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Applications of data mining in business

1.Briefly Summarise why Data mining is used in Business.

2.Discuss about the about the Privacy, Security and Ethical implications of Data mining.

Data mining is a process, which involves discovery of patterns using database management system, machine language and statistics methods. It is a sub part of computer science where the requirements needed is information extraction from a data set and transformation into a simple language for futuristic use. Data mining is the next step followed for the analysis of knowledge discovery in databases.

This report consists of the definition of data mining and its requirement in business. The report is referenced with a recent example to understand the reason. This report also includes the ethical, security and privacy problems of adopting data mining processes along with some examples to support the statements.

Data mining is a very powerful and new tool with a potential to help business organizations or companies acquire the most important aspects, which is customer behavior and new client behavior. Data mining is a process of discovery of knowledge, which requires computer operation to search large data sets and find patterns to analyze the meanings in those data sets (Larose, 2014). The tools involved in data mining is used to predict behaviors of targeted customers and future trends which causes the business organizations or company involved make good decisions in almost every industries including finance, health, retail and production. By analyzing the data sets by technology of pattern recognition and statistical/mathematical tools, data mining identifies facts, relations or patterns.


The detailed uses of data mining includes customer churn which depicts the loyalty of the customer, market segmentation which consists of characteristics of the customers, fraud detection which shows the likeliness of fraud transactions. It also includes direct marketing that allows the highest conversion rates in the market, interactive marketing, which depicts the interests of users accessing a website (Shmueli & Lichtendahl 2017). In addition, trend analysis shows the difference in behavior in customers over a one-month gap, market basket analyzing helps the business organizations or companies to understand the favorable outcome of products to be purchased together with another. Data mining in business involves technologies that help to provide predictable, historical and current strategies that could be implied in the business. The functions of data mining include process mining, online analytics, reporting, text mining, event processing, performance management, and predictive analysis (Provost & Fawcett, 2013). Data mining can help the decision makers in a company or business organization to make successful actions and help the authorities to get information on marketing processes of the competitors, condition of the market or consumer behavior.

News article about data mining

News article about data mining:

According to a recent article from chicagotribune.com in 2013, a collaboration between technical firms in Chicago with the venture capital of CIA ("CIA venture arm invests in Chicago-based maker of artificial intelligence technology", 2017) is explained. Stuart Frankel, the CEO of the startup claims to be very pleased with the portfolio and hopes that contribution to the market in terms of expansion is achieved. The name of the tech firm is Narrative Science in Chicago.

To achieve the collaboration, Narrative Science developed a technology called Quill, which will help the intelligence agency in the identification of large data sets like financial transactions, video surveillances, and social media coverage. The intelligence algorithm of the technology will help in analyzing large collections of data and give a report in English. The program can make many types of formats, which ranges from business reports to tweets.

The news article also provides funny information regarding the Director of CIA (David Petraeus) saying that the technology provided by them is much greater than the technologies seen in most films like the Tom Cruise movies (Goldman, 2015). In addition, they also have confirmed that the technology of removing finger prints or eye prints are still not present.


The link is given as- https://articles.chicagotribune.com/2013-06-06/business/ct-biz-0606-narrative-science-20130606_1_intelligence-community-in-q-tel-technolog

Data mining is used to get the required and meaningful patterns in enormous data sets. The enormous adoption increase of data mining in almost all companies or organizations has created enthusiastic adoption and on the same time, an increased risks and pressures of data information acquisition is accounted for. Data mining has shown great results in cases of health and biomedical research. The pre-detection of outbreaks, detection of specific genes or patterns of side effects by drug ingestion is the places where data mining has shown success ("Big Data, Human Rights and the Ethics of Scientific Research – Opinion – ABC Religion & Ethics (Australian Broadcasting Corporation)", 2017). However, the Snowden revelations, has shown that how the use of data mining led to database hack and other cyber-crime which eventually led to breakage of  democracy, trust, privacy, liberty.

Privacy has become very difficult because of the evolvement in algorithms. Originally, data mining provided users to access information but with modernization, the advantages has greatly increased (Xu et al., 2014). The gathering of user information caused the emergence of many privacy related concerns. For example, the process involving the use of data mining can be used to get information of individuals like number, address, driver’s license, social security id, or e-mail. This has posed certain risks for collection of information from these individuals and analysis of the accrued data to create profiles of the users, which can be used in both the government and commercial sectors.

Implications in data mining

Security is another portion included in data mining. The security implication are seen where the information of individuals is analyzed beforehand. Data mining also helps to confirm individuals with criminal activities and get insights or patterns of criminal activities. It can also check whether dangerous terrorists are involved with any particular patterns of crime. Since, prediction analysis are provided by data mining officials, careful analysis of the details is required before taking necessary steps to deal with as it may happen that sometimes the data that is gathered might not have any reference with the ongoing investigation.


