Efficient Query Processing for Modern Data Management Utkarsh Srivastava, Stanford InfoLab Efficient query processing in any data management system typically relies on: (a) A profiling component that gathers statistics used to evaluate possible execution plans, and (b) A planning component that picks the plan with the best predicted performance. I will first describe a range of modern data management applications, including sensor data processing, continuous queries over data streams, and query processing over web services, for which traditional profiling and planning techniques are inadequate. I will then focus on two specific contributions: a new planning technique for query processing over web services, and a new profiling technique that avoids the need for periodic, full scans of data. I will also summarize my results for profiling and planning in other modern data management scenarios, and I will outline directions for future work in this general area.