Usage of OLAP Cubes as a Data Model for DSS

Nikolai Scerbakov; Alexander Schukin; Eugenia Rezedinova

doi:10.3390/engproc2025104004

Usage of OLAP Cubes as a Data Model for DSS

Nikolai Scerbakov
, Alexander Schukin
, Eugenia Rezedinova^*

^*Korrespondierende/r Autor/-in für diese Arbeit

Institute of Human-Centred Computing (7060)

Publikation: Beitrag in einer Fachzeitschrift › Konferenzartikel › Begutachtung

Abstract

A decision support system (DSS) is a software application designed to determine suitable actions for specific organizational situations. Its main component is a data repository analyzed to produce decisions. This paper describes the data organization (Data Model) as a multi-dimensional OLAP cube with amendments for decision-making support. We present DSS functionality as building (slicing) hyper-cubes into decision sub-cubes. The system’s adjustment and evolution involve changing the granularity of these sub-cubes. We discuss the merging and splitting of hyper-cubes, arguing that this functionality is adequate for creating complex, real-time DSSs for various incidents, such as cybersecurity incidents.

Originalsprache	englisch
Aufsatznummer	4
Fachzeitschrift	Engineering Proceedings
Jahrgang	104
Ausgabenummer	1
DOIs	https://doi.org/10.3390/engproc2025104004
Publikationsstatus	Veröffentlicht - 22 Aug. 2025
Veranstaltung	International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025) - Alexandroupolis, Griechenland Dauer: 18 Juni 2025 → 20 Juni 2025 http://www.eepes.eu

ASJC Scopus subject areas

Biomedizintechnik
Maschinenbau
Wirtschaftsingenieurwesen und Fertigungstechnik
Elektrotechnik und Elektronik

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10.3390/engproc2025104004Lizenz: CC BY 4.0

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N2 - A decision support system (DSS) is a software application designed to determine suitable actions for specific organizational situations. Its main component is a data repository analyzed to produce decisions. This paper describes the data organization (Data Model) as a multi-dimensional OLAP cube with amendments for decision-making support. We present DSS functionality as building (slicing) hyper-cubes into decision sub-cubes. The system’s adjustment and evolution involve changing the granularity of these sub-cubes. We discuss the merging and splitting of hyper-cubes, arguing that this functionality is adequate for creating complex, real-time DSSs for various incidents, such as cybersecurity incidents.

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Usage of OLAP Cubes as a Data Model for DSS

Abstract

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