Any one of those things, you kind of say, 'So what?'
But what we look for is a number of them that on the
surface perhaps don't seem to be related but all seem
to be happening at the same time," she says.
Charnock says had the French bank analyzed that
data, it might have flagged the rogue trader earlier.
But big data is not just about connecting dots to
detect crime. The ability to process so much
information so quickly makes all kinds of things
possible that weren't before. So LinkedIn finds jobs
or people you might like to know about, and biotech
companies can analyze gene sequences in billions of
combinations to design drugs.
Data analytics itself is not new. Two decades ago,
Wall Street hired teams of physicists to analyze
investments. But in the past couple of years,
computing, storage and bandwidth capacity have
become so cheap that it has altered the scale of
what's possible.
Now, with very little money, a gifted student or a
small startup can design bigdata
applications.
"Everywhere you look, there's an opportunity to
collect more data and then apply a statistical or
mathematical approach to understanding what's
happening," says Chris Kemp, chief executive officer
of Nebula, a firm that provides storage and