Abstract

Modern enterprises generate massive volumes of heterogeneous data across finance, human resources (HR), and customer relationship management (CRM) functions. Traditional data warehousing and business intelligence systems struggle to handle the scale, complexity, and real-time analytical demands of such environments, particularly when advanced artificial intelligence (AI) capabilities and human-centric decision-making are required. This paper proposes a cloud-based large-scale data warehousing architecture that enables human–AI collaborative intelligent analytics across finance, HR, and CRM domains. The architecture integrates cloud-native data pipelines, scalable storage and compute layers, advanced analytics, and AI-driven insight generation while maintaining governance, security, and performance. Human expertise is embedded into the analytics lifecycle through interactive visualization, explainable AI outputs, and decision feedback loops. Experimental evaluation and enterprise use-case analysis demonstrate improvements in data integration efficiency, query performance, analytical depth, and decision quality compared to traditional enterprise data warehouse approaches. The results indicate that cloud-based data warehousing combined with human–AI collaboration provides a robust foundation for enterprise-scale intelligent analytics.