1. A computer-implemented method for clustering a plurality of observations included in a dataset, the method comprising: selecting a subset of variables from a set of variables by performing a variable clustering technique, wherein each variable in the subset is associated with each observation in the dataset, and wherein each variable in the subset comprises a representative variable for a different plurality of variables included in the set of variables; for each of a first number of times, randomly selecting an initial value for each variable in the subset to generate a seed value set that includes an initial value for each variable in the subset; generating a number of pre-clusters equal to the first number based on a similarity between each observation in the dataset and each of the first number of seed value sets; and applying a hierarchical clustering algorithm to the first number of pre-clusters to derive a second number of clusters.