DATA WAREHOUSING ARCHITECTURE AND IMPLEMENTATION FOR ENHANCED FINANCIAL REPORTING: A SYSTEMATIC REVIEW

Abstract

This article presents a comprehensive analysis of data warehousing architectures and implementations specifically designed for financial reporting systems. The article examines the evolution, current state, and future trends of data warehousing in financial institutions, focusing on architectural components, implementation frameworks, and business intelligence integration. Through detailed analysis of system design principles, performance optimization techniques, and regulatory compliance requirements, we demonstrate how modern data warehouses can effectively support complex financial reporting needs while ensuring data quality and security. The article highlights critical success factors in implementing financial data warehouses, including dimensional modeling techniques, ETL processes, and integration patterns with existing systems. Our findings indicate that organizations implementing robust data warehousing solutions achieve significant improvements in reporting efficiency, decision-making capabilities, and regulatory compliance. The article also explores emerging technologies such as cloud computing, artificial intelligence, and blockchain, and their potential impact on future data warehouse architectures. This article contributes to both theoretical understanding and practical implementation of data warehousing solutions in financial institutions, providing valuable insights for practitioners and researchers in the field of financial technology and data management.