Testing and static analysis can help root out bugs in programs, but not in data. This paper introduces data debugging, an approach that combines program analysis and statistical analysis to automatically find potential data errors. Since it is impossible to know a priori whether data are erroneous, data debugging instead locates data that has a disproportionate impact on the computation. Such data is either very important, or wrong. Data debugging is especially useful in the context of data-intensive programming environments that intertwine data with programs in the form of queries or formulas.