Moroccan Data Lake Healthcare Analytics for Covid-19

Mohamed Cherradi, Anass El Haddadi, Hayat Routaib

2021

Abstract

The coronavirus pandemic has radically changed the way we live. It has had a major impact on all areas. Researchers around the world are redoubling their efforts to explore solutions to this pandemic. In this context, many researchers attest to the driving role of technologies in the management and resolution of this global health crisis. To allow specialists in the field to better understand the key factors that influence the rapid spread of this epidemic, the establishment of a data lake information system is a major challenge for analyzing heterogeneous data to make effective decisions. This study aims to take advantage of the power of this massive amount of heterogeneous data to construct a data lake system as one of the expected information systems for many organizations. To meet this need, this paper proposes a new approach for data lakes based on dynamic ontologies to manage different data types regardless of their format. In addition to this, we have designed a friendly interface for the digitalization of hospital operations and a dashboard for visualization of the statistics of the covid19.

Paper Citation

in Harvard Style

Cherradi M., El Haddadi A. and Routaib H. (2021). Moroccan Data Lake Healthcare Analytics for Covid-19. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 232-238. DOI: 10.5220/0010731700003101

in Bibtex Style

@conference{bml21,
author={Mohamed Cherradi and Anass El Haddadi and Hayat Routaib},
title={Moroccan Data Lake Healthcare Analytics for Covid-19},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={232-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010731700003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Moroccan Data Lake Healthcare Analytics for Covid-19
SN - 978-989-758-559-3
AU - Cherradi M.
AU - El Haddadi A.
AU - Routaib H.
PY - 2021
SP - 232
EP - 238
DO - 10.5220/0010731700003101