Ferreira A Primer on Process Mining

Practical Skills with Python and Graphviz
2. Auflage 2020
ISBN: 978-3-030-41819-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 96 Seiten

Reihe: Business and Management

The main goal of this book is to explain the core ideas of process mining, and to demonstrate how they can be implemented using just some basic tools that are available to any computer scientist or data scientist. It describes how to analyze event logs in order to discover the behavior of real-world business processes. The end result can often be visualized as a graph, and the book explains how to use Python and Graphviz to render these graphs intuitively. Overall, it enables the reader to implement process mining techniques on his or her own, independently of any specific process mining tool. An introduction to two popular process mining tools, namely Disco and ProM, is also provided. In this second edition the code snippets have been updated to Python 3, and some smaller errors have been corrected.

The book will be especially valuable for self-study or as a precursor to a more advanced text. Practitioners and students will be able to follow along on their own, even if they have no prior knowledge of the topic. After reading this book, they will be able to more confidently proceed to the research literature if needed.

Autoren/Hrsg.

Ferreira, Diogo R.

Inhaltsverzeichnis

1;Preface to the Second Edition;6
2;Preface to the First Edition;7
3;Contents;9
4;1 Event Logs;11
4.1;1.1 Process Model vs. Process Instances;12
4.2;1.2 Task Allocation;13
4.3;1.3 Identifying the Process Instances;14
4.4;1.4 Recording Events in an Event Log;15
4.5;1.5 Event Logs in CSV Format;16
4.6;1.6 Reading an Event Log with Python;17
4.7;1.7 Sorting an Event Log with Python;19
4.8;1.8 Reading the Event Log as a Dictionary;21
4.9;1.9 Summary;22
5;2 Control-Flow Perspective;24
5.1;2.1 The Transition Matrix;24
5.2;2.2 The Control-Flow Algorithm;25
5.3;2.3 Implementation in Python;26
5.4;2.4 Introducing Graphviz;27
5.5;2.5 Using PyGraphviz;29
5.6;2.6 Edge Thickness;30
5.7;2.7 Activity Counts;33
5.8;2.8 Node Coloring;35
5.9;2.9 Summary;37
6;3 Organizational Perspective;39
6.1;3.1 Handover of Work;39
6.2;3.2 Implementing Handover of Work;40
6.3;3.3 Working Together;42
6.4;3.4 Implementing Working Together;43
6.5;3.5 Undirected Graphs;45
6.6;3.6 Edge Thickness;47
6.7;3.7 Users and Activities;48
6.8;3.8 Work Distribution;50
6.9;3.9 Summary;52
7;4 Performance Perspective;54
7.1;4.1 Dates and Times in Python;54
7.2;4.2 Parsing the Timestamps;56
7.3;4.3 Average Timestamp Difference;57
7.4;4.4 Drawing the Graph;59
7.5;4.5 Analyzing the Timeline of Events;61
7.6;4.6 Plotting the Dotted Chart;62
7.7;4.7 Using Relative Time;64
7.8;4.8 Activity Duration;67
7.9;4.9 Summary;70
8;5 Process Mining in Practice;72
8.1;5.1 The BPI Challenge 2012;72
8.2;5.2 Understanding the XES Format;75
8.3;5.3 Reading XES with Python;77
8.4;5.4 Analyzing the Control-Flow Perspective;79
8.5;5.5 Analyzing the Organizational Perspective;82
8.6;5.6 Analyzing the Performance Perspective;85
8.7;5.7 Process Mining with Disco;89
8.8;5.8 Process Mining with ProM;93
8.9;5.9 Conclusion;100
9;References;101