Open AccessTowards data warehouse from open data: Case of COVID-19
Author(s) -
Senda Bouaziz,
Ahlem Nabli,
Faı̈ez Gargouri
Publication year - 2022
Publication title -
international journal of hybrid intelligent systems
Language(s) - English
Resource type - Journals
eISSN - 1875-8819
pISSN - 1448-5869
DOI - 10.3233/his-210010
Subject(s) - data warehouse , nosql , computer science , context (archaeology) , big data , data science , schema (genetic algorithms) , open data , covid-19 , world wide web , database , data mining , information retrieval , infectious disease (medical specialty) , medicine , paleontology , disease , pathology , biology
Since December 2019, we have detected the appearance of a new virus called COVID-19, which has spread, throughout the world. Everyone today, has given major importance to this new virus. Although we have little knowledge of the disease, doctors and specialists make decisions every day that have a significant impact on public health. There are many and various open data in this context, which are scattered and distributed. For this, we need to capitalize all the information in a data warehouse. For that, in this paper, we propose an approach to create a data warehouse from open data specifically from COVID-19 data. We start with the identification of the relevant sources from the various open data. Then, we collect the pertinent data. After that, we identify the multidimensional concepts used to design the data warehouse schema related to COVID-19 data. Finally, we transform our data warehouse to logical model and create our NoSQL data warehouse with Talend Open Studio for Big Data (TOS_BD).