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Author: Admin | 2025-04-28
CONS OF DATA MINING 2 Cons of Data Mining What are the cons of data mining? Describe and provide some examples of cons in data mining that an organization may face. Data mining is about analyzing a large set of data and using the information obtained from the vast collection of data to formulate and making decisions using the conclusion made. The extensive data set will enable an individual to analyze and understand various aspects of elements in an organization. Even though data mining is significant to the organization in understanding various issues in the organization, it has some of the cons and contrary to the users and also the organization at large. One of the negative effects of data mining is that an individual has some limitations on the amount of data he or she can obtain in the organization. For example, organizations such as the healthcare industry, it will be difficult for an individual to collect all the data he or she is seeking to obtain. Also, during the collection of data, it can be expensive and take a lot of time to accumulate all the data required by the individual. Another con of data mining is that it lacks safety and privacy since the collection of data involves several factors, and that may involve breaching the privacy of the individual. During the data mining process, the data collected may be corrupted, sub-standardized, inconsistent, or misinterpreted, thus leading to an incorrect conclusion (Koh & Tan, 2011). An example where the data mining process can lead to inaccurate information is the data obtained through questionnaires. Even though the questionnaire can give insightful information on the progress of a company, some information collected can be misleading and not correct. Some individuals may provide wrong information through the process of answering
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