Big Data Analysis for Business Management: Characteristics, Challenges, Techniques and Examples

This report discusses the characteristics, challenges, techniques and examples of Big Data Analysis for Business Management. It explains how Big Data technology could support business with examples. The report also includes a poster and accompanying paper on Information Systems and Big Data Analysis.

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
1

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
2

Introduction
Big data is one of the field that helps the organisation to analyse and treat in
the information in an effective manner. It is seen that managing the data is a
complex process and there is requirement of a software that assist in data
processing (Oussous and et.al., 2018). It is designed to use, analyse, store the
information in an effective manner. In this report there is discussion related to
characteristics of big data. It is necessary to deal with the challenges in big data
analytics so they are also examined. The techniques that help business organisation
to use big data are also mentioned in the report. In the end of this report some
examples of organisations using big data are mentioned.
What big data is and the characteristics of big data
The business organisations are need of huge information and it is difficult to
handle the same. Big data helps them to manage the information and use it in an
effective manner. The 5V's of big data show the characteristics and the discussion
related to same is underneath:
Volume: It is seen that volume of data collected is huge. The information
being generated by the big organisations is also enhancing. The various platforms
such as social media, IoT devices, financial transactions, videos, and customer logs
are source from which the organisation is being generated (Olivera and et.al., 2019).
3

Earlier storing this was problematic for the business organisations. But now due to
availability of big data business organisations are able to process the data in an
effective manner. The volume of data varies. To illustrate the size of document is in
few kilobyte and the video is in megabytes.
Variety: It is another important characteristic of big data. It means that the
nature of data varies. It is seen that source of data keeps on changing. It is also
updating so that the storage becomes easier. It is seen that earlier data was stored
in database and spreadsheet. Now it is present in the form of PDF, audio, video,
photos etc.
Velocity: It shows the speed at which data is generated. It also helps to know
about the speed of processing the data. It is necessary to note that after analysing
and processing of data the needs and wants of clients can be fulfilled.
Value: It is the most important characteristic of big data. It is seen that speed
of data and other things will not matter if there is value of the data being collected. It
reliability and usefulness of the information matters the most (Coble and et.al.,
2018). The raw data must be converted into information so that value can be created
from the same. The process of converting raw data into useful information creates
value.
Veracity: It is connected to the last discussed characteristic. It shows the
trustworthiness of the data. The data that the business organisation encounter is
unstructured. It is important to filter the information and and use the necessary
information (Characteristics of Big Data: Types & 5V’s, 2020).
These are the characteristics of big data. All of them play a vital role in
collecting, generating and using the data in an effective manner.
The challenges of big data analytics
Data growth issues: It is identified that it is one of the first and foremost
challenges that comes in big data is to store huge data sets in an effective way.
Every day the quantity of data is increasing rapidly. Due to this, it is found that the
storage space is limiting as the data growth issues are increasing (Blazquez and
Domenech, 2018). This is very important for an organisation to take measures as the
space is limiting.
Lack of proper understanding of massive data: Due to insufficient
understanding, now companies are failing in big data initiatives. It is not compulsory
4

that all employees are now about what data is, its importance, processing, storage,
and sources. This will results in not managing big data. This can be understand with
the help of an example. For example, if it is found that employees are not know
about the importance of knowledge storage. This will results in not keeping database
in an effective way.
Lack of knowledge professionals: It is found that companies require highly
qualified and skilful employees in order to run large data tools and modern
technologies. Professionals include data analysts, data scientists and data engineers
who work in giant data sets (Tabesh, Mousavidin and Hasani, 2019). It is found that
organisations are facing many challenges of lack of professionals who have enough
knowledge. It is very important to find professionals so that they can manage bid
data in an effective way. This will creates problems for an organisation as they are
not able to manage the situations effectively.
Confusion while Big Data Tool selection: This is other important issues in
big data challenges which is related to selection of big data tools. It is crucial for an
organisation that they should select the most appropriate tool. Confusion is create
selection process of big data tools. Confusion is creating problems in organisation.
The techniques that are currently available to analyse big
data
Big data is important for today's organisation as they have to deal in huge
information. The techniques that are used to analyse big data are as follows:
Association rule thumbing: This method helps the organisation to discover
the correlation among variable in large database. It helps to know about the factors
that helps to enhance the sales of the company (Schroeder, 2019). The touch points
5

