Causality cannot be proven from observation data. However: with comprehensive data you can get close to proof! The more comprehensive your data, the less likely you are to misinterpret correlation as causation. Comprehensive data means a multi-layered data model.

Our Object Analytics Database is designed to store such complex data – like millions of patients with billions of events (diagnoses, prescriptions, genomic data, etc.). Our Causal Discovery algorithms utilize this object-oriented data storage to efficiently search for direct and indirect explanations for a target event, thereby uncovering potential cause and effect relationships.