  Data stored in a data warehouse are inherently multidimensional, but most
data-pruning techniques (such as iceberg and top-k queries) are unidimensional.
However, analysts need to issue multidimensional queries. For example, an
analyst may need to select not just the most profitable stores
or--separately--the most profitable products, but simultaneous sets of stores
and products fulfilling some profitability constraints. To fill this need, we
propose a new operator, the diamond dice. Because of the interaction between
dimensions, the computation of diamonds is challenging. We present the first
diamond-dicing experiments on large data sets. Experiments show that we can
compute diamond cubes over fact tables containing 100 million facts in less
than 35 minutes using a standard PC.
