1. A method, comprising: determining, by a computer processor, a plurality of features associated with a dataset, wherein the plurality of features comprises a plurality of non-redundant features including a first feature and a second feature; determining, by the computer processor, a plurality of feature subspaces comprising a first feature subspace and a second feature subspace, wherein each feature subspace comprises a respective at least one feature from the plurality of features, and wherein determining the plurality of feature subspaces comprises: determining, by the computer processor, a first relevance metric for the first feature; determining, by the computer processor, a second relevance metric for the second feature; determining, by the computer processor, that the first relevance metric is greater than the second relevance metric; assigning, by the computer processor, a first rank to the first feature and a second rank to the second feature, wherein the first rank and the second rank together indicate that the first feature has greater relevance to the dataset than the second feature; determining, by the computer processor, that the first feature subspace includes only the first feature; and determining, by the computer processor, that the second feature subspace includes the first feature and the second feature; the method further comprising: 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.