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A Multi-Dimensional Analytical Model for Enhancing Predictive Decision Support Systems Using Oracle Business Intelligence Suite Enterprise Edition

Author(s) Ramesh Pandipati
Country United States
Abstract Data-driven decision-making has positioned predictive analytics as a vital component of modern enterprise intelligence systems. This paper introduces a multi-dimensional analytical model aimed at enhancing the performance of Predictive Decision Support Systems (PDSS) through the integration of Oracle Business Intelligence Suite Enterprise Edition (OBIEE). The study systematically layers business data across strategic, tactical, and operational dimensions to generate actionable insights using OBIEE’s advanced reporting, dashboard, and data mining functionalities. The proposed model incorporates real-time data acquisition, OLAP capabilities, and predictive modeling techniques to support informed decision-making in complex business environments. The framework’s effectiveness is evaluated through simulated enterprise scenarios, demonstrating notable improvements in forecasting accuracy and decision efficiency. Two case-based tables and two visual diagrams are included to illustrate both the structural composition and performance outcomes of the model. The findings indicate that fully leveraging OBIEE within a multi-dimensional framework can transform traditional Business Intelligence systems into agile, predictive enterprise solutions.
Keywords Predictive Analytics, Business Intelligence, Oracle OBIEE, Multi-Dimensional Model, Decision Support Systems, OLAP, Data Visualization.
Field Engineering
Published In Volume 6, Issue 11, November 2025
Published On 2025-11-21
Cite This A Multi-Dimensional Analytical Model for Enhancing Predictive Decision Support Systems Using Oracle Business Intelligence Suite Enterprise Edition - Ramesh Pandipati - IJLRP Volume 6, Issue 11, November 2025. DOI 10.70528/IJLRP.v6.i11.1838
DOI https://doi.org/10.70528/IJLRP.v6.i11.1838
Short DOI https://doi.org/hbb4jb
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