BMP4005 - Information Systems: Big Data Analysis & Business Support

This report provides a comprehensive analysis of big data technology and its impact on business. It defines big data and its key characteristics (volume, variety, velocity), discusses the challenges of big data analytics (data security, complexity, maintaining quality), and explores available techniques for analysis (data mining, machine learning, statistics). The report also highlights how big data technology can support business by improving data management, ensuring data privacy, and enhancing customer engagement, providing examples such as ASDA and Tesla. The conclusion emphasizes the importance of big data for investigators and management, noting the challenges that need to be addressed and the potential for rapid operational improvements in the management business.

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Contents
Introduction 2
What big data is and the characteristics of big data 2
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The challenges of big data analytics 3
The techniques that are currently available to analyse big data
4
How Big Data technology could support business, an explanation
with examples 5
Poster 7
References 7
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Introduction
Big data technology is linked with a broader term of data and source of information
that manages several sorts of customers in management. It is an essential and obligatory term
for the management to manage their big data analysis that involves growth in the marketplace
(Adnan, Tanjim, and Adnan, 2021). The management of a business has to develop efficient
operational and functional software for managing the company's roles linked to big data
technology. The following project, covers the discussion of big data technology and their
features. It also explains various challenges that are effective in analyzing big data analytics.
At last, it covers the scenario of the big data techniques that support management's business.
What big data is and the characteristics of big data
Big Data
In the current competitive world, big data techniques are rapidly developing with a
practical impact on the information technology sector. Big data technology covers the
following sections: Hadoop, Spark, Hive, and Cloud. Big data technology is related to the
basic structure essential for managing the source of data. Such technology involves the
software that helps the system manage big data directly linked with the management. The big
data technique also includes the arrangement of several factors that manage the information
of the business and data holding that are efficient for the growth of the business and it will
develop temporal relation of big data. It covers two types of big data technologies that are
functional and as well as analytic big data technology (ALI, and SINIAK, 2021). It will
depend upon the task and activities of the IT sector in the business to analyses and maintain
the big data in a precise way to support the organizational operations. Big data is also help in
increasing the divisions to secured the actions that are essential for the business to develop
big data technology. The business of management can gain higher terms of occurrence in the
market field by big data technology that plays an effective role by presenting a more
comprehensive representation of data precisely.
Characteristics of big data
Big data also require the manner of the management business that follows a suitable
structure to gain higher term of success in an effective and efficient period of way. As the
management required to identify various sort of the factors that are related to big data
technology that are discussed below -
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 The volume of data - On a broader section, the management requires developing a
precise method in managing the larger period of data source, by maintaining the more
general term of data that are also essential for the administration to address the roles
of the business to hire skilled and able and as well as potential individuals. Significant
data volume is large and has a tremendous number of customers who effectively deal
with multinational and national terms of the business (Bettahar, and Aggoun, 2021). Variety of data - It is an immense term in the scenario of big data technologies that
are essential to be maintained effectively. It covers varied sorts of data to ensure that
the variety of big data will get transferred efficiently. The management has to present
their activities and tasks like financial outputs and develop an organizational plan of
action.
 velocity of data - In the present term of competitive world, the velocity of data will
get managed by developing advanced software like HADOP HPCC in the business of
management. The rate of data will have linked with the speed of the information
through which it will transfer from one division to another. It is an essential statement
for the management to manage the velocity of the information that are consistent for
the longer duration of success.
The challenges of big data analytics
Extensive data analysis will relate to an effective management business division to deal
with them. It has fixed aspects; most businesses in the present period will use big data
techniques. The organization requires focusing on big data to capture consumer satisfaction
for the long period of term. Presently, there are various sorts of challenges linked to big data
that are increasing consistently (Calic and Ghasemaghaei, 2021). It covers the efficient need
for data analysis to manage the customers' information. To overcome the problems linked
with big data analysis, the business should develop an in-depth reasoning of solutions by
taking advice from IT experts. The fundamental challenges in comprehensive data analysis
are discussed below - Data security - In the business of big data techniques, data security is linked with
various challenges. It plays an efficient role in maintaining and managing the data
from many sources. The investigator gathers the information from various points, and
the researcher will govern it to offer data security to their customers (Cohen, and
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Macek, 2021). In the present term of whole technology, various operations like
malware and spyware will directly link with the international time of data. It is always
a challenge for management to maintain an influential section of the divisions
effectively and efficiently. Data complexity – The researcher needs to overcome the barriers and issues by
managing the data complexities. The data is analyzable and inflexible, with several
divisions that make it difficult for the researcher to collect the data. It will directly
link with the challenges due to which ethical courses of the task will define the IT
experts in the business to handle the data complexities.
 Maintaining quality Data – Having an effective section for higher divisions of the
information will be hard for the business of management to be held. On the other
hand, business of governance is spending wider divisions of the time than on
overcoming such issues. It follows clean-up for the duplicates, faults, errors,
problems, uniformity, and absences. It also helps the business follow suitable
divisions and motivate to follow operations and functions of the management.
