Data analysts need to understand the quality of data in the warehouse. This is often done by issuing many Group By queries on the sets of columns of interest. Since the volume of data in these warehouses can be large, and tables in a data warehouse often contain many columns, this analysis typically requires executing a large number of Group By queries, which can be expensive. We show that the performance of today's database systems for such data analysis is inadequate. We also show that the problem is computationally hard, and develop efficient techniques for solving it. We demonstrate significant speedup over existing approaches on today's commercial database systems.
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