BSc Business Management, BMP4005: Big Data Analysis Report

This report provides a comprehensive overview of big data, its characteristics (volume, variety, velocity, veracity, and value), and the challenges associated with its analysis, such as the scarcity of knowledge specialists, data integration issues, and data volume growth. The report explores various techniques used to analyze big data, including A/B testing, data fusion and integration, natural language processing, statistics, and data mining. Furthermore, it explains how big data technology supports businesses by enabling better decision-making, product re-development, data safety, client dialogue, automation, and optimal resource utilization, with specific examples. The report concludes by emphasizing the importance of big data for making business predictions and the need for continuous training in its application. The report is accompanied by a poster summarizing the key findings.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
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Contents
Introduction 3
What big data is and the characteristics of big data 4
The challenges of big data analytics 4
The techniques that are currently available to analyse big data
5
How Big Data technology could support business, an explanation
with examples 5
Poster 7
Conclusion 7
References 8
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Introduction
Big data is a sort of information which is massive, brief and
complex. In ordinary times, there was trouble in handling the
information without the innovation. This report contains the
fundamental idea of big data and elements of the big data. There
are a few difficulties which expect to be settled for better working
of the large information innovation. Lately, there are not many
procedures which are useful in examining the information. The
new innovation of large information helps in supporting the
business which works on the benefit of the business.
What big data is and the characteristics of big data
Big data is a term used to suggest the huge measure of
information utilized by information investigators to reach at a
specific resolution. The information is extremely huge which
makes issue in its handling, sorting out and interpreting. The
information can be gathered from different sources, for
example, online entertainment locales, perceptions and
records. Organizations are expected to acquire bits of
knowledge about the client inclinations and changing interest of
the clients. There are a few attributes of huge information which
can be made sense of as given beneath:
a.) Volume – The Big data comprises of different information
which is enormous in size. The organizations need to deal with
the information which is enormous in size and it requires a
method to orchestrate the information.
b.) Variety – The information has a distinctive sort, for
example, organized, semi organized and unstructured. The
organized information is organized in a coordinated way, for
example, tables and takes the assistance of information base
administration framework. The Unstructured information isn't
coordinated well, it doesn't follow a recommended design. The
semi organized information is to some extent organized and
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doesn't utilize formal designs. The information can be either
comprise of homogeneous information or heterogeneous
information.
c.) Velocity – This term mentions to the speed of the
information at which it is made or created. It mirrors the speed
at which information is handling. It prompts administration use
to satisfy the requests of the clients or clients.
d.) Veracity – This term indicates to the honesty of the
information. It shows the legitimacy or exactness of the
information gathered. Numerous information is in the
unstructured structure which makes trouble in arranging the
information. The pace of legitimacy shows the degree of
exactness in the information gathered.
e.) Value – The significant worth of enormous information comes
from the viable activities, solid client connections and a few
business benefits in evaluating connections.
The challenges of big data analytic system.
There are various challenges which are faced by the big data
analytic which can be elaborated as given below-
 Scarcity of knowledge specialists – The idea of
enormous information requires different experts, for
example, information researchers, information examiners
and information specialists to work with the new and
refreshed innovation. The faculty require different
instructional courses to chip away at the huge information
innovation. It might expand the expense of the association
since representatives are furnished with meetings of
preparing. The employing of new experts likewise raises
the costs of the organization.
 Incorporating information from different sources - The
large information is a mix of information from different
sources and it is an intense assignment to coordinate the
information. The sources, for example, online
entertainment pages, email, introductions, reports and
monetary reports. The joining of information is pivotal to
examine and deciphering the information.
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 Information development issues - The size of the
information is developing quickly and it is common
undertaking to deal with such a huge information. The
information is unstructured and comes in the PDF and
pictures. The gathering of information requires different
refreshed programming and develop dramatically with
time.
 Absence of appropriate comprehension of large
information - There are a few information which makes
uncertainty in choosing the classification or sort of
information. The information is colossal and requires clear
and straightforward image of the touchy information.
Thusly, military preparation program should be held for the
workers.
The techniques that are currently available to analyze big data
According to the report of Mckinsey, there are a few procedures utilized by the
enormous partnerships to tackle the issue of the huge and heterogeneous information.
