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Prioritized dynamic cube selection in data warehouse

  • 1199: Computational Intelligence Revolution in Multimedia Data Analytics and Business Management
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Abstract

The main contribution of this paper is to materialize right cubes according to the users’ priority at the right time which can significantly reduce delays in information retrieval and achieve faster decision making. Therefore, we propose a PrioDyna algorithm that maintains the two-level cache space to handle the High priority and the long-term user requests dynamically. The first level cache focuses on the short-lived data cubes considering the cube priority as a selection parameter. In contrast, the second level cache targets the long-term trends by capturing frequently used data cubes requested for the longer run. Different experimental results show that our approach significantly outperforms the state-of-the-art methods in terms of overall cost savings by 2-6% in addition to 15-45% fewer cube evictions and better selection of High priority data cubes by 3-8%.

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  1. Guru Gobind Singh Indraprastha University, Delhi, 110078, India

    Heena Madaan & Anjana Gosain

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  1. Heena Madaan
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  2. Anjana Gosain
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Correspondence to Heena Madaan.

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Madaan, H., Gosain, A. Prioritized dynamic cube selection in data warehouse. Multimed Tools Appl 82, 8113–8135 (2023). https://doi.org/10.1007/s11042-022-13460-4

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