Modeling Quality Level of University Portal Data using Quality Function Deployment (QFD), Case Study: Amir Kabir Universityof Technology

Data Quality plays a vital role in the performance and success of an organization and can be compared to oxygen for human beings. Therefore, maintaining data quality helps organizations in low operating costs and increment in revenue. If data has not been offeredon time and adequate to each department’s quality expectation, such organization may not be able to make successful decisions. First step of data quality enhancement is the acquaintance of data quality dimensions. Identifying and grouping various dimensions of data quality allow experts to use data quality enhancement tools and methods on information improvement processes.

The present study is applied in terms of purpose and analytical-survey research. In this paper, to enhance the level of data quality of university portals, users' requirements (voices) of a university portal have been prioritized using several data quality-related questionnaires by combining Kano & AHP techniques. A designed matrix of a 4-step QFD has been formed, which started with the users' requirements and ended with design methodologies.

As a result of combining Kano & AHP techniques, basic requirements have higher priority than others. It has been defined in this paper that entering data in various formats is the most important users' requirement. Based on QFD analysis, XML & HTML are more proper and useful in comparison to other platforms and programming languages to improve the level of data quality and fulfill users' requirements. In addition, flexibility could be the most important Engineering Characteristics parameter in designing a portal. HVR software can perform a reliable and secure platform to prepare rapid and optimized data integration.

The Quality Function Deployment method could be an appropriate solution to solve problems regarding data quality in the condition that it consists of programming to the designing process.