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Event Log Cleaning for Business Process Analytics

  • Living reference work entry
  • First Online:
Encyclopedia of Big Data Technologies

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Synonyms

Event log preprocessing; Event log repair

Definition

Event log cleaning is a data preparation phase that turns event data into event logs to enable or improve the quality of business process analytics methods like process mining, model enrichment, and conformance checking. Event data might have to be collected from different sources and formats, filtered, transformed, and assigned to the corresponding processes and cases.

Overview

The goal of business process analytics projects is to gain insights into the execution of business processes. It can help to know which questions should be answered by the analysis. Some typical questions are what is done (activities), when is it done or how long does it take (time stamps), in which order (relations), and by whom(resources). In contrast to traditional questionnaires, the process participants do not need to be personally asked about their perception of the process. In business process analytics, the event logs containing process...

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Authors and Affiliations

  1. Vienna University of Economics and Business, Vienna, Austria

    Andreas Solti

Authors
  1. Andreas Solti
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Correspondence to Andreas Solti .

Editor information

Editors and Affiliations

  1. School of Comp. Sci. and Engineering, University of New South Wales School of Comp. Sci. and Engineering, Eveleigh, New South Wales, Australia

    Sherif Sakr

  2. Sch of Info Techno, Building J12, University of Sydney Sch of Info Techno, Building J12, Sydney, Australia

    Albert Zomaya

Section Editor information

  1. Institute of Computer Science, University of Tartu, Juhan Liivi 2, 50409, Tartu, Estonia

     & Marlon Dumas & Matthias Weidlich

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Solti, A. (2018). Event Log Cleaning for Business Process Analytics. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_87-1

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  • DOI: https://doi.org/10.1007/978-3-319-63962-8_87-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63962-8

  • Online ISBN: 978-3-319-63962-8

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