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Autor(en): 
  • Wil M. P. van der Aalst
  • Process Mining: Data Science in Action 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 5 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  April 2018  
    Genre:  EDV / Informatik 
     
    Application software / B / Business applications / Business mathematics & systems / Business—Data processing / Computer and Information Systems Applications / Computer Appl. in Administrative Data Processing / Computer architecture & logic design
    ISBN:  9783662570418 
    EAN-Code: 
    9783662570418 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 30 mm 
    Gewicht:  7314 gr 
    Seiten:  467 
    Illustration:  XIX, 467 p. 250 illus., 13 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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 offersa 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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