Holographic Data Visualization and AI-Driven Image Processing in Cloud Business Intelligence

Abstract

Enterprise business intelligence has long been constrained by two-dimensional display surfaces that flatten inherently multi-dimensional operational data into planar charts and heatmaps. The convergence of commercial light-field display hardware, AI-accelerated neural rendering, and cloud graphics processing unit infrastructure now creates a practical threshold for volumetric business intelligence. This article proposes the Holographic BI Delivery Architecture (HBDA), a cloud-native four-layer pipeline connecting live operational data streams to light-field display hardware. The primary technical contribution is the Sparse Operational Point Cloud (SOPC) encoding format — a novel intermediate representation that transforms tabular and graph-structured business metrics into volumetric point cloud inputs consumable by neural rendering engines without manual three-dimensional scene construction. The three-dimensional Gaussian Splatting renderer achieves rendering throughput and training times sufficient for operational analytics refresh cadences across standard benchmark datasets. A controlled evaluation with enterprise analysts demonstrated substantial decision accuracy improvements and decision speed improvements over flat-screen business intelligence baselines, accompanied by a meaningful reduction in cognitive load as measured by the NASA Task Load Index. These outcomes establish a new engineering frontier at the intersection of cloud analytics, neural rendering, and immersive human-computer interaction.