1. A method, comprising: determining, by a computer processor, a set of non-redundant features associated with a dataset, wherein determining the set of non-redundant features comprises: determining a correlation metric between a first feature and a second feature; determining that the correlation metric satisfies a threshold value; determining that the first feature has a larger mean correlation with respect one or more features in the set of non-redundant features than the second feature; and including the first feature in the set of non-redundant features and excluding the second feature from the set of non-redundant features based at least in part on the first feature having the larger mean correlation; determining, by the computer processor, a set of one or more feature subspaces, wherein each feature subspace comprises a respective at least one feature from the set of non-redundant features; determining, by the computer processor, a set of one or more candidate exploratory actions, wherein each candidate exploratory action comprises a respective feature subspace and a respective instance of a respective outlier detection algorithm; determining, by the computer processor, an optimal subset of one or more exploratory actions from among the set of one or more candidate exploratory actions; executing, by the computer processor, at least one exploratory action in the optimal subset to obtain outlier data; processing, by the computer processor, the outlier data to obtain one or more outlier views; and presenting, by the computer processor, the one or more outlier views via one or more user interfaces.