Causality cannot be proven from observational data. However, with comprehensive data, you can get close to proof. The more comprehensive your data, the lower the risk of misinterpreting correlation as causation. Comprehensive data involves a multi-layered data model.

Our ObjectAnalytics Database is designed to store complex data, such as 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, uncovering potential cause-and-effect relationships.