The bitmap index technology is efficient for query processing in data warehousing applications. This paper focuses on efficient bitmap compression algorithm and examines the space and time complexity of the compressed bitmap index on large data sets from real applications. According to the conventional wisdom, bitmap indices are only efficient for low-cardinality attributes. However, the results show that the compressed bitmap indices are also efficient for high-cardinality attributes. Timing results demonstrate that the bitmap indices significantly outperform the projection index, which is often considered to be the most efficient access method for multidimensional queries.