What
is big data?
An introduction to the big
data landscape.
by Edd Dumbill
Big
data is data that exceeds the processing capacity of conventional database
systems. The data is too big, moves too fast, or doesn’t fit the strictures of
your database architectures. To gain value from this data, you must choose an
alternative way to process it.
The hot
IT buzzword of 2012, big data has become viable as cost-effective approaches
have emerged to tame the volume, velocity and variability of massive data.
Within this data lie valuable patterns and information, previously hidden
because of the amount of work required to extract them. To leading corporations,
such as Walmart or Google, this power has been in reach for some time, but at
fantastic cost. Today’s commodity hardware, cloud architectures and open source
software bring big data processing into the reach of the less well-resourced.
Big data processing is eminently feasible for even the small garage startups,
who can cheaply rent server time in the cloud.
The
value of big data to an organization falls into two categories: analytical use,
and enabling new products. Big data analytics can reveal insights hidden
previously by data too costly to process, such as peer influence among
customers, revealed by analyzing shoppers’ transactions, social and
geographical data. Being able to process every item of data in reasonable time
removes the troublesome need for sampling and promotes an investigative
approach to data, in contrast to the somewhat static nature of running
predetermined reports.
The
past decade’s successful web startups are prime examples of big data used as an
enabler of new products and services. For example, by combining a large number
of signals from a user’s actions and those of their friends, Facebook has been
able to craft a highly personalized user experience and create a new kind of
advertising business. It’s no coincidence that the lion’s share of ideas and
tools underpinning big data have emerged from Google, Yahoo, Amazon and
Facebook.
The
emergence of big data into the enterprise brings with it a necessary
counterpart: agility. Successfully exploiting the value in big data requires
experimentation and exploration. Whether creating new products or looking for
ways to gain competitive advantage, the job calls for curiosity and an
entrepreneurial outlook.
No comments:
Post a Comment