ABSTRACT

When it comes to corporate decision-making, data quality is crucial since it affects operational performance, strategic planning, and efficiency. This study examines how data quality affects decision-making, emphasizing important aspects including timeliness, correctness, completeness, and consistency. Employing a quantitative research methodology, standardized questionnaires were used to gather data from education sector personnel, and statistical software like SPSS was used for analysis. The results show that although high-quality data improves decision-making accuracy and organizational performance, low-quality data results in inefficiencies, resource misallocation, and bad strategic judgments. The paper also identifies issues with data integrity, such as human mistakes, technical limitations, and a lack of control structures. According to the research, firms can improve performance, make better decisions, and keep a competitive edge in a data-driven world by tackling these problems, which include strengthening staff training on data management best practices, investing in automated data validation tools, and putting strong data governance policies into place.