Broadcast scheduling has been extensively studied in wireless environments, where a base station broadcasts data to multiple users. Due to the sole wireless channel's limited bandwidth, only a subset of the needs may be satisfiable, and so maximizing total (weighted) throughput is a popular objective. In many realistic applications, however, data are dependent or correlated in the sense that the joint utility of a set of items is not simply the sum of their individual utilities. On the one hand, substitute data may provide overlapping information, so one piece of data item may have lower value if a second data item has already been delivered; on the other hand, complementary data are more valuable than the sum of their parts, if, for example, one data item is only useful in the presence of a second data item. In this paper, we define a data bundle to be a set of data items with possibly nonadditive joint utility, and we study a resulting broadcast scheduling optimization problem whose objective is to maximize the utility provided by the data delivered.