BMP4005: Big Data Analysis, Business Support & Information Systems

This report provides a comprehensive overview of big data analysis in the context of business management (BMP4005). It begins by defining big data and its key characteristics (variety, velocity, volume, and veracity), followed by an examination of the challenges associated with big data analytics, including problems in data growth, lack of professional knowledge, selection of proper data tools, data security, and understanding big data. The report then discusses currently available techniques for analyzing big data, such as A/B testing, data mining, and data integration. Finally, it explains how big data technology can support business, with examples focusing on customer involvement, data management, and data privacy. The report concludes with a digital poster summarizing the key points and a list of references. Desklib offers this report and many similar resources to aid students in their studies.

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
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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
Poster p
References p
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Introduction
Information system is a process or set of co – ordinate components which works together
to store, process and collect. It refers to the software which assists in organizing and
analyzing data with system having a motive to convert unprocessed data into useful data
which can help industries in decision making. There are several elements of it such as,
software, hardware, procedures, feedback and people. There are many advantages of it
such as creating new job roles, globalization and reducing cultural gap. The following
report will cover characteristics of big data , challenges faced while doing big data
analysis, techniques which are currently available for analyzing big data and how big
data could support businesses.
What big data is and the characteristics of big data
Big data refers to large and complex data components which are analyses to decode
important data that can be very essential for the growth of the organization. It is an
assets that is innovative and cost effective and also helpful in giving insight and decision
making. In today's time it is used by almost every big industry and giving successful
results to the businesses across the world. It is used in many different sectors such as,
IT, retail, banking, healthcare, manufacturing etc. There are 3V's of big data described
briefly below:
 Variety- It contains semi structured, structure and unstructured data which is
gathered from different multiple sources which is earlier used to collected from
database and spreadsheets but now a days it comes in form of blogs, videos,
pictures, mails etc. It is one of the essential feature of big data (Hou, et.
Al,2020).
 Velocity- It refers to the pace of rate at which data is traveling or it means
pace in which data is being made in the present time. In a brief concept it
comes with different difficulties for data centers which is trying to manage with
the variety. It is basically considered that how quickly the data is gather and
saved.
 Volume- Very large quantity of data is being sourced on a consistent basis
from many different portals like machines, networks, social media, business
processes etc. Now data volume has been converted from TB to normal PC
memory with unrecoverable shift to zeta bytes and data processed cannot be
saved or stored at traditional systems.
 Veracity- It follows the state of the stats and on how much companies are
dependable on the results to take any further decisions. The raw data is
collected from the different sources that are crucial for the companies
perspective in order to over see the quality of the products and it also assists
in arranging the figures to restrict the errors which can come and later that
data is analyses (Bates, et. Al,2018).
The challenges of big data analytic
It refers to the procedure of organizing, assembling and analyzing the large quality of
data to disclose the furtive, relative and essential insights. Big data analysis refers to the
appropriate division in the firm. Its prospect is fixed, that many of the firms in the current
time uses this techniques. The organization requires to focus on the big data to
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accomplish consumer satisfaction for a longer period of time. Currently, there are many
kind of problems which is associated to big data that are increasing in regular basis. As
this need is efficacious for data analysis to keep the customer data. In a manner
to ,resolve a issue which is connected to big data analytic s, where organization should
evaluate in depth analysis of capabilities by asking ideas of IT professionals (Dey, Bhatt,
and Ashour, 2018).
the business should develop an in-depth analysis of abilities by taking the suggestions of
IT experts. The basic challenges in big data analytic are as follows -
 Problems in growth of data- It is the one of the major issues of saving data
sets because of lack of understanding and due to this data is rising very
quickly which is making difficulties in storing the data properly and safely at
the authentic place. This difficulty has obligated the firm to save the data in an
unstructured way.
 Lack of professional knowledge- Latest applications and techs are required
to analyses the data for which specific content is required. The skills that are
needed to involve the professionals are IT specialist, researchers, data
scientists and data engineers, so that they analyses and understand the data
which can be beneficial for the organization. It is difficult to find people with
such skills and qualifications.
 Selection of proper data tool- It is bit difficult for the companies to choose
proper tools which can easily fits data and are conveniently operable for
making many software.
