Data Analysis of Coronavirus CoVID-19: Study of Spread and Vaccination in European Countries

• Published in: International journal of advanced computer science & applications Vol. 13; no. 1
• Main Authors: Turki, Hela, Khrouf, Kais
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2022
• Subjects: Coronaviruses; COVID-19 vaccines; Data analysis; Decision analysis; Decision making; Immunization; Pandemics
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2022.0130185

Humanity has gone since a long time through several pandemics, such as: H1N1 in 2009 and also Spanish flu in 1917. In December 2019, the health authorities of China detected unexplained cases of pneumonia. The WHO World Health Organization has declared the apparition of CoVID-19 (novel Coronavirus) that caused a global pandemic in 2020. In data analysis, multiple approaches and diverse techniques were used to extract useful information from multiple heterogeneous sources and to discover knowledge and new information for decision-making; it is used in different business and science domains. In this context, we propose to use the multidimensional analysis techniques based on two concepts: fact (subject of analysis) and dimensions (axes of analyses). This technique allows decision makers to observe data from various heterogeneous sources and analyze them according several viewpoints or perspectives. More precisely, we propose a multidimensional model for analyzing the Coronavirus CoVID-19 data (spread and vaccination in European countries). This model is based on constellation schema that contains several facts surrounded by common dimensions.