1. A computer-implemented method for identifying data heterogeneity, the method comprising: receiving data associated with a column in a database; computing a cluster entropy solely for the data of the column as a measure of data heterogeneity, wherein the cluster entropy is computed by: determining a plurality of soft clusters from the data; assigning a probability to each of the plurality of soft clusters equal to a fraction of data points of the data that each of the plurality of soft clusters contains; and computing the cluster entropy based on a resulting distribution of the plurality of soft clusters, wherein the entropy of the resulting distribution comprises the cluster entropy; determining, via a processor, whether the data of the column is heterogeneous in accordance with the cluster entropy; and providing a determination of whether the data of the column is heterogeneous as an output to a user.