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.
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?
Are you 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, do you have endless data but feel lost in myriads of correlations? Easily understand causation beyond correlation, based on a holistic view of your business objects.