Data Mining in Business: Analysis of Data Mining Tasks and Articles

This report examines the application of data mining within a business context, focusing on its use in various sectors such as retail, banking, and manufacturing. The report addresses how companies utilize data mining to analyze customer behavior, optimize strategies, and improve profitability. It details the advantages of data mining, including its role in building effective marketing campaigns, managing financial records, and tracking manufacturing defects. The report also discusses a web-based tutorial tool, Logic-ITA, used by the University of Sydney to aid students in logical formal proofs. Furthermore, the report analyzes two articles, one discussing big data security and privacy threats and the other focusing on the ethics of scientific research in relation to big data. The report highlights the security and privacy issues associated with data mining, including data breaches and the potential misuse of personal information. Ethical implications, such as the use of mined data for targeted marketing, are also explored. Finally, the report concludes by acknowledging the limitations of data mining, such as the need for skilled analysts to interpret findings and the lack of causal identification, emphasizing the importance of responsible data management.

Running head: DATA MINING IN BUSINESS
Data Mining in Business
Name of Student-
Name of University-
Author Note-

1Data Mining in Business
Table of Contents
Task 1...................................................................................................................................3
Answer to Question 1:.........................................................................................................3
Answer to Question 2:.........................................................................................................4
Task 2...................................................................................................................................5
Article 1 (‘Big data security problems threaten consumers’ privacy’)................................5
Article 2 (‘Big Data, Human Rights and the Ethics of Scientific Research’)............7
Conclusion...........................................................................................................................8
References............................................................................................................................9

2Data Mining in Business
Task 1
Answer to Question 1:
Data Mining is mainly used by companies that have a strong focus on customer that deals
with communication, marketing organizations, financial and retail to determine price and the
transactional data (Ahme & Elaraby, 2014). Also product positioning, corporate profits and
customer preferences are looked after by a company. The records regarding point of sale can be
used by the retailer are done. Records of the customer purchase for further use are used for the
promotion and development of the product.
Every business, from a small industry that is coming up to a large business needs data
mining to maintain the records of the customers and other related issues such as customer
records, the products sale and the payment track made by the customers (Bhise, Thorat &
Supekar, 2013). The process included in data mining is to accumulate all the available haphazard
data into information that are valuable. This data mining helps to arrange huge amount of data
that are available in the company. The data that is present in a company are present in various
different forms. Data mining mainly organize these data into simple organized way.
The advantages of using data mining are
Retail or Marketing- Building models that are based on the historical data
to get an idea in who will acknowledge the campaigns of the new market
strategies are all done by data mining. It also helps to get benefit to the companies
that are retail in a same manner.

3Data Mining in Business
Banking and Finance- Data mining keeps a record of the loan or credit
from the bank. Such records are to be kept in a organized way.
Manufacturing- The manufacturing defects are also can be kept in record
b the manufacturer so there no issues come while reporting the company.
Governments- The records of the government related issues are also
tracked by data mining.
Answer to Question 2:
A tutorial tool is used in the University of Sydney that is web based. The name of the tool
is known as the Logic-ITA (Miled, Reffay & Laroussi, 2013). This web based tool is considered
as the second tutor of the University as it plays a vital role of the teachers in the University. It
has been over a decade that the University is using the system to help the students in completing
their assignments and helps the teachers to maintain a record of over 2000 students in the
university.
The main work of the system Logic-ITA is to help the students with their logical formal
proofs and helps the teachers to keep a watch on the progression of class they are in charge of.
The main function of the system is to find out a conclusion that is related to their proofs. To get
their proofs done, the students have to make formulas one after another with the previously
designed logic formulas and also the predefined rules that were defined in the tool itself till the
derivation is not complete. The teachers can view the student profile weather their proofs are
correct or not and make a database accordingly. The procedures that are performed by the
students are checked and if the steps are incorrect, then error message is prompted to the
students. The part of the module used by the teachers contains a database of all the students in

4Data Mining in Business
the University. Two consecutive tables are maintained by teachers. One table is for the mistake
part made by the student and the other table is for the correctly done steps (Hofmann &
Klinkenberg, 2014). In this mistake table the fields that are present are student login id, question
id, the mistake made by the student and the corrected rule that is needed. In the correct table, the
total number of lines to perform the proof, the starting date and the finish date are mentioned in
the table.
The tool helps to find out the student risks who have not received the training properly on
how to do the work. Cluster visualization helps the find out the student who has failed in their
tasks.
Task 2
Article 1 (‘Big data security problems threaten consumers’ privacy’)
The data demands more efficient execution in the business. These data are in various
different forms. To organize these data or information, data mining is done in an organization.
Analytical techniques that are used in business are mathematical techniques and algorithms. Data
mining helps to organize the information. Maintaining the cost of data mining is not an
affordable method, but to maintain such huge amount of data, data mining is to be done by
company (Ryoo, J., 2017). The best option to cut short the cost of maintain the data mining is the
outsource solution of data mining. Outsource services offers all types of data mining such as data
mining of stock market, data mining regarding statistics all at affordable prices.
Security Issues in Data Mining related issues are
 To mine different types of knowledge in a database is difficult.

