Ending up with a lot of dynamics data ( be it trajectories or wavefunctions) is a common situation we face whenever we are working with real (and sometimes, evenmodel) systems. How can we make sense of these massive data in terms of concepts we understand? In the past two decades I and my team have been using modern dynamical systems theory to uncover simple structures buried under massive trajectory calculations. The power of this tool is due to a very simple property: It allows you to focus on collective behavior of families of trajectories rather than individual ones, thereby helping you to isolate generic behavior. I will give you specific examples from our research which illustrate the use of this powerful tool.