GHCL Digest JUNE 2018

Introduction To Data Analytics
Data science is a set of fundamental principles that guide the extrac on of
knowledge from the data. With vast amount of data now available, companies
in almost every industry are focused on exploi ng data for compe ve edge.
Computers have become far more powerful, networking has become
ubiquitous, and algorithms have been developed that can connect datasets to
enable broader and deeper analysis than previously possible. The convergence
of this phenomenon has given rise to increasingly widespread business
applica ons of data science principles and data mining techniques.
S. N. Deshpande
Data analy cs (DA) is the process of examining data sets in order to draw conclusion about the
informa on it contains. It is not a tool or technology, rather it is the way of thinking and ac ng on data.
PREDECTIVE ANALYTICS
Predic on is booming. It reinvents the industries and run the world.
More and more predic ve analy cs drives commerce, manufacturing,
healthcare, Government, and law enforcement. In these spheres
organiza ons operate more effec vely by way of predic ng behaviour i.e.
Outcome of each individual customer, employee, pa ent, voter and suspect.
High performance sales team is four mes more likely to already be using
predic ve analy cs than underperformers.
PREDICTION IN BIG BUSINESS - THE DESTINY OF ASSETS
Predic on is power. Big business secures a killer compe ve stronghold by predic ng the future
des ny and value of individual assets. In this case by driving mortgage decisions with predic ons about
the future payment behaviour of homeowners, Chase curtailed risk, boosted profit are some of
obvious benefits of data analy cs.
Following are the few challenges which are best addressed with predic on. Will the pa ent's outcome
from surgery be posi ve? Will the credit applicant turn out to be a fraudster? Will the home owner face
a bad mortgage? Will the air fare go down? Will the customer respond if mailed a brochure? By
predic ng these things, it is possible to for fy healthcare, combat risk, conquer spam, toughen crime
figh ng, boost sales, and cut costs.
Few examples out of large poten al which Data Analy cs can predict from data are as below:
1) Australian energy company Energex predicts electricity demand in order to decide where to build
out its power grid, and Con Edison predicts system failure in the face of high levels of consump on.
2) Wall Street firm's trade algorithmically, buying and selling based on the predic on of stock prices.
3) Companies predict which customer will buy their products in order to target their marke ng.
4) The leading career- focused social network, LinkedIn, predicts your job skills.
5) Clinical researchers predict infidelity and divorce. There's even a self help website tool to put odds on
your marriage's long term success (www. Divorce probability .com )
6) Obama was re elected in 2012 with the help of voter predic on.
Shobhit Ninoria
June 2018
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