BMP4005 - Big Data Analysis: Supporting Business with Technology

This report provides an overview of big data, its characteristics (volume, variety, velocity, value), and the challenges associated with its analysis, including data security, lack of skilled professionals, poor tool selection, and data integration issues. It identifies techniques for big data analysis, such as classification tree analysis, association rule mining, machine learning, and social networking analysis. The report also explains how big data technology supports businesses through market research, customer analysis, and improved business intelligence, citing examples of companies like Facebook and Twitter. The conclusion emphasizes the importance of big data for managing information and facilitating business functions.

BSc (Hons) Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
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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
This report is aim to identify the concept of big data. In this technological
world, big data is become an important part for many business and people. It refers
to collection of data which has been stored in software and in order to receive,
analyse and use the information for relevant purposes. It is a way of storing and
assessing large amount of data in a systematic software (Zeadally, Siddiqui, Baig,
and Ibrahim, 2019). It is used by many large organisations who control and consist
large data sets from customers end. Therefore, this report is going to identify various
characteristics which defines how big data works. Also, the challenges and
techniques will be identified to analyse big data and how the technology support
business will also going to outline in the report.
What big data is and the characteristics of big data
Big data is a concept of data storage, analysation and use it in an effective
manner. As IT sector is rapidly growing which enhance the use of internet
technology and requirement of big data. There are many organisation like Facebook,
Amazon, Netflix which gain large data to user interference that must be keep safe
and secure for making its right use (Too Big to Ignore: The Business Case for Big
Data, 2021) Therefore, it has many characteristics which are defined below:
Volume: It defined as the size of big data which is being stored in many
software. It consist high volume in terms of video, blogs, customer logs and other
informations which comes with huge size. Large organisation like Twitter, Facebook
generate data in 7-10 terabytes. The companies need to be prepare with large
volume sets.
Variety: it defines as the variety in which data comes and stored in computer
generated software. This can be structured, semi-structured or unstructured. These
are web pages, social media forums, e-mail documenters, sensor and many other
technological process which influence on the varieties of big data (Munshi, and
Mohamed, 2018). It shows that companies have many opportunities in relation to
collecting large data. As it traditional ways, the data gets stored in spreadsheets
whereas, in modern technology it stored in PDF, video, images and etc.
Velocity: it defines as in which speed data move from one place or format to
another. The data must be processed at good speed so that, the needs of user
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must be fulfil within less time. Big data must be analyse through new ways or
technologies to maintain its speed and varieties in accurate manner.
Value: it is one of the crucial characteristics of big data. It shows that the
initial form of data must provide value in its processing. The business could easily
make effective use of big data in generating value for users by monetising their
needs and wants. It refers to adding something huge in business.
The challenges of big data analytics
It has observed that, big data consist a high requirement in all over the world.
The more there seems to grow in internet and technology, the more it raise the
requirement of big data. Therefore, it comes with some challenges while analysing
big data.
Securing data: it is one of the top most challenges comes while analysing
and using big data. It become difficult to secure a large set of varieties, velocities
and knowledges in a protected software (Sedkaoui, 2018). There are many paths
and hacking ways are developed which break down the security protocols and
enters to make data thefts. This create huge losses for business in terms of money
and customer trust.
Lack of knowledge professionals: as the modern technology is rapidly
growing and comes with new up gradation, software's and many more technical
challenges which is not easy to adopt frequently. Therefore, it become challenging
for business to operate and analyse big data effectively due to having poor
knowledge expertise and make fuller utilisation of big data.
Poor selection of big data tool: it has identified that, big data comes with
numerous techniques and platforms, so it has many tools and techniques to analyse
and generate data. Therefore, having a lot of choices causing trouble for business
to choose the most effective ,one. As it takes time, cost and efforts to analyse the
most suitable one.
Integrating data from a spread of sources: big data generate through a lot
of sources due to having wide reach and universal applicability. Therefore, it comes
through social media, AI, reports, presentation, documents and many others. So, it
becomes problematic for business to gather all these in a combined manner. It
creates data integration problems which could not satisfy the aim of data analytics
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for business and they lack with fulfilling user needs and promote business
intelligence.
The techniques that are currently available to analyse big
data
it has identified that analysing big data might become a challenge for many
business forms who operate at large level (Xiong, Zuo, and Carranza, 2018). So,
there are various crucial techniques which helps in giving best results and fulfil user
needs. Analysing big data is an important activity for all the business as it involve
data regrading business solutions, customer information, their actions and statistics.
