Information Systems and Big Data Analysis: Techniques & Applications

This report provides a comprehensive overview of big data within the context of information systems, defining its attributes and exploring the challenges associated with its analysis. It delves into the techniques used to address these challenges, such as machine learning, regression analysis, and social network analysis. Furthermore, the report highlights how big data technology supports businesses by enabling improved decision-making, smarter product and service delivery, enhanced business operations through automation, and the generation of new income streams, citing examples like Walmart, Royal Bank of Scotland, PeopleDoc, and American Express. The report concludes that big data technology, despite its challenges, is instrumental in driving organizational growth and innovation.

Information Systems
and Big Data Analysis
- A1 Big Data

Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY..................................................................................................................................3
Define big data and its attributes.................................................................................................3
Discuss the challenges faced in big data and the techniques used for solving these issues........4
Explain Big Data Technology Supporting Businesses with certain examples............................5
Poster...............................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
An accumulation of organised, semi organised and unorganised data collected by
organisation that can be extracted for information and can be used in anticipatory modelling,
technological projects and other advanced analytical techniques is termed as big data (Hou and
et.al., 2020). This report consists of Big data definition and its characteristics. It also includes
challenges faced due to analytics of Big Data and the techniques which are presently accessible
for Big data analysis. Support to business due to the use or Big Data technology have also been
considered in the following report.
MAIN BODY
Define big data and its attributes.
Big data is an assemblage of data that is huge in quantity, still has a potential or power to
grow speedily with time. The capacity of data is so huge and large in size that none of the
conventional data management techniques and tools can store it or operate it with efficiency.
Applications or technology that operates or stores big data have become a common factor of data
management structures in entities that supports use of big data analytics. Organisations uses big
data technology to upgrade their operations or working, and also to make available better and
improve services to its customers and promotional or marketing activities which in turn results in
increase in revenue and profits of the entity.
Big data technology carries multiple advantages with it such as:
 Provides better consumer or customer services
 Improves functional efficiency of the organisation
 Determines the risk to the product or services offered by the entity
 Enterprises can use external intelligence services in decision making process
Features of Big data: Big Data is an assemblage of data from a wide and different variety of
sources and commonly describe its five characteristics:
1. Volume: It refers to the unthinkable quantity of information that is created from social
media, cell phones, photographs, videos and credit cards. The name big data is itself
related to a size which means huge or enormous (Ianni and et.al., 2020). Size of data
plays a crucial role in determination of value of data. Also, the size of data totally

depends on the volume of the data. While dealing with Big data solutions, volume should
be kept into mind.
2. Variety: This refers to the heterogeneous sources and the quality of data, both organised
or unorganised are included. In the initial days, the only source of data considered by
most of the applications were databases and spreadsheets. IT is generated in different
varieties. In present scenario, photos and videos are also considered in the analysis of
application (Mangla and et.al., 2020).
3. Velocity: This term means to the generation of speed of the data that how fast a data can
be created or processed to meet the demands and determines the potential of the data. It
plays a vital role as compared to the other features of Big data. It makes available data on
demand and at a faster rate.
4. Variability: This means to the non-uniformity which can be shown by the data in some
cases, therefore restricting the procedures of being able to manage the data efficiently.
5. Value: It is the major concern of the entity using Big data technology. It is the amount of
important, dependable and honest data that needs to be preserved, progressed and
analysed to find and understand the insights.
Discuss the challenges faced in big data and the techniques used for solving these issues.
In this digital era, organisations use big data technology for better decision making, growth
in accountability, increase productivity, make improved and healthier predictions, performance
monitoring and to acquire a competitive advantage over its rivalries.
Major problems faced by using Big data technology are discussed below:
 Unable to provide new or timely insights: Organisations in order to take better and
improved business decisions uses analytics but in some cases it can be observed that the
information’s provided by the new system or applications resemble to the information
which has been provided earlier. This can be due to insufficiency of data, using
traditional approaches in a new system and data takes longer time to respond (Nguyen,
2018).
 Incorrect analytics: This is the main and important challenge faced by the enterprises and
it needs special and speedily attention of the management of the organisation to resolve
it. Inaccurate analytics can be occurring due to poor or inappropriate quality of data

