BSc BMP4005 - Information Systems and Big Data Analysis Report

This report provides a comprehensive overview of big data analysis within the context of business management. It begins by defining big data and outlining its key characteristics, including velocity, volume, variety, value, veracity, and variability. The report then delves into the challenges associated with big data analytics, such as skilled deficiency expertise, issues of data growth, confusion in tool choice, and lack of understanding. Various techniques currently available for analyzing big data, like principal component analysis and linear discriminant analysis, are discussed. Finally, the report elucidates how big data technology can support business functions, providing examples of how it can improve product quality, facilitate better decision-making, reach capable users, and leverage resources to generate income. The document includes a poster summarizing the key points, offering a visual representation of the concepts discussed.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Summary Paper
Submitted by:
Name:
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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
References p
Appendix 1: Poster p
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Introduction
Big data is a collection of the organized and unorganized data it is gather on the
basis of the information that is generated by the market study and feedback and
responses of the users and individuals (Lin and Yang,2019.). It consist some
techniques and other tools to integrate the details and other information that are
beneficial for the company and industry. It is the information which is used in business
and gather altogether so that an organization can have the advantages for the
company as well and its growth. In this report will cover the concept of big data and its
characteristics . After that it will explain that what techniques company uses to
organized huge data. In last what issues they faces while collecting a huge data and
other things and how it impact the business.
What big data is and the characteristics of big data
In this current era, technologies development and creativity are consider in
massive details during managing these tools utilized by different industry to give
growth for their company (Jiang and et., al., 2019). These technologies leads to gain in
gathering data to grow different sources like merchandising governing bodies and
many more. Business concern utilize big data tools to keep a capable position in
rival market and it assist them to make faster and much guided business decisions.
Industries or companies do not have enough spaces to save varied kinds of data
with huge volume . Earlier , companies do not have enough spaces to save data,
they have to delete past data to save new details which can remove crucial data.
This is cost effective which is most secured from other tools .
Characteristics of Big data-
Big data is a combination of organized semi organized , unorganized details that
is gathered which is utilized in tools learning projects , another analytic frameworks it
is application. It is basic tools utilized by consumer behavior desires wants and desires
of them. It has some major characteristics that is listed in below -
1. velocity - it is constant changing due to creativity in the sector of technology. It
refers the measuring of time taken to change unorganized data into organized
form .
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2. Volume - it refers to the value of details which is gathered by a company. It
majorly concentrate on the quantity and capacity of data processing. A company
manipulate and visualize this details to attain business goals.
3. variety - this v explain the huge variety of details which Is included recorded
and it is recorded in unorganized or semi structured form. It covers different
kinds of data due to gatherings from different sources. It recorded data still
required to be processed and summarized and filtration as per the requirements
of business.
4. value - it states to the quality of data which gives better outcomes as per the
company required. It is utilized to fill most crucial data from the saved data
which give quality details to the business regarding their goods, users and rivals.
5. veracity - it states the process of details which is consider queries impure or
conflicted data and also provide regarding programs where business not sure
how to deal with them. It presents that the company elaborately the data truth
and authenticity.
6. variability - it is calculated by the utilization of data to an extent and how fast
into outcomes and also explain the quantity and shape of details . Variability
states to the consistency of data in the altering technological surroundings.
The challenges of big data analytics
During proceeding big data a company facing various issues regarding their
huge to trail for company usage. Determining and improving big data is require d
new skills as compare to earlier data analytical techniques . Some of the main
issues are briefly elaborated in below -
1. deficiency of skilled expertise – in conducting current implied, present
techniques the business required some skills expertise . these could be data analyst
or data scientist. They are required so that the big data shows and create some
sense out of this and add from the numerous data accessibility . they are required
so that the massive data shows with the business can be utilised efficiently by the
business to create some sense out of it and add from the various data sources.
