Parametri
- 467pagine
- 17 ore di lettura
Maggiori informazioni sul libro
This second edition of Wil van der Aalst’s influential work on process mining expands its scope to include data science and big data. It features updates on inductive mining techniques, alignments, an expanded section on software tools, and a new chapter on large-scale process mining. The book is self-contained, covering the full spectrum of process mining from discovery to predictive analytics. Part I introduces data science and process mining, while Part II lays the groundwork in business process modeling and data mining. Part III emphasizes process discovery, the key task in process mining, and Part IV explores conformance checking along with organizational and time perspectives. Part V guides readers in practical applications of process mining, introducing the widely used open-source tool ProM and various commercial products. Finally, Part VI reflects on the presented material and identifies key open challenges. This comprehensive overview serves business process analysts, consultants, managers, graduate students, and BPM researchers, offering valuable insights into the current state of process mining.
Acquisto del libro
Process Mining, Wil van der Aalst
- Lingua
- Pubblicato
- 2016
- product-detail.submit-box.info.binding
- (Copertina rigida)
Metodi di pagamento
Ancora nessuna valutazione.
- Titolo
- Process Mining
- Sottotitolo
- Data Science in Action - Second Edition
- Lingua
- Inglese
- Autori
- Wil van der Aalst
- Editore
- Springer
- Pubblicato
- 2016
- Formato
- Copertina rigida
- Pagine
- 467
- ISBN10
- 3662498502
- ISBN13
- 9783662498507
- Serie
- Tag
- Tecnologia & Ingegneria, Computer & Internet, Economia, Germania, Elaborazione dei dati, Applicazioni, Big Data, Sistemi Informativi
- Descrizione
- This second edition of Wil van der Aalst’s influential work on process mining expands its scope to include data science and big data. It features updates on inductive mining techniques, alignments, an expanded section on software tools, and a new chapter on large-scale process mining. The book is self-contained, covering the full spectrum of process mining from discovery to predictive analytics. Part I introduces data science and process mining, while Part II lays the groundwork in business process modeling and data mining. Part III emphasizes process discovery, the key task in process mining, and Part IV explores conformance checking along with organizational and time perspectives. Part V guides readers in practical applications of process mining, introducing the widely used open-source tool ProM and various commercial products. Finally, Part VI reflects on the presented material and identifies key open challenges. This comprehensive overview serves business process analysts, consultants, managers, graduate students, and BPM researchers, offering valuable insights into the current state of process mining.