Assessing and analysing data quality in service oriented architectures; developing a data quality process

摘要: Over the past decade, Service Oriented Architecture (SOA) approach has become a preferable way of building information systems. This is largely due to its ability enable rapid changes in systems by recombining and scaling existing services. However, more complex SOA becomes, likely are data quality (DQ) issues be encountered. Despite numerous projects failing problems, many organizations individuals still ignoring importance necessity quality. In spite large number studies that have been done on SOA, findings literature practice have shown very little investigated about DQ aspect. Most evaluation approaches date do not consider services’ context semantic accuracy data. The objective this research investigate challenges within service composition. More specifically, goal create method detecting analysing semantically inaccurate specific Service-oriented context. order reach given objective, methodology was proposed which suggests techniques methods for profiling assessing data. The developed following Data Quality Management (DQM) model. Additionally, conduct project, Design Science (DS) oriented for conducting research, focuses development artifacts, used. application usability demonstrated home automation system – type environment. The contribution allows practitioners detect poor environment, preventing damages reducing expenses. It also provides researchers with methods will serve as foundation improving data decision making field.