Neo4j AuraDB Free has been used in several HR applications and use-cases. The author of this post, who is the Head of Product Innovation & Developer Strategy at Neo4j, decided to explore an IBM Attrition Dataset on Kaggle as a way to experiment with AuraDB free. The dataset contains 32 columns of employee data, including attributes like job satisfaction, salary, and education level. The author imported the data into AuraDB free and created nodes for each employee, using the MERGE function to create new nodes if they didn't exist. They then extracted department and role information from the data, creating separate nodes for these concepts and connecting them to the employees. The author also explored temporal data in the dataset, converting date strings to zoned temporals and computing dates until which employees were employed. Finally, they discussed the potential for using graph data science libraries like GraphDB or NetworkX to compute similarity networks or node classification based on attributes, with the goal of identifying employees similar to leavers who have not yet left.