that helps to enhance customer experience are also mentioned and studies under
this technique.
Classification Tree analysis: It is a method that helps to identify the
category to which new observations. The three statistical classifications under this
technique are as follows:
 Assign the documents automatically
 Categorisation
 Develop profiles
Machine learning: It means using software that helps to learn from the data.
It is the ability of computer to without being programmed (Lv and Qiao 2020). It helps
to make predictions on the properties learned from set of training data.
Regression analysis: Under this technique the independent variable is
manipulated to know about its influence on the dependent variable. It helps to know
about the value of dependent variable (Qi, 2020). It helps the business organisation
to know about how customer satisfaction affects the loyalty of customer.
Sentiment analysis: It helps researchers to know about the sentiments of
writers or speakers. It is necessary so that the business organisation is able to make
improvisation and changes accordingly.
Social network analysis: It is a technique that is used by telecommunication
industry in order to enhance relationship with the customers. It helps analyse the
relationship in an effective manner. It helps to know about the areas of improvement
and to influence others.
These are some of the techniques that are being used to analyse big data. It
helps the organisation to fulfil their purpose.
How Big Data technology could support business, an
explanation with examples
It is necessary for the business organisation to use big data. As it directly
support the business organisation and helps in achieving goals and objectives
effectively. It is seen that Tesco is a multinational organisation that uses big data. It
helps the organisations in retain sector to gain advantage over the competitors and
serve best to the customers. It supports the business organisation to know about the
taste and preference so that they are able to provide best value to the customers
6

(Wang, Sherratt and Zhang, 2020). It also helps the customers to use their smart
phones to make orders and get them delivered.
It is also seen that business organisation in hospitality industry uses big data
to know about the trend in market. They are able to bring innovation and use
updated technology by getting right information related to the same. It is important
for them to use the information in an effective manner and satisfy the needs and
wants of customers (Leonelli, 2020). The use of latest technology helps them to
serve best to the customers. It is advantageous for them to use the analysis of
resources in an effective manner.
Conclusion
From the above report, it is analysed that big data is an effective way of
generating and using the information in an effective manner. It is seen that the
company must use the data is such a manner that they are able to achieve success.
The characteristics of big data are mentioned in the starting of this report. Afterwards
the challenges while using big data are analysed. It is necessary to know about the
techniques that help the organisation to adopt big data, they are also mentioned. In
the end of the report the benefits of bug data related to business organisation are
mentioned.
Poster
7

References
Books and Journals
Blazquez, D. and Domenech, J., 2018. Big Data sources and methods for social and
economic analyses. Technological Forecasting and Social Change, 130,
pp.99-113.
Coble and et.al., 2018. Big data in agriculture: A challenge for the future. Applied
Economic Perspectives and Policy, 40(1), pp.79-96.
Leonelli, S., 2020. Scientific research and big data.
Lv, Z. and Qiao, L., 2020. Analysis of healthcare big data. Future Generation
Computer Systems, 109, pp.103-110.
Olivera and et.al., 2019. Big data in IBD: a look into the future. Nature Reviews
Gastroenterology & Hepatology, 16(5), pp.312-321.
Oussous and et.al., 2018. Big Data technologies: A survey. Journal of King Saud
University-Computer and Information Sciences, 30(4), pp.431-448.
Qi, C.C., 2020. Big data management in the mining industry. International Journal of
Minerals, Metallurgy and Materials, 27(2), pp.131-139.
Schroeder, R., 2019. Big Data. Society and the Internet: How Networks of
Information and Communication are Changing Our Lives, p.180.
Tabesh, P., Mousavidin, E. and Hasani, S., 2019. Implementing big data strategies:
A managerial perspective. Business Horizons, 62(3), pp.347-358.
Wang, J., Yang, Y., Wang, T., Sherratt, R.S. and Zhang, J., 2020. Big data service
architecture: a survey. Journal of Internet Technology, 21(2), pp.393-405.
Online
Characteristics of Big Data: Types & 5V’s, 2020 [Online] Available through
<https://www.upgrad.com/blog/characteristics-of-big-data/>
8