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Insight For U & Me
that, we need to understand where we can find this data and
what we can do with it.
Let us see how Big Data can really help different
organisations in their business
- Targeted marketing: There are several small businesses
which cannot compete with the huge advertising budgets
that large organisations have at their disposal. In order
to remain in the game, they have to spend less, yet reach
qualified buyers. This is where the need for analysis and
measurement of data comes in, in order to target the
person most likely to turn into a customer. There is a huge
amount of data that is freely accessible through different
tools like Google Insights, etc. Organisations can find
exactly what different people are looking for, when they
are really looking for it and also find out their locations.
For instance, the CDC (Centre for Disease Control, USA)
uses the Big Data provided by Google to analyse a large
number of searches relating to the flu. With the obtained
data, researchers are able to focus their efforts where there
is a greater need for flu vaccines. The same technique can
be applied for other products as well. - Actionable insights: Big Data can really become like
drinking from a fire hose if we do not know how to turn
different facts and figures into useable information. But
as soon as an organisation learns how to master different
analytical tools, which turn its metrics into readable reports,
graphs and charts, it can make decisions that are more
proactive and targeted. And that’s when it will gain a clear
understanding of the ‘big problems’ affecting the business. - Social eavesdropping: A large chunk of the information in
Big Data is obtained from social chatter on several social
networking sites like Twitter and Facebook. By keeping an
eagle eye on what is being said in different social channels,
organisations can really understand how the public
perceives them and what to do if they need to improve their
reputation. For example, the Twitter mood predicts the
stock market. Johan Bollen once tracked how the collective
mood from large sets of Twitter feeds correlated with the
Dow Jones Industrial Average. The algorithm which was
used by Bollen and his group actually predicted market
changes with 87.6 per cent accuracy.
Applications of Big Data
There is a huge demand for Big Data nowadays, and there are
numerous areas where it is already being implemented. Let’s
have a look at some of them.
- Big Data is used in different government sectors for different
tasks like power theft investigation, deceit recognition and
ecological fortification. Big Data is also used to examine
different food based infections by the FDA. - It is widely used in the healthcare industry by physicians
and doctors to keep track of their patients’ history. - Big Data is also used in the education sector by
implementing different techniques such as adaptive learning,
problem control, etc, to reform different educational courses.
- Big Data is used in fraud detection in the banking sector.
- It is used by different search engines to provide the best
search results. - Different price comparison websites make use of Big Data
to come up with the best options for their users. - Big Data is also used for analysing and processing
the data obtained from different sensors and actuators
connected to IoT. - Different speech recognition products such as Google
Voice and Siri also make use of Big Data to recognise the
speech patterns of the user. - Big Data and data science have taken the gaming
experience to new heights. Different games are now
designed using various Big Data and machine learning
algorithms, which have the self-improving capability
when a player jumps to a higher level. - Big Data is of great help for the recommender and
suggestion tool which prompts us about similar products
to purchase on different online shopping platforms like
Amazon, Flipkart, etc.
Figure 5: Different ways in which Big Data can help any business
(Image source: googleimages.com)
Using Data
to Improve
Performance
How can I
optimize my
marketing
budget?
How do I
define my target
market?
Which offer
generates the
greatest
response?
How do I
improve
customer
retention?
What is
the Lifetime
Value of my
customer?
Which
channel is
most
effective?
Which
demographic
responds to
my offer?
How can I
measure
marketing
results?
(^81)
2
3
5 4
6
7
By: Vivek Ratan
The author has completed his B. Tech in electronics and
instrumentation engineering. He is currently working as
an automation test engineer at Infosys, Pune. He can be
reached at [email protected].
[1] ‘Data Science for Business’ by Tom Facet
[2] http://www.wikipedia.org/
[3] http://bigdata-madesimple.com/
[4] https://bigdata.wayne.edu/
References