BMP4005 - Information Systems & Big Data: Supporting Business

This report provides an overview of big data analytics, its characteristics (velocity, volume, value, veracity, variety), and the challenges associated with its implementation, such as managing large data volumes, collecting meaningful data, visual representation, and handling multiple data sources. It explores various techniques for analyzing big data, including data fusion, A/B testing, data mining, and machine learning. The report further discusses how big data technology supports businesses by enabling data-driven decisions, improving customer understanding, and identifying new growth opportunities, with examples from companies like Tesco and Morrison. It also touches on the impact of big data and automation on HR functions and revenue generation. The document concludes with a digital poster and references, and is available on Desklib, a platform offering a range of study tools and resources for students.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Contents
Introduction p-3
What big data is and the characteristics of big data p-3
1

The challenges of big data analytics p-3
The techniques that are currently available to analyse big data
p-4
How Big Data technology could support business, an explanation
with examples p-5
Poster p-6
References p-6
2

Introduction
Information systems can be considered as an integration of different set of
components which helps in the collection, storing and processing of data so that the
information can be provided to defined users. Furthermore, big data analytics can
be defined as using the advanced analytic techniques which is helpful in large data
sets which covers the structured or the unstructured data(Galetsi and Katsaliaki,
2020). In a more simple way, it can be defined as the technology which is provided
by big data analytics to make the analysis of data sets and to collect or gather the
information. It is used by companies so that they can make their decisions on the
basis of great productivity and can make some improvement in the data driven
decisions. Every data analyst make the collection and processing of information so
that they can make the conventional use of programs. This report will cover
characteristics of big data, challenges of big data analytics, the techniques which
are available for big data and in which way big data can support businesses.
What big data is and the characteristics of big data
Big data analytics can be considered as a process which covers the
collection, organization and analysis of the large sets of data so that their can be a
discovery of useful and productive information. This technique helps the companies
to make the better understanding of the information which is contained in the data.
The analysis of data helps the company to develop the understanding that if the data
is important for them or not. The characteristics of big data have been discussed
below-
 Velocity- It refers to the speed at which the data is processed in which the
higher speed is considered to be most important for the better performance of
data. The velocity will involve different components covering rate of changes,
income data sets.
 Volume- It refers to the amount of data which company is having which is
measured with the help of gigabytes, yottabytes and zettabytes and this is
going to rise in coming years(Rodger, Chaudhary and Bhatt, 2019).
 Value- It is the benefit which company is going to get from the big data which
is useful for the business. The valuable data which will be provided in big data
3

can be helpful to develop different strategies with which it will achieve
success.
 Veracity- It means the information which is been analyzed is useful or reliable
to the company or not. But Veracity provides the ways by which the data
which has been collected or processed can be handled or managed in a
proper way.
 Variety- It refers to the different types of data by which big data can be
developed which covers structured or unstructured. But every type of data
makes some effect on the performance of a company.
The challenges of big data analytics
There are different challenges which the managers of a company have to analyze
and those difficulties are discussed below-
 The amount of data collected- The quantity of data which is available in the
present time is huge as the information is collected at every stage of
interaction of data(Upadhyay and Kumar, 2020). So for removing such type of
challenges it is important there is availability of some type of data system
which can be useful to the business in collecting and making the organisation
of information in an automatic way.
 Collecting meaningful data- As the availability of information and data on
this technology is huge so it becomes very difficult to access the right and
correct data. When employees in a company will be provided with such huge
information then they will also not focus on each information which will be
helpful in adding true value.
 Visual representation of data- When the data is represented in a graph or in
a visual manner then it creates more likely to the employees. Big data tool is
considered to very useful technique but it does not provides the visual graph
and making of such type of graph can at time makes it irritating to the
employees.
 Data from multiple sources- The other problem which is faced from big data
is that to make the analysis of sources from where the data have come from.
4

