Process cubes are a concept introduced in multi-dimensional process mining to handle and analyze processes with multiple perspectives or dimensions. They are inspired by OLAP (Online Analytical Processing) cubes used in data warehousing and business intelligence.

In traditional process mining, event logs are analyzed to extract process models, identify bottlenecks, and discover deviations. However, these approaches typically focus on a single perspective, such as control-flow or time, which might not be sufficient to understand complex processes fully.

Process cubes extend traditional process mining by introducing multiple dimensions, such as time, resources, costs, locations, or organizational structures, to analyze processes more comprehensively. Each dimension can be considered a different perspective from which processes can be viewed and analyzed. For example, the time dimension can help identify trends and patterns over time, while the resource dimension can provide insights into resource usage and performance.

Process cubes are created by aggregating event logs based on these dimensions to form multi-dimensional event data. This data is then used to generate multi-dimensional process models, which can be explored and analyzed using various techniques, such as slicing, dicing, roll-up, or drill-down.

The main differences between process cubes and traditional process mining approaches are:

1. Multi-dimensionality: Process cubes consider multiple perspectives or dimensions to analyze processes, while traditional process mining focuses on a single perspective.

2. Aggregation: Process cubes aggregate event logs based on different dimensions, while traditional process mining typically uses the entire event log for analysis.

3. Exploration: Process cubes provide more flexible exploration and analysis capabilities, such as slicing, dicing, roll-up, or drill-down, which are not available in traditional process mining.

4. Complexity: Process cubes can handle more complex processes with multiple dimensions, while traditional process mining might struggle with such complexity.

5. Visualization: Process cubes offer multi-dimensional visualizations, such as heatmaps or parallel coordinate plots, which are not available in traditional process mining.

In summary, process cubes in multi-dimensional process mining provide a more comprehensive and flexible approach to process analysis by considering multiple dimensions. This helps to gain deeper insights into complex processes, which might not be possible with traditional process mining approaches.