ERP systems, at present, are found to be inflexible to adapt to changing organizational processes. They are required to quickly adjust to changing processes and value-added chains and streamline their internal organizational structure. Data in ERP systems is becoming increasingly voluminous in their transactional programs. In this scenario, ERP systems are increasingly exposed to big data wherein the combined analysis of larger amounts of structured and unstructured data from disparate systems takes place in a short amount of time. Big data analytics requires greater use of predictive analytics to uncover hidden patterns and their relationships to visualize and explore data. The evolution of big data and predictive analytics have given a new way for exploring new frontiers in analytics-driven automation and decision management in highvolume, front-line operational decisions. In this paper the authors have focused on predictive capabilities of ERP systems, to analyze current data and historical facts in order to identify potential risks and opportunities for any organization. Analytical Decision Management & Business Rules are used to deploy decision as a service.
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