Provenance for business events
by Rafat Hammad; Ching-Seh Wu
International Journal of Big Data Intelligence (IJBDI), Vol. 1, No. 4, 2014

Abstract: In today's business environment, applications generate massive amounts of business data at various levels of granularity. During execution of business processes, a number of issues may occur, e.g., system failures, process failures, service failures, or human errors, that can result in the processes not executing as expected, and as a result not adhering to the required compliance concerns. Business provenance is an emerging concept which gives the flexibility to capture information required to address a specific compliance or performance goal. This paper discusses the importance of data provenance and presents a framework to capture, model, and persists provenance for business events data. We propose a method to model the business events in such a way that can be used for continuous compliance monitoring and for historical root cause analysis. We present a design of our proposed framework and its components along with a prototype implementation.

Online publication date: Sat, 24-Jan-2015

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