Even though the world is spherical, data analytics today relies on flat tables, oversimplifying real-world complexity. It’s time to change this. ObjectAnalytics allows for analyzing complete objects as they exist in real environments. In this video, Paula and Robo explain the concept of ObjectAnalytics in an intuitive way:
Causal Discovery Intro : From Correlation to Causation to Artificial Intelligence
Why is ObjectAnalytics crucial for understanding cause-and-effect relationships? Causes can only be identified if they are present in the data, making extensive information about the analyzed object essential for Causal Discovery. This comprehensive information leads to complex data, highlighting the importance of ObjectAnalytics. In the second video, Paula and Robo discuss the challenges of Causal Discovery and explain why ObjectAnalytics provides an ideal foundation for it.
ObjectAnalytics Intro : A paradigm shift - Why we should use whole objects instead of flat tables