Data Mining Report: Business Applications, Implications, and Ethics

This report provides a comprehensive overview of data mining in business, exploring its applications, security, privacy, and ethical implications. It begins by summarizing the use of data mining in various sectors like retail, finance, and healthcare, highlighting its role in making business decisions, segmenting markets, and predicting trends. The report includes a news article from Forbes discussing how data mining empowers consumers to control their digital footprint. It then delves into the major security, privacy, and ethical concerns associated with data mining, such as data breaches, privacy violations, and ethical dilemmas faced by companies. The report evaluates the significance of these implications for the business sector, using examples like Walmart and IBM to illustrate how companies address security and privacy issues. It emphasizes the importance of ethical considerations in data mining to prevent misuse of data and protect individual rights, concluding that data mining is considered neutral and focuses on the ethical questions and concerns related to the data.

Report
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Contents
Task 1...............................................................................................................................................2
Briefly summarise why data mining is used in business.............................................................2
Article/news item relating to data mining in business.................................................................3
Task 2...............................................................................................................................................4
Identify the major security, privacy and ethical implications in data mining.............................4
Evaluate how significant these implications are for the business sector. Include Examples......5
References........................................................................................................................................7

Task 1
Briefly summarise why data mining is used in business.
The data mining includes the retail, finance, healthcare and the manufacturing which is
considered important for using the tools and techniques. The business is based on discovering the
patterns in order to make the business decisions for the sales trends, development of the smarter
marketing campaigns and then predicting all the customer loyalty functions. The specific uses
are based on:
a. The market segmentation which is to identify about the customer characteristics and then
work on the products of the company
b. The fraud detection and customer churning will help in identifying the transactions.
c. The direct marketing and the interactive standards are for the individual accessing of the
website which is considered to be obtained at a higher response rate.
The automated prediction of the trends and the behaviours helps in handling the processes where
there is a targeted marketing standard for maximising the returns on the investments. There are
predictive problems for the targeted marketing, which includes the use of the data on the
promotional mails to identify about the targets with maximising the return on the investments.
(Marinakos et al., 2016). The automation process with the unknown patterns are set to determine
about the hidden patterns with the use of business rules that are for the competitive advantage.
The increased revenues are from the credit card operations which are tested through the non-
intuitive possibility. The business trends are based on the knowledge driven decisions with the
check on how the retail companies adapt the data mining with the segments set for the regency,

frequency and monetary groups. The customer works with the utilities which includes the terms
that are used for the customer and for the collation of the billing information, handling the
customer services interactions, visits to the website and the other metrics.
Article/news item relating to data mining in business
https://www.forbes.com/sites/julianmitchell/2017/01/25/this-data-mining-startup-gives-
consumers-the-tools-to-own-their-digital-footprint/#4d9093b618db
As per the analysis, the articles about how the business is able to work on the data mining with
the specific sample pool. The data footprints help the users to collect and share the information
directly with the companies with the evolvement of the complete control of the personalised
data. The users can easily reclaim the control of the data with the empowering and setting of the
price or the barrier to access. The technology is based on the fact how there is a possibility to
ensure the privacy with the storage of the data locally on the device of the user, with the
normalised and aggregated form of the data. The specific business operations are to handle the
personal data backup. The data mining helps in the empowering of the consumers to set the
digital footprint. The company Digi.me has been focusing on making the future for the
individuals where there is a build-up of the scalable business for mobile, where the personalised
data platforms are based on individual sharing values set in between both sides of transaction.
The personalised data company is evolving with the individuals to become aware of the online
privacy and setting the personal dataset online.

Task 2
Identify the major security, privacy and ethical implications in data mining
Security: The security is based on the processing with creating the sequence with the queries to
extract information with the large amount of the data. The data mining techniques can easily be
used for the recovering of the problems with the database security. The growth of development is
based on the primary challenges with the consumers that will encounter the data analysis without
any giving of the right to use the information for any specific forms of the records. The
development of models can easily lead to the reduced security where the users might face certain
issues as well. The data mining is based on extracting the information where the companies
include certain forms of the security issues. (Huang et al., 2016). There are companies who need
to monitor the access for the data and check with the parts of warehouse to handle the access.
Privacy: The data mining standards set with the privacy and the legal issues are considered to be
the growing conflicts where there are governmental and the corporate entities that would lead to
setup of the information amount. The parts include the concern where the data is collected with
stored data warehouse, where the access is based on information. The technologies are based on
the extraction of data comes with finding different information and relationships for the
customers and then extracting the data. This leads to the customer’s information collection about
him/her. The technologies are available where the data mining could be for the extraction of the
data from the data warehouse. This helps in finding the different information and the relationship
for the customers with making connections that are based on the extraction. This would be able
to put the customer information as well the privacy at risks. (Pereira et al., 2016). The data
mining is mainly for the arrangements of the data and then to cover the consumer information

