BSc Business Management: Big Data Analysis Report, BMP4005

This report, prepared for a BSc (Hons) Business Management course, provides a comprehensive overview of Big Data analysis. It begins with an introduction to Big Data, defining it as a large activity cycle that analyzes vast information to reveal data for informed business decisions, including market trends and customer satisfaction. The report details the characteristics of Big Data, following the 'V's: Volume, Variety, Velocity, and Value. It then addresses the challenges of Big Data analytics, such as the shortage of skilled professionals, issues in data collection, and security concerns. The report explores various techniques for analyzing Big Data, including A/B testing, information fusion, statistical methods, machine learning, natural language processing, and data mining. Finally, it explains how Big Data technology supports businesses by improving product quality, securing information, aiding in business forecasting, optimizing resource use, and attracting potential customers. The report includes a digital poster in the appendix summarizing the key points, and it cites several relevant academic references. This report is submitted by a student and available on Desklib, a platform offering AI-based study tools for students.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Summary Paper
Submitted by:
Name:
ID:
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Contents
Introduction 3
What big data is and the characteristics of big data 3
The challenges of big data analytics 3-4
The techniques that are currently available to analyse big data
4-5
How Big Data technology could support business, an explanation with
examples 5-5
References 6
Appendix 1: Poster 7
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Introduction
Big Data is a large activity cycle which analyses the huge information to
reveal data which helpful for the business firm to make abreast decision forecasting.
It includes market trends, client or customer satisfaction, hidden figure and
correlation (Manjunath and Hegadi., 2018). In the following report, the discuss are
related to big data such as functions of big data, meaning and challenges of big
data, methods that are presently accessible to observe the big information and at
last ideas of the huge collection which helps the business concern along with its
examples. In appendix one digital poster are also attached which cover all the points
of the following report in a suitable way.
What big data is and the characteristics of big data
Big data is a group of information which are gathered from several new
sources. In other words, it is data which are researched by researcher as a primary
data. It is basically including bunch or combination of many types of information
related to the particular sector or whole economy that are large of velocity and
volume. It is used by the business firms, industries, hospitals, agriculture department
and many more to increase its profitability, growth and adopting new technologies.
Big data consist four characteristics which is followed V's that are as follows:
 Volume (Mass): The data are collected from primary source are always
presented in a raw or scatter form. After collecting all initial information in raw
form, the business enterprises or the researcher creates tables, graphs or
charts for understanding the data easily and appropriately. The main
importance of this data is, it contains quality data, facts and case studies. The
organization uses this gathered data for targeting the profitable market.
 Varieties: Big data is collected in various form because it is collected by the
researcher himself for a particular objective (Ansari and Li, Y., 2018). These
data are always presented in two forms unorganized way or semi-organized
way it is depend on the situation or work. The semi organized or structured
information include poster, images, texts and sometimes a clip of video and
the unorganized contain manually written messages, recordings or voice
mails.
 Velocity (Speed): Velocity is referring as the average or minimum taken by the
researcher or business firms to gathered the data.
 Value: Value is referring as most necessary element at the time of big data
collection. It always tries to gather the useful information which helps the
business concerns to make more profit and company growth.
The challenges of big data analytics
In present time, the population attract only on those products or service which
are advanced and brand new. It is easy to say that technology is an important
source of income to develop the economy and business market.
 Less number of knowledgeable peoples: Every firm or organization wants to
increase its profit and expands its business in a short period of time. For
implementing this organization need a skilled or knowledgeable person for
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their operations which include social media handler, IT specialist, engineers
and so on. The organization also appoint those people who are helpful to run
the organization such as MIS executive, operation executive, manager,
director, etc. Currently all business firm have its own portal and software
where they record all the day to day information (Shehab, Taher and
Mohamed., 2021). But the main issues are created when the competitors
create some special goods and service using new tools and technologies and
attracts large numbers of customers and clients. Due to this practice profit
and incomes of the other company are decreases because they create
monopoly. To Cover up this situation manager appoint experienced
professionals.
 Problem in collecting information: It is big challenge for the researcher to large
quantity data in a proper way and it is also creating problematic condition for
the business enterprises to maintain this big data because it is not say that
researched provide a structured information. It may be in a form of semi-
organized or unorganized because it brings from different sources.
 Confusion in selecting appropriate techniques: It is always a problematic
situation that what tool should be consider to find out or analyze the big data
because it is a very vital practice to allocate a single method for
understanding the information properly (Hauck, Morgensternand and Kliewer.,
2019). The whole data is depending on the techniques; it indicates whether
the collected are useful or not.
 Security of information: Each and every organization tries to secure its data
from outsiders because If its leaks, it creates problem for the business. But
generally big data have a high chance for escape. Big data contain large
process such as observing, arranging and summarizing that it not easy to
secure.
