Information Systems and Big Data Analysis

This report covers the meaning and characteristics of Big Data, challenges in Big Data analytics, techniques to analyze Big Data, and how Big Data technology supports businesses. It also includes examples of how Big Data is used in different industries. The report is relevant for students studying Information Systems and Big Data Analysis.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION ..........................................................................................................................2
TASK ..............................................................................................................................................2
Meaning of Big Data and the characteristics of the Big data. ...................................................2
The challenges of big data analytic.............................................................................................3
The techniques that are currently available to analyse big data.................................................4
How Big data technology supports business with examples:.....................................................5
CONCLUSION ...............................................................................................................................5
References........................................................................................................................................7

INTRODUCTION
Endless sources and insights to business has been provided by the Big data analytic. This
is very essential as this, not only bring enhancement in performance but also help in identifying
the unrealized opportunities available in every industry (El Alaoui, Gahi and Messoussi, 2019).
This ultimately give assistance in customer personalize. This assist the firm in fraud detection
and identify the hidden values with the help of collective data. The following report is going to
cover the meaning of Big data with its characteristic This report also covers the challenges of the
big data analytic and the techniques that are currently present to the big data. Afterwards this
report covers that how Big Data technology could support business with proper explanation and
example.
TASK
Meaning of Big Data and the characteristics of the Big data
Big data may be defined as a term which are used to describe the collection of data that
are huge in size and yet growing exponentially with time (What is Big Data? Introduction,
Types, Characteristics, Examples 2022). Example of big data analytics are stock exchanges,
social media sites, jet engines, etc. The valuable data may be acquired from the information of
the client, from server, and transactions like purchase, sales, employee history, financial
transaction and many more. This information not only give assistance to the apprehension of the
structure but also give assistance in effective business decision making. Some characteristic of
the Big Data has been discussed below:-
Volume :- this refer to huge amounts of data which is generated every second in the large
organisation(Jin, Xing and Wang, 2020). These data has been assorted from different sources
like social media, videos and financial transaction and many more. The volume of the data is
very important as this help in understanding the value and determinants of the collected data .
Variety:- this refer to the different sources of data and their nature. Earlier the data have been
available in data base and spreadsheet but in the recent years the massive data has been altered
and now these data have been presented in photos, audio files, text files and PDF s. For its
storage and analysis variety of data is very important.

Velocity :- this is related to the overall velocity at which the huge data are being rendered and
established. The velocity of the massive data production is linked in such a manner that which is
essential for fulfilling the demand of the user and effective analytical thinking
Value :- value is being considered as one of the most important among all the characteristic of
the bid data. The data must be reliable and useful no matter how fast the data has been
generating(Lin and Yang, 2019). First the raw data has been converted into information by the
data scientist and then pattern identification is done on this data. If the process is success then
the data is being considered as valuable.
Veracity :- this characteristic of the bid data is totally connected with the previous one. This
characteristic defines the degree of accuracy as well as trustworthiness of the collected data. As
the the data which have been collected by an individual is mostly unstructured. It is very
important for them to filter out the unwanted information and use rest of the data for processing.
.
The challenges of big data analytic
The analysis of the big data plays a very important role for the organisation. This not only
help in managing the risk but also help in enhancing the decision making process of the
company. In addition to this, this bring the accountability within the management, enhancing
their financial health and also help the employees and management in predicting the losses and
performance. Different types of challenges within the Big data analysis has been discussed
below:-
Lack of proper understanding of Big data:- the most important challenge which is associated
with the big data is the lack of proper understanding. Due to insufficient understanding
organisations are fail in their Big Data initiatives. Employees of the company don't know about
what is data, its storage process and its importance(Müller, Fay and Vom Brocke, 2018). For
example like if the importance of the data storage is not understand by the employees of the
company then they are not capable of backing up the sensitive data.