The various methods utilized in enormous information are made sense of as given
beneath
 A/B testing- It is otherwise called split or bucket testing. It is a strategy which
is utilized to analyze the two different pages and assists in concluding which
with paging performs better. The A/B testing is a structure which includes a
few stages, for example, gathering information in which bits of knowledge are
given about the start of enhancing. There are a few objectives which are
expected to be recognized, Goal can be clicking a button or connection to
acquisition of item and sign up of email. Whenever the objective is chosen,
the age of theory is finished. Then, at that point, varieties are made and
results are dissected. Data fusion and data integration – The process of data
fusion includes the analysis of data by breaking into various parts. On the
other hand, integration of data includes the organizing of data in a single
database.
 Natural language processing – It is a type of method utilized in artificial
intelligence and software engineering. It takes the utilization of calculations to
tackle the particular issue. Calculations are bit by bit methodology to take care
of an issue. Indeed, even flowcharts are utilized to address the calculations in
a graphical configuration. It utilizes the language which looks like with a
straightforward English language and justifiable by the people without any
problem.
 Statistics – This is a method which gather, sort out and dissect the
information. It is utilized in the dynamic interaction. The assortment of
information by involving the essential and optional sources helps with taking
choices. The essential information is known as direct information on the
grounds that the actual scientist gathers the information while if there should
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be an occurrence of auxiliary exploration the all-around existed information in
magazines, pamphlets and paper are utilized.
 Data mining – It is a course of tracking down examples and relationships with
countless information. The information is extracted and broke down by
utilizing the methodology of information mining. There are different sorts of
information mining: perceptive information mining and illustrative information
mining.
How Big Data technology could support business, an
explanation with examples
The big data innovation assists different business with
knowing the latest things of the market and inclinations of the
customer. There are different manners by which large information
logical help business which can be expounded as given
underneath
• Settling on better business choices - The innovation of
enormous information empowers to recognize the market designs
which assists in knowing the utilization with designing of the
purchasers.
• Re-development of products: The huge information is useful
in gathering and using input. It assists with taking the perspectives
on the client fragment. The association begins delivering items
which are supportive of the clients. It will upgrade economies of
scale and make shifts in the techniques for creation.
• Data safety - The associations are utilizing a few
programming which shield the information from the infections and
other malware dangers. It help with getting the information
actually. It assists with putting away and recover the information as
indicated by the necessities of the clients.
• Dialogue with clients - In each establishment, there is a
fundamental need to know the needs of the client. It assists the
companies with realizing the objective market and work as
indicated by that market. It is conceivable by utilizing the strategies
of the large information.
• Automation - The innovation of enormous information has the
ability to support the interior effectiveness and activities by utilizing
automated process. With the utilization of further developing
distributed computing and putting away reachable.
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• Ideal usage of assets - Big data innovation assists with
recognizing the assets of the association. Assuming that the
assets are designated to the compelling source, it will bring about
the increase in benefits.
Poster
Conclusion
Based on above report, it can be concluded that immense or
enormous data is huge for the associations. It is useful to make
expectations about the business execution. There are a few types
of the information, for example, organized, semi organized and
unstructured. In any case, structure the information is essential for
taking the functional and monetary choices of the association. The
enormous information innovation additionally utilizes programming
to shield from the danger and dangers of the market. The
enormous information assists organizations with filling in powerful
way. Subsequently, the advances should be utilized with absolute
attention to detail and persistent preparation ought to be given to
the new representatives to utilizing the innovation of huge
information.
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References
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experience: Empirical evidence from big data analytics. International Journal of
Contemporary Hospitality Management.
Liu, X., Sun, R., Wang, S. and Wu, Y.J., 2020. The research landscape of big data: A
bibliometric analysis. Library Hi Tech.
Shams, S.R. and Solima, L., 2019. Big data management: implications of dynamic
capabilities and data incubator. Management Decision.
Sharma, P., Borah, M.D. and Namasudra, S., 2021. Improving security of medical big data by
using Blockchain technology. Computers & Electrical Engineering, 96, p.107529.
Tran, H.Y. and Hu, J., 2019. Privacy-preserving big data analytics a comprehensive
survey. Journal of Parallel and Distributed Computing, 134, pp.207-218.
Upadhyay, P. and Kumar, A., 2020. The intermediating role of organizational culture and
internal analytical knowledge between the capability of big data analytics and a
firm’s performance. International Journal of Information Management, 52,
p.102100.
Zhan, K., 2021. Sports and health big data system based on 5G network and Internet of
Things system. Microprocessors and Microsystems, 80, p.103363.
Zhang, X., Yu, Y. and Zhang, N., 2020. Sustainable supply chain management under big
data: A bibliometric analysis. Journal of Enterprise Information Management.
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