Process mining is a field that revolves around the use of data-driven techniques to analyze and improve business processes. It typically involves three main types of activities: process discovery, conformance checking, and process enhancement. Each of these activities focuses on different aspects of process analysis and improvement.

1. Process Discovery:
Process discovery is the initial step in process mining, where the goal is to construct a process model based on the data available from event logs. Event logs are records of the steps (events) executed in a business process, and they capture the sequence and timing of events as the process instances are executed. During process discovery, algorithms are used to derive a visual representation (a model) that describes how the process typically operates. This model might be a Petri net, a Business Process Model and Notation (BPMN) diagram, or another type of process diagram. The primary purpose is to understand the general flow of the process as it actually occurs.

2. Conformance Checking:
Once a process model has been discovered, conformance checking is used to compare the actual process execution (the event logs) with the process model. This step is vital for analyzing the deviations from the ideal or expected behavior. Conformance checking helps in identifying non-compliance, variations, and potential issues like bottlenecks, rework, or policy violations in the process. It provides insights into the quality and reliability of the process by highlighting inconsistencies and areas for improvement.

3. Process Enhancement:
Process enhancement, also referred to as process improvement or process optimization, is the phase in which insights derived from process discovery and conformance checking are used to improve the process. It goes beyond simply mapping and verifying the process to actively introduce changes that optimize performance. The enhancements could address a variety of objectives, such as increasing efficiency, reducing costs, improving customer satisfaction, or conforming to regulations. Process enhancement might involve changing the process structure, reassigning resources, automating certain tasks, or even re-engineering the entire process.

Process enhancement differs from process discovery and conformance checking in its focus on modification and improvement of the process. While discovery is about learning what the process looks like and conformance checks are about how well reality matches the model, enhancement is about acting upon those insights to create a better process.

In summary, process mining encompasses the entire lifecycle from discovering what the actual process looks like (process discovery), checking how well the actual execution adheres to the model or desired state (conformance checking), and then taking steps to improve the process based on the information gathered (process enhancement).