Business Management through Big Data Analysis

This report covers the use of Big Data analysis for effective business management. It explains the characteristics of Big Data, challenges faced in Big Data analytics, techniques available for Big Data analysis, and how Big Data technology could support business with examples. The subject is BSc (Hons) Business Management, and the course code is BMP4005 Information Systems and Big Data Analysis.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
Submitted by:
Name:
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Contents
Introduction p
What big data is and the characteristics of big data p
The challenges of big data analytics p
The techniques that are currently available to analyse big data
p
How Big Data technology could support business, an explanation with
examples p
Poster p
References p
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Introduction
This report will cover up the business management through the big data analysis which is
required for functioning the business in an effective way containing the vital information from the
software to the hardware having the knowledge of the internal factors of the business. The key
aspect of the characteristics of the big data which helps in evaluating the business as per the
today's scenario. Covering up the challenges which the big data face in the business with the
techniques that are currently available for it for analytical approach of conquering the challenges
for the better understandings of the market and generating a profits through having the
information about the needs and requirements of the customers as per the present situation of the
market along with that it would be having the vital information about the big data technology
which supports the business in a way which would be having the source of the information about
the importance of the big data and how it is required as looking forward the present
situations(HaririFredericksBowers,2019)
What big data is and the characteristics of big data
The data which contains the huge amount of data which has been evaluating by the time. It
has more volume than the ordinary data and it has more complexity. It is unable to manage
through the system of traditional software because of the huge size it has it does not get stored in
the database of the computer but it get stored in the data warehouse which consists the petabytes
of 1024 terabytes which have the large variety enhancing with additional velocity. Big data
provides advanced analytical insights and intelligence in the business which is used in the
agriculture and for environmental protection that could be collected via satellite imagery covering
the whole globe in 30 times as it is helpful in the process of decision making as well.
CHARACTERISTICS OF BIG DATA :
1) VOLUME : Big Data explanation is clear by it's name only and which has a huge
size of data which plays a vital role in finding out the value of the data and determine
whether the data is big data or not as it is always depend on the volume of the data
that is why volume is one of the characteristics which always be required to get
considered during dealing with the big data solution(Al-MekhlalKhwaja,2019).
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2) VARIETY : It is related to the heterogeneous source and structured nature of the data and
unstructured as well. There used to have only spreadsheets and databases which used to collect
sources of the considered data trough most of the applications but now data has variety of
unstructured data containing few issues of the storage mining and analyzing data in the forms of
videos , photos , email , pdf and audio etc.
3) VELOCITY : The velocity of Big Data deals with the speed of the data in which sources
such as business , networks , social media , mobile devices etc. It refers to the speed of the
generation of data and the speed of the data which has been generated for meeting the
requirements of the real potential in the data.
4) VARIABILITY : Constraint the process of being able to handle and manage the data
efficiently because of the inconsistency which could be shown through the data time to time.
5) VERACITY : It is related to the accuracy of the numbers of the big data as it is
helpful for having the analysis of the consistency and quality of the big data which
looks forward the incomplete data or the errors which has been there in the big
data(Younas,2019).
The challenges of big data analytics
Big Data faces many different difficulties and some of those difficulties have been explained
below :
 PRIVACY AND SECURITY : Big data needs large space for the storage and usually it
becomes a challenge as it is necessary for performing the security checks and observation because
the data is very large and beneficial.
 ANALYTICAL CHALLENGES : The analysis needs to be done in structured , semi
structured or unstructured way because of the huge size of the big data.
 SHARING AND ACCESSING DATA : Having access of the data from the public
depository leads in having the various difficulties and it can result as considerable
challenges as it is huge in terms of size(ZhangHuangBompard,2018).
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 TECHNICAL CHANGES : There are 3 types of technical changes Quality of data where
big data forces on having the quality data storage and contains the relevant data which has been
required for the better results then there is Fault Tolerance which have the intricate algorithms
which is very difficult in engineering. Lastly there is Scalability which determines the rapid
growth of big data resulting to have the scalability issue which is arising in the storage of data
leading to a challenges of storing the huge amount of data and execute various goal oriented job
which could result as the failure of system.
