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In the dynamic realm of data mining and database research, ethical considerations are crucial for ensuring responsible practices. [1] This paper delves into the ethical dimensions inherent in data mining within database research, addressing challenges and proposing solutions. It focuses on issues like data privacy, informed consent, algorithmic bias, and transparency. The research has a dual purpose: firstly, to comprehensively assess ethical aspects, unraveling dilemmas faced by researchers; and secondly, to formulate guidelines fostering ethical conduct in data mining. In this paper different variables have been identified and component analysis has been applied to identify the important variable as per the responses of the professional in the field of data mining. From the result it is very clear that the two most dominant factors which hold prominent place in the field of ethical consideration in data mining are Regulatory environment and trust and acceptance. The ethical consideration should stem from the said variables as tested through a questionnaire. By enhancing ethical awareness and accountability, the research contributes to maintaining the integrity of data-driven research practices, providing valuable insights into the complexities of the field and promoting transparency and societal trust.
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Dubey et al. (2024) studied this question.
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