Master data definition and the privacy classification in government agencies: Case studies of local government - Haneem, F. (American Scientific Publishers, 2017)
The Master Data Management (MDM) empowers government agencies to consolidate and integrate multiple master data sources to a single source of truth. With MDM, the master data from different agencies that are valuable across agencies, applications and services will be identified and managed in a central repository as a high quality enterprise master data. However, the MDM establishment usually hindered by a data policy where most of the government agencies are reluctant to share their master data due to widespread privacy concerns. Hence, this study aims to define master data and its privacy classification in each government agencies by using a qualitative and quantitative data analysis approach. It involves participative case studies from seven (7) Malaysia’s local government agencies. The study identifies 36 sets of master data which generally grouped into three domains which are; (1) customers’ profile, (2) services and products, and (3) service providers’ profile. From these master datasets, 20 datasets (56%) are classified as open data. The result indicates that the government agency has a high potential to share these open master data to the centralized MDM platform with no worry of the privacy issues. This study presents a significant contribution to the MDM research area by clarifying master data definition and its privacy classification in government agencies.