Kennedy, Oliver AndrzejLee, SteveLoboz, CharlesSmyl, SlawekNath, Suman2011-05-232011-05-232011-05-23201110.1145/1989323.1989482https://infoscience.epfl.ch/handle/20.500.14299/67746We present Fuzzy Prophet, a probabilistic database tool for constructing, simulating and analyzing business scenarios with uncertain data. Fuzzy Prophet takes externally defined probability distribution (so called VG-Functions) and a declarative description of a target scenario, and performs Monte Carlo simulation to compute probability distribution of the scenario’s outcomes. In addition, Fuzzy Prophet supports parameter optimization,where probabilistic models are parameterized and a large parameter space must be explored to find parameters that optimize or achieve a desired goal. Fuzzy Prophet’s key innovation is to use fingerprints that can identify parameter values producing correlated outputs of a user-provided stochastic function and to reuse computations across such values. Fingerprints significantly expedite the process of parameter exploration in offline optimization and interactive what-if exploration tasks.Probabilistic databaseMonte CarloBlack boxSimulationtext::conference output::conference proceedings::conference paper