Extending Visual OLAP for Handling Irregular Dimensional Hierarchies

Comprehensive data analysis has become indispensable in a variety of environments. Standard OLAP (On-Line Analytical Processing) systems, designed for satisfying the reporting needs of the business, tend to perform poorly or even fail when applied in non-business domains such as medicine, science, or government. The underlying multidimensional data model is restricted to aggregating only over summarizable data, i.e. where each dimensional hierarchy is a balanced tree. This limitation, obviously too rigid for a number of applications, has to be overcome in order to provide adequate OLAP support for novel domains. We present a framework for querying complex multidimensional data, with the major effort at the conceptual level as to transform irregular hierarchies to make them navigable in a uniform manner. We provide a classification of various behaviors in dimensional hierarchies, followed by our two-phase modeling method that proceeds by eliminating irregularities in the data with subse...

• Type: Conference
• Year: 2006
• Where: DAWAK
• Authors: Svetlana Mansmann, Marc H. Scholl
• Keywords: Complex Multidimensional Data, DAWAK 2006, Information Management, Multidimensional Data, Multidimensional Data Model