ASEAN Countries’ Life and Death Expectancy Visualization Dashboard

Abstract

Death is the complete cessation of life processes that every living thing experiences at some point. It is influenced by various factors, including biological, behavioral, and societal determinants. Big data and data visualization are essential tools for understanding complex datasets and making informed decisions. This study focuses on life and death expectancy in ASEAN countries, aiming to address increasing rates of heart diseases, cancer, accidents, and infectious diseases by developing an interactive dashboard using Power BI. Despite available data, there is a lack of user-friendly dashboards that inform the public about causes of death, contributing to a lack of awareness and preventive measures. The objective is to identify trends and patterns in life and death expectancy, design and develop a dashboard, and evaluate its usability. The research scope includes collecting data from official sources like the Department of Statistics Malaysia and Kaggle and classifying the causes of death into meaningful categories. The significance of this study lies in providing accessible information to the public, raising awareness about health issues, and aiding individuals and governments in making informed health decisions. By highlighting health disparities and informing public health policies, the dashboard aims to improve healthcare systems and overall quality of life in ASEAN countries. This research follows the Waterfall Model, including planning, design, development, implementation, and evaluation phases. The process involves extracting, loading, and transforming data through Apache Hive. Microsoft Power BI is used to visualize the data extracted from the warehouse. The dashboard was evaluated by 40 respondents to validate its functionality, usability, and overall performance. Positive feedback highlights its potential as a valuable tool for public health in ASEAN countries.