BSc Hons Business Management: Information Systems & Big Data Analysis

This report provides an overview of big data, defining its characteristics (volume, velocity, variety, veracity, and value) and exploring its evolution. It discusses the challenges associated with big data analytics, including inefficient knowledge, lack of skilled professionals, data growth issues, and security concerns. The report also outlines various techniques used for big data analysis, such as A/B testing, data fusion and integration, data mining, machine learning, and natural language processing. Furthermore, it highlights the advantages of utilizing big data to improve organizational performance, focusing on gaining competitive advantages, redeveloping products, and ensuring data safety, citing Asda as an example. The report concludes with a list of references used for the analysis.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
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Contents
Table of Contents
Introduction................................................................................................................................4
What big data is and the characteristics of big data ............................................................4
The challenges of big data analytic.......................................................................................5
The techniques that are currently available to analyse big data ........................................6
How Big Data technology could support business, an explanation with examples..............7
References .................................................................................................................................7
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Introduction
A big data is defines about the variety data which contains greater variety, arriving in increasing
volumes and with more velocity. The big data has been described with some management of data
with huge overwhelming amount of information (Saide and Sheng, 2020). As exact evolution of
big data includes number of preliminary steps of foundation. Through providing the big data used
by the multinational companies on which evolution of modern technology is interwoven with the
evolution of big data. The foundation of big data becomes an issue for the US census bureau in
1880. They estimated it would take eight years to handle process of data collected during 1880
census and predicated the data from 1890 more than 10 years of process. In this report,
characteristics and challenges of big data along with techniques which are currently used to
analyze big data.
Explanation and features of Big Data
Big Data is term that used to describe large, hard to manage volumes of data. This is
specifying about both structured and unstructured that inundate business on day to day basis. This
big data as been analyzed for insight that improve their decision and give confidence for making
strategic business moves (Dinh, Karmakar and Kamruzzaman., 2020). There are the five
characteristics of Big Data on which company regulates their business through effective manner: Volume: This is first feature of Big data, it depicts about that companies manage
skyrocketed around 2012. As they began collecting more than three millions pieces of
every individual data. Velocity: It is second feature of big data where the companies need that information to
flow quickly as to close real time possible. As the Velocity can be more important
than volume because it gives us bigger competitive advantages. There is sometimes to
having better limited data in real time that has lots of data in low speed. Variety: This is third feature of big data as it is one of the most crucial element as it
refers to gathered of data from various sources and their income. The origin of
massive data has been altered in recent years and now it is available through photos,
audio files, text files and PDF. Veracity: This feature of big data is linked with the value features, which can be
defined as the accuracy relative to combined massive and massive data as majority
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information get encountered is unorganized. It makes crucial to separate important
and essential data for better definition.
 Value: This is an important feature related to big data as it helps to collect the data to
present the valuable information and reliability for analyzing it successfully. This is
important for the raw material which is reliable and valuable to better clear the
irrelevant data for identify the pattern analysis.
Problems with the utilization of Big Data
Big Data is also important to analysis of an organization to better understand where
the risk management to assist for improvement the procedure to making effective decision
making (Côrte-Real, Ruivo and Oliveira., 2020). This improves accountability; bring
financial, life or health for employees to guide and also monitor the performance for further
development and also to predict the losses. There are many challenges that may be faced buy
an organization while using big data that are elaborated below.
 Inefficient knowledge about Big-data and its uses: There is shortage of knowledge
and skills to handle the big data where it is proceeding, stored and it overall value
have been challenged for various organisation. There is improper and inadequate
knowledge and understanding about big data within an organization leads towards the
inefficient and ineffective use of this big data..
 Lack of Knowledge professionals: This is important to have skilled and talented
professionals in order to successfully run modern technology and large data tools. In
the organisation requires skilled data scientist and analysts along with engineers. This
has been one of holding challenges of big data analysis due to lack of such
professionals in the industry.
 Data Growth issues: This is among the primary challenges of big data that the
systems like cloud computing and cloud storage handling issues are also required. To
collect higher quality information stored at cloud based systems of organization is
declining from massive platform.
