A Primer on Process Mining (eBook)

Preface to the Second Edition 6
Preface to the First Edition 7
Contents 9
1 Event Logs 11
1.1 Process Model vs. Process Instances 12
1.2 Task Allocation 13
1.3 Identifying the Process Instances 14
1.4 Recording Events in an Event Log 15
1.5 Event Logs in CSV Format 16
1.6 Reading an Event Log with Python 17
1.7 Sorting an Event Log with Python 19
1.8 Reading the Event Log as a Dictionary 21
1.9 Summary 22
2 Control-Flow Perspective 24
2.1 The Transition Matrix 24
2.2 The Control-Flow Algorithm 25
2.3 Implementation in Python 26
2.4 Introducing Graphviz 27
2.5 Using PyGraphviz 29
2.6 Edge Thickness 30
2.7 Activity Counts 33
2.8 Node Coloring 35
2.9 Summary 37
3 Organizational Perspective 39
3.1 Handover of Work 39
3.2 Implementing Handover of Work 40
3.3 Working Together 42
3.4 Implementing Working Together 43
3.5 Undirected Graphs 45
3.6 Edge Thickness 47
3.7 Users and Activities 48
3.8 Work Distribution 50
3.9 Summary 52
4 Performance Perspective 54
4.1 Dates and Times in Python 54
4.2 Parsing the Timestamps 56
4.3 Average Timestamp Difference 57
4.4 Drawing the Graph 59
4.5 Analyzing the Timeline of Events 61
4.6 Plotting the Dotted Chart 62
4.7 Using Relative Time 64
4.8 Activity Duration 67
4.9 Summary 70
5 Process Mining in Practice 72
5.1 The BPI Challenge 2012 72
5.2 Understanding the XES Format 75
5.3 Reading XES with Python 77
5.4 Analyzing the Control-Flow Perspective 79
5.5 Analyzing the Organizational Perspective 82
5.6 Analyzing the Performance Perspective 85
5.7 Process Mining with Disco 89
5.8 Process Mining with ProM 93
5.9 Conclusion 100
References 101