Data growth issues: -the storage of the large amount of data and setting up the data and
knowledge properly is also being considered as the foremost challenge of Big Data. The data of
the companies has been stored in the data centre and databases. This has been increased in a
very rapidly. This challenge affects the handling of the data which ultimately reflect on the
process.
The techniques that are currently available to analyse big data
The techniques of collecting Big Data helps in analysing, understanding and storing of
the data in a very proper manner. Suitable techniques must be used in order to complete the
task(Ye, Zheng and Tu, 2020). These techniques not only help in the decision making process
but also help in carry out the desired output and reduce the risk. Some techniques for analysing
the Big data has been discussed below: -
 A/B test:- this technique of data analysis involves comparing a control group with a
variety of test groups, in order to identify all the changes and treatment which improve
the given objective variable. This test only be possible if the groups are of a big size to
gain the meaningful differences.
 Data fusion and data integration: -in this technique focus has been paid on the
combined set of techniques which help in analysing the massive data different origin and
solutions. For an accurate and effective data this technique provide successful insight
which is relative to the original data collected from an individual
How Big data technology supports business with examples:
 Making better business decisions- Big Data helps by providing tools to the business
wherein they can make decisions based on accurate data and not just on some
assumptions (Zhang, Huang and Bompard, 2018). It is thus also known as data
democratisation because it helps in data exploring by the business users. For example,
well known Walmart company provides data access to its people in a controlled manner
through the Walmart's Data Cafe.
 Understanding the customers- it basically denotes that through data it is easier to
understand the requirements of the customers and serve them according to what they
wish. Thus it can be a great advantage for businesses to work by understanding their
customers. Famous example of this is the Disney which uses big data to understand the

behaviour of the visitors at their theme parks. They have also started the use of Magic
Band which is a wristband that serves as Id, entry key, etc.
 Improving the operations of business- Business sectors are increasingly becoming
automated through the use of big data (Müller, Fay, and Vom Brocke, 2018). For
example, chatbots are used to keep an active interaction with employees.
 Generating Income- Big data is not just easing the processes and the decision making
but it is also helping in boosting the revenue and income generation. For example,
American Express is using it to keep a track of both the businesses and customers and the
transaction carried out by them. Amex is using this data in bringing closeness between
customers and businesses. Delivering smarter products and services- When customer needs are understood by a
business, it helps them in designing product and services which are smart and automated
(Sestino, A., and et. al., 2020). For example, Royal Bank of Scotland is making the use of
Big data for giving their customers the best service while also saving their time and
money.
CONCLUSION
It can be concluded from this report that Information system and Big data analysis helps
in getting insights through the examination of large data. It helps in uncovering information
which can be market trends, hidden patterns, customer preferences which eases the business
organizations in making decisions that are carefully taken from the analysis. It helps to gather
information that can make a business perform and operate better. It is essential for the businesses
in making data-driven decisions so that they can have an advantage over their other competitors
in the market. Big data has various characteristics like volume, value, variety, Velocity, etc. it
helps businesses improve their work with respect to giving them an understanding of their
customers’ preferences.

References
El Alaoui, I., Gahi, Y. and Messoussi, R., 2019, April. Full consideration of Big Data
characteristics in sentiment analysis context. In 2019 IEEE 4th International
Conference on Cloud Computing and Big Data Analysis (ICCCBDA) (pp. 126-130).
IEEE.
Jin, L., Xing, M. and Wang, R., 2020, April. Operation framework of the command information
system based on big data analysis. In 2020 IEEE 5th International Conference on Cloud
Computing and Big Data Analytics (ICCCBDA) (pp. 459-462). IEEE.
Lin, H.Y. and Yang, S.Y., 2019. A cloud-based energy data mining information agent system
based on big data analysis technology. Microelectronics Reliability, 97, pp.66-78.
Müller, O., Fay, M. and Vom Brocke, J., 2018. The effect of big data and analytics on firm
performance: An econometric analysis considering industry characteristics. Journal of
Management Information Systems, 35(2), pp.488-509.
Sestino, A., and et. al., 2020. Internet of Things and Big Data as enablers for business
digitalization strategies. Technovation, 98, p.102173.
Ye, Z., Zheng, J. and Tu, R., 2020. Network evolution analysis of e-business entrepreneurship:
big data analysis based on taobao intelligent information system. Information Systems
and e-Business Management, 18(4), pp.665-679.
Zhang, Y., Huang, T. and Bompard, E.F., 2018. Big data analytics in smart grids: a
review. Energy informatics, 1(1), pp.1-24.
Online
What is Big Data? Introduction, Types, Characteristics, Examples 2022
[Online] Available through: <https://www.guru99.com/what-is-big-data.html>./