Analysis of Big Data and Information Systems: A Comprehensive Report

This report provides a comprehensive overview of big data and information systems. It begins by defining big data and outlining its key characteristics, including volume, velocity, variety, variability, and veracity. The report then delves into the challenges associated with big data analytics, such as outdated technology, data sharing issues, and poor data quality. It also explores various techniques used for analyzing big data, including A/B testing, classification, sentiment analysis, and social network analysis. Furthermore, the report examines how big data technology can support businesses by analyzing risk, ensuring data safety, and improving communication with users. The conclusion emphasizes the crucial role of big data analysis and information systems in sustaining business growth and meeting customer needs effectively.

Information systems and
big data analysis

Table of Contents
INTRODUCTION...........................................................................................................................3
TASK...............................................................................................................................................3
What big data is and the characteristics of big data....................................................................3
The challenges of big data analytics and the techniques that are currently available to analysis
big data........................................................................................................................................4
How big data technology could support business.......................................................................6
CONCLUSION ...............................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
The word business management is refer to the systematic administration of business
organization. The big data basically refer to the set of data which is stored in systems in large
number. The information systems is basically defined as the various types of equipments or tools
which is used by organization for run their functions smoothly. Due to the effective use of big
data organization easily gained adequate information regarding business operations (Alaei,
Becken and Stantic, 2019). With help of using various information organization easily developed
long term and short term plans for sustaining the popularity of their product and services
effectively. The report will cover what big data is and the charateristics of big data. It further
explains the challenges of big data analytics and the techniques which are currently available to
the evaluation of big data.
TASK
What big data is and the characteristics of big data
The big data is basically a complicated set of information which is being used by various
companies. These also explianed about various sources for achieving the data on internet. The
big data basically refers to various types of information at one place. In current scenerio
informations are made at any time. Moreover, it is related into immense accumulation of
important data through which the arrangement and entity is needed for evaluating, visualization,
storing and administration. The customary techniques of information which is not created for
negotiating the high volume along with the complicated, that would evetually reduce the
particular software of big data. The information systems is basically a integrated set of elements
storing, processing and collecting informations in effective manner.
Characteristics of big data -
 Variety – It is also known as heterogeneous source which is belongs in the category of
both unstructured and structured information. In previous time spreadsheet and database
are the origins of data which is implemented by various applications But in todays time,
data is delivered and produced in various types which includes pdf, audio, photoes,
videos emails and others regarding the analysis of application. With help of applying this
kind of information challenges are highly increased to organization for maintaining space
in their systems.

 Volume – The concept of big data itself represents the size of data which are huge in
number. The value of data is determining the size of informaion which is essential for
organization. In aspect of characteristics, due to storing data in huge volume organization
is able to provide high quality goods and services to users for long duration.
 Velocity – Those data which are responsible for generating speed, in which speed is
processed and created for getting the demands with help of determining actual potential
of data. In big data analysis, the velocity is dealing with pace where datas are circulated
with various sources. The names of those sources are cell phones, application logs,
various social media websites and others (Aljumah, Nuseir and Alam, 2021).
 Variability – It refers to the inconsistency which had been displayed through evaluating
data in many times. Due to keeping inconsistency in the flow of information,
organization is not able to facilitate high quality services and goods to customers. It leads
to decrease the revenue and goodwill of organization effectively in market. Hindering the
procedure of being capable for handling and managing information in effective way.
 Varacity – It involved the accuracy and quality of data. The data's which is collected
having low components which may be imprecise or not being able to provide insight
essentially. But in some circumstances the collected data might be highly complex for
tracking in utilize and will created confusion instread of facilitating insights in effective
manner.
The challenges of big data analytics and the techniques that are currently available to analysis
big data
There are different types of challenges that are comes in the category of big data analytics and
those are described below -
 Utilization of outdated technology – With the use of outdated technology datas are not
processed and delivered to lower level employees quickly. Due to this the performance of
lower level employees are easily reduced at higher rate. The other disadvantage for using
outdated technology is that here workers within organization is not able to serve quality
services and products to customers for long time. In today's time modern technology are
highly required and capable for processing huge amount of data quickly.
 Sharing of datas – With help of accessing the data from public depository, it will
provide output in aspect of raising various issues which leads to decrease the

