Data Mining in Business: ITC516 Security and Ethical Report

This report delves into the multifaceted world of data mining, examining its crucial role in modern business operations. It begins by highlighting the reasons for data mining's widespread use, emphasizing its ability to analyze customer behavior and uncover valuable patterns. The report then explores various sectors where data mining finds application, including customer relationship management (CRM), fraud detection, education, and financial banking. A recent news article is analyzed to illustrate how data mining is used to identify houses at high risk of fire. The report then moves on to discuss security, privacy, and ethical implications associated with data mining. It highlights major security issues such as data breaches, access control difficulties, and the challenges posed by the sheer size of big data. The report also addresses privacy concerns arising from data collection and usage, as well as ethical considerations related to data mining's impact on human rights and scientific research. The importance of transparency and accountability in data mining practices is stressed. In conclusion, the report underscores data mining's transformative impact on business while cautioning against the potential risks and the need for responsible implementation. It emphasizes the importance of protecting customer privacy and maintaining ethical standards in the use of big data.

Running head: ITC516
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Name of Student
Name of University
Author’s Note

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TASK 1
Reasons for usage of data mining in the business
Why data mining is used?
Data mining is considered to be an important for the business process which helps to
study the pattern about the customer behavior towards its company. With the help of data mining
an unknown credible pattern can be explored which is helpful in business processing.
Various Sectors where data mining can be used
Data mining has wide application in various businesses some of them are listed:
CRM (Customer relationship management)
To establish a good relationship with the customer data mining can be used by the
company to analyze the customer data through which a certain pattern can be decoded (Wu,
2014). The decoded pattern can be used to retain, acquire customers and can also be used to
make strategies which is focuses on the customers.
In detecting fraud and lies
With the help of data mining a meaningful pattern is programmed and if any pattern
which is not valid is termed as a fraud, thus detecting it as a lie or fraud.
Education
In the education field the data mining is used for predicting the leaning behavior of the
student which is helpful for the institution to approximate the results of the student (Siemen & d
Baker, 2012).

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Financial Banking
In bank a huge amount of data is recorded every second who includes account number,
customer name, balance amount and many other things. In order to maintain such huge amount
of data and decode them to study the pattern of the customer way of doing banking, data mining
is used.
Healthcare business
Data mining helps to analyze data like best medicine practices, cost, volume of patients in
each category related data can be find out.
Recent article/news item relating to data mining business
Data mining start up enigma to expand commercial-business
The following article discusses about the death of five people due to the raging fire in the
New Orleans the fire was so intense that it engulfed the whole house the deputy mayor Andy
Kopplin condemned the news as the real tragedy but he also said that it as preventable if the each
houses in its neighborhood contained fire alarms. The officials decided to install fire alarms in
the houses which are at major risk of fire (Lohr, 2017). In order to select the house to install fire
alarms which is at most risk, they took the help of a startup company Enigma which is working
in the field of open data that involves collecting and mining public government information to
find the house which is at most risk.
The news article discusses that the officials in New Orleans are taking the help of the
technology in order to find the house which is at the most risk of the fire to install the fire alarm

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in them. The technology used here is data mining through the data mining enigma will analyze
the public records to gain insight to find the target houses.
Conclusion
From the article it can be concluded that data mining is not only limited for the business
purpose. If analyzed the importance of the data mining, it can be used in any field which is
shown in the above article that the data mining is used by New Orleans government to find the
house which is at most risk of fire to install the fire detectors (Miner, 2012). Big data is simply
the collection of huge amount of the data to derive a useful pattern which can be used as
information. Therefore it is applicable in the entire field which can be imagined.
References
Lohr, S. (2017). Data Mining Start-Up Enigma to Expand Commercial Business. Nytimes.com.
Retrieved 10 August 2017, from https://www.nytimes.com/2015/06/23/technology/data-
mining-start-up-enigma-to-expand-commercial-business.html
Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE transactions
on knowledge and data engineering, 26(1), 97-107.
Siemens, G., & d Baker, R. S. (2012, April). Learning analytics and educational data mining:
towards communication and collaboration. In Proceedings of the 2nd international
conference on learning analytics and knowledge (pp. 252-254). ACM.
Miner, G. (2012). Practical text mining and statistical analysis for non-structured text data
applications. Academic Press.

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Task 2:
Introduction
The report discusses the concept data mining and the major security problems in data
mining, privacy problems related to the data mining, the ethical implication related to the data
mining. It further discusses about the importance of this implication in the business and finally
concludes how effectively the company should use the data mining in keeping the mind the
privacy of its customer.
Analysis
Major security Issues in the data mining
Nowadays every operation is performed through the computer therefore it store the huge
amount of the data which can be misused if gets in the wrong hand ("Big data security problems
threaten consumers' privacy", 2017). The application of the big data is huge like predicting the
result before two to three days of its occurrence or studying the customer behavior (Aggarwal,
2013). The biggest challenge which is faced in this field to prevent the misuse of the data which
can compromise its privacy. Here is some of the threat which is related to the big data.
The big data size

