Big Data Analysis: Techniques, Business Support - BMP4005 Semester 1

This report provides a comprehensive overview of big data, including its characteristics, challenges in analysis, and various techniques used to analyze it, such as data mining, data integration, and A/B testing. It further explores how big data technology can support businesses by aiding in decision-making, automation, and providing better customer insights with relevant examples. The report concludes that while big data is crucial for organizational development by enabling informed decisions, it requires expert knowledge and secure handling, highlighting the importance of staying updated with the latest trends and techniques in the field.

Big Data

Table of Contents
INTRODUCTION ..........................................................................................................................3
MAIN BODY...................................................................................................................................3
Discuss about big data along with its characteristics..................................................................3
Ascertain the challenges of big data analytics and techniques for analysing it..........................4
Describe the manner in which Big data technology can help businesses with the help of
examples where required.............................................................................................................6
CONCLUSION .....................................................................................................................8
REFERENCES................................................................................................................................9

INTRODUCTION
Data can be defined as a qualitative and quantitative information of any person, company,
economy or the whole country. It is a single value comprising of one variable. As per the
concept, it is a raw arrangement of figures and subjective material which needs to be properly
transformed into a well structured knowledge. This helps businesses in analysing their
performance with the help of this information. It can be represented in graphs, images or tables.
But collection of this data used to be a lengthy and complex process. But evolution of many
techniques made this procedure of gathering, arranging and interpretation of material very easy
(Dasgupta, 2018). This report discusses about the history of big data and its features. It further
describes the difficulties faced and techniques used while analysing it. It also provides the ways
in which the technology used in it can help companies.
MAIN BODY
Discuss about big data along with its characteristics.
It is a group of large amount of facts and figures that are not easy to be handled by
humans and that too especially by traditional methods. These are sum of all the activities of
business that takes place on daily basis. It may or may not be structured. It is not possible for
humans to handle and sort this complex data without any external help. The older or
conventional methods of management software cannot solve the purpose. It requires a properly
developed tools and techniques for conducting analysis on this huge data which is growing
frequently at a large level. Modern applications are developed for examining this data
automatically and storing all its content in some warehouse (Hamilton, 2021). This also raises
the capability to check out the collection with better insights. These tools assists the users in
making use of all this data at any point of time and that too is available to them in a correct
format. The information provided in this is always complete. These modern techniques extracts
the exact content and communicate it after analysing that is required by the business. But it
demands the professionals and other users of big data to be always updated about the changing
taking place in data, techniques applied on them, so that they can use that knowledge for
competing with the rival firms.
Characteristics of Big Data

 Volume – This data comprises of large content. By making use of technology, the users
can easily track this information and that too with more accuracy. It will also improve the
quality of knowledge. In modern times, it is normally measured in terms of Gigabytes,
Yottabytes.
 Value- It refers to the advantages that can receive from this data. Organisation should
choose the set of information according to its needs. This is the biggest feature of big data
that a correctly chosen content can raise the value of organisation.
 Velocity- It refers to the speed at which the data is processing. It is very much important
to use such a tool that can handle this high velocity for processing this big data.
 Visualization- It means to present the data in the form of charts and graphs. It has now
become common as the professionals has to deal with non technical clients on daily basis
and by presenting this data in the form of charts, they can easily make them clear about
the finding of the content (Lai, Lai and Lai, 2021).
 Variety- Their are various types of data available which can have different impact on the
performance of the industry. It is very important for them to analyse each and every type
of data properly. Also this data is available from variety of sources. So, it is necessary to
check out the reliable source.
 Volatility- the data keep on changing constantly. In most of the cases, the data collected
on one day is different from the information viewed on next day. This variability in data
affects the performance of companies and also the makes it difficult to have a hold on
correct and updated information.
Ascertain the challenges of big data analytics and techniques for analysing it.
It refers to the process of checking the whole data for finding out all types of hidden
information such as any kind of correlation, patterns or trends in that data. This helps the firms in
making more informed decisions for their organisation (Silva, Khan and Han, 2020).
Challenges faced while analysing the big data
 Lack of Professional Knowledge- It is important to use contemporary applications and
tools for examining the data. This analysis requires particular knowledge on the related
field. Their is a need of professional skills held by professionals like researchers,
scientists, analysts and engineers. These people c an easily understand the data and can

