Massive advancements in healthcare technology have helped to generate a tons of data about the patient's health. Data with several dimensions are produced as a result of the patients' clinical trails. The foundation for big data analytics in the healthcare sector is knowledge creation from extremely large and diverse data sets, enabling the detection of disease risk factors like cardiovascular or respiratory disorders. Instead of doctors acting as the only key aspect in determining the risk factors and diagnose of the diseases, intelligent machines can be more successful. Cardiovascular disease is one of the main diseases which is a threat to most people. Hence, data analysis and prediction model on cardiovascular disease (CVD) have been built because of its prominence. In this study, the impact of diabetes on cardio vascular disorders is examined using a deep learning neural network model. The accuracy of the model and F1 score of the suggested methodology are clearly higher than those of the majority of the current methodologies used in the literature.