With the wide availability of GPS devices in our lives, massive amounts of object movement data have been collected from various moving object targets, such as mobile devices, animals, and vehicles. In the last decade, Moving Object Databases (MOD) have attracted many researchers. Analyzing such data has deep implications in many areas, such as ecological study and traffic control. In this study, we focus on moving object data (moving points) analysis and retrieve valuable information for knowledge discovery. In this research, a moving object data model is implemented in the object-relational database system, additionally some special queries and data mining techniques are performed. Retrieving information directly from unorganized spatial-temporal data is almost impossible. However, not only a vast amount of spatial-temporal data sets organized into MOD data model but also the discovery of valuable knowledge from spatial-temporal data to help decision support processes is possible now owing to this research implementation.