Information Systems and Big Data Analysis for Business Growth

This report provides a comprehensive overview of information systems and big data analytics, highlighting their importance in supporting business growth. It defines big data, outlines its key characteristics (volume, variety, velocity, variability, and veracity), and discusses the challenges associated with big data analytics, such as poor data quality, outdated technology, and information sharing issues. The report also explores various techniques for analyzing big data, including A/B testing, classification, statement analysis, and social network analysis. Furthermore, it examines how big data technology can support businesses through improved communication with consumers, product re-manufacturing based on client feedback, risk analysis, and data security measures. The conclusion emphasizes the significance of information systems and big data analytics in identifying customer needs, fostering positive relationships, and sustaining organizational growth.

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..................................................................5
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
The information system is basically defined as a set of integrated components which is
used by organization for processing, collecting and storing the information in efficient manner.
The information systems are also essential for faciliating knowledge, information regarding
goods and services to users within low time (Dagilienė and Klovienė, 2019). The big data
analysis is referring to the advanced tool which is used by firm for analysing and diversifying the
complex data effectively. 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.
TASK
What big data is and the characteristics of big data?
The big data is referring to information in large amount which is in the form of structured
and unstructured data. The information’s are created in quick manner and being shared with the
immense variety of sources. Due to having large amount of data, organization easily identify the
needs and desires of customers within low time. The main role of big data analysis and
information system is to collect, storing and processing various data quickly. Due to this the
services and other functions of organization are easily run in smooth manner. Customary
techniques of information is not developed for managing high volume and complicated, which
will eventually slowing down the particular software of big data. Various platforms which is
related with big data are specifically developed for managing data in large number which are
comes in systems in huge varieties and high velocities.
In aspect of big data, it has various characteristics which are described below -
 Volume – According to the name big data, it itself represents the size of information
which is large in volume. The value of information is determining the size of data.
According to this characteristic due to storing the information in high volume company
easily deliver the quality and right goods to customers for long time.
 Variety – It is defined as a nature of information and heterogeneous source which is
comes in the category of both structured and unstructured. In previous days, databases
and spreadsheet are the origin of information which is executed by mostly applications.
But in present time information is considered in the type of audio, pdf, videos, photoes,

emails and others in aspect of application analysis. Due to using this kind of data
challenges are raised for organization to maintain space in their systems.
 Velocity – That information’s which is generating speed, in which speed is created and
process for getting the demands with help of determining the actual potential of
information. The velocity in big data is dealing with pace where the information is
circulated from different sources which includes social media sites, application logs, cell
phones and other various networks.
 Variability – It is defined as an inconsistency which had been shown with help of
information at many times. Due to having inconsistency in the flow of data, firm is not
able to deliver the quality products and services to customers for long time (Forrester,
2019). Hindering the process of being capable for managing and handling the data in
efficient manner. The capability regarding extracting the value from large amount of
information are highly important as value of information is increased and is totally based
on insights which may be extracted by them.
 Veracity – It involves the quality and accuracy of information. The information which is
gathered may have less elements which may be imprecise or not being able to facilitate
essential insight. Sometimes gathered information might be complicated and complicated
for tacking in use and will creates confusion instead of provided insights effectively.
The challenges of big data analytics and the techniques that are currently available to analysis
big data
There are various challenges which are comes in the analysis of big data are discussed below -
 Poor quality of data source – When systems are based on information, where having the
error or defects and is unfinished. Those type of information’s are highly responsible for
generating poor output. The procedure of validation of information and managing quality
in data is sustained the effective coordination between employee and employer.
 Use of outdated technology – Due to the use of outdated technology information’s are
not processed in fast manner which leads to decrease the performance of employees
effectively. The other drawback of outdated technology is that here employees with in
firm is not able to deliver best quality goods and services to users in long time. Modern
technology which is highly capable for processing large amount of information quickly

