Strategies to enhance data quality in information management systems: an analysis of challenges and opportunities

Document Type : scientific articles

Authors

1 ‏King Abdul Aziz University

2 King Abdulaziz University

Abstract

Data quality is essential for successful enterprise information management systems, directly influencing decision-making accuracy and operational efficiency. In today’s data-driven environment, this study examines strategies to enhance data quality, along with the challenges and opportunities they entail. It explores core data quality concepts, contributing factors, and the role of information management systems in data organization and analysis. The study uses an analytical approach to review prior literature, identify effective strategies, and examine the challenges organizations face in applying these improvements.

Key findings highlight that data quality has a direct impact on the effectiveness of information management systems, significantly influencing decision-making. Strategies aimed at enhancing data quality improve operational efficiency and reduce error rates. Additionally, technologies like artificial intelligence and big data analytics are critical in refining data quality and identifying hidden patterns. However, technical and cultural barriers often hinder the application of these strategies, necessitating flexible plans for effective implementation.

The study recommends adopting unified data quality standards to improve accuracy and consistency, investing in modern technologies, and providing continuous training to boost employee awareness. Forming dedicated teams for regular data quality checks and creating response plans for technical issues are also advised. These insights offer a comprehensive view on data quality’s role in supporting organizational goals.

Keywords

Arab International Journal of Knowledge Management
Volume 4, Issue 4
October 2025
Pages 15-64

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