ETL Model for Pandemic Data Processing


연구 분야: Databases



학회: 2025 IEEE 23rd World Symposium on Applied Machine Intelligence and Informatics (SAMI)


초록

This paper presents the development and implementation of an Extract-Transform-Load (ETL) model aimed at processing pandemic data. The model gathers data from various official sources, transforms it for easy analysis, and provides insights through graphical representations. Implemented using Python, the system automates data extraction and visualization, offering an accessible tool for understanding pandemic trends.


Author Profile
Lukáš Tomaščik

Department of Computers and Informatics Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia

Andorra
Author Profile
Norbert Ádám

Department of Computers and Informatics Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia

Andorra
Author Profile
Nikola Geciová

Department of Mathematics and Theoretical Informatics Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia

Andorra

📄 논문 정보

발행 연도 2025년
인용수 54
출판 국가 Andorra
사이트 IEEE
좋아요 수 0

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