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The amount of the data present in the big data is itself is the huge challenge to protect
these data from wrong hands to protect the customer’s privacy. A single breach can put
thousands of customer data at risk. A report in 2014 of the breaching of the Arkansas University
has compromised around fifty thousand student private data and in the same year e-commerce
giant e-bay has compromised over two hundred million customer’s data (Sagiroglu &
Sinanc,2013). The Amazon, in order to protect the data it distributing its data to twelve of its data
centers in the world to minimize the effect.
The access control difficulty
In order to protect the information it is recommended to have single access point, but it is
not possible in the case of the big data as it is the storage of huge amount of data and it is not
possible to have single access point for the big data, which make its vulnerable to breaching. The
software company does not take security as its high priority as it can cost them time and money
(Malik, Ghazi & Ali, 2012). An example can be software company Hardtop, a software has a
very basic security features but many big companies uses Hardtop as their corporate data
platform, despite its limitation
The privacy issues in the data mining
Privacy in place of security
In order to provide extra security to the customer data on the customer’s demand
the company uses access control, encryption, intrusion detection or backups. In order to apply
the extra security the company demands more private information of the customer to make the
data more secure (Davis, 2012). To update the security of the data the company treats every
person as a potential hacker who can pose threat to their security, even though the agency has

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sufficient information that a particular customer is not the terrorist it still makes more decrypted
version of his data.
The big data usage
The usage of the big data also raises the great concern. Various companies are using the
big data to track the online move of the customer to study their choices and the big data
companies are helping them to achieve their target by providing the private data to these
company (Jensen, Jensen, & Brunak, 2012). The big data can claim that they are doing this in
order to make online experience friendlier but the same information can be used against the
customer.
The Big Data, Human rights and the ethics of scientific research
It is truly the digital age for the world as almost all the operations are implemented with
the help of computers. There has been great revolution in the digital age. The online data which
is amassed can be analyzed to yield knowledge ("Big Data, Human Rights and the Ethics of
Scientific Research – Opinion – ABC Religion & Ethics (Australian Broadcasting
Corporation)", 2017). On one hand the big data has proved to be a potential application in the
entire sector like banking, healthcare sector, finance; it is also used for the research purpose in
area of biomedical, public health. It has also helped in the early detection of the disease
outbreaks thus treating with the possible solution, but on other hand through Snowden

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revelations the public came to know about the amount government surveillance on the people
thus misusing the power of big data which has not only compromised the privacy but also failed
the trust in them (Kitchin, 2013). The cybercrime and hacking news has created the fears among
people and made the digital world more vulnerable to hacking.
Ethical implication in data mining
The primary goal behind the usage of data mining is to analyze the huge and UN
meaningful data and derive some information or pattern which can be used in healthcare,
marketing, education and other various sectors. Data mining are used in these sectors to study the
customer behavior and follow according to it this it can in enhancing a company's revenue or
profits. Ethical implication is much different from the legal implication (Davis, 2012). To steal
the data and using it illegally comes under the legal implications but to develop the mindset and
carry out the business according to it comes under unethical business. The whole concept of data
mining is not bad as it has many useful advantages, and it is not going to stop despite its
limitations. The well known problem with data mining is when the private data of the individual
is used to market the products in order to target others (Poldrack & Gorgolewski, 2014). Though
companies appear to focus on the idea that more the data mining the more will be the sales of
their products. This might be acceptable with them but there will be disagreement with
customers.
Importance of these implications
The above described is the major issue with the data mining and it should be avoided by
the company. If a customer feel his privacy has been compromised by the company for the sake
of his own benefits. Then he has every right to take legal action against the company (Torgo,

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2016). It is the duty of the company to maintain the transparency in the usage of the big data and
if there is any breach in its data then it should take the responsibility for the loss.
Conclusion
From the report it can be concluded that the data mining has revolutionized the way of
doing business it has the application in every sector be it a health or finance or marketing. It is
also used as a security purpose for detecting fraud and lies by studying the customer behavioral
pattern. The data mining business is going to expand in coming age. The company has to
maintain transparency while using the big data should take the responsibility if there is any
breach in its data

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References
Aggarwal, C. C. (Ed.). (2013). Managing and mining sensor data. Springer Science & Business
Media.
Davis, K. (2012). Ethics of Big Data: Balancing risk and innovation. " O'Reilly Media, Inc.".
Jensen, P. B., Jensen, L. J., & Brunak, S. (2012). Mining electronic health records: towards better
research applications and clinical care. Nature reviews. Genetics, 13(6), 395.
Kitchin, R. (2013). Big data and human geography: Opportunities, challenges and
risks. Dialogues in human geography, 3(3), 262-267.
Malik, M. B., Ghazi, M. A., & Ali, R. (2012, November). Privacy preserving data mining
techniques: current scenario and future prospects. In Computer and Communication
Technology (ICCCT), 2012 Third International Conference on (pp. 26-32). IEEE.
Poldrack, R. A., & Gorgolewski, K. J. (2014). Making big data open: data sharing in
neuroimaging. Nature neuroscience, 17(11), 1510-1517.
Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In Collaboration Technologies and
Systems (CTS), 2013 International Conference on (pp. 42-47). IEEE.
Torgo, L. (2016). Data mining with R: learning with case studies. CRC press.
Big data security problems threaten consumers' privacy. (2017). The Conversation. Retrieved 12
August 2017, from https://theconversation.com/big-data-security-problems-threaten-
consumers-privacy-54798

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Big Data, Human Rights and the Ethics of Scientific Research – Opinion – ABC Religion &
Ethics (Australian Broadcasting Corporation). (2017). Abc.net.au. Retrieved 12 August
2017, from http://www.abc.net.au/religion/articles/2016/11/30/4584324.htm