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Data analysis is a significant component for the enhancement of a firm. The data analysis software and techniques are crucially utilized for the diversification of the stats of a firm thereby recognizing the inclinations with respect to the customers and construct a bonding. Data mining is a part of data analysis techniques and these software supports the organizations to obtain additional knowledge about the customer demands and the trend that is pertinent in the market.
The advent of the new and improved techniques have led to the increase in the use of the online services as it would lead to the segmentation of the information that are discovered from the customers and then are obtained by the companies for evaluation so that they can give out efficient services. It is seen that numerous organizations utilize the data analytics like the method of data mining that supports in obtaining information about the consumers in the most appropriate manner. These techniques aid in explaining the future trends of the consumers (Zhao 2015). It is seen that the customers have extensive understanding about the fact that the firms record their personal data in order to initiate the method of data mining. It is seen that the customers do not prefer that their personal information is not unutilized and are not falling into the wrong hands. The requirement for maintain privacy is important and therefore, it is seen that the organizations undertake ethical implications and methodological concerns to preserve the privacy of the data (Witten et al., 2016). The process of data mining gives out several concerns and thus, several belvederes are displayed, that reveals the appropriate utilization of the procedures.
The process of data mining is described as gathering the unidentified data that were available from the previous histories out of the large data sets and it is seen that if they are utilized in an accurate way, it would lead to rise in understanding. Kop et al., (2015) reveals that data mining is only a single step of data analytic tools for the attainment of the analytical techniques and the understanding the behavior of the customers. Web mining even known as the data mining process even adds certain knowledge regardingthe overall process of data mining and methodologies associated with it that are spontaneously applied to extract and determine the data from the online services and online documents. The definition discussed in this paper describes the concepts in the most efficient way. The process is by far provides the expanded form of the process of data mining that is secured by the moral codes of conduct to limit the intervention of the personal security or any other injuries that can have an effect on the society (Gandhi & Armstrong 2016). The fortification of the information is the most vital function for the companies and they frame their task according to the routing standards that have been developed and follow the recommended methods that will be useful in providing a proper point of start for the firms as they develop their policies of data fortification. Therefore, it can be said that data safeguarding is the utmost role of the organizations.
The introduction of data mining within the organizations has mainly been due to innumerable factors. The advantages of exploiting the process of data mining are well understood by the firms in the current scenario. It is known that data mining was mainly used for tracking any fraudulent operations and to analyze the national security of a country. However, recently with the advent of globalization, there have been various companies that have been entering the market of various countries and thereby increasing their customer base (Larose 2014). In order to organize the vast information with respect to customers organizations have been implemented the data mining procedure as reduces their work load and they can segregate the personal information of the consumers from the general information that can be shared with everyone. During the traditional method that were used by the organizations there was a confusion regarding, which data were personal and which were for general use. This led to misplacement of the data and the data falling into false hands thereby leading to problems for the consumers. The consumers were reluctant to share their original data. However with the introduction of data mining the information can be segmented with ease and this helps the firms to protect their personal information (Koh et al., 2015). The main role of data mining is to predict the future inclination of the market and the behaviors of the consumers with respect to the knowledge driven process of undertaking a decision. The mechanism of data mining can be useful for revealing the challenges that are faced by the organization. Data mining reduces the resolving time that traditionally took more time to rectify the challenges of the organization (Fan et al., 2014). The process of data mining improves the database mechanism with respect to the information that has not been discovered. Therefore data mining transforms the process of statistical evaluation within the organization.
The ethics and the moral conducts are essential to be examined so that the actions of individuals can be well understood. The ethics are established by looking at the sentiments of the society where the organization operates and thereby satisfying the consumers. Culture is regarded as the tombstone for the creation of ethical standards. The process of ethics is constructed with the help of a pool of moral assessment that sustains organizational behavior and attitudes of the human beings. It is the most effective process of completing a job that are demanded by the society and can be controlled under the legal system of a country (Shmueli et al., 2016). The assistance of the society is vital in order to frame an effective ethical procedure. There are circumstances when certain companies undertake unethical procedures but they perform by staying within the legal system. The ethical implication in a firm requires to be framed by looking at the factors that reveals discovers what is right and wrong.
