1. A method for clustering a set of data points, the method comprising: generating, within volatile or non-volatile storage of at least one computing device, a first cluster that includes a set of data points; computing, by at least one process executing on the at least one computing device, a set of similarity values for a plurality of data point pairs within the set of data points; wherein each similarity value in the set of similarity values corresponds to a respective data point pair from the plurality of data point pairs and is computed by the at least one process based, at least in part, on a distance between the respective data point pair and a set of one or more arbiter data points; partitioning, within volatile or non-volatile storage of the at least one computing device, the first cluster into a set of two or more clusters; wherein each cluster of the two or more clusters includes a respective subset of data points from the set of data points; determining, by at least one process executing on the at least one computing device and based at least in part on the set of similarity values, whether to partition at least one cluster of the set of two or more clusters to generate a final set of clusters; outputting, by the at least one computing device, an analytical result that is generated, based at least in part, by analyzing cluster-specific data representing one or more clusters from the final set of clusters.