Published Article

ABSTRACT

This study examined big data descriptive analytics as a determinant of effective Library Management Systems in tertiary institutions in Akwa Ibom State, Nigeria. To carry out the study, a descriptive survey design was adopted. The study was conducted in Akwa Ibom State, Nigeria. The population of the study comprised all librarians in Akwa Ibom State, Nigeria. A purposive (judgmental) sampling technique was used to select librarians from selected public and tertiary institution libraries in the state. The technique was adopted because the respondents were considered knowledgeable and experienced in library management practices. The sample consisted of 15 librarians from the University of Uyo Library, 5 librarians from the Akwa Ibom State University Library, 5 librarians from the Akwa Ibom State Polytechnic Library. This gave a total sample size of 25 respondents. Data were collected using a structured questionnaire entitled "Big Data Descriptive Analytics and Good Library Management System Questionnaire (BDDAGLMSQ)." The instrument was validated by an expert in Test, Measurement, and Evaluation to ensure its clarity, relevance, and suitability for the study. A reliability coefficient of 0.91 was obtained, indicating that the instrument was highly reliable. The data collected were analyzed using descriptive statistics to answer the research questions and regression analysis to test the hypothesis at the 0.05 level of significance. The findings revealed that Enhancement of Strategic Decision-Making recorded the highest percentage response (40.00%), followed by Streamlining Operational and Administrative Efficiency (28.00%), Optimization of Resource Discoverability (20.00%), and Personalization of User Experience and Services (12.00%). The regression analysis further showed a strong positive relationship between Big Data Descriptive Analytics and Library Management Systems (R = 0.978, R² = 0.957, Adjusted R² = 0.955). The ANOVA result indicated a significant influence of Big Data Descriptive Analytics on Library Management Systems (F = 509.223, p < 0.05), leading to the rejection of the null hypothesis. The study concluded that Big Data Descriptive Analytics is a critical determinant of effective Library Management Systems because it enhances strategic decision-making, improves resource discoverability, strengthens user-centered services, and increases operational efficiency. One of the recommendations made was that Library staff in tertiary institutions should be trained in big data analytics tools and data management techniques to improve their technical competence.