BSc (Hons) Business Management: Big Data Analysis Report, BMP4005

This report provides a comprehensive analysis of big data and information systems, focusing on the characteristics of big data, including velocity, variety, volume, value, veracity, and variability. It explores the challenges associated with big data analytics, such as inaccurate analytics, long system response times, complex data analytics, and the high cost of maintenance. The report then delves into various techniques used for big data analysis, including machine learning, social network analysis, and association rule learning. Furthermore, it examines how big data technology can support businesses, providing examples of increased market intelligence, better customer insight, smarter recommendations, agile supply chain management, and data-driven innovation. The report concludes by emphasizing the significance of big data analysis and information systems in enhancing organizational operations and decision-making.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
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Name:
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Table of Contents
Introduction................................................................................................................................2
What big data is and the characteristics of big data ............................................................2
The challenges of big data analytics......................................................................................3
The techniques that are currently available to analyse big data ......................................4
How Big Data technology could support business, an explanation with examples .............4
Conclusion.................................................................................................................................6
Poster.........................................................................................................................................6
References .................................................................................................................................7
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Introduction
Big data information system is defined as the combination of different kinds of data and
data can be structured, unstructured and semi- structured. These data and information can be
used by the organization in different ways such as analysis of the application by using
advanced technology, storing data securely and in learning projects. Whereas information
systems is a set of elements which provides gathering, storing and processing of data in
respect to provide information and technology. Big data analysis is a advanced techniques
used for diverse data sets (Dartmann, Song and Schmeink, 2019) . The aim of this report is
evaluate the characterize of big data, challenges of big data analysis, techniques that
evaluates big data and these technology supports in enhancing working structure.
What big data is and the characteristics of big data
Big data refers to the data which comprises huge collection of data sets which is large in
size and available in different forms. It uses to mine or generate the information and uses the
information for the enhancement of the organization. This can be used in by different
organization in respect to make progress in their data sets and evaluate information that is
relevant for organization. It has different characteristic which generates in-depth knowledge
about the big data. It has various characteristic which gives detail understanding about the
big data, some of them are discussed below:
 Velocity- It is defined as the speed at which data is being created in the real time. It
comprises various rates that makes change in data, linking and connecting incoming
data in daily operations.
 Variety- This characteristic state that there are huge variety of big data such as
unstructured data, semi-structured data and structured data , these are collected from
multiple sources(Hopkins and Hawking, 2018) . Before Big Data data could only be
used in making of spreadsheet or database forms but in the current scenario there are
multiple variety in it which includes PDFs, photos, videos and many more.
 Volume- It comprises the size and amount of data that companies used in respect to
make analysation. Big data manages huge volume of data in the daily operations of
companies.
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 Value- The most important characteristics of big data is that it usually generated by
in-depth discovery and pattern recognition which gives more impactful results and
develops stronger relations with consumers.
 Veracity- There is another important characteristic which helps in managing data in
more accurate ways. At times it helps ion generating executive level confidence.
Variability- Big data helps in altering nature of data by managing it relevantly and in detail
analysation.
The challenges of big data analytics
There are various challenges that is being faced by organisations in a way of
implementing big data analytics which is given below:
 Inaccurate analytics- If the companies completely depend on the big data in respect to
manage their information and data then they may face some defects and error in the
information system (Hung, He and Shen, 2020) . Inaccurate data some times results
in mismanagement in the understanding of the knowledge and then it reflects on the
profitability and success of the company.
 Long system response time- There are times where generating information takes
much time than needed and it become challenging for batch processing. Taking time
in in-depth analyzing data delayed company projects and working patterns.
 Long system response time- Another issue which is faced by the organization in using
big data is that it becomes way more complicated when used by the different
companies. At times organization finds it difficult to generate value from various
datasets. This challenge may occur because of misinterpretation in data visualization
and because of over engineered systems.
 Expensive maintenance- Using outdated technology in the analyzing of data does not
generate impactful results but implementing machinery requires lot of investment.
