Big Data Analysis: Role of Information Systems in Business Growth

This report provides an overview of big data analysis and its importance in modern business. It discusses the characteristics of big data, including value, velocity, variety, volume, veracity, visualization, and volatility, emphasizing the need for effective data management strategies. The report identifies challenges in big data analytics, such as a lack of understanding of complex data, integration of data from different sources, and ensuring data security. Techniques for analyzing big data, including machine learning and A/B testing, are explored. The report concludes by highlighting how big data technologies support business growth by enabling better decision-making, improving marketing strategies, and enhancing overall business processes. The use of technologies like HTML and Google Analytics for data analysis is also mentioned.

Information systems and
big data analysis

Contents
INTRODUCTION...........................................................................................................................2
Big data and its characteristics:...................................................................................................2
Challenges of big data analytics and techniques of analysing big data:......................................3
How big data technology supports business:...............................................................................5
CONCLUSION................................................................................................................................5

INTRODUCTION
Big data analysis is known as those processes that are used for controlling and managing
large amount of data and information by the management of the business organisation. With the
dynamic nature of business environment, it can be seen that the level of data and information is
increasing as there are changes in the company's management as well as their customers that are
present in the market (Almansouri and Masmoudi, 2019). The customers play an important role
by creating a huge data that is needed by the company for storing and managing information in
effective way. The data is very important in a business enterprise as it is used by business entity.
These play an important role as they are of greatly valuable aspect of the enterprise. For the
success of the enterprise, the data management is very important in the marketing framework. It
is necessary for the business entity to secure and protect their data from the loss as well as from
cyber-attacks. This report discusses and evaluates the concept of big data and its characteristics.
Big data and its characteristics:
There is presence of various kinds of data that are categorised in three segments which
are unstructured, unstructured and semi structured. There is a separate importance and value of
all these three segments in the business organisation. Structured data is known as that data which
is prepared in structured format as it is stored and kept in unique structure. It is that data which is
easily accessible and can be stored by user for the purpose of its effective use for user.
Unstructured data is that data which is not present in format form and is not easily accessible for
user (Huang, Wang and Huang, 2020). The concept of big data can be understood with different
types of characteristics in effective manner. The various characteristics of big data are described
as follows:
 Value: It is characteristic of the data that does not matter with the data amount and its
processing speed but it has its importance value that is for the user. It is necessary for the
processed data to see that it is reliable and useful for the enterprise. For the management,
it is very important in the organisation that there is development of various effective
strategies for data management.

 Velocity: This data characteristic is related with the processing speed and information
generation. For the company, it is important that the company has analysed the data
velocity so that it is evaluated and analysed that it is useful or not.
 Variety: It can be seen that the data can come from one of many other sources or it is
same nature. There is presence of different types of data sources that are used in
extracting them (Kolisetty and Rajput, 2020). There is extraction of large number of data
from these sources that are present in unique nature.
 Volume: This data characteristic is related with the data amount that is generated in the
enterprise within specific time period. For the company, it is possible that there is
presence of many data sources that creates and makes huge amount of data, which is
necessary to be managed for the company.
 Veracity: It is necessary for using data as it makes accuracy and true information. The
veracity of data is important and necessary because the company needs accuracy in the
operating of its various functions and operations. It also helps and guides in reduction of
the efforts wastage of the employees.
 Visualization: It is known as presentation of data in a very effective and attractive
manner thereby making it easy to understand and for complete usage in the business
organisation. There are numerous new and advanced ways that are present in market that
are used to making the data very effective and efficient with the help of maps, charts,
graphs and others.
 Volatility: Volatile is connected with changing data rate along with its life span. The data
nature is very dynamic and changing at it every stage of their functioning. It is possible
that the nature of the data keeps on changing from origin of the process.
Challenges of big data analytics and techniques of analysing big data:
There is possibility of company that they analysed the data and information so that it is useful
and valuable for the organisation. Various challenges are present during the operating and
functioning of the company (Ren and Ding, 2019). Brief discussion that is connected with the
same is discussed below:

 Lack of understanding of complex data: As the data level is increasing regularly in the
market thereby resulting in more complexities in the business. There is presence of some
companies in the market that lack proper learning platforms and methods in their entity.
This is because there is weak understanding by the management about the concepts
(Xiaorong, Shizhun and Songtao, 2018). It is necessary for those entities for the
implementation and development of various learning platforms in their enterprise for
reducing this problem.
 Integration of data from different sources: The biggest challenge faced by the
companies is multiple sources of data in big data analysis. There are various sources of
data that are present in the enterprise that are helpful in increasing the data volume as
there are negative results for the entity in the management of this data
(https://www.integrate.io/blog/get-data-from-multiple-sources/).
 Security and safety of data: The security and safety of the data is yet another challenge
that is faced by company. There are numerous cyber-attacks that happen on the
company's servers. There is even theft of the data as it is used for negative purpose. It is
necessary for the enterprise's management to develop an effective and efficient security
system within the entity. This will lead to security and safety of their data in the
organisation.
Various techniques are present and they are used in big data analysis. Some of them are
explained below:
 Machine learning: There are numerous machineries and technologies that are developed
in the market and are used for analysis by entities. These store greatly large amount of
data and information in their organisation. There is presence of many features in these
machines that are enjoyed by entities such as security of data, easily accessibility and
others.
 A/B testing: It is technique used for data management that is needed by the entity in
differentiating the data (Yang, 2021). This is done on the basis of factors and nature. The

A/B testing technique guides and helps the management to increases the sales of the
organisation.
 Statistics: It is technique that is used in data analysis. In this data is gathered from
various sources and it is represent in statistical manner that results in easy understanding
of data concept for the organisation management.
How big data technology supports business:
The big data technologies are necessary in growth and success for organisation. It helps in
grabbing different opportunities for the organisation from the market. In the market there are
technologies present that makes the big data for the company more understandable and reliable.
This data is used in many business functions like production, marketing and other by the
management. This results in more competitive and productive nature of process of organisation.
The effective and efficient marketing framework enabling the company in attracting more
customers (Zwilling, 2022). These new and advanced technologies used by data management
possess very attractive and useful tools that are used for security and safety of the data. These
technologies are helpful to the management in having secured and productive data for their
organisation. The company uses these like Bright Blue Consulting uses technologies like HTML
2 and google analytics as well as jQuery for analysing big data in its operating.
CONCLUSION
From this report it is concluded that the data management is important and valuable factor of
the organisation that requires focus and concentration from the management. The use of new and
advanced technology is very important for the data management as it is discussed above in this
report. There are various types of characteristics that are important and help in differentiating as
evaluated and discussed above within this report.

REFERENCES
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implementation on firm performance. Information Systems Frontiers, 22(2), pp.475-
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Ren, P. and Ding, R., 2019, March. The application and development of big data in transport
logistics industry in China. In 2019 IEEE 3rd Information Technology, Networking,
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