Implementation

GCAM is building a platform with which medical insights can be gained. In addition to conventional methods of analysis, it also applies modelling methods and machine learning algorithms.

The logical, structured data model is created using tools which do not themselves hold data but simply map the structure of the underlying systems (virtual data warehouse). This ensures that no personal data is stored outside the various medical institutes. The identified systems are exclusively connected to a virtual (semantic) layer and interrelated with one another. Starting from this semantic layer, the data acquired gets validated to check for consistency. After this, the data is anonymized and transferred to a server cluster for the actual analysis, using big data algorithms.

After transferring the anonymized data to GCAM, different analysis algorithms are applied to the acquired dataset and are compared against each other. The insights gained here is qualitatively assessed and evaluated in cooperation with medical professionals. 

GCAM has committed itself to modern technology. Only software components from the Hadoop open source environment are used for the data management and analytics. GCAM establishes the basis for undertaking the data management on-site itself, i.e. the entire hardware will be located directly at GCAM.