make extract some useful information out of it. But this cannot be done by any normal
person.
 Data storing issue- Today, data is growing at a large scale and it is very difficult for
uninformed person to store this data easily. Its growth is becoming a challenge for all to
store it safely and accurately. This forces the organisations to keep it in structured format.
 Security issues- this is necessary to keep the data in secure form and at authentic place.
This thing is also required to be kept in mind that the organisations store it at such a place
where it can be retrieved easily and no unauthorised person can have access over it
(Somani, And Deka, 2017).
 Lack of understanding- Most of the people feels it challenging to interpret the data as
they do not understand that what the data is saying. Understanding the content is a big
challenge as each time, this data keeps on changing, its variables are different for every
data. It happens because of lack of knowledge which firms could not avail to their
analysts.
Techniques of analysing big data
 Data mining – It helps in exploring and analysing the complete set of data in order to
search out the pattern involved in solving it. It is a tool that extracts some patterns from
big set of data by integrating methods from statistics and machine learning models. It
aims at providing useful information to the of the database to the organisations by making
use of software applications in computers (Wamba, 2017).
 Data Integration- It is the process of combining the whole set of information derived
form various sources. It holds the capacity to handle large amount of data which is
impossible for the human to handle and analyse. It is important for organisations to
analyse the trend of market in order to take right decision at right time. The data collected
is aligned with the present knowledge of firm with the help of applications like Tableau,
SPSS and many more.
 A/B Testing – This tool is used for controlling the whole data and contrasting its
variables with that to the test groups so that environment can be controlled in more better
manner. It accumulates the content to analyse it which helps it in taking further decisions
for the business and controlling various situations.

Describe the manner in which Big data technology can help businesses with the help of examples
where required.
Big data technology can be used in almost all kinds of industries as it provides a different
perspective to the members to look at the situations. This helps them in finding solutions to their
lot of problems. Following are the ways in which the analysis of big data helps the companies.
 Taking decisions- businesses uses these techniques for making choices. The presence of
volume in data makes it more difficult to analyse it manually. This can be done smartly
with the help of applications. Through this, companies takes their decisions.
 Automation- The world is growing very fast and there is a need of reviewing this data
fast in order to combat the competition. The use of technology helps in solving this
purpose. Use of applications completes the work of days in a single click only.
 Better customer insight – It aids the firm to generate information about the changes
taking place in the choices of customers and their expectations. Techniques of big data
helps in discovering out this information from the different sources (Yıldırım, Okay and
Özdemir, 2021).

CONCLUSION
From the above analysis, it can be concluded that the big data plays an important role in
development of organisation as well as countries. Its main factor is that it understands the
information deeply and extracts out best knowledge out of it. It analyses the whole data
accurately and helps the firms in taking effective decisions. But it requires expert knowledge and
understanding for examining the whole data and handling it securely. Their are various
applications which helps in analysing this data.

REFERENCES
Books and Journals
Dasgupta, N., 2018. Practical big data analytics: Hands-on techniques to implement enterprise
analytics and machine learning using Hadoop, Spark, NoSQL and R. Packt Publishing
Ltd.
Hamilton, S., 2021. Real-time big data analytics, sustainable Industry 4.0 wireless networks, and
Internet of Things-based decision support systems in cyber-physical smart
manufacturing. Economics, Management, and Financial Markets. 16(2). pp.84-94.
Lai, C.S., Lai, L.L. and Lai, Q.H., 2021. Smart grids and big data analytics for smart cities.
Springer International Publishing.
Silva, B.N., Khan, M. and Han, K., 2020. Integration of Big Data analytics embedded smart city
architecture with RESTful web of things for efficient service provision and energy
management. Future generation computer systems. 107. pp.975-987.
Somani, A.K. and Deka, G.C. eds., 2017. Big data analytics: Tools and technology for effective
planning. CRC Press.
Wamba, S.F., 2017. Big data analytics and business process innovation. Business Process
Management Journal.
Yıldırım, M., Okay, F.Y. and Özdemir, S., 2021. Big data analytics for default prediction using
graph theory. Expert Systems with Applications. 176. p.114840.
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