As of today, Big Data is a major Buzzword in
town…”Thing Big and see bigger returns with Big
Data Analytics You're sitting on a gold mine” says Frank J. Ohlhorst in
his book Big Data Analytics.
One of the greatest strengths of big data is how it
can be used to provide fresh insights to decision makers. Big data can
reveal customer and market trends that, when spotted quickly enough, can
lead executives to move rapidly on new business ventures ahead of competitors. The
beauty of the increasingly digital landscape is that every single digital
interaction that occurs – from scheduling a doctor’s visit via email to
entering a chat session with a customer agent regarding a product issue to
commenting about a brand experience on Facebook – becomes an electronic record
that companies can make use of, notes Inc. magazine reporter J.J. McCorvey
in a recent blog.
The Big Data “funda” is simple:
“More is better.” If you can give me more data about a customer—if you can
capture more aspects of their behavior, their connections with others, their
interests, and so on—then one can pin down exactly what this person is all
about. It can be anticipated what they will buy, and when, and for how much,
and through what channel. These improvements will further impact industries
across the board from education, to healthcare, government, retailing and
manufacturing.
But on the Flip side we have “junta”
which believes, More data doesn't necessarily mean better results, and
while Big Data can be powerful, it still needs the *right* data to draw useful
conclusions. Getting the right data isn't as easy as using machine
learning on someone's twitter stream. Obviously we need data to draw conclusions and analyze problem. But the question is how much data do we need? For instance, do we need a second-by-second log of the shopper’s location? Would it be truly helpful to integrate this series of observations with other behavioral data (e.g., which products the shopper examined)? Or would this just be nice to know? And how much of this data should we save after the trip is completed?
It is believed that many of these patterns are pretty obvious & consistent and they are not as radical as they are being portrayed.
The Debate is on and heating up but the Big Data Scientist have an edge when it comes to the veneer of respectability..lets us see if the tide turns in the long run!
The Debate is on and heating up but the Big Data Scientist have an edge when it comes to the veneer of respectability..lets us see if the tide turns in the long run!
Source : MIT Technology Review
