Data Visualization uses computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity and variability has increased considerably. This is due to the availability of uncertainty, error and tolerance information. The talk discusses visual steering to support decision making in the presence of alternative scenarios. Multiple, related simulation runs are explored through branching operations. To account for uncertain knowledge about the input parameters, visual reasoning employs entire parameter distributions. This can lead to an uncertainty-aware exploration of (continuous) parameter spaces. Coping with the heightened visual complexity and variability requires advanced strategies like comparative visualization, integrated views and inclusion of fuzzy sets in the visualization process.