that they have lost control of it.
The best way to deal with these drawbacks of the data deluge is, paradoxically, to make more data available in the right way, by requiring greater transparency in several areas. First, users should be given greater access to and control over the information held about them, including whom it is shared with. Google allows users to see what information it holds about them, and lets them delete their search histories or modify the targeting of advertising, for example. Second, organisations should be required to disclose details of security breaches, as is already the case in some parts of the world, to encourage bosses to take information security more seriously. Third, organisations should be subject to an annual security audit, with the resulting grade made public (though details of any problems exposed would not be). This would encourage companies to keep their security measures up to date.
Market incentives will then come into play as organisations that manage data well are favoured over those that do not. Greater transparency in these three areas would improve security and give people more control over their data without the need for intricate regulation that could stifle innovation. After all, the process of learning to cope with the data deluge, and working out how best to tap it, has only just begun.