Information Systems and Big Data Analysis: Strategies and Impact

This report provides an overview of big data analysis within the context of information systems, highlighting its characteristics, challenges, and impact on business. It discusses the volume, variety, and velocity of data, as well as challenges such as data integration, security, and privacy. The report also examines techniques like data mining, machine learning, and statistics used for analyzing big data. Examples of companies like Morris Garages, Astra Zeneca, Amazon and Sainsbury's illustrate how big data technology supports business improvement, customer engagement, and overall growth. The conclusion emphasizes the importance of big data analysis for organizations to generate effective strategies and achieve their development goals.

What big data is and the characteristics of big data
In modern world big data analysis has become one of the most effective
perspective that leads towards affecting IT industry growth within an
organization. The important tools which are used within big data analysis are
Hadoop, Spark, NO-SQL, Hive and Cloud. In this technology and software
that has been used for big data analysis leads towards facilitating and
handling of information required to be used by organizations for their
betterment. Also, it helps upon analysing market condition which impacts
process of various department within an organization. There are different big
data technology that has been used for making operations regarding data
analysis conducted more effectively (Ju, Liu and Feng, 2018). It benefits
organization through creating ease within working environment. Thus big
data analysis has effective operations to be performed within an organization
that leads towards conducting data analysis in secured manner bringing better
stability. Further, big analysis plays important role within modern operations
of business that makes employees issues and customers’ needs to be fulfilled
by an organization. This makes important role to be played within business
operations making organization grow towards accomplishment of success
with modern marketing trends t
INTRODUCTION
Big data analysis means those perspectives which relates with various kinds
of activities related to data collection performed within an organization. Through this
analysis an organization is able to develop understanding about marketplace and its
growth which makes path of success paved for an organization. Also, big data analysis
has helped in making storage of data possible in order to prepare strategies and form
decisions leading towards organizational growth. The organization applying big data
analysis requires to use various kinds of software and programs that makes data
collection ad storage possible with better approach. In this report things are based over
particular relates to big data and its characteristics. Further, the file discuss about
various kinds of strategies which is used for applying information technology within
big data analysis. In the end assistance over big data analysis has been explained
through various facts impacting business.
Information Systems and Big Data Analysis

Information Systems and Big Data Analysis
Characteristics of big data
Big data holds importance within an organization about different kinds of
factors that makes data generation possible for accomplishment of goals and
objectives. This requires various characteristics and traits which has been discussed in
relation to big data analysis as follows:
 Volume of facts- It is important for an enterprise to boom its techniques that
has been dealing within big fats collection(Kolisetty and Rajput, 2020). Thus
big data volume makes moderate data base formed about types of client an
organization has as per product sales. In order to analyse big data volume facts
various kinds professionals and experts must be hired by organization which
makes appropriate results attained.
 Variety of facts- These facts are responsible for providing data over various
kinds of critical aspects which is important for growth in market. Also, variety
of data makes organization develop diversity within its various products or
services. Through using information technology such data is stored by
enterprises. Under these facts various elements are covered making technology
used with information to enhance profit and revenue generation capacity of an
organization.
 Velocity of facts- It is considered as the speed of facts via way of means of
which it is transferred from one deliver to another. In the brand new times
tempo of facts is managed via advanced software program software like
HADOP HPCC inside the industrial organization. It can be very masses critical
for a enterprise to control tempo of facts constantly for long term success of
industrial organization.
The challenges of big data analytics
Big data analysis and software used within it makes business
organizations more relevant towards data collection on large scale. It holds
importance within business operations and functions which makes large
customer base created with technological enhancement of IT department(Li
and et. al., 2022). Further, it is based over creating diverse components that
makes situation evolved by figuring out large information in relation to
marketing trends, customers preferences and product circulation. In order to
deal with various situations of data analysis professional advice is taken
from IT professionals. To implement these advice various challenges are
faced within big data analysis which has been discussed as follows:
 Data integration- This is based over controlling of big data that has
made integration of various components possible within an
organization. The information has important role to play in terms of
duties regarding research with data intergradation.
 Data complexity- This is based over addressing information over
complexity over research making issues solved. Data complexity is
an effective angle which is related with ethical usage of data making
information collected from authentic source only.
 Data safety- This is another challenge that has been faced by an
organization while performing online operations. It holds importance
as it directly makes sensitive information of clients and employees
leaked. To develop safety various IT software should be used while
data collected so that not virus or malware is able to hack or disrupt
online portals and taken sensitive information from it. In modern

