Big Data Analysis for Business Management: Techniques, Challenges, and Opportunities

This report covers the concept of Big Data Analysis for Business Management, including the characteristics, challenges, and techniques of Big Data. It also explains how Big Data technology could support business organizations, with examples. The report includes a poster and accompanying paper on Information Systems and Big Data Analysis. Course code: BMP4005.

Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Accompanying Paper
Submitted by:
Name:
ID:
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Contents
Introduction 3
What big data is and the characteristics of big data 3
The challenges of big data analytics 4
The techniques that are currently available to analyse big data
5
How Big Data technology could support business, an explanation with
examples 6
Poster 7
References 8
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Introduction
Big data analysis refers to a process of inspecting large and complex data which has been
used in order to disclose the data. For instance, correlation preferences, hidden pattern and market
trends. This tool is useful in extracting the relevant information from large data which is helpful
for the company for making effective decision which leads to the reduction of risk. Information
system has a wide concept in the economy because all the business organizations are related to the
IT sector which include wide range of solution. The information system use internet which is
associated with network of devices for the purpose of ensuring the connectivity along with the
exchange of data. The communication network is created with the use of information technology
and by creating and administrating databases the information is safeguard. Information system
plays an important role in the organization as it perform several operations. Such as, conducting
business transactions, managing the organization, interaction with customers and many more. This
report deals with the concept of big data which include characteristics, challenges with the
technique of big data. Furthermore, it will cover the description of how big data technology
support the business organization.
What big data is and the characteristics of big data
Big data is defined as the data which is fast, long and complex and it is really difficult to
process with that b the use of traditional methods. Big data analysis include the actions of
accessing and storing the huge amount of information for analytics has been around for a long
time. Big data analytics are made for the purpose of helping the organization for taking data
driven decisions which leads to the improvement of businesses results. By the use of Big data,
organizations can improve their work performance by providing better services to their customers
which leads to the increment in the overall revenue and bottom line. The size of data is large and it
is impossible to process with that data by the use of traditional method. Big data analytics makes
the data easier for the companies so that they can use it for the purpose of finding new
opportunities which also result in the smarter management of the company. Hence, it is related to
the generation of higher profit by performing the business operations in more effective and
efficient manner which also result in happy customers and positive feedback. Big data involve
several functions such as data mining, data storage, data visualization, data analysis and many
more. Below mentioned are the some characteristics of Big data:
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 Volume: Big data deals with the several of technology processes which are related to
the large amount of data which has been collected from several of resources such as
social media, machines, networks and many more.
 Velocity: The velocity of big data is related to the speed of flow of data from various
sources such as application logs, social media sites, sensors, business processes,
networks, and many more.
 Variety: Data is found in any type of format such as numeric data, audios, videos,
financial transaction, emails and many more. In simple words, this feature of big
data defines the nature of extracting the data (Wang and et.al, 2020). Above
mentioned are the modern formats of data whereas in the ancient times, spreadsheets
and databases were used.
 Value: It refers to the benefits abstracted from the data. It is necessary that the data
should be relevant and valuable for processing. Data is consider as valuable after its
successful analysis.
 Veracity: This feature is related with the reliability and trustworthiness of data as
there are many ways to translate the data. In simple words, it can be said that the
accuracy of data can be determined.
The challenges of big data analytic
The challenge of Big data refers to the searching of best way of managing the large
amount of data, which also involve storing and analyzing the information in multiple data stores.
Some of major challenges of big data analytics are explained below as:
 Lack of knowledge professionals: In order to use the big data techniques, the
organizations are required to hire professional people having proper skills of using
large data tools. Some of professionals of big data who work with the several tools of
data are known as data engineer, data analyst and data scientist.
 Lack of proper understanding of Massive data: Due to the insufficient
understanding, organizations are fail in their big data initiatives. Mostly the
employees are not aware about the data, its storage, importance, source, processing
and many more.
 Data Growth Issues: One of the major challenge of big data analytics is storing of
large sets of knowledge. The quantity of knowledge being stored in data centers and
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databases of organizations increases quickly. It is really a huge challenge to handle
these massive data.
 Confusion while big data tool selection: It is a confusing step to select the most
simplest tool for giants data analysis and storage. There are several questions while
selecting any tool and it has been found that sometimes the companies are not able to
find out the answers.
The techniques that are currently available to analyse big data
It has been found that the organizations use a variety of techniques for data management in
order to acquire more insight into speed, scope and depth. Some of techniques of analyzing big
data are given below:
 Machine learning: It refers to the technique of big data which make the data
more understandable by displaying more trends and patterns. This technique work
as advantage in accelerating the processes by the use of algorithms in order to
making decisions (Sun and et.al, 2020). It is related with the recognition of trends
& patterns, upcoming information and then data is converted in visualize form. It
also provide prediction which is a limitation in human analyst.
 A/B Testing: Under this technique, the comparison among the two variants of a
version have been done for the purpose of identifying the the better performers
under a controlled environment. It perform the function of comparison, hence the
successful completion of A/B testing technique result in the higher earn of profit.
 Statistics: While analyzing the big data, it perform the function of collecting,
organizing and inferring the data by the use of several research methods such as
base surveys and experiments. Statistical technique make it easy to analyses the
big data by inferring understanding about implicit data sets or the fact that it is
trying to explain.
How Big Data technology could support business, an explanation
with examples
The technologies of big data provide new opportunities for business growth from the
internal view for the purpose of increasing interaction with users or customers. Big data provide
the tools to the business organizations which are helpful in making smart decisions based on the
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data or assumptions. The big data offers new perspective for companies to discover information
which can be utilized in appropriate way. Big data can help the business organizations in the
below mentioned ways:
 Understanding the Customers: By the use of big data, the companies performing
business operations can get to know more about their customers. The marketers get
to know more insider to their customers that what they want, what channels they use
to buy the products, what they will use and many more. For instance, Disney is
leveraging Big data technology for the purpose of understanding the behavior of
visitor at its theme park (Pramanik and et.al, 2017).
 Delivering smarter services or products: When an organization get to know about
the needs and preferences of their customers, they just focus on the production of
smarter products or services. Disney is doing this with its MagicBrand initiative.
For instance, Royal Bank of Scotland is using big data for the purpose of delivering
a better service to their customers. RBS is beginning to harness the potential of this
knowledge to better meet customer's need.
 Generating an income: Big data not only improve the decisions making processes
but it also leads to the understanding the behavior of customers. It helps the
organization in boosting the revenue or creating the extra additional income stream.
For example, American Express is handling more than 25 percent of credit card
transactions in the US. Amex is leveraging the data generated by these transactions
for the purpose of bringing the businesses and customers close together.
Poster
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References
Pramanik and et.al, 2017. Big data analytics for security and criminal investigations. Wiley
interdisciplinary reviews: data mining and knowledge discovery. 7(4). p.e1208.
Sun and et.al, 2020. Big data analytics for venture capital application: towards innovation
performance improvement. International Journal of Information Management. 50.
pp.557-565.
Wang and et.al, 2020. Big data analytics on enterprise credit risk evaluation of e-Business
platform. Information Systems and e-Business Management. 18(3). pp.311-350.
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