DATA-DRIVEN TRANSFORMATION: OPTIMIZING ENTERPRISE FINANCIAL MANAGEMENT AND DECISION-MAKING WITH BIG DATA

Abstract

This study explores the transformative impact of big data on enterprise financial management, highlighting significant improvements in decision-making efficiency, data quality, and risk management capabilities. Through a mixed-methods approach that includes meta-analysis, surveys, interviews, and case studies, the research reveals a substantial increase in decision-making efficiency, better integration of diverse data sources, and more accurate financial reporting. Practical benefits such as reduced data processing times and improved credit risk assessments are identified, alongside challenges like the skill gap in data science, cultural resistance, and technical difficulties in integrating new technologies with legacy systems. Addressing these challenges requires strategic leadership, continuous training, and investment in scalable infrastructure. Despite these hurdles, the long-term advantages of big data adoption, including enhanced financial reporting and resource allocation, underscore its value in driving organizational performance and competitiveness. This study provides empirical evidence and practical insights, offering a valuable foundation for organizations aiming to leverage big data in their financial management practices.