Information Systems and Big Data Analysis
 Management of facts- Big data has handled various kinds of facts which
is used by an business enterprise in order to gain success(Zhang and et.
al., 2020). Through software program of IT department strong and
effective impacted is created upon sales and revenue generation. For
example Morris Garages that is an multinational vehicle agency located
in UK. It has capacity over controlling various factors which are applied
globally for organizations growth.
 Privacy of facts- The privacy of data is very important which makes
business organization improve software and other IT programs that stores
information within them. This is responsible for securing clients
information in more secured manner. For example Astra Zeneca that is
British multinational Pharma organization has been keeping data
collected about disease commonly existing within country making
customers preferences formed.
 Customer engagement- The customers engagement has been facilitating
large data that has lead towards synchronization of organization possible
with its customers. Customers engagement is done with the data by
preparing proper chart over consumption of data. For example Sainsbury
has been using product data to obtain customers satisfaction by satisfying
their needs.
The techniques that are currently available to analyses big data
The strategies to be had to examine bigdata are cited below:
• Data mining- The data mining is based over using devices within an
organization that makes big data analysed more effectively(Madrid and et. al.,
2019). According to data mining it is used for extracting styles which makes
techniques and device become more effective in nature. Also, it makes database
enhanced more effectively through using various techniques.
• Machine getting to know- These aspects is based over artificial
intelligence and device which makes technology improved and algorithm based
over it. The device is related upon evaluating upon various business aspects that
are wider in nature.
• Statistics- This is that technology which is used for process, control,
and examine of data which are used by an organization for evolving its
operations from time to time. These techniques and technology has made shaping
of valuable data possible. Further, technology and techniques makes data more
valuable in nature for displaying of products and services provided by an
organization.
How Big Data technology could support business, an explanation with examples
In this modern competitive environment big data technology has been
helping business organization to grow with better perspective that makes path to
be formed for conducting business that handles aspects related to employees and
customers. The big data technology plays crucial role in supporting business to
work over various factors that has been explained as follows:

Introduction to Business Studies
• Business improvement and boom- In the marketplace success of
commercial enterprise dreams and goal is the primary standards of an
commercial enterprise agency that leads over achievement of commercial
enterprise agency. Example, Amazon is an American e-trade agency which
makes gamer obtain essential objectives with the assist of large facts era inside
global marketplace.
CONCLUSION
From the above discussion it can be marked out that big data
analysis is an important perspective which is used by an organization to
research. Through big data collection all kinds of important information
which makes generation of methods possible regarding perspective that makes
organizations development possible. In this report various aspects related to
big data, challenges faced within it and its impact over organization has been
explained with the helps of examples.
REFERENCES
Books and Journals
Boranbayev, S and et. al., 2018. Method of processing big data. In Information
Technology-New Generations (pp. 757-758). Springer, Cham.
Jiang, D and et. al., 2019. Big data analysis based network behavior insight of cellular
networks for industry 4.0 applications. IEEE Transactions on Industrial
Informatics, 16(2), pp.1310-1320.
Ju, J., Liu, L. and Feng, Y., 2018. Citizen-centered big data analysis-driven governance
intelligence framework for smart cities. Telecommunications Policy, 42(10),
pp.881-896.
Kolisetty, V.V. and Rajput, D.S., 2020. A review on the significance of machine learning
for data analysis in big data. Jordanian Journal of Computers and Information
Technology (JJCIT), 6(01), pp.155-171.
Li, X and et. al., 2022. Big data analysis of the internet of things in the digital twins of
smart city based on deep learning. Future Generation Computer Systems, 128,
pp.167-177.
of the Madrid, O.C and et. al., 2019. Big data and machine learning in critical care:
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Zhang, C and et. al., 2020. An energy-aware cyber physical system for energy Big data
analysis and recessive production anomalies detection in discrete manufacturing
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