BSc Business Management: BMP4005 Big Data Analysis Report

This report provides an overview of big data, defining it as information that traditional methods cannot process, and discusses its characteristics: volume, variety, and velocity. It outlines the challenges of big data analytics, including a lack of skilled professionals, understanding massive data, data growth issues, tool selection confusion, integration from disparate sources, and security concerns. The report explores techniques for analyzing big data such as A/B testing, data mining, machine learning, and data integration. Furthermore, it explains how big data technology can support business by providing competitive advantages, improving consumer dialogue, redeveloping products, and enhancing data safety. The report concludes that big data is crucial for business growth and success when handled effectively, emphasizing the importance of addressing its challenges and leveraging its analysis techniques.

BSc (Hons) 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
References p
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Introduction
Information systems and big data is important for every business. Data is the most
important thing because it will help company to grow but managing such large data is
also challenging. This report has discussed about the concept of big data and its
challenges. Further it will evaluate techniques of big data and how technology can help
today’s business.
What big data is and the characteristics of big data
Big data is refers to those information or data which cannot be processed or evaluated by
using the traditional method of processing or technique. Nowadays organisations are
having more big data but they are unable to find out value from within because of the
availability in the raw form or in the unstructured form and also company do no have
knowledge that they should use big data where and how (Dash and et.al., 2019).
As per the research managers of the company doesn’t have the insights access of their
jobs.as companies are working in the environment where they are having the capacity to
store as much data they want but they does not have idea to how to saturate the raw
data. As it name suggests that big data means the data which is large in size and does
not gets processed easily. But with the help of information technology, things are
becoming easy and also people and technology have got interconnected.
Characteristics of big data-
Volume:
The volume of data which is stored is increasing day by day and the data which is
created and stored in today’s world are not analysed at all.which is the biggest problem.
For every big organisation now it has become normal to generate terabytes of data
everyday. If think properly than it can be seen that every activity which is doing through
electronic medium is generating data where it is downloading something to changing TV
channel etc. organisatiosn are facing the problem of big data because they have data
stored with them in large volume (Allam and Dhunny, 2019).
Variety:
As the technology is evloving and the use of smart phones are also increasing,
companies are becoming more complex. The have variety of big data availble with them
which are raw data, structured, unstructured data etc. traditional analytic platforms are
unable to handle the varieties of big data.
Velocity:
As the volume and variety of data has increased just like that the velocity of data which is
generated should be handled properly. Velocity means the speed of the data arriving and
stored.
The challenges of big data analytics
There are many challenges which are associated with big data which are as follows:
Lack of knowledge professionals-
Organisations required skilled and knowledgeable experts for the purpose of using
modern technologies and handling data tools (Kolajo, Daramola and Adebiyi, 2019).
These experts can be data analysts, data engineers, data scientists etc. which can work
with diffferent tools and can handle giant data. Nowadays companies are lacking over
data professionals. As data handling tools are changing and individual do not have much
knowledge on the advanced tool.
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No proper understanding over massive data:
Employees of the enterprize are not efficient in understanding the importance, storage
and processing of the big data. Data professionals have idea of exactly what is
happening but other employees does not have the clear picture of it. If the employees are
unaware of the data importance than they will not store the sensitive data.
Data growth issues:
One of the major challenge is the stroing the large data in proper manner. As the quantity
of data which is stored in companies are increasing rapidly. When the quatity grows with
time than it becomes difficult to handle it (Favaretto and et.al., 2020).
Confusion is selecting big data tools:
Often it has seen that organisation are confused in regards of selecting easy tool which
can store and handle big data easily.there are lots of tool available in the market so
selection the best tool within the variety of tool is the complex process. There are high
chances that companies make poor decisions and select inappropriate technology which
results in wasting of time, money, efforts etc.
Integration of data from spread of soruce:
Data is generated from various platforms which are cutomer logs, social media page,
emails, financial reporting, presentations etc. combining all the data together to make
one report is the difficult process. Intergrating daata is complex for the purpose of
reporting, evaluation, business intelligence etc.
Security of data:
Keeping security of such huge data sets is the other major challenge. Often it is notices
that enterprizes are busy with storing and analyzing the data and they neglect the
security part of it. If data is not secured than it can be hacked by hackers and hackers will
use the data in blackmailing company.
The techniques that are currently available to analyse big
data
A/B testing-
This is the big data analyse technique which compares variety of test groups with the
control group, in order to find out that what are the treatments required for improving the
objective variable (Zhu and et.al., 2018). This technique is used to test large number
which is availble in big data. Random method is used in this test within two variants
which is A or B. in this particular statistics statistical hypothesis testing is being used.
Data mining:
This is the most common tools which are used by many data experts. This data mining
tool is used in extracting the different data patterns from the huge data sets by using
combined methods of machine learning and statistics. Example while understanding that
which segment of customer will reach to the discount or offers given by the company,
customer data is mined by the experts.
Machine learning:
This technique belongs to the area of artificial intelligence, machine learning process are
utilized by the data experts. It has evaluated from the computer science and used
computer algorithms for providing the data assumptions. Coding is done from taking out
assumptions from the data sets. It also helps in providing various predictions to the
experts. In simple language this technique is based on the computer algorithms which is
helpful in improvisation of data.
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Data integration:
It combines various technique which integrate and evaluate the data from various
sources (Lv and Qiao, 2020). The insights which is arised from the single source of data
are accurate and more efficient.