which includes the confidentiality and the privacy. The way is through the data aggregation
where the data could easily be handled in the form of different sources.
Ethical Concerns: The major use of the data mining includes the serious implications where the
companies generally seem to face some ethical dilemma where there is a need to decide if the
company should be aware of the personal information or not. (Ryoo, 2016). For this, there is a
need to check on how hurt the competitive advantage is in the market place, with the check on
deciding about the lack of the ethical concerns which leads to the loss of the consumers. The
company make use of the data mining and then work on the awareness programs that are for the
different applications. The consideration is about the wisdom.
Evaluate how significant these implications are for the business sector. Include Examples
Considering the company like Walmart, there have been approach set for the restricted extensive
database where the storage is of the stocks, stores and the data that is collected. The companies
have the products which are allowed under the database of Walmart, where there are companies
to handle the mining with the information that related to the sales of the product. The restriction
of the accessibility with the companies to work on the product offers is based on the accessibility
where Walmart has been able to show the concern of the security and the privacy when it is for
the data mining. (Shmueli & Lichtendahl, 2017).
Considering the privacy of IBM which works on the different methods of the mining. Here, there
is a need to work on the individual factors where there is a creation of accurate models. The IBM
works on the development of privacy preservation, where there is a randomisation of the
information with the transfer of the data. The data mining includes the gathering of information

and not impeding to the rights of privacy of the customer. There are different companies which
works on the governmental analysis with the use of the data mining for the jobs. Hence, for this,
there is a need to check on the quick transfer and processing that will make it easy for the
employees to identify the theft risks. (Shmueli et al., 2016). The privacy concerns are important
for the data mining with the risks evaluated through it. There are concerns about how the
consumers could buy the product and not become conscious of the technology of data mining.
The ethical concerns for the company includes the use of the data and then work on the
discrimination of the people based on the racial and the sexual orientations. The data mining is
considered to be illegal where the individuals need to be protected from any type of the unethical
activity. This will include the decision-making process and know about how the information
could be used. Through this, there are certain straightforward consequences which are for
making use of the information and relating to the privacy and individuality. The wrong use of the
data could easily be caused when the people fail to handle the unethical issues. (Tasioulas, 2016).
It is considered to be illegal as there is a major focus on the value and the protection so that there
is a possibility to work with the threats and the dangers to discuss about the different issues. The
experts consider the data mining to be neutral with the data that is for the questions and concerns
related to ethics.

References
Huang, D.W., Chen, J.L., Deng, P. and Lü, L., 2016, December. Big Data Mining and
Intercultural Business Discourse Studies: A Case Study of Li Ning's Corporate Social
Responsibility Reports. In Industrial Informatics-Computing Technology, Intelligent
Technology, Industrial Information Integration (ICIICII), 2016 International Conference
on (pp. 119-122). IEEE.
Marinakos, G. and Daskalaki, S., 2016. Viability prediction for retail business units using data
mining techniques: a practical application in the Greek pharmaceutical
sector. International Journal of Computational Economics and Econometrics, 6(1), pp.1-
12.
Pereira, S., Torres, L., Portela, F., Santos, M.F., Machado, J. and Abelha, A., 2016. Predicting
Triage Waiting Time in Maternity Emergency Care by Means of Data Mining. In New
Advances in Information Systems and Technologies(pp. 579-588). Springer, Cham.
Roiger, R.J., 2017. Data mining: a tutorial-based primer. CRC Press.
Ryoo, J. ‘Big data security problems threaten consumers’ privacy’ (March 23, 2016)
theconversation.com http://theconversation.com/big-data-security-problems-threaten-
consumers-privacy-54798
Shmueli, G. and Lichtendahl Jr, K.C., 2017. Data Mining for Business Analytics: Concepts,
Techniques, and Applications in R. John Wiley & Sons.
Shmueli, G., Patel, N.R. and Bruce, P.C., 2016. Data Mining for Business Analytics: Concepts,
Techniques, and Applications with XLMiner. John Wiley & Sons.
Tasioulas J. ‘Big Data, Human Rights and the Ethics of Scientific Research’ (December 1, 2016)
abc.net.au http://www.abc.net.au/religion/articles/2016/11/30/4584324.htm