Data mining is a process that involves extracting useful information and insights from large data sets using various techniques and methodologies. Over the years, the field of data mining has evolved with new trends and technologies that have enabled the development of more sophisticated and accurate models. This paper examines five new trends that have emerged in data mining patterns, including anomaly detection, ensemble learning, graph mining, time-series analysis, and deep reinforcement learning. We analyze these trends and discuss their potential implications for the future of data mining, and also explore new innovations in algorithms that have enhanced these trends.