UTD Press Journals
Economics, Management and Sustainable Growth
Review Article Published August 27, 2026 Article emsg20260014

SiriusBI - A Comprehensive LLM-Powered Solution for Data Analytics in Business Intelligence: Uncertainty and Sensitivity Analysis

Abstract

Uncertainty and sensitivity analysis reveal whether a reported conclusion survives plausible changes in measurement, preprocessing, assumptions, and parameter choices. This structured evidence review evaluates "SiriusBI: A Comprehensive LLM-Powered Solution for Data Analytics in Business Intelligence" alongside nine author-disjoint, topically matched publications in enterprise data intelligence. It compares construct definitions, evaluation choices, operating assumptions, and reported limitations instead of treating bibliographic similarity as empirical equivalence. Viewed through measurement uncertainty and sensitivity analysis, the map separates claims supported by the available record from questions that still require full-text extraction, replication, or new experiments. The synthesis is interpretive rather than meta-analytic and therefore does not present a pooled effect estimate or a new causal result. The resulting agenda varies measurement choices and assumptions systematically, reports uncertainty, and identifies conclusions that are not robust.

Keywords
enterprise data intelligencemeasurement uncertainty and sensitivity analysisevidence synthesisreproducibilityresearch evaluation
References
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Publication details
Journal
Economics, Management and Sustainable Growth
Volume
1 (2026)
Article number
emsg20260014
License
CC BY 4.0