5Data Mining in Business
 At different steps of abstraction a collective knowledge of mining is
done.
 Data mining ad-hoc and data mining language related to query.
 Visualization and expression of data mining.
 Pattern evaluation is also difficult.
Data Mining Privacy Issues play an important role business processes. Information
mining has pulled in huge intrigue particularly in the previous decade with its huge space of
uses. From the security point of view, information mining has been appeared to be valuable in
going up against different sorts of assaults to PC frameworks. Be that as it may, a similar
innovation can be utilized to make potential security dangers (Witten et al., 2016).
Notwithstanding that, information gathering and examination endeavors by government
organizations and organizations raised feelings of trepidation about protection, which persuaded
the security safeguarding information mining research. One part of security safeguarding
information mining is that, we ought to have the capacity to apply information mining
calculations without watching the classified information esteems. This testing undertaking is as
yet being examined (Provost & Fawcett, 2013). Another perspective is that, utilizing information
mining innovation a foe could get to secret data that couldn't be come to through questioning
instruments risking the security of people.
Ethical Implication of Data Mining With the ascent of information mining applications to
different segments, there is an equal ascent in worries about the morals of digging client
information for the thought process of benefit (Mostafavi & Barnes, 2017). The way toward
mining information by organizations is not going to decrease later on; rather it will increment
with more associations getting to PC control.

6Data Mining in Business
A standout amongst the frequently referred to issue with mining individual information is
the point at which the data mined from a person's utilization conduct is utilized to advertise more
items and administrations to that person (Roiger, 2017). Here organizations seem to concentrate
on the reasoning that if more information is mined then offers of items will consequently
increment. While this might be consistent with some degree it would seriously strife with clients.
Article 2 (‘Big Data, Human Rights and the Ethics of Scientific Research’)
Some of the underlying testing brings about security saving information mining have
been distributed. Be that as it may, there are as yet many issues that need advance examination
with regards to information mining from both protection and security viewpoints (Tasioulas J.,
2017). This workshop plans to give a meeting spot to academicians to distinguish issues
identified with all parts of protection and security issues in information mining together with
conceivable arrangements. Specialists and professionals working in information mining,
databases, information security, and insights are welcome to present their experience, as well as
research comes about.
Another zone of concern is the moral utilization of information mining applications in the
social insurance industry. Understanding data is required by law to be assembled just with finish
assent by the patient (Wu et al., 2014). What's more, such data can be gotten to or utilized by
look into organizations simply after many levels of security checks. Regardless of the controls on
paper and the organizations actualizing, a few coordinators perform dishonest mining of
information with no assent or endorsement keeping in mind the end goal to find another item that
may bring high income.

7Data Mining in Business
Conclusion
While information mining speaks to a noteworthy progress in the sort of diagnostic
apparatus right now accessible, there are constraints to its ability. One constraint is that despite
the fact that information mining can help uncover examples and connections, it does not tell the
client the esteem or essentialness of these examples. These sorts of judgments must be made by
the client. A second restriction is that while information mining can recognize associations
amongst practices and additionally factors, it doesn't essentially distinguish a causal relationship.
Fruitful information mining still requires talented specialized and expository experts who can
structure the examination and decipher the yield. Information mining is ending up progressively
regular in both the private what are more, open segments. Ventures, for example, managing an
account, protection, drug, and retailing regularly utilize information mining to diminish costs,
improve research, and increment deals. In general society part, information mining applications
at first were utilized as a way to recognize misrepresentation and waste, however have developed
to likewise be utilized for purposes for example, measuring and enhancing program execution.

8Data Mining in Business
References
Ahmed, A. B. E. D., & Elaraby, I. S. (2014). Data Mining: A prediction for Student's
Performance Using Classification Method. World Journal of Computer Application and
Technology, 2(2), 43-47.
Bhise, R. B., Thorat, S. S., & Supekar, A. K. (2013). Importance of data mining in higher
education system. IOSR Journal Of Humanities And Social Science (IOSR-JHSS) ISSN,
2279-0837.
Ryoo, J. (2017). Big data security problems threaten consumers' privacy. The Conversation.
Retrieved 12August2017, from http://theconversation.com/big-data-security-problems-
threaten-consumers-privacy-54798
Tasioulas J. (2017). Big Data, Human Rights and the Ethics of Scientific Research – Opinion –
ABC Religion & Ethics (Australian Broadcasting Corporation). Abc.net.au.
Retrieved 12 August 2017, from
http://www.abc.net.au/religion/articles/2016/11/30/4584324.htm
Hofmann, M., & Klinkenberg, R. (Eds.). (2013). RapidMiner: Data mining use cases and
business analytics applications. CRC Press.
Miled, M., Reffay, C., & Laroussi, M. (2014). An early evaluation of the HiPPY tool usage: the
France-IOI case study. ISSEP 2014, 45.
Mostafavi, B., & Barnes, T. (2017). Evolution of an intelligent deductive logic tutor using data-
driven elements. International Journal of Artificial Intelligence in Education, 27(1), 5-36.

9Data Mining in Business
Provost, F., & Fawcett, T. (2013). Data Science for Business: What you need to know about data
mining and data-analytic thinking. " O'Reilly Media, Inc.".
Roiger, R. J. (2017). Data mining: a tutorial-based primer. CRC Press.