A unifying foundation to design and implement process-aware information systems This publication takes on the formidable task of establishing a unifying foundation and set of common underlying principles to effectively model, design, and implement process-aware information systems. Authored by leading authorities and pioneers in the field, Process-Aware Information Systems helps readers gain a thorough understanding of major concepts, languages, and techniques for building process-aware applications, including: * UML and EPCs: two of the most widely used notations for business process modeling * Concrete techniques for process design and analysis * Process execution standards: WfMC and BPEL * Representative commercial tools: ARIS, TIBCO Staffware, and FLOWer Each chapter begins with a description of the problem domain and then progressively unveils relevant concepts and techniques. Examples and illustrations are used extensively to clarify and simplify complex material. Each chapter ends with a set of exercises, ranging from simple questions to thought-provoking assignments. Sample solutions for many of the exercises are available on the companion Web site. Armed with a new and deeper understanding, readers are better positioned to make their own contributions to the field and evaluate various approaches to a particular task or problem. This publication is recommended as a textbook for graduate and advanced undergraduate students in computer science and information systems, as well as for professionals involved in workflow and business process management, groupware and teamwork, enterprise application integration, and business-to-business integration. A Solution's Manual is available online. An Instructor Support FTP site is also available.
This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.
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