Efficient Query Processing for Multidimensional Data Cubes

Rimi, Rejwana Tasnim; Hasan, K. M. Azharul

doi:10.1007/978-3-030-52856-0_51

Cited by 2 publications

(1 citation statement)

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“…The cube consists of dimensions that can be used to answer OLAP queries on the basis of the measurement (count). Multidimensional cube is selected due to its advantages, such as fast complex query response and excellent performance [52], [53].…”

Section: Etlmentioning

confidence: 99%

Implementing data-driven decision support system based on independent educational data mart

Hamoud

Hussein

Alhilfi

et al. 2021

IJECE

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<span>Decision makers in the educational field always seek new technologies and tools, which provide solid, fast answers that can support decision-making process. They need a platform that utilize the students’ academic data and turn them into knowledge to make the right strategic decisions. In this paper, a roadmap for implementing a data driven decision support system (DSS) is presented based on an educational data mart. The independent data mart is implemented on the students’ degrees in 8 subjects in a private school (Al-Iskandaria Primary School in Basrah province, Iraq). The DSS implementation roadmap is started from pre-processing paper-based data source and ended with providing three categories of online analytical processing (OLAP) queries (multidimensional OLAP, desktop OLAP and web OLAP). Key performance indicator (KPI) is implemented as an essential part of educational DSS to measure school performance. The static evaluation method shows that the proposed DSS follows the privacy, security and performance aspects with no errors after inspecting the DSS knowledge base. The evaluation shows that the data driven DSS based on independent data mart with KPI, OLAP is one of the best platforms to support short-to-long term academic decisions.</span>

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Section: Etlmentioning

confidence: 99%