A Data Warehouse Schema for Monitoring Regional COVID-19 Case Registration

A Data Warehouse Schema for Monitoring Regional COVID-19 Case Registration

연구 분야: Databases

학회: 2022 International Conference on Information Management and Technology (ICIMTech)

From all websites in Indonesia, ‘variant’ is an important aspect that was excluded. Based on that limitation, we deliver an enhancement of a data warehouse design. The research methodology adopted Ralph Kimball's Four Step methodology in designing dimensional model of data warehouse that defined four core elements of data warehouse such as business process, granularity, dimensional table, and fact table. Several dimensional tables with different granularity are combined with a fact table and formed a snowflakes schema as the research outcome. The proposed design included ‘variant’ as a new dimension to complete date, patients, and health centers dimensions. The proposed design is expected to deliver regional COVID-19 case analysis that covered risk, vaccine, therapeutics, and diagnostic is expected to present when the snowflake schema is implemented. For further development, it is expected to test the acceptance of the proposed a data warehouse schema in operating regional COVID-19 case analysis.