Classification of tree analysis: it defines as a technique in which new
observations an classification take place. It helps in classifying and use the data in
simpler way. It reduce the complexities for big data simulation. It has mainly three
statistical classification which are categorisation, develop profile, assign the
documents automatically.
Association rule thumbing: this technique of big data analysis helps in
analysing the relation among variables presented in the data sets. These variables
helps in fulfilling the aim of collecting big data. It involves all the actions, touchpoints
and key elements of users which helps the business to fulfil their needs and make
sales.
Machine learning: it is a computer generated techniques which has various
benefits to the business. It is a part of artificial intelligence through which business
organisation could easily interpret customer actions and predict the knowledge an
information which will be helpful for keep them satisfied (Shirazi, and Mohammadi,
2019). This technique used to classify all the statistical areas and analyse where the
data goes high and low.
Social networking analysis: this technique helps the IT mangers to gather
and analyse big data through way of social media platforms. As it is a direct way of
making communication and interacting with audience in order to gain knowledge
about market or any important information. It helps in gaining relevant data which
avoid misunderstandings and wrong interpretation.
These are the important techniques which must be applicable to gain success in IT
industry.
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How Big Data technology could support business, an
explanation with examples
big data technology is become most widely used and important concepts for
business organisation. Every company runs their activities in relation to marketing,
branding, promotions, interpersonal relations through internet and social media
ways. Therefore, it contains a large number of data integration in the field of IT and
computer software. Big data is also been helpful for the companies who wants to
achieve their targets at global platforms. Facebook, Twitter are the top most
companies which has created a high revenue through big data technology. As they
need to save, secure ad store all the users actions, communication and field of
search (Babar, and Arif,2019). There are a lot of benefit in every business industry
through big data uses. It is beneficial to conduct proper market research, analyse
potential customer and make strategies to grow and expand into market. The
machine learning, AI technology CRM approach are a part of big data technology to
provide an insight about what business customer want and how they reach on
business practices. Therefore, big data is helpful in managing critical business
functioning through modern ways. It provide a lot of opportunities to know user better
and provide them a valuable experience towards services (Wang, Ding, Yu, and
Zhao, 2020). Industry like IT, retail, hospitality are all taking advantages through
ascertaining google analytics and user interference.
Conclusion
The report has concluded that, big data is an important concept for the whole
world of business. It has analysed that big data is required to keep the informations,
files, documents and necessary data sets in a systematic manner. The report has
presented various characteristics like volume, velocity, value and variety. The Vs of
big data plays a vital role in presenting the data in proper manner. Also, the report
has identified various challenges in terms of security, growth of data, arrival of data
from different sources and poor selection of big data tool. All these challenges
influence on the functioning of business. Therefore, it has outlined various
techniques and to support big data analytics. Also, it has identified that big data is
helpful in providing benefits to the business organisation as it makes the functions of
marketing, generating sales easier for the business.
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Poster
References
Zeadally, S., Siddiqui, F., Baig, Z. and Ibrahim, A., 2019. Smart healthcare: Challenges and
potential solutions using internet of things (IoT) and big data analytics. PSU
research review.
Munshi, A.A. and Mohamed, Y.A.R.I., 2018. Data lake lambda architecture for smart grids big
data analytics. IEEE Access, 6, pp.40463-40471.
Sedkaoui, S., 2018. Data analytics and big data. John Wiley & Sons.
Xiong, Y., Zuo, R. and Carranza, E.J.M., 2018. Mapping mineral prospectivity through big
data analytics and a deep learning algorithm. Ore Geology Reviews, 102, pp.811-
817.
Shirazi, F. and Mohammadi, M., 2019. A big data analytics model for customer churn
prediction in the retiree segment. International Journal of Information
Management, 48, pp.238-253.
Babar, M. and Arif, F., 2019. Real-time data processing scheme using big data analytics in
internet of things based smart transportation environment. Journal of Ambient
Intelligence and Humanized Computing, 10(10), pp.4167-4177.
Wang, F., Ding, L., Yu, H. and Zhao, Y., 2020. Big data analytics on enterprise credit risk
evaluation of e-Business platform. Information Systems and e-Business
Management, 18(3), pp.311-350.
Online
Too Big to Ignore: The Business Case for Big Data, 2021. [Online] Available through
https://onlinelibrary.wiley.com/doi/book/10.1002/9781119204039
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