Process Cubes play an essential role in multi-dimensional process mining and are an advanced form of process mining, a technique used to analyze business processes based on the trace logs of the system-to-system interactions and user-to-user interactions. 

Traditional process mining techniques majorly focus on a single perspective of the business process and provide a static and monolithic view of the process. They consider event logs and map out the start-to-end process flow based on the recorded trace logs.

Process Cubes, on the other hand, offer a multi-dimensional view of the business process. They provide the ability to slice, dice, and drill-down the processes based on several dimensions like time, geographical location, organizational units, etc. Each cell in the process cube contains a set of events or an entire process model, allowing for various kinds of operations like roll-up, drill-down, slice, dice, and pivot. 

Process Cubes enable a more detailed and context-aware process analysis. For example, they can help identify how processes differ between different regions or departments, discover seasonal trends, or evaluate and compare the performance. Also, they allow for the exploration of various versions of the process model simultaneously, and the aggregate operations can generate abstracted views of the process.

In summary, the main difference between traditional process mining approaches and process cubes is the perspective of analysis. While the former primarily focuses on providing a single, monolithic view, the latter considers multiple dimensions simultaneously, allowing for a more comprehensive and in-depth process analysis.