Data-Driven Impact: Performing Big Data Analysis for Evaluating the Effectiveness of Academic Libraries in Achieving SDGs

Objectives: This study investigates the applications of big data in academic libraries, focusing on trends, challenges, and implementations. The primary objective is to explore how libraries utilize big data to improve services, optimize decision-making, and address emerging challenges while contributing to the achievement of the SDGs (Sustainable Development Goals). Theoretical Framework: The research is anchored in the concept of data-driven decision-making, emphasizing the transformative potential of evidence-based insights. This framework underpins the investigation into how big data supports personalized services, resource management, and strategic planning within academic libraries. Method: The study employs a four-phase methodology: data collection, cleaning, integration, and analysis. Publications from 2014 to 2023 were sourced primarily from Scopus. Data cleaning ensured relevance and accuracy, while integration facilitated comprehensive meta-analysis. Analytical tools and techniques, including bibliometric analysis, were utilized to identify trends, technologies, and contributions from leading countries and authors. Results and Discussion: Findings reveal that big data significantly enhances user experience, resource management, and decision-making. Technologies such as data mining, machine learning, and blockchain enable service personalization, resource security, and user behavior prediction. The study highlights notable contributions from countries like the USA, China, and the UK, along with the impact of influential authors. However, challenges persist, including concerns about data privacy, skill gaps among staff, and infrastructure limitations. Research Implications: The findings suggest practical strategies for academic libraries, including prioritizing staff training, fostering international collaboration, and establishing robust data governance policies. These measures are critical for overcoming challenges and maximizing the benefits of big data. Originality/Value: This study offers a comprehensive analysis of big data applications in academic libraries, providing actionable recommendations for library professionals and researchers. It bridges a gap in the literature by identifying long-term impacts and opportunities for integrating emerging technologies, such as AI and IoT, in library operations.