Big Data Analytics and Information Management Decision-Making in Nigerian Commercial Banks: An Empirical Assessment

This study empirically assesses the application of big data analytics (BDA) to information management decision-making processes in Nigerian commercial banks. In an era of exponential data growth, the capacity to extract actionable intelligence from large datasets is increasingly determining competitive advantage and operational efficiency in banking. The research employs a quantitative survey design targeting chief information officers, data analysts, records managers, and senior administrative decision-makers in twenty commercial banks. A validated BDA adoption and decision quality instrument is administered to 240 respondents. Multiple regression and mediation analysis techniques are used to test the hypothesised relationships. The Resource-Based View Theory and the Data-Driven Decision-Making Framework provide the theoretical anchors, with literature from 2021 to 2024 on big data in Nigerian banking supporting the study. Dimensions examined include BDA infrastructure quality, analytical capability, data governance maturity, decision speed, and decision accuracy. The study addresses the gap in empirical work linking BDA specifically to information management decision quality (as distinct from financial decision-making) in the Nigerian banking context. Recommendations target the CBN's IT supervision directorate and bank technology investment committees. Keywords: big data analytics, information management, decision-making, commercial banks, Nigeria