A first framework for Top-K cubes queries

Abstract

Data Warehouse (DW) and OLAP systems are effective solutions for the online analysis of large volumes of data structured as cubes. Usually organizations and enterprises require several cubes for their activities. In this context, we define a new kind of queries: “Top-k Cubes queries”. Top-K cubes queries allow searching the most relevant k-cubes among a collection of cubes. Then, in this paper we propose a first framework for Top-K cubes queries where queries are expressed in natural language to meet the easiness need of unskilled IT decision-makers. An implementation in a ROLAP architecture is also provided.