Slice is one of the major operations in on-line analysis processing, which has played an important role in the application of decision support. In this paper, a method of mining exceptional slices is presented for extracting the distribution feature of the slice data based on the technique of the singular value decomposition, and the exceptional slices can be found by utilizing the distance-based outlier detection technique on the singular value feature. The effectiveness of the approach is experimentally demonstrated on the artificial data and the real slices data.