ABSTRACT
This paper focuses the attention on a real-life case study represented by the design, the development and the practice of OLAP tools over big COVID-19 data in Canada. The OLAP tools developed in this context are further enriched by machine learning procedures that magnify the mining effect. The contribution presented in this paper also embeds an implicit methodology for OLAP over big COVID-19 data. Experimental analysis on the target case study is also provided.
ABSTRACT
This paper focuses the attention on a real-life case study represented by the design, the development and the practice of OLAP tools over big COVID-19 data in Canada. The OLAP tools developed in this context are further enriched by machine learning procedures that magnify the mining effect. The contribution presented in this paper also embeds an implicit methodology for OLAP over big COVID-19 data. Experimental analysis on the target case study is also provided. © 2022 IEEE.