ABSTRACT
Multi-dimensional data analysis applications are largely used in computing technologies for the identiÀcation, discovery and analysis of business data. Enterprises generate massive amounts of data every day. This data comes from various aspects of their products, for instance, the sale statistics of a series of products in each store. The raw data is extracted, transformed, cleansed and then stored under multidimensional data models, such as the star-schema1. Users query this data to help make business decisions. The queries are usually complex and involve large-scale data access. Here are some features for multi-dimensional data analysis queries:
• queries access large datasets performing read-intensive operations; • queries are often quite complex and require different views of data; • query processing involves many aggregations; • updates can occur but infrequently, and can be planned by the administrator to execute at an expected time.
