An Improved Hybrid Data Warehousing Architecture for Cloud Service Providers

Traditional Data Warehouses (DWHs) are inefficient for handling the growing volume, variety, and velocity of modern data. This paper introduces a novel hybrid data warehousing architecture designed for cloud service providers (CSPs), which integrates the strengths of Data Warehouses, Data Lakes, and Data Marts into a unified framework. This innovative architecture enables seamless integration and processing of structured, semi-structured, and unstructured data, addressing the challenges posed by diverse data types in cloud environments. Unlike traditional approaches that treat data processing in isolation, the proposed architecture supports both real-time and batch processing within a single system, improving query performance and facilitating dynamic decision-making. The architecture's flexibility allows it to efficiently manage large datasets and adapt to fluctuating workloads. A key feature of this system is its focus on scalability, security, and real-time analytics, making it particularly suitable for CSPs across service models such as IaaS, PaaS, and SaaS. The proposed hybrid repository model significantly enhances data governance and ensures robust data protection. By unifying different data storage models, it optimizes storage management and streamlines data access.