1. A data processing system implemented method of directing a data processing system to improve execution efficiency of a database workload to be executed against a database, the database comprising database tables, the database workload identifying at least one of the database tables, the data processing system implemented method comprising: identifying candidate database tables being identifiable in the database workload, the identified candidate database tables being eligible for organization under a clustering schema; simulating database workload performance based on clustering data points along each of a plurality of candidate clustering dimensions at an estimated finest useful dimension granularity (FUDG) coarsification level; selecting the identified candidate tables according to whether execution of the database workload is improved if the selected identified candidate table is organized according to the clustering schema; and organizing the selected identified candidate tables according to the clustering schema prior to the database workload being executed against the database, wherein the estimated finest useful dimension granularity (FUDG) coarsification level comprises estimating the point at which granularity resulting from coarsification is optimal such that any finer granularity results in storage expansion exceeding an acceptable amount.