FDZ Data: This dataset stems from a public use file, published by the FDZ, see here or here for more details. It contains data from over 700 thousand patients and millions of diagnoses and prescriptions. Due to privacy issues, the original dataset has been decorrelated. However, we also used this complex real-world dataset to simulate certain dependencies into it. This semi-synthetic dataset can now be used to test the strengths of ObjectAnalytics and our Causal Discovery algorithms in a realistic scenario.
Click to launch the FDZ data model.
BPI Data: The data used in this example comes from the BPI Challenge 2019. This dataset represents a business process, specifically the sequence of events involved in processing a purchase order with multiple items & actions.
Click to launch the BPI ObjectAnalytics model.
NBA Data: This example uses data from the NBA, covering teams, players & matches from the 1946 to 2023 seasons. The raw data is sourced from the R package nbastatR.
Click to launch the NBA ObjectAnalytics model.