INTEGRATING BUSINESS INTELLIGENCE AND MACHINE LEARNING FOR ENHANCED DEMAND FORECASTING

Abstract

This paper explores the convergence of traditional statistical approaches with cutting-edge machine learning techniques—ranging from ensemble models to neural networks—in the context of demand forecasting. It introduces a structured framework for categorizing analytical platforms based on their primary use cases, deployment formats, and end-user profiles. Solutions such as Microsoft Power BI, SAP Integrated Business Planning (IBP), Amazon Forecast, Tableau, and Oracle Demand Management Cloud are examined in detail. The significance of robust data architecture is emphasized as a critical factor in building accurate predictive models. Additionally, the article highlights how the integration of Business Intelligence (BI) systems with enterprise platforms and cloud-based technologies can drive competitive advantage and sustainable business growth.