Information quality analysis and data error detection

Business process modelling plays an important role for design, development, and improvement of today’s most businesses. The automation of multiple activities within an information system, would amplify the velocity of workload; which would lead to more efficient process and production as a result. The more is the quality of information, the more effective the business process will be. The challenge of today’s most business processes is to lessen the error rate and prove the high quality of data within a process. This will emphasize how important it is to find a solution for every error, and find a way to erase it. Identifying where the current error has been planted, is one of the main issues in every business information system. This dissertation aimed to provide a comprehensive methods and techniques to overcome the information quality problems within a business process. in particular, we discuss the different aspects of information quality, its relationship with inflicted costs, finding the root of problems alongside with their probabilities, techniques and methodologies to improve the information quality, and developing a model to detect, locate, and understand the error causes of the business process.