performance of company effectively. At the time of sharing informations in huge amount
between multiple users, sometimes data are not delivered in proper manner. For reducing
this type of issues it is necessary for various organizations that they must use advanced
equipments in their services and job role. In this way employees are able to do their work
work with full interest and passion and in fast manner.
 Poor quality of data source – When the equipments are totally depend on data, various
types of defects or errors are highly occurred in file and it sustained unfinished. Those
types of datas are highly responsible for generating output in poor manner (Aversa,
Hernandez, and Doherty, 2021). The process of validation of data and keeping quality in
information is maintained the effective communication between employer and employee
for long time.
There are different types of techniques which are presently available for analysing the big
data in effective manner are described below -
 A/B testing – Here comparison are made between different types of groups of primary
controlling which have the intention for determining the treatment. Due to the use of this
type of testing the flow of data between top, middle and lower level employees are
effectively sustained for long duration. It leads to enhance the goal components and it is
happened only in those case where more than two elements are compared with others in
aspect of gaining the technique for examining the objectives effectively.
 Classification – There are various kinds of tools which are used by organizations for
evaluating the categories effectively. Due to this very fewe datas are monitor and
belonged to learning which is useful for taking right and difficult situations for long
duration. Due to the effective use of this tool informations are delivered to employees in
low time.
 Analysis of statement – This type of method is highly beneficial for understanding the
wants and expectations of customer base from selected brands. Due to this the activities
of company are strongly improved which is beneficial for interpreting the emotions by
utilizing various datas which is gained by several people statements.
 Analysis of social social network – Due to the effective use of this tool the relationship
between organization and consumers are highly improved. It also assist for understanding
the social framework of consumers in effective manner. It is a very effective tool for

improving analytical capabilities in any type of field such as health care, marketing
analytics etc.
How big data technology could support business
 Analysis of risk – It refers to the analysis of companies which are responsible for
effecting business functions in both positive and negative aspects. Due to the effective
analysis by using various sources such as reports, newspapers, social media and so on
organization easily understand the current situation in market. With help of this analysis
other companies easily knows the present competition in market and done modifications
in products according to competition (Garcia-Arroyo and Osca, 2021).
 Safety of data – The analysis of big data is useful for identifying whole data base in the
firm. For safeguarding various types of information in system, it is mandatory for firm
that they must advanced softwares and various antiviruses for long time. Due to this
company is able to protect their informations from various crackers and hackers
effectively.
 Communication with users – In present time the mind of the users are enough
intelligent for having better understanding of their priorities in efficient manner. In this
way the revenue of organizations are highly enhanced for long time. The effective
communications are managed in the functions of business enterprises by utilizing
different types of social media platforms. Due to this company is able to increase the
reach to users with the assistance of big data and easily sustained interactions with
customers by knowing their requirements.

CONCLUSION
After the evaluation of above data, it concludes that big data analysis and information
systems plays major role for sustaining the company growth in long term. Due to the effective
utilization information system and big data analysis company easily identify the requirements of
customers within low time. In this way the positive relationships are strongly sustained between
employee and customer for long time. The report will cover what big data is and the
characteristics of big data, the challenges of big data analytics and the techniques that are
currently available to analysis big data. It further covers how how big data technology could
support business.

REFERENCES
Books and Journals
Alaei, A.R., Becken, S. and Stantic, B., 2019. Sentiment analysis in tourism: capitalizing on big
data. Journal of Travel Research, 58(2), pp.175-191.
Aljumah, A.I., Nuseir, M.T. and Alam, M.M., 2021. Traditional marketing analytics, big data
analytics and big data system quality and the success of new product
development. Business Process Management Journal.
Aversa, J., Hernandez, T. and Doherty, S., 2021. Incorporating big data within retail
organizations: A case study approach. Journal of retailing and consumer services, 60,
p.102447.
Garcia-Arroyo, J. and Osca, A., 2021. Big data contributions to human resource management: a
systematic review. The International Journal of Human Resource Management, 32(20),
pp.4337-4362.
Hong, Y., Zhang, M. and Meeker, W.Q., 2018. Big data and reliability applications: The
complexity dimension. Journal of Quality Technology, 50(2), pp.135-149.
Johnson, J.M. and Khoshgoftaar, T.M., 2020. The effects of data sampling with deep learning
and highly imbalanced big data. Information Systems Frontiers, 22(5), pp.1113-1131.
Kachaoui, J. and Belangour, A., 2019, March. Challenges and benefits of deploying big data
storage solution. In Proceedings of the New Challenges in Data Sciences: Acts of the
Second Conference of the Moroccan Classification Society (pp. 1-5).
Sun, Y., Shi, Y. and Zhang, Z., 2019. Finance big data: management, analysis, and
applications. International Journal of Electronic Commerce, 23(1), pp.9-11.
Wang, Q., Ouyang, X. and Zhan, J., 2019. A classification algorithm based on data clustering
and data reduction for intrusion detection system over big data. KSII Transactions on
Internet and Information Systems (TIIS), 13(7), pp.3714-3732.