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    Process Mining: Data Science in Action
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    Process Mining: Data Science in Action

    By Wil van der Aalst

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    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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