Abstract
Abstract In real-time Business Analytics scenarios, like Business Activity Monitoring (BAM) or Operational Intelligence, speeding up ETL is fundamental to provide business users with up-to-date data in order to support decision-making process and to optimize business operations. Conventional ETL processes extract data from heterogeneous operational data sources, transform them according to some predefined semantic and syntactic rules, and finally load results into a new (relational or data warehouse) model, in order to be processed both for business monitoring or analysis. Usually the whole loading process is presented as a technical aspect, far from business facts. In real-time Business Analytics context the traditional ETL approach can still be valid, provided that ETL process has to be designed in a way that circumscribes individual business events and facts and makes them independent one from another. In this context we propose a control-flow- based approach to ETL process modeling, which starts from business facts identification, and represents ETL processes using BPMN notation, which is the foundation for machine-readable code. Our main contribution consists in a proposal for structuring ETL processes and related objects and in its application to a business case.
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