Report on Information Systems and Big Data Analysis Techniques

This report provides a comprehensive overview of big data analysis, starting with a definition of big data and its key characteristics (volume, variety, velocity, value, and veracity). It then delves into the challenges associated with big data analytics, such as data growth issues, lack of proper knowledge, and a shortage of skilled professionals. The report outlines various techniques currently used to analyze big data, including association rule mining, A/B testing, data mining, social network analysis, classification tree analysis, and regression analysis. Furthermore, it explores how big data technology can support businesses, providing examples from the retail and hospitality sectors. The report concludes by emphasizing the importance of understanding and utilizing big data to effectively manage information and gain a competitive edge, alongside a digital poster representing these concepts.

Information Systems and
Big Data Analysis

Table of Contents
Introduction......................................................................................................................................3
What big data is and the characteristics of big data ........................................................................3
The challenges of big data analytics................................................................................................4
The techniques that are currently available to analyse big data ......................................................5
How Big Data technology could support business an explanation with examples .........................6
Poster................................................................................................................................................6
CONCLUSION................................................................................................................................8
REFERENCES:...............................................................................................................................9
Books and Journals.....................................................................................................................9

Introduction
Big data has facilitated the work on managing the work in an effective manner. There is
need of software that help in managing the data and it is a complex process. It can be defines as
collection of data that contains great variety, increasing volume and great velocity (Hariri,
Fredericks and Bowers, 2019). In this report there is discussion related to big data and its
characteristics. Afterwards, there are some techniques that assist in managing big data and they
are also part of the report. In the end, a digital poster related to big data is also presented.
What big data is and the characteristics of big data
There is huge information and data that is being collected by the business organisation.
The use of big data helps to manage the information and get useful data from the same. It is a
field that helps to analyse and systematically extract information from data sets (Ghani and
et.al., 2019). There are 5Vs of big data and they are discussed underneath:
Volume: The volume of data being required and used by business organisation is
enhancing. There is need of big data techniques that help in managing the data in proper manner.
The business organisation collects the data from different sources such as IoT devices, social
media, videos, financial transactions, and customer logs (Saggi, and Jain, 2018). It is problematic
for the business organisation and they are unable to manage the work. The processing of data is
now facilitated with the help of big data. The volume of data varies according to the types of file.
Variety: This characteristic shows that the data varies by its nature. The data is not
collected from the same source and that is the reason of heterogeneity of data. The data can be in

the form of PDF, audio, photos, video, etc. The use of big data facilitates the processing the
variety of data.
Velocity: This shows the data at which data is being produced. There is need to match the
speed of data and manage it in effective manner. The processed data is then used by the client
and satisfy their needs and wants.
Value: It is important to value the data that is being collected. The data must be collected
from right source so that it is reliable and authentic. The use and reliability of the data matters
the most and will help the clients to use the information effectively (Choi, Wallace and Wang,
2018). The raw data must be converted into useful information so that value can be extracted
from the same. It is seen that process of converting raw data in useful information is important.
Veracity: It is important to have details related to trustworthiness of data. The data that is
being encountered by the organisation is unstructured. The use of big data assist in filtering out
the information and then use the most valuable data.
The above mentioned are the characteristics of big data. By using them properly the
business organisation is able to collect and manage information in vital maner.
The challenges of big data analytics
It include the best way of handling the numerous amount of data. Big organisation
producing a huge amount of data every minute. The amount of data produce by an organisation
make a challenge to store, manage, and analyse the data (Ristevski and Chen, 2018). Every large
business organisation face a challenge of managing the huge amount of useful data. There are
various major challenges that face by an organisation some are below:
 Data growth issues: It is foremost challenge that faced by an organisation. Company
face the challenge to store huge amount of useful data in an effective way. The amount of
data increase exponentially with the time, it become challenging activity to handle.
Companies need to choose modern techniques to handle these range of data. Business
entities would also choose big data tools like Hadoop, NoSQL and other technologies.
 Lack of proper knowledge of massive data: Due to insufficient understanding of big
data company fail to manage big data. Employees must know what data is, what its
storage, processing, and importance. For example if employee don't have the significance
of knowledge storage, they couldn't keep the backup of useful data (Mehta and Pandit,

