ITECH 1100: Analyzing Data Mining Disruption in Clothing Industry

This report explores the potential impacts of data mining on the clothing industry, focusing on its ability to provide insights for decision-making, improve operations, and reduce costs. It covers data mining processes like data integration, cleaning, transformation, pattern evaluation, and presentation. The report also discusses brainstorming techniques to identify problems and solutions, ethical considerations, and potential disruptions caused by data mining implementation. Furthermore, it highlights the importance of regulations and ethical measures to control the industry and maximize benefits. The report concludes with a video plan outlining the major impacts of data mining on the clothing industry, including improved customer experiences and enhanced basket analysis. Desklib offers similar solved assignments and past papers for students.

Running head: UNDERSTANDING THE DIGITAL REVOLUTION
The potential impacts of data mining
On the clothing industry
Name of the Student
Name of the University
Author Note

1
UNDERSTANDING THE DIGITAL REVOLUTION
Part 1: Research
The main aim of the report is to identify the potential impact that arises with the use of
data mining in clothing industry. The main reason behind using data mining process is that it
offers a huge set of data that are used for identifying the insights associated with the vision of
data. With the help of data mining it is expected that the system will be able to have an effective
way of decision making process. Data mining helps in gathering the requirements effectively by
understanding the needs of the system. The data mining concept plays a major role in managing
the activities. The data mining concept helps in understanding the performance of the
organization. Data mining has earned a huge importance in the clothing industry as it offers an
effective way of managing the tasks with the use of business intelligence. Data mining mainly
focuses on collecting huge amount of data that can be analyzed for a variety of formats. This
helps in improving the operations, reduces the cost incorporated in the development process and
also ensures an effective decision is made with the help of the process. This allows the business
to collect a huge amount of data that has the potential to enhance the business performance. Thus
it can be stated that with the help of data mining it becomes easy to manage the activities that are
taking place within the clothing industry. The other processes which include in data mining are,
 Data Integration
 Data Cleaning
 Data Transformation
 Pattern Evaluation
 Data Presentation

2
UNDERSTANDING THE DIGITAL REVOLUTION
Part 2: Brainstorming
The brainstorming process is referred to the group activity that is being conducted for the
purpose of identifying the specific problems that are gathered for the purpose of evaluating the
process. While brainstorming on an idea it becomes essential to create a group that will be able
to meet the needs of the present generation. After this process there is a need to present the
problems so that it becomes easy to define the problems. The system will also provide an
effective guide for the purpose of supporting the users. With the help of brainstorming it is
expected that the user will be able to develop an effective solutions. By implementing data
mining within the clothing industry it is expected that the production will increase and will also
provide better support towards the clothing industry.
The data mining method has gained a huge importance in other industries also. Data
mining has gained a huge importance in healthcare industry and ensures a better way of
improving the health care system. This mainly uses data analytics for the purpose of identifying
the best practices that has the potential to improve the healthcare facility that is provided towards
the patients. Data mining has also gained huge importance in market basket analysis as it offers a
modeling technique for the purpose of understanding the behavior possessed by the buyers. The
information related to the buyers is stored within a system that helps in analyzing the trait
possessed by the users. The manufacturing industry has also implemented the data mining
concept for the purpose of enhancing the relationship between the architecture and products of
the manufacturing industry.
The brainstorming methodology makes it easy determine the possible consequences that
are likely to come along with the implementation of data mining in the clothing industry. The
clothing industry will earn huge profits with the use of data mining technology. This makes the

3
UNDERSTANDING THE DIGITAL REVOLUTION
processing effective and ensures that the organization is able to meet the target. However it is
expected that the companies related to clothing will get impacted if they fail to implement data
mining effectively. Moreover the competition within the market will also increase that will
hamper the overall performance of the organisation. The implementation of this technology will
enhance the performance of the system and will ensure better performance of the clothing
industry. Brainstorming technique will define ways for analyzing the requirements that are
gathered throughout the process and will ensure that an effective result is being delivered
towards the organization.
Part 3: Regulation and Ethics
The Lawrence Lessig regulation states that t there are four major forces associated with
the constraints that includes laws, social norms, market and architecture. Ethics plays a major
role in determining the performance of the clothing industry. While implementing a technology it
becomes essential to identify the impact that will be created with the use of the technology. Data
mining is mainly referred to the technology that possesses the ability to enhance the performance
of the system. Thus it becomes essential to have an effective measure that will ensure better
performance of the industry. The main reason behind implementing data mining in clothing
industry is to enhance the productions. The ethical implications will come when the
implementation of data mining will impact the performance of the system and has the potential
to harm the other organizations that are operating without the use of proper processing. After
analyzing the impacts associated with the data mining in the clothing industry it can be stated
that there is a huge need to have a proper control over the industry. This will provide better
advantages towards the industry and will ensure that huge benefits rate is obtained with the use