There are some of the sources which are not useful and can provide not that
reliable information to the business.
The techniques that are currently available to analyze big
data
There are different techniques which can be uses by businesses to make the
analysis of big data and those techniques are been discussed below-
 Data fusion and data integration- This technique is useful in that area
where there is a combination of different set of methods which helps in the
analysis and integration of data from different and multiple sources(Centobelli
and Ndou, 2019). When such integration takes place then at this time the
solutions and results which are provided to the management of a company is
also more reliable and accurate.
 A/B testing- This technique is useful for making the comparison from the
control group to different types of test group so that it can be identified that
what new changes or improvement can be made to any of the objective
variable.
 Data mining- This is the most common tool which is helpful in the analysis of
big data technology. In this method different patterns of information and data
sets are being extracted with the method of data mining through the help of
statistics and machine learning.
 Machine learning- Machine learning is the methodology which takes the help
of different software which can learn from the different data sets. This method
is developed on the basis of different algorithm of computers which can
provide the best assumptions that if the information provided by the big data
analytics is right or not(Teng and Khong, 2021).
5

How Big Data technology could support business, an
explanation with examples
Big Data is a compilation of all procedures and instruments connected to the
use and management of big data sets. With Big Data, business organizations can
utilise statistics, and find more beneficial consumers. It can also assist the firms to
generate fresh brands, services, and commodities. This concept assists the
businesses to acknowledge the designs, styles, and choices, it is a large website
created which leads to the interaction with individuals of different systems(Kauffmann
and et. al., 2020). Big data will assist the firms to use their information or data and
utilise them to recognise new chances. That will result to smart business ventures,
important functions, increment in profitability and happy consumers.
Various examples related in which big data support the business are:
Big Data allows businesses the instruments they require to build smart decisions
which are related to data not speculation or feelings. But for that, everyone in the
firm must have approach for the data they require to upgrade their decisive making
process. Tesco use big data in which data should not be extended to be the only
realm of IT departments and analysis. Instead, users across the Tesco should be
capable in the analysis and look into the data so that they can give solution to their
critical business queries. Tesco has an access to data which is known as data
regularisation. It contains various flows of internal and external data which can be
divided for delivering different perceptions.
Morrison use big data to deliver a great service to their consumers. They know many
things about their consumers from what they want to purchase etc. and also they
start to tackle the capability of their understanding to meet their better needs.
Big Data generate many new chances for growth and development. It may even
result in a new class of businesses like those that recognise and compile the whole
sector data. Most of the firms will be surviving in the centre of a great flow of data
about services and commodities, suppliers and customers, intentions of customers
and preferences, and many more(Swaminathan, 2018). Firms in all industries should
begin creating their Big Data abilities with a great strength. Big Data assists a firm in
a variety of ways in which it is utilised in both the public and private sectors.
6

HR Company of Asda helps in improving all the business operations of the company
which includes robotics and automation. Big Data and automation has the ability to
change that completely or at least magnifying various human-related procedure from
hiring to learning and growing of a business. For example, chat bots are now utilised
to solve the common staff queries, and AI-based teaching courses can detect when
a trainee has difficulty holding a specific lesson(Chatfield and Reddick, 2018). Big Data
is not only about increment in the working procedure and decision making, or
understanding more and various things about workers and consumers of the
company, data can be watched to increase revenue or create alternative revenue.
Poster
Paste your digital poster here
7

References
Centobelli, P. and Ndou, V., 2019. Managing customer knowledge through the use of big
data analytics in tourism research. Current Issues in Tourism. 22(15). pp.1862-
1882.
Chatfield, A.T. and Reddick, C.G., 2018. Customer agility and responsiveness through big
data analytics for public value creation: A case study of Houston 311 on-demand
services. Government Information Quarterly. 35(2). pp.336-347.
Galetsi, P. and Katsaliaki, K., 2020. Big data analytics in health: An overview and
bibliometric study of research activity. Health Information & Libraries Journal.
37(1). pp.5-25.
Kauffmann, E. and et. al., 2020. A framework for big data analytics in commercial social
networks: A case study on sentiment analysis and fake review detection for
marketing decision-making. Industrial Marketing Management. 90. pp.523-537.
Rodger, J.A., Chaudhary, P. and Bhatt, G., 2019. Refining information systems
competencies: the role of big data analytics resilience in organisational learning.
International Journal of Business Intelligence and Systems Engineering. 1(3).
pp.226-250.
Swaminathan, J.M., 2018. Big data analytics for rapid, impactful, sustained, and efficient
(RISE) humanitarian operations. Production and Operations Management. 27(9).
pp.1696-1700.
Teng, S. and Khong, K.W., 2021. Examining actual consumer usage of E-wallet: A case
study of big data analytics. Computers in Human Behavior. 121. p.106778.
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.
8