2018). To remove this type of hurdle company should conduct seminars and works shops
of big data.
 Lack of knowledge professionals: To store and analyse big data company need skill
data professionals. These professionals will include data scientist, data analytical, and
data engineers. One of the big data challenge that company face is less availability of data
professional in the business organisation. Company need to appoint and recruit skills
professionals. Also, conduct training and development programmes for these
professionals. If employees of the organisations are not able to manage the problems
effectively it will create problem.
The techniques that are currently available to analyse big data
The business environment is dynamic and keeps on changing. There is need to collect the
information related to changes and analyse the same. The use of big data facilitates the business
organisation to manage the information properly (Cirillo, and Valencia, 2019). There are certain
techniques that help to manage the work with the help of several techniques that are mentioned
below:
Association rule thumbing: It is a method that assist in bringing correlation among the
different variables in large data. There are certain points that have impact on the sales of the
company. It is necessary to know about the information and then grab the factors to know their
correlation with the sales of the company. Along with that it helps to study some of the factors
that result in enhancing customer experience.
A/B testing: It is a technique under which the comparison of control group is done with
variety of tests. It helps to analyse the changes that are required to attain the objectives. This
assist in enhancing the e-commerce rate and bring meaningful differences (Singh and El-Kassar,
2019).
Data mining: It is tool that is used commonly use in big data analytics. It helps to extract
the pattern in which the large organisation manage the data set. This helps to segment the
customers data and then manage the data base (Amankwah-Amoah and Adomako, 2019). There
is need to work in such a manner that helps to get best details out the information that is being
used.
Social network analysis: It is a tool that is being used by telecommunication industry to
manage the data and analyse information. The benefit of using this technique is to enhance the

relationship with the customers. The model also helps to know about the areas that need
improvement and then make the right changes.
Classification Tree analysis: It is a method under which the business organisation is
able to categorise the new information. The new observations are being analysed under this
technique and the three statistical classification are as follows:
 Assign the documents automatically
 Categorisation
 Develop profiles
Regression analysis: There are two variables dependent and independent. In this
technique the independent variable is manipulated so that so that its influence of dependent
variable can be understood. The impact of loyalty programmes on the satisfaction level of
customers can be analysed with the help of this technique.
How Big Data technology could support business an explanation with
examples
The use of big data has enhanced the ease for business organisations. They are now able
to complete the work in effective manner and manage the information properly. The need of
using big data is enhancing day by day (Sivarajah and et.al., 2020). For example, Tesco is a
multinational business organisation in retail sector. The company uses the data in order to now
about the competitors and the strategies being used by them. The same is used by them to gain
edge over the competitors being present in the market. Along with that, they collect information
regarding taste and preference of the customers and then make improvements in the product. All
this helps the company to use meaningful information that makes them successful.
To illustrate, the hospitality sector is also using big data and getting benefits by using the
same. There is need to manage the data so that insights can be taken. They use the information to
know about the trend that is present in the market. It also helps the company to bring innovation
and use latest technology so that success can be attained. It is necessary to use the information
for success of the company.

Poster

CONCLUSION
From the above report, it is concluded that a business organisation use large data set in
order to manage the work. There is need of understanding the concept of big data and using the
same in order to manage the data in proper manner. The characteristics of big data are important
part of this report. There are certain challenges that are being faced by the company at the time
of analysing the data and they are also evaluated in the report. The techniques and tool of big
data analytics are presented for better use by the business organisation. In the end, some practical
example of business organisation using big data are given.

REFERENCES:
Books and Journals
Amankwah-Amoah, J. and Adomako, S., 2019. Big data analytics and business failures in data-
Rich environments: An organizing framework. Computers in Industry, 105, pp.204-212.
Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data analytics in operations management.
Production and Operations Management, 27(10), pp.1868-1883.
Cirillo, D. and Valencia, A., 2019. Big data analytics for personalized medicine. Current opinion
in biotechnology, 58, pp.161-167.
Ghani, N.A and et.al., 2019. Social media big data analytics: A survey. Computers in Human
Behavior, 101, pp.417-428.
Hariri, R.H., Fredericks, E.M. and Bowers, K.M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data, 6(1), pp.1-16.
Mehta, N. and Pandit, A., 2018. Concurrence of big data analytics and healthcare: A systematic
review. International journal of medical informatics, 114, pp.57-65.
Ristevski, B. and Chen, M., 2018. Big data analytics in medicine and healthcare. Journal of
integrative bioinformatics, 15(3).
Saggi, M.K. and Jain, S., 2018. A survey towards an integration of big data analytics to big
insights for value-creation. Information Processing & Management, 54(5), pp.758-790.
Singh, S.K. and El-Kassar, A.N., 2019. Role of big data analytics in developing sustainable
capabilities. Journal of cleaner production, 213, pp.1264-1273.
Sivarajah, U and et.al., 2020. Role of big data and social media analytics for business to business
sustainability: A participatory web context. Industrial Marketing Management, 86,
pp.163-179.