How Big Data technology could support business, an
explanation with examples
Big data is the technique which is used in managing huge data sets. Big data can be
used by the business for attaining growth and success. Big data helps the business in
making new services, experience and products. There are various benefits which big
data can provide business which are as follows-
Providing competitive advantage to business-
Many firms are using big data for gaining the competitive advantage. Many new
companies are providing tough competition to other companies by using data driven
strategies for capturing the market and by providing innovative products. It can be find
out that every organisation from IT to healthcase industry all are using big data from
gaining the competitive advantage. Experts are also saying that big data can provide lot
of opporttunities in terms of growth to the business.
Dialogue with consumers-
Nowadays consumers are smart enough and they know exactly what they want. Before
purchasing anything consumers compare each and everything. They have conversation
with the business by using various social media platforms and also raise their query if
they are having any. Big data helps companies in reaching towards their target customer
group. This help company in engaging with real time conversation with the consumers. It
is important for the cmpany to give priority to the customers and also to fulfil their
demand if company want to survive in the market for the long time period.
Redeveloping products:
Big data can be used by the firms for gathering feedbacks from the customers. When
company will take feedback from the customers then they will understand needs of the
customers. By knowing the needs of the customers company can re develop the
products according to the customer preference. By reading the comments which
customer gives on social media through that also company can find out the customer
needs. Example: if company want to know the customer preference than they can carry
question and answer activity on social media platforms which will be helpful in getting
knowledge about the customers taste (Oussous, Benjelloun, Lahcen and Belfkih, 2018).
Likewise company can also collect information on material affect costs, lead times,
performance etc. company can even upgrade the productivity of their production unit with
the help of big data.
Data safety:
There are various big data safety tools which can be used by the company for securing
their data. As it will be helpful to the company in knowing about the internal threats. With
the help of tools and technique company can keep their sensitive information safe. That
is why there are many organisation which is focusing on big data for the protection and
safety purpose.
Conclusion
Through this report it can be conlcuded that big data is said to as the large data sets or
information which is available and stored with the company and which are also difficult to
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handle. This report has discussed about various challenges regarding big data which can
be massive data, lack of data experts etc. there are also many techniques which is used
for big data analysis which are A/B testing, data mining etc. big data is used by business
for attaining safety and growth and success.
Characteristics of Big data
Volume:
The volume of data which is stored is increasing day by day and the data which is
created and stored in today’s world are not analysed at all which is the biggest problem.
Variety:
As the technology is evolving and the use of smart phones are also increasing,
companies are becoming more complex.
Velocity:
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As the volume and variety of data has increased just like that the velocity of data which is
generated should be handled properly.
The challenges of big data analytics
Lack of knowledge professionals-
Organisations required skilled and knowledgeable experts for the purpose of using
modern technologies and handling data tools.
No proper understanding over massive data:
Employees of the enterprize are not efficient in understanding the importance, storage
and processing of the big data.
Data growth issues:
One of the major challenge is the storing the large data in proper manner. As the quantity
of data which is stored in companies are increasing rapidly.
Confusion is selecting big data tools:
Often it has seen that organisation are confused in regards of selecting easy tool which
can store and handle big data easily. there are lots of tool available in the market so
selection the best tool within the variety of tool is the complex process.
Techniques that are currently available to analysis big data
A/B testing-
This is the big data analyze technique which compares variety of test groups with the
control group, in order to find out that what are the treatments required for improving the
objective variable.
Data mining:
This is the most common tools which are used by many data experts. This data mining
tool is used in extracting the different data patterns from the huge data sets by using
combined methods of machine learning and statistics
Machine learning
This technique belongs to the area of artificial intelligence, machine learning process are
utilized by the data experts
Data integration:
It combines various technique which integrate and evaluate the data from various
sources.
How Big Data technology could support business
Providing competitive advantage to business-
Many firms are using big data for gaining the competitive advantage. Many new
companies are providing tough competition to other companies by using data driven
strategies for capturing the market and by providing innovative products.
Dialogue with consumers-
Nowadays consumers are smart enough and they know exactly what they want. Before
purchasing anything consumers compare each and everything.
Redeveloping products:
Big data can be used by the firms for gathering feedbacks from the customers. When
company will take feedback from the customers then they will understand needs of the
customers.
Data safety:
There are various big data safety tools which can be used by the company for securing
their data. As it will be helpful to the company in knowing about the internal threats.
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References
Allam, Z. and Dhunny, Z.A., 2019. On big data, artificial intelligence and smart
cities. Cities. 89. pp.80-91.
Dash, S. and et.al., 2019. Big data in healthcare: management, analysis and future
prospects. Journal of Big Data. 6(1), pp.1-25.
Favaretto, M. and et.al., 2020. What is your definition of Big Data? Researchers’
understanding of the phenomenon of the decade. PloS one. 15(2). p.e0228987.
Kolajo, T., Daramola, O. and Adebiyi, A., 2019. Big data stream analysis: a systematic
literature review. Journal of Big Data. 6(1). pp.1-30.
Lv, Z. and Qiao, L., 2020. Analysis of healthcare big data. Future Generation Computer
Systems. 109. pp.103-110.
Oussous, A., Benjelloun, F.Z., Lahcen, A.A. and Belfkih, S., 2018. Big Data technologies:
A survey. Journal of King Saud University-Computer and Information
Sciences. 30(4). pp.431-448.
Zhu, L. and et.al., 2018. Big data analytics in intelligent transportation systems: A
survey. IEEE Transactions on Intelligent Transportation Systems. 20(1). pp.383-398.
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