The Development of a Database Management Model for Decision Support Systems (DSS) of the Office of the Vocational Education Commission
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Abstract
This research aims to (1) examine the current conditions and challenges in the management of the information database system used to support decision-making at the Office of the Vocational Education Commission (OVEC), and (2) develop guidelines for designing and improving the information database system for online performance reporting. The sample group consisted of 90 personnel from the Office of the Vocational Education Commission. Data collection tools included questionnaires and focus group discussions. The data were analyzed using descriptive statistics and content analysis.
The research findings revealed that:
- The current information database system of the Office was rated at a high
level overall. The highest-rated aspects were data storage, data accuracy verification, and information presentation. The proposed development framework for the database system covers five key areas: data collection, verification, processing, presentation, and storage. The framework emphasizes the importance of clearly defined objectives, fostering internal collaboration, applying appropriate technologies, and ensuring data security.
- The proposed guidelines for designing and improving the online
performance reporting database system for the Office of the Vocational Education Commission can be categorized into five main areas: (1) Data Collection – Clearly define data objectives, engage specialized personnel, and promote interdepartmental collaboration to ensure efficient data collection. (2) Data Verification – Emphasize accuracy and consistency between existing and updated data, with experts verifying data quality. (3) Data Processing – Establish structured data relationships, assign clear responsibilities, and utilize modern tools to enhance processing efficiency. (4) Data Presentation – Use the data to enhance personnel capacity, support interdepartmental coordination, display results via dashboards (e.g., Google Data Studio), and inform policy-level decision-making. (5) Data Storage – Implement systematic data storage practices, conduct regular backups, and employ appropriate security measures to protect against data loss or unauthorized access.
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