Abstract
Population information system provides an understanding of population dynamics through big data for. This study analyzes the demographic transition across ten ASEAN countries from 1980 to 2050 using cloud-based big data analytics. By leveraging Google Cloud Platform's SQL BigQuery, longitudinal datasets of Crude Birth Rate (CBR) and Crude Death Rate (CDR) were extracted from the U.S. Census Bureau international database. The data were then processed and visualized using Tableau Public to map the temporal and spatial shifts in demographic patterns. The results reveal diverse stages of demographic transition within the region, ranging from advanced aging societies like Singapore and Thailand to high-growth stages like the Philippines and Laos. This divergence highlights the varied socio-ecological challenges faced by different nations, such as labor shortages or environmental pressure. This paper demonstrates how population data analytics can provide actionable insights for policymakers to design tailored strategies for community resilience.