This paper explores the interplay between Data Utilization (DU), Predictive Analytics (PA), Data-driven Innovation (DI), Decision Support Systems (DSS), and Ethical Data Governance (EDG). The study emphasizes the critical role of DU and PA in fostering DI, which in turn enhances DSS and EDG within organizations. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the relationships between these constructs, using the SmartPLS software. The findings indicate that effective data utilization and predictive analytics significantly contribute to DI, with strong positive relationships. DI, in turn, has a notable positive effect on both DSS and EDG. The high R² values suggest that DU and PA explain a significant portion of the variance in DI, DSS, and EDG, highlighting their collective impact on organizational performance. The study concludes that fostering an environment where data is effectively utilized and predictive analytics are integrated into decision-making processes can lead to substantial improvements in innovation and governance practices. Future research should explore additional variables and longitudinal studies to further understand the long-term effects of these factors on organizational performance.This paper explores the interplay between Data Utilization (DU), Predictive Analytics (PA), Data-driven Innovation (DI), Decision Support Systems (DSS), and Ethical Data Governance (EDG). The study emphasizes the critical role of DU and PA in fostering DI, which in turn enhances DSS and EDG within organizations. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the relationships between these constructs, using the SmartPLS software. The findings indicate that effective data utilization and predictive analytics significantly contribute to DI, with strong positive relationships. DI, in turn, has a notable positive effect on both DSS and EDG. The high R² values suggest that DU and PA explain a significant portion of the variance in DI, DSS, and EDG, highlighting their collective impact on organizational performance. The study concludes that fostering an environment where data is effectively utilized and predictive analytics are integrated into decision-making processes can lead to substantial improvements in innovation and governance practices. Future research should explore additional variables and longitudinal studies to further understand the long-term effects of these factors on organizational performance.