which is incomplete or contains defects or errors and also due to faults in the system of
flow of data.
 Complications in using data analytics: Organisations find it difficult to extract value
from data when using data analytics becomes complicated. This complexity arises due to
less technical knowledge and when the users find it difficult to understand the system,
data and the reports (Sharma, Borah and Namasudra, 2021).
Techniques for analysing Big data: Machine learning: It involves software program that can learn from data. It provides
systems the capability to grasp without being defining programmed, and focuses on
building projections supported on known properties absorbed from sets of instructing
data. It aids in differentiating between junk and non-junk mail messages and make
suggestions based on the provided substance. Regression Analysis: It concern with contriving some independent variable to perceive
how it influences a dependent variable. It states how the value of a dependent variable
alters when the independent variable is deviated. It works best with continual quantifiable
information like mass, velocity or age group. Social network analysis: A method that was initially utilised in the telecom sector and
then rapidly acquired by sociologists to learn interpersonal relation and applied to
examine the relationships between groups in many sectors and commercial undertakings.
Explain Big Data Technology Supporting Businesses with certain examples.
With the use of Big Data, organisations can utilize analytics, and illustrate or build out the
most valuable or cherished customers. It can also assist industries in creation of new experiences
or content, services and products. Big data technology can aid businesses in five ways which are
discussed below:
 Making improves business decisions: Big data assist the businesses in taking smarter
decisions that are supported by data and not merely on assumptions. Users of the
company across the world have an ability to investigate and question data so that they can
response their most crucial business questions. This organisation's wide approach to data
is referred to as data democratisation (Vo and et.al., 2019). Walmart is an outstanding
example of this data democratisation. Significantly, Walmart supplies its people to

approach to data in a well organised manner securing that people who are not known of
the technology do not get engulf by data and can easily discover the solution they want.
 Delivering Smarter services or products: When an organisation come to know about its
customers, it starts delivery smarter or suitable products or services for its customers
which fulfil their needs completely and satisfies them to the fullest. Royal Bank of
Scotland (RBS) is a great example of organisation using Big Data to deliver a better
service to its clients. RBS is beginning to support the potential of this knowledge to
amend and improve its efficiency in order to meet its customer wants or needs.
 Improving business operations: The outgrowth in automation is supported by Big Data.
Robotics and high technology may be outdated in production industry lines. But,
progressively, a number of business sectors and operations are becoming more efficient,
effective and automated (Zhao, Xu and Wang, 2019). PeopleDoc, a HR software
company, that has launched a Robotic Process Automation platform, that operates
besides present system of the company and perceive for procedure or events that could be
automate
 Generating an Income: Big Data is not just about rising procedure and conclusions, or
knowing more about its customer's data can be processes and decisions, or understanding
more about customer’s data can be monetised to encourage or create an auxiliary income
stream. American Express is generating income by the aid of Big Data technology.
CONCLUSION
From the above prepared report, it can be concluded that, the Big data technology assist the
businesses along with facing various challenges and providing techniques or methods to face
those challenges and aid in the growth of the organisation.

Poster

REFERENCES
Books and Journals
Hou, R., and 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.
Ianni, M., and et.al., 2020. Fast and effective Big Data exploration by clustering. Future
generation computer systems, 102, pp.84-94.
Mangla, and et.al., 2020. Mediating effect of big data analytics on project performance of small
and medium enterprises. Journal of Enterprise Information Management.
Nguyen, T.L., 2018, December. A framework for five big v’s of big data and organizational
culture in firms. In 2018 IEEE International Conference on Big Data (Big Data) (pp.
5411-5413). IEEE.
Sharma, P., Borah, M.D. and Namasudra, S., 2021. Improving security of medical big data by
using Blockchain technology. Computers & Electrical Engineering, 96, p.107529.
Vo, A.H., and et.al., 2019. An overview of machine learning and big data for drug toxicity
evaluation. Chemical research in toxicology, 33(1), pp.20-37.
Zhao, Y., Xu, X. and Wang, M., 2019. Predicting overall customer satisfaction: Big data
evidence from hotel online textual reviews. International Journal of Hospitality
Management, 76, pp.111-121.