Business process analytics using a big data approach

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

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

97 Citations (Scopus)

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.

Original languageEnglish
Article number6674000
Pages (from-to)29-35
Number of pages7
JournalIT Professional
Volume15
Issue number6
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • big data
  • business analytics
  • business process analytics
  • business process management
  • information technology

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