Fusion Cubes: Towards Self-Service Business Intelligence

Abello A., Darmont J., Etcheverry L., Golfarelli M., Mazon J.N., Naumann F., Bach Pedersen T., Rizzi S., Trujillo J., Vassiliadis P., Vossen G.


Zusammenfassung
Self-service business intelligence is about enabling non-expert users to make well-informeddecisions by enriching the decision process with situational data, i.e., data that have a narrowfocus on a specific business problem and, typically, a short lifespan for a small group of users.Often, these data are not owned and controlled by the decision maker; their search, extraction,integration, and storage for reuse or sharing should be accomplished by decision makers withoutany intervention by designers or programmers. The goal of this paper is to present the frameworkwe envision to support self-service business intelligence and the related research challenges; theunderlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can bedynamically extended both in their schema and their instances, and in which situational data andmetadata are associated with quality and provenance annotations.

Schlüsselwörter
Metadata discovery, metadata quality, schema discovery, data integration, data warehouses, data cube, data fusion, business intelligence, ETL, open data



Publikationstyp
Aufsatz (Zeitschrift)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2013

Fachzeitschrift
International Journal of Data Warehousing and Mining

Band
9

Ausgabe
2

Erste Seite
66

Letzte Seite
88

Sprache
Englisch