Database Reference
In-Depth Information
kind of data complements the data that we use to drive decisions today. Most
of the data out there is semistructured or unstructured. (To clarify, all data has
some structure; when we refer to
unstructured data
, we are referring to the sub-
components that don't have structure, such as the freeform text in a comments
field or the image in an auto-dated picture.)
Consider a customer call center; imagine being able to detect the change in
tone of a frustrated client who raises his voice to say, “This is the third outage
I've had in one week!” A Big Data solution would not only identify the terms
“third” and “outage” as negative polarity trending to consumer vulnerability,
but also the tonal change as another indicator that a customer churn incident
is trending to happen. All of this insight can be gleaned from unstructured
data. Now combine this unstructured data with the customer's record data
and transaction history (the structured data with which we're familiar), and
you've got a very personalized model of this consumer: his value, how brittle
he's become as your customer, and much more. (You could start this usage
pattern by attempting to analyze recorded calls not in real time, and mature
the solution over time to one that analyzes the spoken word in real time.)
An IBM business partner, TerraEchos, has developed one of the most
sophisticated sound classification systems in the world. This system is used
for real-time perimeter security control; a thousand sensors are buried under-
ground to collect and classify detected sounds so that appropriate action can
be taken (dispatch personnel, dispatch aerial surveillance, and so on) depend-
ing on the classification. Consider the problem of securing the perimeter of
a nuclear reactor that's surrounded by parkland. The TerraEchos system can
near-instantaneously differentiate the whisper of the wind from a human
voice, or the sound of a human footstep from the sound of a running deer.
In fact, if a tree were to fall in one of its protected forests, TerraEchos can affirm
that it makes a sound even if no one is around to hear it. Sound classification
is a great example of the variety characteristic of Big Data.
How Fast Can You Analyze? The Velocity of Your Data
One of our favorite but least understood characteristics of Big Data is
velocity
.
We define velocity as the rate at which data arrives at the enterprise and is
processed or well understood. In fact, we challenge our clients to ask them-
selves, once data arrives at their enterprise's doorstep: “How long does it
take you to do something about it or know it has even arrived?”
