Exploring Strategic Indexes by Semantic OLAP Operators
Claudia Diamantini, Domenico Potena · 2010
At strategic and decision levels of information systems, information models are defined by a set of high-level measurable performance indexes, calculated by composition of more basic pieces of information, and aggregated along a number of different dimensions. Although the multidimensional model is able to effectively capture the aggregative characteristics of strategic information, it fails to represent its compound nature. Hence, index semantics is not completely specified and OLAP operators allow only to analyze indexes through the different aggregation dimensions. In this paper we discuss a novel set of OLAP operators resulting from a previously defined model for the semantic annotation of a Data Warehouse (DW) schema. These operators perform the analogous of drill down operators on index components instead of dimensions, both at intensional and extensional level. This means that both the definition of an index in terms of components and compositions operators and the actual values of the components can be hierarchically explored on-line, giving final users better ways to understand the meaning of the complex information encoded in a DW, its correctness, and more powerful tools to analyze it. A prototype implementing the proposal is presented. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.