The data generated in the field of medicine are voluminous and complex. In addition, there is diversity in the types of data being generated and high speed management is required for them. Traditional data processing applications are unable to work with these data as a whole. Also, traditional database management systems pose difficulties in managing them. Big Data Systems allow the discovering of knowledge and reveal useful information from complex, heterogeneous and voluminous data. The implementation of the Big Data systems in the field of medicine offers the possibility of having all the data when making decisions. In medicine, these systems can help predict epidemics, cure diseases, improve patient quality of life, avoid preventable deaths, and cut costs. However, building these systems presents quite a number of issues to be addressed and challenges to be managed. The drive now is to understand as much about a patient as possible, as early in their life as possible , hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later. The main purpose of the article is to study the construction of a Big Data System for better health care. This study will help provide an appropriate solution that addresses the issues and manages the challenges posed by the implementation of a Big Data system in the medical field.