Analyse multigraduelle OLAP

TL;DR

This paper introduces a new OLAP operator called 'BLEND' that enables multigradual analysis by transforming multidimensional structures during querying, allowing flexible analysis at various granularity levels with minimal additional cost.

Contribution

The paper presents the design and implementation of the 'BLEND' operator for OLAP systems, facilitating multigradual analysis within strict hierarchies.

Findings

BLEND enables flexible multigradual analysis.

Implementation shows minimal performance overhead.

Valid combinations are studied within hierarchical constraints.

Abstract

Decisional systems are based on multidimensional databases improving OLAP analyses. The paper describes a new OLAP operator named "BLEND" to perform multigradual analyses. The operation transforms multidimensional structures during querying in order to analyse measures according to various granularity levels, which are reorganised into a single parameter. We study valid combinations of the operation in the context of strict hierarchies. First experimentations implement the operation in an R-OLAP framework showing the slight cost of this operation.