Medical Care Evolution was an ITEA project aiming to build a system of systems to collect, align and analyse heterogeneous health data so that medical professionals can make more informed decisions. The objective was to provide relevant information to support patients and healthcare professionals in their decision making on diagnosis, treatment and further monitoring; from reactive to preventive actions

I worked on the design and development of an Health Data Ingestion Stack respecting to the principles of Big Data Lambda architecture so that it can be highly scalable, as shown in the figure below. The design utilized several existing technologies to read data from various sources, process through batch or streaming layers, and apply data processing and transformation methods to produce prepared data for machine learning, or in a more general sense analytical solutions.