The moral liabilities that a company is answerable to their customers and therefore it are their role to roam around and obtain figures and facts from the customers so that they can rectify the discrepancies that are available within the information given by the consumers (Nadiammai & Hemalatha 2014). There are various theoretical establishments that are prepared by companies to prepare the codes of ethics. It is seen that ethical implication can have a positive effect on the association of the firm with respect to their exterior partners. The codes even has a positive impact on the top level management of the firm and this up lifts them to establish a healthy culture leading to improved end results for the firm (Jain & Srivastava 2013).
The convenience of the information is enhanced even with the implementation of ethical standards. The companies tries to frame an extensive ethical strategy so that the customers are satisfied with their initiative and motivates them to share their information that can be useful for the process of data mining and increase the understanding of the customers by the industries. The use of ethical standard implies that the privacy of the personal information is maintained and thereby prohibits the exploitation of this information by other parties who are associated with the firm (Kaur & Aggarwal 2013). The implication of ethical standard is obvious as it typically safeguards the personal information and even segregates the general and personal information and thereby even aids the scientific analysts of the organization to analyze only the relevant information for their research (Fan and Bifet 2013). It is crucial that all the information are maintained in a server network with various protections and can be easily be accessible to only the parties who require this information in order to undertake any decisions or complete the data mining analytics.
Ethical implication is significant while assembling and recording the information in an effective way as the implementation of ethics establishes the feeling of safekeeping about the safety of the privacy thereby satisfying them (Braha 2013). Ethical procedure is undertaken to collect the data and the customers are not compelled to provide the information. The customers have the liberty to share their information up to limit they want. The companies therefore, introduce several operations thereby gaining an idea about their customers that develops their service and the procedure of data mining (Roiger 2017).
The paper under consideration is mainly constructed in order to understand the data analytical tools, mainly the technique of data mining and their role that helps in the enhancement of any firm. The next section of the study reveals the use of ethical standards and code of conducts that are essential to make the customers well aware of the processes that are used by the companies for the collection and the storing of their information and makes satisfies them that their data are in safe hands.
Braha, D. (Ed.). (2013). Data mining for design and manufacturing: methods and applications (Vol. 3). Springer Science & Business Media.
Fan, C., Xiao, F., & Wang, S. (2014). Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques. Applied Energy, 127, 1-10.
Fan, W. and Bifet, A., 2013. Mining big data: current status, and forecast to the future. ACM sIGKDD Explorations Newsletter, 14(2), pp.1-5.
Gandhi, N., & Armstrong, L. J. (2016, October). Rice crop yield forecasting of tropical wet and dry climatic zone of India using data mining techniques. In Advances in Computer Applications (ICACA), IEEE International Conference on (pp. 357-363). IEEE.
Jain, N., & Srivastava, V. (2013). Data mining techniques: a survey paper. IJRET: International Journal of Research in Engineering and Technology, 2(11), 2319-1163.
Kaur, P., & Aggarwal, H. (2013). Analysis of different Web Data Mining Techniques: A review.
Koh, H. C., Tan, W. C., & Goh, C. P. (2015). A two-step method to construct credit scoring models with data mining techniques. International Journal of Business and Information, 1(1).
Kop, R., Hoogendoorn, M., Moons, L. M., Numans, M. E., & ten Teije, A. (2015, June). On the advantage of using dedicated data mining techniques to predict colorectal cancer. In Conference on Artificial Intelligence in Medicine in Europe (pp. 133-142). Springer International Publishing.
Larose, D. T. (2014). Discovering knowledge in data: an introduction to data mining. John Wiley & Sons.
Nadiammai, G. V., & Hemalatha, M. (2014). Effective approach toward Intrusion Detection System using data mining techniques. Egyptian Informatics Journal, 15(1), 37-50.
Roiger, R. J. (2017). Data mining: A tutorial-based primer. CRC Press.
Shmueli, G., Patel, N. R., & Bruce, P. C. (2016). Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner. John Wiley & Sons.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.
Zhao, Y. (2015). Data mining techniques.
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