Ethics is supposed to be of help if there is reason involved but can provide obligations if information pursuing is required. For example, health care scientists who are engaged with big data are not considered for their self-interest research in terms of money or fame but by the acquisition of public materials, which is supposed to benefit people (Yoo et al., 2012). However, the use of these goods depends on the ethics implied. The right to privacy tells people to imply their rights of acting in any scientific inquiries and to benefit from them (Turner, 2014). The right to science allows favors participation of citizens in scientific works. In modern times, the development in technologies caused an increase in the count of citizens exercising their rights of participation in scientific works. In health records, sometimes people demand their rights to check for information from newly made surveys or equipments.  

Significance of in businesses:

The information collection by using data mining process has made legit uses as well as abuses ("Big data security problems threaten consumers' privacy", 2017). For example, if the use of prediction can be applied to know the weather condition after two days, uses of it will increase and this will invite security or privacy threats. In 2014, the breach of Arkansas University system affected 50,000 people and information of 145 million people was breached from eBay at the same time.

For buyers, the requirement of increased security in terms and conditions of the company or organization involved, agreements and trust seals are required to be collected from the companies or organizations that are involved in the collection of data. The requirement for more security measures like encryptions, illegal access detection and corporate methods are being taken up in the companies or organizations involved to increase security and tighten the relationship with the consumers.

Significance of in businesses

The need for increasing the revenue made is the most targeted concept present in nearly all business organization. The need to deliver targeted advertising is achieved by tracking the preferences and activities of the customers involved by the use of data mining. For example, the Personality Insights software of IBM helps to build an individual profile based on their activities in the internet (Junior & Inkpen, 2017). These activities are presented to be advantages for the customers to provide them valuable results but the usefulness lies only within the company or organization involved. For example, the insurance companies target users based on these data personalities.


These security concerns must be successfully removed as the power present from harnessing data mining can be used to detect many fraudulent activities and provide advantages (Provost & Fawcett, 2013). The main aspects to reference by the power of data mining are the transparency of the processes while providing security and privacy concerns from the companies or organizations involved. The authorities busy with data handling must provide satisfactory explanations of the data being collected and analyzed and the reason behind that. People are also needed to be educated about the storage and collection of these data and companies must give satisfactory explanations about the protection they provide to safeguard them which helps in building trust.

Conclusion:

Thus, it can be concluded from the report that there are many uses of accepting data mining in business. Its implementation helps the business organizations or companies to get successful insights regarding customer behavior or market analysis. However, the risk it poses is much greater and it is the responsibility of the involved organization or business to gather the necessary information to provide security in terms of privacy, security and ethics. This way the company can improve their customer relationship and do business for a long time

References:

Big data security problems threaten consumers' privacy. (2017). The Conversation. Retrieved 9 August 2017, from https://theconversation.com/big-data-security-problems-threaten-consumers-privacy-54798

Big Data, Human Rights and the Ethics of Scientific Research – Opinion – ABC Religion & Ethics (Australian Broadcasting Corporation). (2017). Abc.net.au. Retrieved 9 August 2017, from https://www.abc.net.au/religion/articles/2016/11/30/4584324.htm

CIA venture arm invests in Chicago-based maker of artificial intelligence technology. (2017). tribunedigital-chicagotribune. Retrieved 9 August 2017, from https://articles.chicagotribune.com/2013-06-06/business/ct-biz-0606-narrative-science-20130606_1_intelligence-community-in-q-tel-technology

Goldman, J. (Ed.). (2015). The Central Intelligence Agency: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies [2 volumes]: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies. ABC-CLIO.

Junior, R. A. P., & Inkpen, D. (2017, May). Using Cognitive Computing to Get Insights on Personality Traits from Twitter Messages. In Canadian Conference on Artificial Intelligence (pp. 278-283). Springer, Cham.

Larose, D. T. (2014). Discovering knowledge in data: an introduction to data mining. John Wiley & Sons.

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.".

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.".

Shmueli, G., & Lichtendahl Jr, K. C. (2017). Data Mining for Business Analytics: Concepts, Techniques, and Applications in R. John Wiley & Sons.

Turner, B. (2014). Universal Declaration of Human Rights. The Statesman’s Yearbook: The Politics, Cultures and Economies of the World 2015, 8-10.

Xu, L., Jiang, C., Wang, J., Yuan, J., & Ren, Y. (2014). Information security in big data: privacy and data mining. IEEE Access, 2, 1149-1176.

Yoo, I., Alafaireet, P., Marinov, M., Pena-Hernandez, K., Gopidi, R., Chang, J. F., & Hua, L. (2012). Data mining in healthcare and biomedicine: a survey of the literature. Journal of medical systems, 36(4), 2431-2448.

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