A Comparative Study of Data Warehouse Architectures in Enhancing Enterprise Data Portals through Logical Data Integration Strategies

Abstract

As enterprises increasingly rely on data-driven strategies, the need for efficient, scalable, and user-friendly data portals has grown exponentially. Traditional data warehouse architectures, centered on physical integration through Extract-Transform-Load (ETL) processes, face significant limitations regarding latency, scalability, and accessibility for non-technical users. This paper explores the transformative potential of logical data integration strategies, focusing on their ability to enable seamless, real-time access to distributed data sources. By leveraging keyword-based retrieval systems and virtual integration layers, enterprises can overcome the barriers posed by traditional systems. A detailed analysis of conventional and logical data integration approaches is presented, supported by case studies and pilot implementations that demonstrate enhanced user engagement, reduced costs, and improved operational efficiency. This paper concludes with actionable recommendations for implementing logical data integration frameworks to revolutionize enterprise data management.