<![CDATA[Data quality is a critical determinant of the success of information systems in supporting organizational decision-making processes. In the digital era, organizations increasingly rely on database-based information systems to manage, process, and distribute information efficiently. However, the effectiveness of these systems depends heavily on the quality of the data being processed. Poor-quality data can lead to inaccurate information, reduced user trust, operational inefficiencies, and ineffective strategic decisions. Therefore, maintaining high data quality has become a crucial organizational priority. This study aims to analyze the influence of data quality dimensions on the effectiveness of database-based information systems. The methodology employed is a qualitative approach through a literature review, examining various scientific journals, theses, books, and relevant academic references related to data quality and information system performance. The results indicate that data quality dimensions, including accuracy, completeness, consistency, and timeliness, significantly influence information quality, user satisfaction, system usability, and net benefits for organizations, as described in the DeLone and McLean Information Systems Success Model. Furthermore, the integration of data quality management through the Total Data Quality Management (TDQM) framework and the implementation of database normalization up to the Third Normal Form (3NF) have been proven to improve operational efficiency, reduce data redundancy, and enhance information integrity. This study concludes that proactive data quality management is a strategic asset that supports organizational competitiveness, improves decision-making quality, and contributes to sustainable business performance in the digital era.]]>
Copyrights © 2026
