An Ontology-Based Autonomic System for Improving Data Warehouses by Cache Allocation Management

Vlad Nicolicin-Georgescu (1) , Vincent Benatier (2) , Rémi Lehn (1) , Henri Briand (1)

1 LINA - Laboratoire d'Informatique de Nantes Atlantique
2 SP2 Solutions

With the increase in the amount and complexity of information, data warehouse performance has become a constant issue, especially for decision support systems. As a consequence, decision experts are faced with the management of all this information, and thus realize that special techniques are required to keep good performances. This paper proposes an approach to data warehouse systems improvement based on Autonomic Computing. The idea is that by rendering certain tasks autonomic, such as the configuration of cache memory allocations between groups of data warehouses, we ensure a better data warehouse management at a lower cost and save substantial decision experts' time that can be used on higher level decision tasks.

Mots clés: decision support system; data warehouse; ontology; autonomic computing

Domaines: Autre [cs.OH]

Vlad Nicolicin-Georgescu, Vincent Benatier, Rémi Lehn, Henri Briand. An Ontology-Based Autonomic System for Improving Data Warehouses by Cache Allocation Management. Workshop “Knowledge and Experience Management” (FGWM) 09, Sep 2009, Darmstadt, Germany. pp.31-37. ⟨hal-00422475⟩