A ascertain the information they contain within them.

 A STUDY ON CORPORATE’S BIG DATA ANALYTICS

                            SANNIDHANAM
ANURAG

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      B.COM (COMPUTERS) STUDENT AT ST.JOSEPHS
DEGREE AND PG COLLEGE

 

 

ABSTRACT

Big data analytics has
come in to use by the corporate sector due to the failure of the process-based
applications system to scrutinize numerous volumes of data (Eg-: Aadhar card).
Big data deals with scrutinizing huge volume data sections in order to ascertain the information they
contain.
The main objective of this study is to know the importance of big data in
post-modernistic technological advancement and how we can make more changes in
the corporate sector by implementing big data techniques. The scope of study is
restricted to the use of big data techniques in corporate sectors to know all the different
solutions to more quickly resolve or enhance a particular situation. The
outcomes I determined from this study is that big data is highly instrumental
to corporate sector (especially to the customers of the health sector) if the
rules and regulations are implied as per the need and wants of big data
analytics, big data would be the most pleasing technology to scan numerous data
in single go

Key words-: process-based
application system, examining, technological advancement, solutions,
specialized, cost effective 

INTRODUCTION

BIG DATA

Big data the
word ‘Big’ here states huge/numerous
data, hence Big data deals with scrutinizing large
volume data sections
in order to ascertain the information they contain within them. In simple words
it is the extremely huge data sets that may be scrutinized using artificial intelligence to
provide the organization with patterns, trends, and associations, especially
relating to human behavior and interactions. It is the most trending technique
used in the 21st Anno Domini era by almost all the big corporate
sectors out there, as the techniques of 
big data are accepted throughout the globe this paved a huge platform
for big data technique users.

BIG DATA ANALYTICS

Whereas
coming to big data analytics, big data
analytics is the technique of scrutinizing of huge and different data segments which helps to
simplify present trends of the market, preferences and other valuable
information that can help the corporate world take more-knowledgeable
decisions.

METHODOLOGY OF THE STUDY

 Data collection instrument:

The data that is
used in this research is mainly of secondary nature. The data is collected from
secondary sources such as various websites, journals, newspapers, books, etc.
the analysis used in this project has been done using selective technical tools.

LITERATURE REVIEW

 

 

TECHNIQUES OF BIG DATA
ANALYTICS

1.     Prescriptive
method

2.     Predictive
method

3.     Diagnostic
method

4.     Descriptive
method

1.    
Prescriptive analytics-: This type of analysis reveals what actions should be taken.
This is the most valuable kind of analysis and usually results in rules and
recommendations for next steps, but this approach is rarely used. Where big
data analytics in general puts light on a subject, prescriptive analytics gives
you the perfect ability to answer the pros and cons, for example if you choose
health sector.  You can better manage the
patients frequency by using prescriptive analytics to measure the number of
patients who are clinically obese

2.    
Predictive analytics-: An analysis of likely situations of what might happen. The
deliverables are usually a predictive forecast use big
data to identify past patterns to predict the future. For example, companies
are using predictive analytics for the entire sales process, etc. Properly
tuned predictive analytics can be used to support sales, marketing, or for
other types of complex forecasts.

3.     Diagnostic analytics-: This technique is nothing but pooling back at past deeds of the
business to know what and why it happened. Diagnostic analytics is nothing but
checking the mistakes committed in the past and finding the cause of the
mistake

4.     Descriptive analytics-: What is presently
happening in the organization based on the data ascertained data. A simple
example of descriptive analytics would be ascertaining how much credit limit
can be given to a customer this would be possible only when the preceding
previous years financial performance is known by the bank to predict their customer’s
likely financial performance

From the following techniques
used I can conclude that there is deduction in the amount of huge data
available in the organization is and the data which is worthy is grasped by big
data analytics to provide the organization with more effective results during
the decision making

LIMITATIONS OF BIG DATA ANALYTICS

1.     The implementation of big
data techniques in an organization is very expensive

2.    
There
is lack of awareness of big data in the present global market

3.     Big data techniques can
only be implemented by the large scale organizations as the small scale cannot
afford specialized labor and the installation costs

4.    
It
requires knowledge in the techniques used only then an organization can
successfully adopt it.

5.    
The
lack of stability of the employees who are knowledgeable of big data analytics

FINDINGS
AND CONCLUSIONS AND SUGGESTIONS

1.     Big data is highly instrumental to
corporate sector to find effective results

2.     The first time installation cost would be very high but once
the tool is installed it would be cost effective

3.     The organization should increase the salaries of the
specialized people with big data analytics so that there would be employees
stability

4.     The tool need to be updated as per the requirements of the
tool in order to get best results