• DocumentCode
    44784
  • Title

    Business Process Analytics Using a Big Data Approach

  • Author

    Vera-Baquero, Alejandro ; Colomo-Palacios, Ricardo ; Molloy, Owen

  • Author_Institution
    Univ. Carlos III de Madrid, Leganés, Spain
  • Volume
    15
  • Issue
    6
  • fYear
    2013
  • fDate
    Nov.-Dec. 2013
  • Firstpage
    29
  • Lastpage
    35
  • Abstract
    Continuous improvement of business processes is a challenging task that requires complex and robust supporting systems. Using advanced analytics methods and emerging technologies--such as business intelligence systems, business activity monitoring, predictive analytics, behavioral pattern recognition, and "type simulations"--can help business users continuously improve their processes. However, the high volumes of event data produced by the execution of processes during the business lifetime prevent business users from efficiently accessing timely analytics data. This article presents a technological solution using a big data approach to provide business analysts with visibility on distributed process and business performance. The proposed architecture lets users analyze business performance in highly distributed environments with a short time response. This article is part of a special issue on leveraging big data and business analytics.
  • Keywords
    business data processing; data analysis; activity monitoring; behavioral pattern recognition; big data approach; business analytics; business intelligence systems; business lifetime; business process analytics; continuous improvement; event data; predictive analytics; type simulations; Analytical models; Business processes; Data handling; Data storage systems; Distributed databases; Information management; big data; business analytics; business process analytics; business process management; information technology;
  • fLanguage
    English
  • Journal_Title
    IT Professional
  • Publisher
    ieee
  • ISSN
    1520-9202
  • Type

    jour

  • DOI
    10.1109/MITP.2013.60
  • Filename
    6560078