Implementation of new technology process data in more faster way but because of
much expense some companies are not ready to implement it.
The techniques that are currently available to analyse big data
There are different techniques that are currently available in big data analyzing, some of them
are described below:
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 Machine learning- It comprises data that learn from software. It generates capability
to learn the systems without programmed. It is very impactful in learning what user is
expecting and provides recommendations based on the information. It also very
impactful in giving appropriate content in order to attracting more customers.
 Social network analysis- This a method which is used in telecommunications sector, it
is also useful for sociologist in order to analyses interpersonal relationships
(Maheshwari, Gautam and Jaggi, 2021) . Social network evaluation used in
explaining different social structure in making customer base and for generating direct
ties in respect to connect individual.
 Association rule learning- It is the techniques of determining interesting relations
between different variables and have large database. It helps mainly in placing
product in better proximity, extracting data of the visitors from websites and check
systems logs in respect to detect inappropriate activity.
How Big Data technology could support business, an explanation with examples
Big data allows various business organizations in order to manage customers in wider
aspects. It evaluates ways by which organization cam engage with their customers in real life.
It manages different sets of data and analyses it for generating information which is very
beneficial for organization (Papadopoulos and Balta, 2022) . In the context of organization it
provides various benefits to it , some of them are discussed below:
 Increased market intelligence- Big data evaluate the complex behavior of the
customers in detail and also provide wide understanding of the market place with its
changing dynamics. By analyzing various aspects helps organizations in the product
development and also assist in modern market intelligence.
 Better customer insight- Big data evaluates its customers and their needs and
generates them wide range to choose from. It gives information from internal and
external sources through surveys, external sources of organization, through social
media activity and many more.
 Smarter recommendations and audience targeting- It analyze the information from
various sources and enforce it in making changes in the techniques and methods of
the company. It majorly helps in targeting the buyers . Example- If a customer is
checking different sites in order to check the new range of tops and jeans then big
data consumes that information and use it in making change in organization.
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 Agile supply chain management- Another benefit o big data that its helps in
integrating data on the basis of customer needs and trends from various sites, retail
application and by suppliers data. It also develops the information on real time
processing of the goods and services which results in effective supply chain
(Upadhyay, and Kumar, 2020). Example- It generates constant information about the
supply chain of the companies, which results in making work more effective and
faster.
 Data driven information- There are different tools and technology that are available
in the market in respect to make enhancement in the products and services. It
provides data that informs about the changes that are taking place with that is shares
implementation of the innovation in different products.
Conclusion
From the above report it is concluded that big data analysis and information is an important
aspects in the working of the organization. This reports covers multiple aspects of big data
analysis and information systems. This report covers the meaning and characteristic of the big
data which are Velocity, Variety, Volume, Value, Veracity and Variability. Apart from that it
also covers the challenges and issues in implementing big data such as inaccurate analysis,
long system response tome, expensive maintenance and complicated data analytics. The
techniques that used with big data are association rule learning, machine learning and social
networking analysis. At last it discusses about how big data provides benefits to the
organization and supports business. It supports in multiple ways such as better customer
insight, increasing market intelligence , smarter recommendations and audience targeting and
data driven innovation.
Poster
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References
Dartmann, G., Song, H. and Schmeink, A. eds., 2019. Big data analytics for cyber-physical
systems: machine learning for the internet of things. Elsevier.
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Hopkins, J. and Hawking, P., 2018. Big Data Analytics and IoT in logistics: a case study. The
International Journal of Logistics Management.
Hung, J.L., He, W. and Shen, J., 2020. Big data analytics for supply chain relationship in
banking. Industrial Marketing Management, 86, pp.144-153.
Maheshwari, S., Gautam, P. and Jaggi, C.K., 2021. Role of Big Data Analytics in supply
chain management: current trends and future perspectives. International Journal of
Production Research, 59(6), pp.1875-1900.
Papadopoulos, T. and Balta, M.E., 2022. Climate Change and big data analytics: Challenges
and opportunities. International Journal of Information Management, 63, p.102448.
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.
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