The techniques that are currently available to analyze
big data
A/B TESTING : Different types of groups are compared through a main controlling group
intended for determining the treatment which will improve the objective variables and basically an
experiment where 2 or more than 2 variables are compared for getting chosen which will analyze
which one is better for achieving the goal(BamiahBrohiRad,2018).
CLASSIFICATION : There are numbers of techniques that have been used for determinin the
categories to which the new data belongs to and this is refer as a supervised learning which helps
in the decision making by contributing the various amount categories.
SENTIMENT ANALYSIS : It helps to understand the requirements or expectations of the
customers from it's chosen brand which leads for having an enhancement in the services of the
business which helps in interpreting the emotions with the data which has been provided as it
helps in compounding the sentiments of the people.
SOCIAL NETWORK ANALYSIS : This analysis is used for enhancing the relationship
between the customers and the business fir understanding the social structure of the customers and
the first was the telecommunication industry for using this and after which it has been used by the
social scientists for finding out the social concept and evaluating the bond between the individuals
and for mercantile activities along with that the nodes determines the individuals who are in a
system while having the ties determines the relationship between the individuals for having the
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analysis of the use of the social network in terms of the business and evaluating the connections
between individuals or the customers.
How Big Data technology could support business,
an explanation with examples
COMMUNICATING WITH CONSUMERS : Customers are smarter to understanding
the priorities as per the present time for exploring everything before making a purchase. Moreover
communication with the business organizations via different social media platforms. Business
becomes enable to reach the customers with the help of big data and interacting with them for
their needs and desires because of the huge competition in the market business organizations have
to treat their customers as per their requirements(PilipczukCosencoKosenko,2019).
REMANUFACTURING PRODUCTS : Big data is helpful in analyzing the needs and
requirements of the customers through the feedback system for the customers through the help of
the customer which can update the features and qualities customers wants in the product.
Company understand these feedback by the big data and make the changes in the product.
RISK ANALYSIS : It is the analysis company do which could impact the operation of the
business. It helps in scanning the feeds of social media , newspaper reports for knowing about the
current marketing scenario as it would help the company for understanding the current
competition of the market and have the development in the product according to the competition
of the market(Ghani el. at.,2019).
DATA SAFETY : Big data analytics could help in finding out the entire data base within the
organization and having the knowledge about every kind of internal threats through the company
and would be able to remove or resolve the threats and keep vital information safe.
NEW REVENUE SYSTEM : Big data helps in knowing about making more revenue for the
company and give the information about the needs and wants of the customers as per the
requirements of the customers.
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Poster
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References
Hariri, R.H., Fredericks, E.M. and Bowers, K.M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data, 6(1), pp.1-16.
Al-Mekhlal, M. and Khwaja, A.A., 2019, August. A synthesis of big data definition and
characteristics. In 2019 IEEE International Conference on Computational Science
and Engineering (CSE) and IEEE International Conference on Embedded and
Ubiquitous Computing (EUC) (pp. 314-322). IEEE.
Younas, M., 2019. Research challenges of big data. Service Oriented Computing and
Applications, 13(2), pp.105-107.
Zhang, Y., Huang, T. and Bompard, E.F., 2018. Big data analytics in smart grids: a
review. Energy informatics, 1(1), pp.1-24.
Bamiah, S.N., Brohi, S.N. and Rad, B.B., 2018. Big data technology in education:
Advantages, implementations, and challenges. Journal of Engineering Science and
Technology, 13, pp.229-241.
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Pilipczuk, O., Cosenco, N. and Kosenko, O., 2019. Big Data: Challenges and opportunities in
financial management. Problemy Zarządzania, (5/2019 (85)), pp.9-23.
Ghani, N.A., Hamid, S., Hashem, I.A.T. and Ahmed, E., 2019. Social media big data
analytics: A survey. Computers in Human Behavior, 101, pp.417-428.
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