 Security of Data- It is important to save the data at authentic and safe place
from where the data can be recover it by chance misplaced but only
authorized person can access to the data. It is very daunting challenge to
securely save such a important data. Many organization are busy in knowing
the depth of the data but are not mainly focusing on security of it.
 Understanding big data- If the person is in the place of knowing the data
then it will be convenient to interpret it but understanding the data is the main
challenge as usually the type of device available in the data could be
contrasting. IT only happens b cause of not having proper understanding that
firms are a not able to provide their IT analysts (Hamad, Fakhuri, and Abdel
Jabbar, 2020).
The techniques that are currently available to analyse big
data
There are several techniques which are available to analyses the data are:
 A/B Testing- It is a method which is used in take control of data and
examining the variables in the different test centers to analyses the better
controlling atmosphere. It also gather the data which is used in evaluating
and giving the improved outcomes by creating the possibility and taking
control on the variables.
 Data Mining- It helps in finding and evaluating the quality of the data to
find a suitable way of solving it. It is helpful in business analytic to
proceeds the proper utilization and charge of the AI (Artificial
Intelligence) that is very crucial in choosing and understanding the data.
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Its main goal is to give the require data from the database to system
and to the software in the PC's of the firms (Pan, 2019).
 Data Integration- It helps in managing the large data which is in size of
gigabytes and terabytes which is next to impossible to evaluate by the
humans. It is essential for the firms to evaluate the trend of the market
so that it can be useful for the organizations in the decision making and
for the well being of the consumers. The data gathered is in the
formation with the present data of the firm with using software like
SPSS, python, Tableau etc.
How Big Data technology could support business, an
explanation with examples
The way of technology which is helpful in the industry of data and gives a whole new
view to look at the data in the firm to utilize in the proper way. Now a days in the current
situation, this technique helps the company to evaluate quickly by giving the business in
managing old data of clients. Several business management can make the competitive
benefits with the help of big data technique/ This technique assist in managing the
organization concerned factors which are as follows below:
 Customer Involvement- It is expedited by big data techniques. As it will
facilitates in syncing the data and it is also a key term of duty of information
practice section in the management to keep the data as per to the quantity of
consumers. It helps in gaining the importance of the manage ment by
increasing consumer satisfaction because it will make trust in management
(Wright and et. Al,2019).
 Management of data- Big data technology assist in managing the data which
support the company in a organized manner. This technique uses in vast
terms of software and divisions which will be convenient for the firm to
keeping big terms of data. The data which is maintained by this technique is
easily approachable for management for a longer term which also helps in
managing the clients efficiently and effectively.
 Privacy of data- It is very important for consumers and organization in any
industry. By utilizing the instruction of methods in big data technologies, it
plays an important role in growth of management by keeping the data of the
clients privates which will increase the value of customers by keeping their
large amount of data private (Liu, 2018) .
Poster
Paste your digital poster here
References
Liu, Y., 2018, January. Big data technology and its analysis of application in urban
intelligent transportation system. In 2018 International Conference on Intelligent
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Transportation, Big Data & Smart City (ICITBS) (pp. 17-19). IEEE.
Pan, L., 2019. A Big Data-Based Data Mining Tool for Physical Education and
Technical and Tactical Analysis. International Journal of Emerging
Technologies in Learning, 14(22).
Dey, N., Bhatt, C. and Ashour, A.S., 2018. Big data for remote sensing:
Visualization, analysis and interpretation. Cham: Springer, p.104.
Hou, et. Al,2020. Unstructured big data analysis algorithm and simulation of Internet
of Things based on machine learning. Neural Computing and
Applications, 32(10), pp.5399-5407.
Bates, et. Al,2018. Why policymakers should care about “big data” in
healthcare. Health Policy and Technology, 7(2), pp.211-216.
Hamad, F., Fakhuri, H. and Abdel Jabbar, S., 2020. Big data opportunities and
challenges for analytics strategies in Jordanian Academic Libraries. New
Review of Academic Librarianship, pp.1-24.
Wright and et. Al,2019. Adoption of Big Data technology for innovation in B2B
marketing. Journal of Business-to-Business Marketing,26(3-4), pp.281-293.
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