A META-ANALYSIS OF BUSINESS INTELLIGENCE DECISION SUPPORT SYSTEMS IN LARGE ENTERPRISES THROUGH SQL-DRIVEN REPORTING

This systematic review and meta-analysis examines how Business Intelligence/Decision Support Systems (BI/DSS) built on SQL-driven reporting affect enterprise outcomes in large organizations. Following PRISMA (2020) procedures, a preregistered protocol guided database searches (Web of Science, Scopus, ABI/INFORM, IEEE Xplore, ACM Digital Library, Google Scholar), dual-reviewer screening, risk-of-bias appraisal, and standardized data extraction. Eligible studies reported empirical outcomes in medium/large enterprises where BI/DSS included relational warehousing, ELT/ETL, governed SQL semantics, and visualization/OLAP delivery. Quantitative synthesis used random-effects models with REML and Knapp–Hartung adjustments; heterogeneity and robustness were explored with moderator analyses, influence diagnostics, and publication-bias checks. The final corpus comprised k = 79 studies. Evidence of financial impact was common: 54 studies reported improvements in at least one indicator (e.g., operating margin, ROA, working-capital efficiency), typically attributed to standardized KPI semantics, repeatable variance analysis, and faster close-to-report cycles enabled by version-controlled SQL, conformed dimensions, and reconciliation layers. Non-financial effects were even more prevalent: 61 studies associated BI/DSS with greater decision speed, higher diagnostic depth/forecast accuracy, and reduced compliance and operational risk, supported by lineage-aware ELT, bitemporal histories, and embedded data-quality controls. Meta-regression indicated stronger effects under higher governance maturity (analytics competency centers, stewardship networks, KPI registries), greater SQL/semantics maturity (effective-dated reference data, SCD-aware dimensions), and in multinational settings that standardized core KPI math while localizing currencies, tax rules, calendars, and language via parameter tables. Across sectors and geographies, the mechanism recurring in successful cases was the codification of business policy as auditable, executable SQL surfaced through usable dashboards/OLAP, with human capabilities (training, support, decision rights) converting technical potential into coordinated action.