This project aims to model and develop a Data Lake (repository that contains structured, semi-structured and unstructured data) for data from patients in the healthcare system. This Data Lake contains both relational databases and unstructured data (result of image exams) and semi-structured data (XML files that are exported by equipment) that make up the patient's history. The planning is for this Data Lake to be accessed via mobile application and via the Web. The Data Lake will be powered by both doctors, laboratories, and the patient himself. Doctors will be able to access the patient's entire life in a clear, safe and fast way. Thus, if the patient changes doctors, all of their information remains available in an integrated manner. Doctors will be able to exchange vital patient information with each other via the system. An example would be a patient who finds out he has diabetes and needs his nutritionist to reevaluate his diet. Within minutes the patient would have access to a new diet sent by his nutritionist. In an emergency, the patient, even unconscious, could have his data released via the doctor's ID, taking responsibility for the access in an extraordinary way. If the patient so wished, he could obtain prognoses about probable diseases that he could develop based on analysis of the data of his health history through the application of Artificial Intelligence techniques. In addition to the clear advantages for the patient, the government would have a much more reliable and secure mass of data to carry out its analyzes for the public health policies adopted. In cases of emergencies such as pandemics, the government could quickly and safely know the groups of risks that would have to be insured and their current situation.