Towards data warehouse from open data: Case of COVID-19

Senda Bouaziz, Ahlem Nabli, F. Gargouri
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Abstract

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).
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从开放数据走向数据仓库:以COVID-19为例
自2019年12月以来,我们发现了一种名为COVID-19的新病毒的出现,并已在全球传播。今天的每个人都非常重视这种新病毒。尽管我们对这种疾病知之甚少,但医生和专家每天都在做出对公众健康有重大影响的决定。在这一背景下,开放数据数量众多,种类繁多,分散分布。为此,我们需要将数据仓库中的所有信息大写。为此,在本文中,我们提出了一种从开放数据特别是COVID-19数据中创建数据仓库的方法。我们首先从各种开放数据中识别相关来源。然后,我们收集相关数据。之后,我们确定了用于设计与COVID-19数据相关的数据仓库模式的多维概念。最后,我们将数据仓库转换为逻辑模型,并使用Talend Open Studio for Big data (TOS_BD)创建NoSQL数据仓库。
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