BSc Business Management: Big Data Analysis Report - BMP4005

This report provides an overview of big data, its characteristics (volume, variety, velocity, veracity, and value), and the challenges associated with its analysis, including the lack of skilled professionals, data integration issues, and understanding massive datasets. It explores various techniques for big data analysis, such as A/B testing, data fusion, natural language processing, statistics, and data mining. The report also highlights how big data technology can support businesses by enabling better decision-making, product redevelopment, enhanced data safety, improved customer dialogue, automation, and optimal resource utilization. The conclusion emphasizes the significance of big data for organizations in making predictions about business performance and the importance of continuous training for employees in utilizing big data technologies effectively.

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 type of data which is massive, prompt and
complex. In traditional times, there was difficulty in processing the
data without the technology. This report contains the basic concept
of big data and features of the big data. There are several
challenges which require to be solved for better functioning of the
big data technology. In recent times, there are few techniques
which are helpful in analyzing the data. The new technology of big
data helps in supporting the business which improves the
profitability of the business.
What big data is and the characteristics of big data
Big data is a term used to signify the large amount of data used
by data analysts to reach at a particular conclusion. The data is
very huge which creates problem in its processing, organizing
and interpreting. The data can be collected from various
sources such as social media sites, observations and
documents. Companies are required to gain insights about the
customer preferences and changing demand of the customers.
There are several characteristics of big data which can be
explained as given below:
a.) Volume – The big data consists of various data which is big
in size. The companies has to manage the data which is large
in size and it requires a procedure to arrange the data.
b.) Variety – The data has a various types such as structured,
semi structured and unstructured. The structured data is
arranged in a organized manner such as tables and takes the
help of data base management system. The Unstructured data
is not organized well, it does not follow a prescribed format.
The semi structured data is partially structured and does not
use formal structures. The data can be either consist of
homogeneous data or heterogeneous data.
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c.)Velocity – This term refers to the speed of the data at which
it is created or generated. It reflects the speed at which data is
processing. It prompts service use to fulfill the demands of the
clients or customers.
d.)Veracity – This term refers to the truthfulness of the data. It
shows the validity or accuracy of the data collected. Many data
is in the unstructured form which creates difficulty in sorting the
data. The rate of validity shows the level of accuracy in the data
collected.
e.) Value – The important value of big data comes from the
effective operations, strong customer relationships and several
business benefits in quantifying relationships.
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-
 Lack of knowledge professionals – The concept of big
data requires various professionals such as data
scientists, data analysts and data engineers to work with
the new and updated technology. The personnel require
various training sessions to work on the big data
technology. It may increase the cost of the organization
because employees are provided with sessions of training.
The hiring of new professionals also raise the expenses of
the company.
 Integrating data from various sources – The big data is
a combination of data from various sources and it is a
tough task to integrate the data. The sources such as
social media pages, e-mail, presentations, reports and
financial reports. The integration of data is crucial for the
purpose of analyzing and interpreting the data.
 Data growth issues – The size of the data is growing
rapidly and it is typical task to handle such a massive
data. The data is unstructured and comes in the PDF and
images. The assembling of data require various updated
software and grow exponentially with time.
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 Lack of proper understanding of massive data – There
are some data which creates ambiguity in selecting the
category or type of data. The data is huge and requires
clear and transparent picture of the sensitive data.
Therefore, military training program mes must be held for
the employees.
The techniques that are currently available to analyse big
data
As per the report of Mckinsey, there are several techniques used by the big corporations
to solve the issue of the massive and heterogeneous data. The different techniques used
in big data are explained as given below-
 A/B testing- It is also known as split or bucket testing. It is a method which is
used to compare the two different web pages and helps in deciding which
page performs better. The A/B testing is a framework which involves several
steps such as collecting data in which insights are provided about the
beginning of optimizing. There are several goals which are required to be
identified, Goal can be clicking a button or link to purchases of product and
sign up of email. When the goal is decided, the generation of hypothesis is
done. Then variations are created and results are analyzed.
 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 form of technique used in artificial
intelligence and computer science. It takes the use of algorithms to solve the
specific problem. Algorithms are step by step procedures to solve a problem.
Even flowcharts are used to represent the algorithms in a graphical format. It
uses the language which resembles with a simple English language and
understandable by the humans easily.
 Statistics – This is a technique which collect , organize and analyze the data.
It is used in the decision making process. The collection of data by using the
primary and secondary sources assists in taking decisions. The primary data
is known as first hand data because the researcher itself collect the data
whereas in case of secondary research the already existed data in
magazines, brochures and newspaper are used.
 Data mining – It is a process of finding patterns and correlations with a large
number of data. The data is extracted and analyzed by using the approach of
data mining. There are various types of data mining : predictive data mining
and descriptive data mining.
How Big Data technology could support business, an
explanation with examples
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The big data technology helps various business to know the
current trends of the market and preferences of the consumer.
There are various ways in which big data analytic support
business which can be elaborated as given below-
 Making better business decisions – The technology of big
data enables to identify the market patterns which helps in
knowing the consumption pattern of the buyers.
 Re-develop products : The big data is helpful in collecting
and utilizing feedback. It helps to take the views of the
customer segment. The organization starts producing
products which are in favor of the customers. It will
enhance economies of scale and make alternations in the
methods of production.
 Data safety – The organizations are using several
software which protect the data from the viruses and other
malware threats. It assist in securing the data effectively. It
helps to store and retrieve the data according to the needs
of the customers.
 Dialogue with customers – In every institutions, there is a
basic need to know the priorities of the customer. It helps
the corporations to know the target market and work
according to that market. It is possible by using the
techniques of the big data.
 Automation – The technology of big data has the power to
boost the internal efficiency and operations by using
robotic process. With the use of improving cloud
computing and storing within reach.
 Optimum utilization of resources – Big data technology
helps to identify the resources of the organization. If the
resources are allocated to the effective source, it will result
in the boost of profits.
Poster
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Conclusion
On the basis of above report, it can be concluded that huge
or massive data is significant for the organizations. It is helpful for
the purpose of making predictions about the business
performance. There are several forms of the data such as
structured, semi structured and unstructured. In whatever form the
data is, it is vital for taking the operational and financial decisions
of the organization. The big data technology also uses software to
protect from the threat and risks of the market. The big data helps
businesses to grow in effective manner. Therefore, the
technologies must be used with utmost care and continuous
training should be provided to the new employees for using the
technology of big data.
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References
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pp.49-67.
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Jabbour, A.B.L., 2018. Management theory and big data literature: From a review to
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