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Today s information systems need to meet the challenges of increased regulation, clients demand of customized products and services, and the accelerating speed at which business is conducted. Companies must manage thousands of business rules represented in software code, in database, in spreadsheets, and in paper-based policy manuals. A business process rules engine (BPRE) enables an organization to increase its agility and speed to adapt to business process changes, while increases rule transparency, flexibility, and accuracy of processing. The contribution of this book is the design,…mehr

Produktbeschreibung
Today s information systems need to meet the challenges of increased regulation, clients demand of customized products and services, and the accelerating speed at which business is conducted. Companies must manage thousands of business rules represented in software code, in database, in spreadsheets, and in paper-based policy manuals. A business process rules engine (BPRE) enables an organization to increase its agility and speed to adapt to business process changes, while increases rule transparency, flexibility, and accuracy of processing. The contribution of this book is the design, implementation, and evaluation of a novel BPRE that overcomes many of the implementation, validation, and maintenance problems associated with large monolithic rule repositories. The design adopts a database approach and an innovative and efficient database rule match algorithm. The evaluation of the BPRE artifact comes from user surveys that help uncover the business values and the issues relatingto user acceptance of a business process rules engine. The design has been successfully implemented in a large financial services organization.
Autorenporträt
Wayne Huang is Systems Director at a Fortune 500 company. He has extensive experience in leading large information system projects. He holds Ph.D. in Information Management from Stevens Institute of Technology. His research interests are in business rules engine, workflow automation, data quality assurance, and predictive analytics.