Multidimensional Business Benchmarking Analysis on Data Warehouses

Akiko Campbell, Xiangbo Mao, Jian Pei and Abdullah Al-Barakati
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Akiko Campbell: LiveLabs Medical Laboratories, Burnaby, Canada
Xiangbo Mao: Simon Fraser University, Burnaby, Canada
Jian Pei: Simon Fraser University, Burnaby, Canada
Abdullah Al-Barakati: King Abdulaziz University, Jeddah, Saudi Arabia

International Journal of Data Warehousing and Mining (IJDWM), 2017, vol. 13, issue 1, 51-75

Abstract: Benchmarking analysis has been used extensively in industry for business analytics. Surprisingly, how to conduct benchmarking analysis efficiently over large data sets remains a technical problem untouched. In this paper, the authors formulate benchmark queries in the context of data warehousing and business intelligence, and develop a series of algorithms to answer benchmark queries efficiently. Their methods employ several interesting ideas and the state-of-the-art data cube computation techniques to reduce the number of aggregate cells that need to be computed and indexed. An empirical study using the TPC-H data sets and the Weather data set demonstrates the efficiency and scalability of their methods.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdwm00:v:13:y:2017:i:1:p:51-75

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