 Low level of Understanding: The analysis of big data is not a small or
understandable for every one that is why it needs some skilled person to
observing the information and these people are known as professionals and
these skilled professionals demands large money. Due to this organization
appoint unexperienced employees and faced the business failure conditions.
The techniques that are currently available to analyse big
data
The company generally uses new techniques and method for growth and
development of the business. In present time, McKinney’s find out the different
methods for presenting and analyzing the big data such as quantitative method.
Some of techniques are explained are as follows:
1. A/B testing method: It is a type of method with inter link the control group to
several form of testing group for figuring out which techniques are useful for
the business (Seddik, Routaib and El Haddadi., 2021). It also makes a theory
of variables that contain both independent and dependent variables.
2. Information fusion and integration: This type of method indicates that data
are present in a form of various techniques mixture from large sources and
solutions. This practice ensure that data are concluded and interpreted at last.
3. Statistics: It is term which is presented in the form of numerical data or
quantitative data. These data helpful for easy and quick understanding and
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also helpful at the time of comparison and analyses. This tool is basically
divided into two parts descriptive series or inferential series and helps in
measuring the central tendency and examine the data respectively.
4. Machine learning: It is most useful and fast technique to observe the
collected report. This tool helps to record, save and share the data quickly
and fruitfully. There work should be done in a computer, laptops and in other
type of recording machines (Segooa and Kalema., 2018). It also gives the
suggestions or ideas to done the work properly and accurately.
5. General language implementing: It is the type of tool which predict the
human language. It is referred as several names that are artificial intelligence,
computer science and scientific discipline. This method also helps to analyses
whether the data are correct or not.
6. Data mining: This method provides the accurate form of data through
mathematics, statics and learning of machine. It is basically gives the right
amount of data by eliminating the useful information. After that, it useful for
the organization to observe the easily.
How Big Data technology could support business, an
explanation with examples
Big data is useful of the business enterprises to understand the market
environment and current trend. This is taken place on behalf of the customer needs,
demands and satisfaction in terms of product and services. Presently buyers
attractive on those goods which are prepared with new technologies and ideas. In
the following several types of technologies are described in context of the business:
 Increase the quality of goods: Business organization always try to sells its
goods and services in large quantity to improve its performance. It is taken
place with the help of big data because it analyzes the needs of customers.
The company also uses big data in updating the product quality and
modification.
 Secure and safe the information: The analyses of big data helpful in providing
the correct information and also helps in securing the information from errors,
frauds and leaking risks (Fries., 2021). These data are kept in the
technologies such as computers.
 Business forecasting and decision-making: The collection of big data report
helps the organization in proper decision making because this information
provide the case studies and ways to improve the growth and development. It
also helpful to comparing the one company to another.
 Effective and efficient use of natural resource: Big data collection take more
time but these collected data are always primary and quantitative. After this
company is helpful in securing and utilizing its natural effectively and
efficiently without any wastage.
 Attracts potential customers: Researcher gather the big data according by
remembering the customer sanctification and needs because they are major
source of income and business expansion (Meier., 2019). The organization
ensure that the production of goods need to done on the basis of customer
demand. It also provides what type or product or technology are in trend or
business profit making.
References
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Manjunath, T.N. and Hegadi, R.S., 2018, December. Literature Review on Big Data
Analytics and Demand Modeling in Supply Chain. In 2018 International
Conference on Electrical, Electronics, Communication, Computer, and
Optimization Techniques. (ICEECCOT) (pp. 1246-1252). IEEE.
Ansari, A. and Li, Y., 2018. Big data analytics. In Handbook of Marketing Analytics.
Edward Elgar Publishing.
Shehab, R., Taher, M. and Mohamed, H.K., 2021. Live big data analytics resource
management techniques in fog computing for tele-health
applications. Jordanian Journal of Computers and Information
Technology. 7(1).
Seddik, S., Routaib, H. and El Haddadi, A., 2021. Harnessing Machine Learning and
Big Data Analytics for Real-World Applications: A Comprehensive
Survey. Proceedings of the Computational Methods in Systems and
Software. pp.734-747.
Fries, T.P., 2021, December. Big Data Analytics Using Fuzzy Clustering for Network
Security. In 2021 IEEE International Conference on Big Data. (Big
Data) (pp. 5894-5896). IEEE.
Segooa, M.A. and Kalema, B.M., 2018, March. Leveraging big data analytics to
improve decision making in South African public universities. In 2018
IEEE 3rd International Conference on Big Data Analysis (ICBDA) (pp. 9-
13). IEEE.
Meier, A., 2019. Big Data Analytics. HMD Praxis der Wirtschaftsinformatik. 56(5),
pp.879-880.
Hauck, F., Morgenstern, S. and Kliewer, N., 2019. Big data analytics im
Bahnverkehr. HMD Praxis der Wirtschaftsinformatik. 56(5). pp.1041-1052.
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Appendix 1: Poster
Paste your digital poster here
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