Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/23304
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dc.contributor.authorVelinov, Goranen_US
dc.contributor.authorKon-Popovska, Margitaen_US
dc.date.accessioned2022-10-03T12:52:41Z-
dc.date.available2022-10-03T12:52:41Z-
dc.date.issued2002-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/23304-
dc.description.abstractData Warehouses (DW) and Online Analytical Processing (OLAP) are essential elements of Decision Support Systems (DSS), they enable business decision makers to creatively approach, analyze and understand business problems. OLAP data is frequently organized in the form of multidimensional data cubes each of which is used to examine a set of data values, called facts. Each fact is combination of multiple dimensions with multiple levels per dimension. The goal of this paper is the introduction of a multidimensional data model. The model is able to represent and capture natural hierarchical relationships among members (attributes) within a dimension. Moreover the data model is able to represent the relationships between dimension members and facts by mean of cube cells.en_US
dc.publisherInstitute of Informatics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University in Skopje, Macedoniaen_US
dc.subjectdata warehouses, OLAP, multidimensional data model, data cubeen_US
dc.titleMultidimensional Data Model for Data Warehousesen_US
dc.typeProceedingsen_US
dc.relation.conferenceThird International Conference on Informatics and Information Technologyen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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