Maintaining data cubes under dimension updates

OLAP systems support data analysis through a multidimensional data model, according to which data facts are viewed as points in a space of application-related "dimensions", organized into levels which conform to a hierarchy. The usual assumption is that the data points reflect the dynamic aspect of the data warehouse, while dimensions are relatively static. However, in practice, dimension updates are often necessary to adapt the multidimensional database to changing requirements. Structural updates can also take place, like addition of categories or modification of the hierarchical structure. When these updates are performed, the materialized aggregate views that are typically stored in OLAP systems must be efficiently maintained. These updates are poorly supported (or not supported at all) in current commercial systems, and have received little attention in the research literature. We present a formal model of dimension updates in a multidimensional model, a collection of primitive operators to perform them, and a study of the effect of these updates on a class of materialized views, giving an algorithm to efficiently maintain them.