The rapid evolution of the data mining field has facilitated enormous achievements and new developments in organizations. To extract the potentially valid, understandable, novel, and useful data, data mining has become a non-trivial process in the real world due to its advantages of broad applicability, understanding, and scientific progress. With the tremendous improvements in the technologies and complexities in the different fields, data mining often confronts the advanced network and computational resources, heterogeneous data formats, ever-increasing business challenges, disparate data sources, research, and scientific fields. Advancements have shaped the current data mining applications in the different integration models of the data mining methods to cope with the data mining challenges. Nowadays, ubiquitous data mining, short text mining, distributed data mining, multimedia data mining, sequence, and time-series data mining are the emerging data mining trends.