Author Description

Online Analytical Processing (OLAP) is a database paradigm that supports the rich analysis of multi-dimensional data. OLAP is often supported by a logical structure known as the Cube, a data model that provides an intuitive array-based perspective of the underlying data. However, supporting efficient OLAP query resolution in enterprise scale environments is an issue of considerable complexity. In practice, the difficulty of the problem is exacerbated by the existence of dimension hierarchies that sub-divide core dimensions into aggregation layers of varying granularity. Common hierarchy-sensitive query operations such as Rollup and Drilldown can be very costly. Moreover, facilities for the representation of more complex hierarchical relationships are not well supported by conventional techniques.