Automated planning is a combinatorial problem that is important to many NASA endeavors, including ground operations and control applications for unmanned and manned space flight. There is significant value to integrating planning and data mining to create better planners. We describe current work in this area, covering uses of data mining to speed up planners, improve the quality of plans returned by planners, and learn domain models for automated planners. The central contribution of this paper is a snap shot of the state of the art in integrating these technologies and a summary of challenges and open research issues.