Advanced Computing, IT Strategy, and Network-Optimized Frameworks for Retail Business Intelligence

Abstract

This study addresses a problem in retail business intelligence (BI) modernization: retailers upgrade compute and analytics, yet dashboards still suffer from stale data, inconsistent KPIs, and unreliable Realtime performance because computing, governance, and network engineering are implemented in silos. The purpose is to test, using a quantitative cross sectional, case-based synthesis, whether advanced computing capability (AC), IT strategy alignment (ITSA), and network optimized frameworks (NOF) jointly improve BI service quality and decision usefulness in retail deployments. The sample comprises literature derived cloud and BI cases, with each publication treated as a case unit representing an architecture or evaluated deployment. Key variables are AC (cloud elasticity, distributed processing, streaming ingestion, modular orchestration), ITSA (data governance and stewardship, BI operating model, KPI ownership), NOF (WAN traffic engineering, observability, resiliency, edge placement), and BI outcomes (data freshness, dashboard latency, uptime, KPI consistency, adoption intensity). The analysis plan applies a standardized 1 to 5 evidence scoring rubric per case, vote counting of hypothesis support, and an Integrated Capability Index computed as the mean of AC, ITSA, and NOF. Findings show strong support for AC with a composite score of 4.2/5 (SD 0.6; 76% support), led by cloud elasticity (M 4.4; SD 0.6; 78% support) and distributed processing (M 4.3; SD 0.7; 74% support). ITSA scores 3.9/5 (SD 0.6; 70% support), driven by governance and stewardship (M 4.2; SD 0.7). NOF shows moderate to strong support at 3.7/5 (SD 0.6; 62% support), with observability highest (M 4.0; SD 0.7). Integrated configurations outperform siloed upgrades: high integrated cases report BI_Perf of 4.4/5 versus 3.1/5 in low integrated cases. Implications are that retailers should manage BI as an end-to-end service by coordinating cloud scale, KPI governance, and network reliability with explicit latency, freshness, and uptime targets to sustain secure decision support across omnichannel operations.