The COVID-19 pandemic has been a global disaster with significant impacts. In response to it, an unprecedented amount of data was generated. This data has been utilized in various ways for research and policymaking. In this webinar, Professor Ko will examine the significance of data quality from the perspective of data analytics and explores how the use of different data and timing of analysis can sensitively alter outcomes in statistical analysis. He argues that the issue of data quality is relevant not only in developing countries but also in developed ones, asserting that it must be thoroughly considered before employing advanced analytical methodologies. By identifying the causes of data quality issues, he aims to provide insights on how data should be produced and shared in future pandemic situations. Additionally, he presents cases of collecting and sharing analysis results using Open APIs, and aims to suggest future directions for the development of public data analytics.