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Using the entity-attribute-value model for olap cube construction

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publicationPerspectives in Business Informatics Research - 10th International Conference, BIR 2011, Proceedings
PublisherSpringer Verlag
Number of pages14
Volume90 LNBIP
ISBN (Print)9783642245107
Publication statusPublished - 2011
Publication typeA4 Article in a conference publication
Event10th International Conference on Perspectives in Business Informatics Research, BIR 2011 - Riga, Latvia
Duration: 6 Oct 20118 Oct 2011

Publication series

NameLecture Notes in Business Information Processing
Volume90 LNBIP
ISSN (Print)18651348


Conference10th International Conference on Perspectives in Business Informatics Research, BIR 2011


When utilising multidimensional OLAP (On-Line Analytic Processing) analysis models in Business Intelligence analysis, it is common that the users need to add new, unanticipated dimensions to the OLAP cube. In a conventional implementation, this would imply frequent re-designs of the cube's dimensions. We present an alternative method for the addition of new dimensions. Interestingly, the same design method can also be used to import EAV (Entity-Attribute-Value) tables into a cube. EAV tables have earlier been used to represent extremely sparse data in applications such as biomedical databases. Though space-efficient, EAV-representation can be awkward to query. Our EAV-to-OLAP cube methodology has an advantage of managing many-to-many relationships in a natural manner. Simple theoretical analysis shows that the methodology is efficient in space consumption. We demonstrate the efficiency of our approach in terms of the speed of OLAP cube re-processing when importing EAV-style data, comparing the performance of our cube design method with the performance of the conventional cube design.