2. Issues of data growth - the most crucial issue that has been raising
related to the big data is the raising issues this data sets. It is an issue
for the business to save to save these in the data centers or database of
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the company as the numbers are raising these in the data centers. As
these raises with just seeded up ratio. The issues to save and determine
the data and utilization it effectively for the company activity is becoming
a projects for the business company (Fényes, Németh and Gáspár,2021).
3. Confusion in tool choice - because of the values of data with the companies
certain times it becomes very complex for the company to analyses which tool must
be utilized by the business to assess and extract details from the sources of data
accessibility. It leads to companies selecting irrelevant tools for the details
extracted and usage of big data and this bad selection of instruments and policies in
results in ineffective decision making and extracting from the global data.
4. Lack of understanding - the value of data in analyzing in big data is very
huge hence sometimes the business fails to understand the meaning
and execution of details . workers of the company are not trained to
manage the business and that leads in losing the business identity and
other thing (shrivastava and et., al., 2021).
The techniques that are currently available to analyse big
data
Here are some techniques which is used by the company to analyses big data listed in
below (Feng, 2019,).-
1. Principle component analysis - this methodology is utilized in the conversation
of inter link variable into a unit of unrelated variables that contain still quality of
details . Small data set are easy to manage and analyses as well as it reduces the
time and efforts of the company. It plays an essential role to reduce the value of
variables an saving more and more details .
2. Linear discriminant analysis - this method is most popular or basic
dimension reduction tools utilized for eliminating issues in machine learning. It turns
details in low quantity and raises the quality of details.
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How Big Data technology could support business, an
explanation with examples
here are some points that will how it impact the business functions.
1.grows the goods quality - it gives the company with different types of details that
can be utilized by the company for its advantages to add more and more users base
. This education that exists with the business has the capability to make powerful
bonds with the presented users and attracts new buyers.
2. Better decision making – it gives business with the tools that are required for
creating and smart decisions for the company due to these decisions are on the b
basis of sets of extracted data and not on any ideas. In instance the company
requires to provide the access of the data to all the members of the company who
required to make good decisions.
3. Reaching capable users - it can play an important role to reach and connect
the business with new business as with the assistance of the data the company. It is
more about what is being wanted and requested as well as required in the
marketplace. It helps in targeting users and making users base along with that it is
according to the advantages by their own asset of analyses the users also
reaching giving them with the requirements of goods and services.
4. Using the sources to make income - it is not only utilized for developing
the goods and services . It can also be utilized to use the other less
explored departments and can use by reaching on the lacking
resources that can be use with the assistance of this big data (Carra and
et., al., 2020.) .
References
Carra, G., and et., al., 2020. Data-driven ICU management: using Big Data and
algorithms to improve outcomes. Journal of Critical Care, 60, pp.300-304.
Feng, P., 2019, January. Big data analysis of e-commerce based on the internet of
things. In 2019 International Conference on Intelligent Transportation, Big Data
& Smart City (ICITBS) (pp. 345-347). IEEE.
Fényes, D., Németh, B. and Gáspár, P., 2021. Design of LPV control for autonomous
vehicles using the contributions of big data analysis. International Journal of
Control, pp.1-12.
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Jiang, D., and et., al., 2019. Big data analysis based network behavior insight of cellular
networks for industry 4.0 applications. IEEE Transactions on Industrial
Informatics, 16(2), pp.1310-1320.
Lin, H.Y. and Yang, S.Y., 2019. A smart cloud-based energy data mining agent using
big data analysis technology. Smart Science, 7(3), pp.175-183.
Shrivastava, A.,and et., al., 2021. Automatic robotic system design and development
for vertical hydroponic farming using IoT and big data analysis. Materials
Today: Proceedings.
Tao, D., Yang, P. and Feng, H., 2020. Utilization of text mining as a big data analysis
tool for food science and nutrition. Comprehensive reviews in food science and
food safety, 19(2), pp.875-894.
Wang, J. and Lv, B., 2019. Big data analysis and research on consumption demand of
sports fitness leisure activities. Cluster Computing, 22(2), pp.3573-3582.
Appendix 1: Poster
Paste your digital poster here
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