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.

White paper: Von Korrelation über Kausalität zu künstlicher Intelligenz

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White Paper: “From
Correlation to
Causation to AI”

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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?

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Are you an Application Developer and feel hampered by clumsy backends?

Unleash your creativity to build analytical applications with whole objects at your fingertips!

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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.

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