0000000000184099
AUTHOR
Sandro Bimonte
Enrichissement de schéma multidimensionnel en constellation grâce à la Classification Ascendante Hiérarchique
National audience; Les hiérarchies sont des structures cruciales dans un entrepôt de don-nées puisqu'elles permettent l'agrégation de mesures dans le but de proposer une vue analytique plus ou moins globale sur les données entreposées, selon le niveau hiérarchique auquel on se place. Cependant, peu de travaux s'intéressent à la construction de hiérarchies, via un algorithme de fouille de données, pre-nant en compte le contexte multidimensionnel de la dimension concernée. Dans cet article, nous proposons donc un algorithme, implémenté sur une architecture ROLAP, permettant d'enrichir une dimension avec des données factuelles.
Une nouvelle approche mixte d'enrichissement de dimensions dans un schéma multidimensionnel en constellation Application à la biodiversité des oiseaux
International audience; Les entrepôts de données (DW) et les systèmes OLAP sont des technologies d'analyse en ligne pour de grands volumes de données, basés sur les be-soins des utilisateurs. Leur succès dépend essentiellement de la phase de conception où les exigences fonctionnelles sont confrontées aux sources de données (méthodologie de conception mixte). Cependant, les méthodes de conception existantes semblent parfois inefficaces, lorsque les décideurs définissent des exi-gences fonctionnelles qui ne peuvent être déduites à partir des sources de don-nées (approche centrée sur les données), ou lorsque le décideur n'a pas intégré tous ces besoins durant la phase de conception (approche c…
Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering
20 pages; International audience; Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing with complex applications existing design methodologies seem inefficient since decision-makers define functional requirements that cannot be deduced from data sources (data driven approach) and/or they have not sufficient application domain knowledge (user driven approach) (Sautot et al., 2014b). Therefore, in this p…
Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology
[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE; International audience; Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping methodology, integrating two different DM algorithms, to define dimension hierarchies according to decision-maker knowledge; (ii) a complete UML Profile, to define a DW schema that integrates both the DM algorithms; (iii) a mapping process to transform multidimensional …
Dimension enrichment with factual data during the design of multidimensional models: application to bird biodiversity
20 pages; International audience; Data warehouses (DW) and OLAP systems are technologies allowing the on-line analysis of huge volume of data according to decision-makers’ needs. Designing DW involves taking into account functional requirements and data sources (mixed design methodology) [1]. But, for complex applications, existing automatic design methodologies seem inefficient. In some cases, decision-makers need querying, as a dimension, data which have been defined as facts by actual automatic mixed approachs. Therefore, in this paper, we offer a new mixed refinement methodology relevant to constellation multidimensional schema. The proposed methodolgy allows to decision-makers to enric…
A Methodology and Tool for Rapid Prototyping of Data Warehouses Using Data Mining: Application to Birds Biodiversity
Data Warehouses (DWs) are large repositories of data aimed at supporting the decision-making process by enabling flexible and interactive analyses via OLAP systems. Rapid prototyping of DWs is necessary when OLAP applications are complex. Some work about the integration of Data Mining and OLAP systems has been done to enhance OLAP operators with mined indicators, and/or to define the DW schema. However, to best of our knowledge, prototyping methods for DWs do not support this kind of integration. Then, in this paper we present a new prototyping methodology for DWs, extending [3], where DM methods are used to define the DW schema. We validate our approach on a real data set concerning bird b…