4
UNDERSTANDING THE DIGITAL REVOLUTION
of data mining. The main aim behind using data mining technology is to divide the works into
different clusters parts.
Part 4: Disruption
There is a huge need to mitigate the issues that comes along with the implementation of
data mining in the clothing industry. The clothing industry needs to utilize the technology
effectively so that it can achieve the benefits. There is a high need to determine the performance
of data mining that will provide better support towards the organization. With the use of an
effective technology in the clothing industry it can be stated that there is a high need to have
proper control over the technology so that it can attract maximum number of customers. The
major event that takes place within the clothing industry is collecting the proper raw materials
for the purpose of processing the output so that they can meet the need of the industry. This will
also help in making effective decision. It can be stated that the data mining technology will help
in improving the performance of the system. The major actors that are involved with the process
include the stakeholders associated with the project implementation and the main uses of the
clothing industry.
Part 5: Video plan
The main aim of this assignment was to describe the major impacts that are likely to be
faced by the use of the data mining technology on the clothing industry. While developing the
assignment I have focused on outlining the major impacts associated with the data mining. Data
mining is considered as one of main technology that benefits the users with enhanced
technology. Data mining offers great benefits towards the clothing industry by providing better

5
UNDERSTANDING THE DIGITAL REVOLUTION
support towards the industry. The major benefit that is offered with the use of data mining is that
offers an effective layout for the stores and ensures an effective way of improving the customer
experiences and increases the profits. Apart from this the data mining will also ensure a better
way of basket analysis. This will ensure better performance of the clothing industry. The main
reason behind implementing data mining within the clothing industry is that it helps in improving
the customer satisfaction by enhanci8nng the process associated with the clothing industry. From
the video plan it will become easy to manage the activities. This will help in understanding the
tasks effectively that are taking place.

6
UNDERSTANDING THE DIGITAL REVOLUTION
References
Ahmad, P., Qamar, S., & Rizvi, S. Q. A. (2015). Techniques of data mining in healthcare: a
review. International Journal of Computer Applications, 120(15).
Chen, F., Deng, P., Wan, J., Zhang, D., Vasilakos, A. V., & Rong, X. (2015). Data mining for
the internet of things: literature review and challenges. International Journal of Distributed
Sensor Networks, 11(8), 431047.
Chen, K. T., & Luo, J. (2017, April). When fashion meets big data: Discriminative mining of
best selling clothing features. In Proceedings of the 26th International Conference on World
Wide Web Companion (pp. 15-22). International World Wide Web Conferences Steering
Committee.
Crockett, D., & Eliason, B. (2016). What is data mining in healthcare. Insights: Health Catalyst.
Dua, S., & Du, X. (2016). Data mining and machine learning in cybersecurity. Auerbach
Publications.
Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business
intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32.
Hanuska, A., Chandramohan, B., Bellamy, L., Burke, P., Ramanathan, R., & Balakrishnan, V.
(2016). Smart clothing market analysis. Technical Report.
Jothi, N., & Husain, W. (2015). Data mining in healthcare–a review. Procedia Computer
Science, 72, 306-313.
KS, D., & Kamath, A. (2017). Survey on Techniques of Data Mining and its Applications.

7
UNDERSTANDING THE DIGITAL REVOLUTION
Mardonova, M., & Choi, Y. (2018). Review of wearable device technology and its applications
to the mining industry. Energies, 11(3), 547.
Ryan, D. (2016). Understanding digital marketing: marketing strategies for engaging the digital
generation. Kogan Page Publishers.
Tan, P. N. (2018). Introduction to data mining. Pearson Education India.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
learning tools and techniques. Morgan Kaufmann.
Ye, Y., Li, T., Adjeroh, D., & Iyengar, S. S. (2017). A survey on malware detection using data
mining techniques. ACM Computing Surveys (CSUR), 50(3), 41.
Zumbo, B. D., & Hubley, A. M. (Eds.). (2017). Understanding and investigating response
processes in validation research(Vol. 26). Springer International Publishing.