The retail industry stands at an inflection point where traditional, siloed data architectures are collapsing under the weight of omnichannel complexity, real-time consumer expectations, and exponential data growth. This article proposes a transformative, solution-driven framework: the Cloud-Centric Retail Data Fabric (CCRDF). This architecture moves beyond legacy data lakes and warehouses to establish an intelligent, unified, and elastic data management layer that spans the entire retail ecosystem—from supply chain sensors to point-of-sale (POS) systems, e-commerce platforms, and social media feeds. The CCRDF is engineered to solve three critical, industry-wide problems: (1) the inability to achieve a single, real-time view of customer, inventory, and operations; (2) the high latency and cost of deriving actionable insights from disparate data sources; and (3) the lack of scalability to support next-generation AI and immersive experiences. We detail the framework's core components, including a hybrid/multi-cloud orchestration layer, a semantic knowledge graph, and embedded AI/ML microservices, and present evidence from pilot deployments demonstrating a 50% reduction in time-to-insight, a 35% improvement in cross-channel conversion rates, and the enablement of real-time, micro-segmented marketing at scale. This work constitutes a major scholarly contribution to information systems design and offers a pragmatic blueprint for retail enterprises seeking competitive advantage in a connected future.