and inexpensive manner. Therefore, in future time technology which is being utilized in
aspect of big data analytics will get outdated and sooner required more resources.
 Sharing of information – Through the access of information from the depository of
public will resulted in occurring various problems which is not good for any organization.
During the time of sharing data in large number with multiple users, sometimes
information’s are not send in systematic manner.
There are various types of techniques which are currently available for evaluating the big data
effectively which are described below -
 A/B Testing - Here various kinds of groups are compared with the groups of primary
controlling which having the intention for determine the treatment. It leads to increase the
goal element and it is happened only when more than two components are compared with
others to achieving the technique for gaining and examining the objectives. With help of
this type of testing the flow of information between employee and employer are easily
maintained for long time.
 Classification – There are different number of tools which are being utilized for
determining the categories (Guo and Wang, 2019). In this way fewer information’s are
monitor and belongs the learning which will support for taking effective decisions by
contributing different categories.
 Analysis of statement – It assist in understanding the expectations and wants of
customer base from the selected brand. In this way services of organization are highly
improved which is useful for interpreting the emotions by using various information’s
which is received by the statement of several peoples.
 Analysis of social network – It is utilized for improving the relationships between
customers and organization and also for understanding the social framework of customers
effectively. It can be a great tool to improve analytic capabilities in any field, for example
marketing analytics, churn prediction, health care, etc.
How big data technology could support business
 Communication with consumers – In today’s time the base of customers are very
intelligent enough for knowing their priorities effectively. Then according to that the sale
of company product are highly increased in low time. The strong communications are
maintained in the activities of business enterprises with help of using various social

media platform. In this way organization is able to enhance the reach to customers by the
support of big data and made interactions with users by knowing their wants and desires.
 Re manufacturing products – Due to the effective use of big data, organization is able
to evaluate their goods, according to the feedbacks which is received by clients. Then
after evaluating feedbacks modifications are made in their goods and services which
leads to enhance the customer satisfaction level at higher rate.
 Analysis of risk – It is defined as evaluation of organizations which impact the activities
of business (Jeong and Park, 2019). It supports in scanning of the feed of newspapers,
reports, social media and others to understand the present situations of the market. Due to
this various companies easily get support for knowing the current competition in market
and done changes in goods according to competition.
 Safety of data – Analytics of big data is beneficial for finding the whole database within
company. For protecting all types of data in the system it is necessary for organization
they must intall antiviruses and other advanced softwares. Then in this way organization
is able protect their data from various hackers and crackers for long time.

CONCLUSION
From the above analysis it is understood that information systems and big data analytics
are the very important tools for sustain the growth of organization for long time. Due to the
effective use of information systems and big data analysis organization is able to identify the
needs and desires of customers quickly. 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
Dagilienė, L. and Klovienė, L., 2019. Motivation to use big data and big data analytics in
external auditing. Managerial Auditing Journal.
Forrester, V.V., 2019. School management information systems: Challenges to educational
decision-making in the big data era. arXiv preprint arXiv:1904.08932.
Guo, T. and Wang, Y., 2019. Big data application issues in the agricultural modernization of
China. Ekoloji, 28(107), pp.3677-3688.
Jeong, Y.S. and Park, J.H., 2019. Advanced big data analysis, artificial intelligence &
communication systems. Journal of Information Processing Systems, 15(1), pp.1-6.
Mikalef, P. and Krogstie, J., 2020. Examining the interplay between big data analytics and
contextual factors in driving process innovation capabilities. European Journal of
Information Systems, 29(3), pp.260-287.
Rahul, K., Banyal, R.K. and Goswami, P., 2020. Analysis and processing aspects of data in big
data applications. Journal of Discrete Mathematical Sciences and Cryptography, 23(2),
pp.385-393.
Shastri, M., Roy, S. and Mittal, M., 2019. Stock price prediction using artificial neural model: an
application of big data. EAI Endorsed Transactions on Scalable Information
Systems, 6(20).
Sun, Z., Sun, L. and Strang, K., 2018. Big data analytics services for enhancing business
intelligence. Journal of Computer Information Systems, 58(2), pp.162-169.

Poster