15.10.2023: Dr. Michael Haft performs @ML Week, Berlin
Mark your calendar: Xplain Data CEO takes stages at Machine Learning Week 2023 ML Week 2023 Talk: From Correlation to…
Mark your calendar: Xplain Data CEO takes stages at Machine Learning Week 2023 ML Week 2023 Talk: From Correlation to…
Causal DiscoveryBot: AI Innovation at SPS 2023 Xplain Data introduces its autonomous Causal DiscoveryBot at SPS – smart production solutions…
Get ready for the industry event of the year when Nuremberg hosts the SPS – Smart Production Solutions! ‘Bringing Automation…
Xplain Data´s ObjectAnalytics Database demonstrates scalability from the smallest computers to servers with 256 cores and TB of RAM Xplain…
Xplain Data announces its inclusion in the prestigious AI Startup Landscape 2023, a comprehensive analysis of Germany’s thriving AI startup…
July 2023: Release of highly anticipated Gartner AI Hype Cycle and report Xplain Data is proud to announce its prestigious…
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 ObjectAnalytics 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.
Why not develop next generation intelligent algorithms by operating on entire objects instead of tables, rows, and columns?
Unleash your creativity to build analytical applications with whole objects at your fingertips!
Easily understand causation beyond correlation, based on a holistic view of your business objects.