Causality cannot be proven from observation data. But: We can get close to a proof – if there is comprehensive data! The more comprehensive data you have, the less you will be prone to misinterpret correlation as causation. Comprehensive data means a multi-layered data model. Our Object Analytics Database is designed to store such complex data, e.g., millions of patients with billions of events (diagnoses, prescriptions, genomic data … ). 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.
Are you a Data Scientist and tired of SQL for analytics? Why not develop next generation intelligent algorithms by operating on entire objects instead of tables, rows and columns?
You are an Application Developer and feel hampered by clumsy backends? Unleash your creativity to build analytical applications with whole objects at your fingertips!
As a Business Analyst you have endless data but feel lost in myriads of correlations? Easily understand causation beyond correlation based on a holistic view to your business objects.