Hierarchy-based Update Propagation in Decision Support Systems

Autor: Haitang Feng, Nicolas Lumineau, Mohand-Said Hacid, Richard Domps
Přispěvatelé: Base de Données (BD), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2)
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Zdroj: Database Systems for Advanced Applications (DASFAA)
Database Systems for Advanced Applications (DASFAA), Apr 2012, Busan, South Korea. pp.261-271, ⟨10.1007/978-3-642-29035-0_20⟩
Database Systems for Advanced Applications ISBN: 9783642290343
DASFAA (2)
DOI: 10.1007/978-3-642-29035-0_20⟩
Popis: International audience; Sales forecasting systems are used by enterprise managers and executives to better understand the market trends and prepare appropriate business plans. These decision support systems usually use a data warehouse to store data and OLAP tools to visualize query results. A specific feature of sales forecasting systems regarding future predictions modification is backward propagation of updates, which is the computation of the impact of modifications on summaries over base data. In Data warehouses domain, some methods propagate updates in hierarchies when data sources are subject to modifications. However, very few works have been performed so far regarding update propagation from summaries to data sources. This paper proposes an algorithm named PAM algorithm, to efficiently propagate modifications on summaries. Experiments on an operational application (Anticipeo) have been performed to validate our algorithm.
Databáze: OpenAIRE