Data Mining Applications

Business Analytics Article Summary
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Business Analytics Article Summary
Data mining has become a valuable addition to today's world. Different industries rely on data mining to make predictions and better decisions. In their article, Apte et al. (2002) reveal that data mining applications are used in the insurance, direct-mail marketing, healthcare, and retail industries to reduce business costs, improve service quality, and increase business profitability. Effective data mining requires predictive modeling, where population data is segmented, and predictive models are developed for each segment to enhance predictive accuracy. These rely on historical data of the target individual. Predictive profiling, however, depends on historical data of the target individual as well as the larger population. It can be useful for customer segmentation, forecasting, and customization (Apte et al., 2002). The potential of data mining applications to solve many business problems calls for the development of better, more accurate techniques and tools to help businesses use available data to provide solutions.
Bartschat et al. (2019) also agree that data mining has become an integral part of life in recent years, providing solutions for business and life sciences industries, among others. Many data mining tools have become available, making it difficult for users to select the most suitable tools. However, data mining has come a long way, evolving from its statistical roots to become one of the most sought processes in areas such as the internet of things and smart technology. The increasingly large data sets available in today's world have necessitated the standardization of data mining processes. The data structure has also shifted from a 2-dimension to a 6-dimension (Bartschat et al., 2019). When identifying a suitable data mining tool, users should consider which user group they belong to, the tasks for their data mining, the structure of the data, the license model, and the data import and export options. The tools can al...