This article employs Exploratory Data Analysis (EDA) using Power BI to investigate the relationship between sleep and heart health. A 3-step methodology was adopted including data processing, visualizations, and inferences. It explores factors affecting sleep patterns, such as daily routines and environmental influences, using dynamic visualizations to uncover detailed insights often missed in traditional analyses. By transforming raw data into interactive visuals, the study offers actionable insights for personalized sleep strategies and preventive measures. This holistic approach aims to bridge gaps in understanding, empowering individuals, healthcare professionals, and policymakers. Through proactive interventions informed by these findings, the study seeks to catalyze improvements in cardiovascular well-being, aiming for a healthier future.