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Business Process Analytics Using a Big Data Approach
Nov.-Dec. 2013 (vol. 15 no. 6)
pp. 29-35
Alejandro Vera-Baquero, Universidad Carlos III de Madrid
Ricardo Colomo-Palacios, Universidad Carlos III de Madrid
Owen Molloy, National University of Ireland
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.
Index Terms:
Information management,Data handling,Data storage systems,Distributed databases,Analytical models,Business processes,business analytics,business process analytics,business process management,big data,information technology
Alejandro Vera-Baquero, Ricardo Colomo-Palacios, Owen Molloy, "Business Process Analytics Using a Big Data Approach," IT Professional, vol. 15, no. 6, pp. 29-35, Nov.-Dec. 2013, doi:10.1109/MITP.2013.60
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