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Although data mining (DM) has already become more important recently, there are few comprehensive studies and categorization schemes to discuss the characteristics for DM. Applying bibliometric method, this paper explores research potential of DM in Taiwan through comparing globalization DM trends, forecasts and citations from 1993 to 2016 by locating heading “data mining” in topic in the Web of Science (WoS) database. The bibliometric analytical technique was used to examine the topic in WoS journals from 1993 to 2016, we found of 245 articles of Taiwan and 3053 articles of globalization. This paper surveys and classifies DM articles between Taiwan and globalization using the following eight categories – publication year, citation, document type, country/territory, institute name, language, source title and research area – for different distribution status in order to find the difference and how DM technologies and applications have developed in this period. Finally, the study will analyze DM technology trends, forecasts and citations based on the above results. Also, the paper performs the K-S test to check whether the distribution of author article production of Taiwan and globalization follows Lotka’s law or not. According to the analyzing results, this paper provides a roadmap for future researches, abstracts technology trend information and facilitates knowledge accumulation. Therefore, the researches of DM in Taiwan can follow and concentrate the globalization categories, and create the potential in the near future.