 Securing Data: It is a mere problem in the big data analysis that security theft and
cyber security are increasing in the rapidly evolving technological world. The better
process, storing and analyzing the data through organization miss out with crucial
elements of security that leads to security theft (Nadikattu., 2020). This is the type of
unprotected data can be utilized to mitigate the risk of hacker.
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Available Techniques of Big Data Analysis
Some of the techniques to collect Big Data are required to analysis and storing it in an
optimistic manner. For utilizing Big Data, it is critical to search for yje best techniques for
managing it that can help to develop best results.
In following there are various techniques has been mentioned as below: A/B test: This technique involves that determines for effective comparison of a
various test group with controlled group of data in order to discrete suitable or
alteration which would enhance more provided target available. Data fusion and data integration: This techniques focus on combining set of
techniques in order to analysis along with integrates big data from various origins
from solutions (Anshari and Sumardi, 2020). This would provide successful insights
to collect the accurate data which are relative collected from individual origin. Mining data: It is been referred as common instrument and techniques in order to
analyses along with integrate towards mining of data and extracting effective structure
and software within the database. It can help to acquire useful data effectively and
efficiently.
 Machine learning: The machines that learn through artificial intelligence can be
helpful to make effective use of Big Data and utilize it to create better effective
results. The machine learning also helps to s create effective results and performance
of the business operations.
 Natural language processing: According to this technique and analyzing human
languages through improving sub sets with computing machines sciences for
linguistic intelligence.
Advantages of Big data to Improve Organizational Performance
The utilization of Big Data is very effective and it can help to increase the performance of the
organization which is very important to the people. Big data can be utilized to collect,
classify, present, analyses and interpret the consumer data in order to understand customer
needs and market trends to create products and services that attracts maximum customers.
The major benefits that can be gained by the company by utilizing big data are as follows:
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 Gain Competitive Advantages: Big data provides information about the customers by
collecting, classifying, presenting, analyzing and interpreting the consumer data in
order to understand customer needs and market trends to create products and
services that attracts maximum customers.
 Re Develop Product: The effective analysis of Big Data provides assistance to an
organisation in order to understand about where the product is exactly lacking in
terms of quality or prices. Through this, customer behavior also measured to
purchase the customer within their overall behavior overall organisational product.
 Data Safety: Utilizing the big data can provide higher safety of the company’s data
by providing backup options so that recovery can be done with the help of cloud
software and other techniques. This enhances the security of the data on the physical
level because even if the physical data is destroyed the digital backups can be
utilised.
For Example Asda utilizes Big Data technology for providing assistant to the organization in
determining the completion, market trends, customer demands, changing environments, data
backups etc. (Vitari and Raguseo, 2020). The big data also helps to optimize data of the
company and retrieve the useful information if they are physically fragile.
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Poster
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References
Saide, S. and Sheng, M.L., 2020. Toward Business Process Innovation in the Big Data Era: A
Mediating Role of Big Data Knowledge Management. Big Data, 8(6), pp.464-477.
Dinh, L.T.N., Karmakar, G. and Kamruzzaman, J., 2020. A survey on context awareness in
big data analytics for business applications. Knowledge and Information Systems,
62(9), pp.3387-3415.
Côrte-Real, N., Ruivo, P. and Oliveira, T., 2020. Leveraging internet of things and big data
analytics initiatives in European and American firms: Is data quality a way to extract
business value?. Information & Management, 57(1), p.103141.
Nadikattu, R.R., 2020. Research on data science, data analytics and big data.
INTERNATIONAL JOURNAL OF ENGINEERING, SCIENCE AND, 9(5), pp.99-
105.
Anshari, M. and Sumardi, W.H., 2020. Employing big data in business organisation and
business ethics. International Journal of Business Governance and Ethics, 14(2),
pp.181-205.
Jha, A.K., Agi, M.A. and Ngai, E.W., 2020. A note on big data analytics capability
development in supply chain. Decision Support Systems, 138, p.113382.
Vitari, C. and Raguseo, E., 2020. Big data analytics business value and firm performance:
linking with environmental context. International Journal of Production Research,
58(18), pp.5456-5476.
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