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ABSTRACT

Business processes drive the operations of an enterprise. In the past, the focus was primarily on business process design, modeling, and automation. Recently, enterprises have realized that they can benefit tremendously from analyzing the behavior of their business processes with the objective of optimizing or improving them. In our research, we address the problem of warehousing business process execution data so that we can analyze their behavior using the analytic and reporting tools that are available in data warehouse environments. We build upon our previous work that described the design and implementation of a generic process data warehouse for use with any business processes. In this paper, we show how to automate the population of the generic process warehouse by tracking business events from an application environment. Typically, the source data consists of event streams that indicate changes in the business process state (i.e., progression of the process). The target schema is designed to allow querying of task and process execution data. The core of our approach for processing progression data relies on the construction of generic templates that specify the semantics of the event streams extraction and the subsequent transformations that translate the underlying IT events into business data changes. Using this extensible template mechanism, we show how to automate the construction of mappings to populate the generic process warehouse using two-levels of mappings that are applied in two-phases. Interestingly, our approach of using ETL technology for warehousing process data can be seen the other way around. An arbitrary ETL process can be modeled as a business process. Hence, we describe the benefit of modeling ETL as a business process and illustrate how to use our approach to warehouse ETL execution data, and to monitor and analyze the progress of ETL processes. Finally, we discuss implementation issues.

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