Excess sugar levels in the bloodstream cause the problem of diabetes. When the amount of insulin produced by the body is reduced, it results in a long-term chronic disease characterized by high glucose levels. Diabetes is one of the fastest-growing chronic diseases in the world. This area must always be prioritized to follow the progress in the field of diabetes prediction. There is a need to figure out the behavior of parameters affecting diabetic people’s health and aim for prevention by synergizing visualization techniques and advanced machine learning methodologies. This work contributes to better comprehension and management of diabetes for the enhancement of overall public health. Visualization of the corresponding disease from a statistical point of view is a mark for the future healthcare system. In this work, age-wise analysis of diabetes is demonstrated along with other health parameters for visualization using Tableau. A dashboard is constructed using Tableau, consisting of graphs and trend lines for various health parameters related to diabetes, through which the disease can be explored from various angles. Along with the Tableau dashboard, various well-recognized machine learning classification models are utilized to train and classify diabetes, among which the Support Vector Machine demonstrated the best results. Our proposal involves utilizing Tableau for in-depth analysis and comprehensive evaluation to demonstrate superior performance in understanding health indicators influencing diabetes. The rationale behind incorporating Tableau into our study lies in the observed absence of prior research that focuses on visualization and thorough analysis of health parameters.