Trajectory data mining plays a most important role in the real world application which enables to predict the moving location details of humans, vehicles, animals and so on. Trajectory data analysis is a most difficult task due to frequent changing location details of humans due to its continuous mobility. Trajectory data might consist of more noise details which is more complex to analysis. It is required to have more concentration on the trajectory data analysis to ensure the accurate trajectory data mining outcome. There are various research methods had been proposed by different researchers to perform the analysis of trajectory data. In this analysis work, discussion of various trajectory data analysis techniques has been given. This analysis work provides the detailed discussion of working procedure of each trajectory data analysis method with the samples. And also comparison evaluation of the research techniques in terms of merits and demerits is given in order to evaluate the performance. Finally numerical evaluation of the research techniques is provided based on different performance metrics. From this numerical evaluation, best method has been chosen as base work to enhance the trajectory data mining.