Description

 

Recent efforts to support analytical tasks have pointed out the necessity to come up with flexible, powerful means for analyzing the issued queries and exploit them in decision-oriented processes (such as query recommendation or physical tuning). Issued queries should be decomposed, stored and manipulated in a dedicated subsystem.

 

For doing so, we first need to represent analytical queries in a rich format that we can exploit later. In this collaboration we propose to represent analytical sessions in terms of a multidimensional algebra. The next step will involve exploiting such constructs to recommend (in an OLAP fashion) new prospects of analysis to the user.

Related publications

2015
Pedro Furtado, Sergi Nadal, Verónika Peralta, Mahfoud Djedaini, Nicolas Labroche, Patrick Marcel: Materializing Baseline Views for Deviation Detection Exploratory OLAP. DaWaK 2015
Maximiliano Ariel López, Sergi Nadal, Mahfoud Djedaini, Patrick Marcel, Verónika Peralta, Pedro Furtado: An Approach for Alert Raising in Real-Time Data Warehouses. EDA 2015

2011
Oscar Romero, Patrick Marcel, Alberto Abelló, Verónika Peralta, Ladjel Bellatreche: Describing Analytical Sessions Using a Multidimensional Algebra. DaWaK 2011