The Air Force's Information Technology Systems require modernization in order to meet the growing need of standards-based, service-oriented architectures. Recognition and emphasis on improving the data quality used in operational systems has increased over the past several years. Improving data quality requires a methodology encompassing complex data error analysis, exception handling, and remediation. Data quality issues arise for many reasons, such as data entry errors, poor system interface design, and invalid data transformations. Data quality initiatives must emphasize master data management practices, data quality analysis and monitoring, and sound error identification and error handling techniques. Perduco will provide a strong framework, with well thought out processes for handling errors and improving data quality, a critical Air Force asset. Our Error Handling Engine (EHE) and Data Quality Engine (DQE) prototype will demonstrate the ability to detect data errors and facilitate correction protocols.
Benefit: A working framework with the functionality to identify and manage data errors in addition to managing and tracking data quality initiatives through the use of a flexible data quality engine. Perduco believes there will be numerous potential commercial applications relevant to many industries including, but not limited to the following: Healthcare Manufacturing Finance
Keywords: Data Quality Managem
