Projects are considered successful when completed on time as per baseline schedule and within allocated target budget. Cost overrun is a worldwide challenge to successful completion of construction projects. To overcome this problem, earlier studies were conducted to investigate the main causes of cost overrun. Knowledge Discovery in Data (KDD) and data mining techniques have been implemented successfully in other research areas to extract new and useful knowledge from historical data. These techniques can be also applied to projects’ historical data if this data is captured in an organized and consistent manner. First section of this paper applies a comprehensive literature review on previous research to detect the major factors causing cost overrun. This analysis resulted in selecting twelve major factors that can be easily measured and analyzed at construction projects. After that, a data acquisition model is developed to capture the relevant historical data and metadata from completed construction projects in a reliable data warehouse. The developed data warehouse would enable the implementation of KDD and data mining techniques to tackle cost overrun problem.