The techniques that are currently available to analyze big
data
 Data mining is a predominant technologies that are used by management to manage
extensive data analytic. It deals with varied approaches in terms of statistical and
machine learning with the aim of performing the functions and operations of the
business of management. Data mining pulls several sorts of divisions from a broader
set of data (Hirschheim, 2021).
 Machine learning – Machine learning will relate with the message that is directly
followed with the division of AI (Artificial Intelligence), machine learning, etc. On
the other hand, machine learning will concentrate on the structural concept of
computer science and algorithmic programs. Machine learning also provides various
analyses based on numerous sections with suitable orientations.
 Statistics - The technology includes managing and measuring such data worldwide
with a different and expandable structure term that develops and creates with a
defined section of the time. Big data technology follows the reasonable period of form
and size that is valuable (Lu, and Zhang, 2021). It helps in managing accurate and
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effective sections that can exist in the business, goods, and market performance for
the effective advancement and the betterment of the industry of management.
How Big Data technology could support business, an
explanation with examples
In the current competitive environment, big data technology helps the business create their
dealing rapidly by providing management in maintaining past term of data of their customers
effectively and efficiently. Several managerial sections can develop competitive advantages
with the support of big data technology. The big data technology will support in maintaining
the organization that holding the elements that are discussed below - Management of data - Big data technology will help maintain the source of the
information that supports the leadership business in an unionized manner. It helps in
retaining the customer effectively and efficiently. The big data techniques use the
broader term of software program and divisions that will be efficient for the industry
to manage high terms of pieces of information. The data collected by the big data
techniques are available for management intending to maintain frequent dealing for
the more extended time. For example, ASDA is an international United Kingdom-
based supermarket that manages significant terms of the source of their staff faculty,
part-time workers, customers, etc. With Privacy of Data – Data privacy is a practical and essential term for both management
and customers in the area. By utilizing the courses of the actions and tasks in big data
technology, it plays a vital role in organizational development by maintaining the
privacy of their customers and users' source of data (Shayakhmetova, et.al., 2021). It
will increase the value of customers by maintaining the privacy of a broader amount
of data. For example, Tesla is international UK-based car management that supports
several private divisions of the data with the help of big data technologies effectively
and efficiently.
 Customer engagement – Customer engagement is also a section that facilitates big
data techniques. It will also help in synchronizing the source of data in the
management business. It is a primary term that involves roles and obligatory sections
of the informatics practices with the motive of managing the divisions in the industry
to manage information to manage the number of customers (Silva, et.al., 2021).
Customer engagement is a fundamental precedence of all management that covers big
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data technologies that will also support to increase the organization's value by
maximizing the consumer satisfaction that will create consumer belief in the business
of management. For instance, the business of management of ASDA is a
multinational retail organization based in the United Kingdom. The management of
ASDA effectively maintains their accomplished customer engagement and
satisfaction with the help of big data techniques.
CONCLUSION
From the above mentioned report, it has been concluded that big data is an effective term of
the source of data that is useful for the investigator and the management. The big data
techniques also support the investigator manage an effective and higher amount of data than
using suitable methods. The researchers also involve several terms of the challenges and
issues that need to be overcome in terms of the big data techniques. It also covers several
further aspects that also maintain the dealing with several complexities in the management
business. Big data also covers the importance of the big data techniques in terms of their
applications in the industry for rapid operations and functioning.
Poster
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References
Adnan, T.T., Tanjim, M.M. and Adnan, M.A., 2021. Fast, scalable and geo-distributed PCA for
big data analytics. Information Systems, 98, p.101710.
ALI, B. and SINIAK, N., 2021. The need for big data analytics in decision-making in today's
world. VPLYV INDUSTRY 4.0 NA TVORBU PRACOVNÝCH MIEST 2020, p.14.
Bettahar, B. and Aggoun, A., 2021. The Role of Big Data Analysis and Strategic Vigilance in
Decision-Making. In Big Data Analytics (pp. 107-120). Apple Academic Press.
Calic, G. and Ghasemaghaei, M., 2021. Big data for social benefits: Innovation as a mediator
of the relationship between big data and corporate social performance. Journal of
Business Research, 131, pp.391-401.
Cohen, S. and Macek, J., 2021. Cyber-Physical Process Monitoring Systems, Real-Time Big
Data Analytics, and Industrial Artificial Intelligence in Sustainable Smart
Manufacturing. Economics, Management & Financial Markets, 16(3).
Hirschheim, R., 2021. The attack on understanding: How big data and theory have led us
astray: A comment on Gary Smith's Data Mining Fool's Gold. Journal of Information
Technology, 36(2), pp.176-183.
Lu, Y. and Zhang, J., 2021. Bibliometric analysis and critical review of the research on big
data in the construction industry. Engineering, Construction and Architectural
Management.
Shayakhmetova, B.K., and et.al., 2021, April. Descriptive Big Data Analytics in the Field of
Education. In 2021 IEEE International Conference on Smart Information Systems
and Technologies (SIST) (pp. 1-5). IEEE.
Silva, N., and et.al., 2021. Advancing logistics 4.0 with the implementation of a big data
warehouse: a demonstration case for the automotive industry. Electronics, 10(18),
p.2221.
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