Process cubes are a key concept in multi-dimensional process mining, which is an extension of traditional process mining. Traditional process mining typically focuses on discovering and analyzing process models from event logs, providing insights into the control-flow perspective of processes.

Process cubes, on the other hand, offer a more comprehensive view by incorporating additional dimensions beyond control flow, such as time, resources, and data. A process cube is essentially a multi-dimensional data structure that aggregates event data across multiple dimensions. This allows for more in-depth analysis and enables the discovery of patterns and relationships that might not be evident in a traditional process mining approach.

For instance, by adding the time dimension, you can analyze how process performance changes over different periods. Adding the resource dimension can help identify which resources are more efficient or which tasks are often handled by certain resources. The data dimension can reveal how data attributes influence process outcomes.

In summary, while traditional process mining primarily focuses on the control-flow perspective, process cubes in multi-dimensional process mining provide a more holistic view, incorporating multiple dimensions for more detailed and nuanced process analysis.