A Primer on Process Mining

Practical Skills with Python and Graphviz

verfasst von: Diogo R. Ferreira

Verlag: Springer International Publishing

Buchreihe : SpringerBriefs in Information Systems

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.
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.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Event Logs

Abstract

This chapter explains how event logs are generated by the execution of multiple instances of a business process. The kind of event logs that are used for process mining have a particular structure and can be stored in a text file. The chapter explains how to parse those files and read the event log using the Python programming language. The sorting of events in an event log is also discussed.

Diogo. R. Ferreira

Chapter 2. Control-Flow Perspective

Abstract

This chapter explains how to derive a control-flow model for a business process, based on counting transitions between events. A simple control-flow algorithm is described together with its implementation in Python. The chapter also introduces Graphviz as a means to display the resulting model. Several improvements are described for better visualization of the resulting model.

Diogo. R. Ferreira

Chapter 3. Organizational Perspective

Abstract

This chapter describes the main techniques to analyze the interactions and collaborations between participants in a business process. These techniques consist in simple algorithms that are straightforward to implement in Python. The chapter also provides an introduction to the use of process mining techniques to discover organizational structure and to analyze the distribution of work between participants.

Diogo. R. Ferreira

Chapter 4. Performance Perspective

Abstract

The performance perspective is concerned mainly with time. Examples of interesting time measurements are the average time it takes to perform an activity, the maximum time it takes for the process to reach a certain point, or the average end-to-end duration of each process instance.

Diogo. R. Ferreira

Chapter 5. Process Mining in Practice

Abstract

Over the years, the process mining community has placed several real-world event logs in the public domain. Most of these event logs have been released in the scope of process mining competitions, where contestants could use any of the available techniques, or even develop new techniques, to discover the business process.

Diogo. R. Ferreira

Backmatter

Titel: A Primer on Process Mining
verfasst von: Diogo R. Ferreira
Verlag: Springer International Publishing
Electronic ISBN: 978-3-319-56427-2
Print ISBN: 978-3-319-56426-5
DOI: https://doi.org/10.1007/978-3-319-56427-2