Integrating Business Analytics and Machine Learning for Immediate Decision Making Through a Unified Framework
Al Akhir1*, Sonia Khan Papia2, Sonia Nashid3, Fahim Rahman4, Ariful Islam1
Journal of Ai ML DL 1 (1) 1-8 https://doi.org/10.25163/ai.1110366
Submitted: 06 January 2025 Revised: 09 March 2025 Accepted: 12 March 2025 Published: 12 March 2025
Abstract
Background: Businesses need to make quick decisions to stay competitive in today's digital transformation era. Business Analytics (BA) and Machine Learning (ML) have combined to create a revolutionary method for analyzing large datasets which enables immediate decision-making. The practical use of BA and ML integration remains insufficiently studied particularly across multiple industry sectors.
Methods: The research conducted a quantitative survey among 100 business professionals who represent the retail and finance sectors as well as manufacturing, healthcare and information technology industries. The researchers used a structured questionnaire to measure BA and ML integration levels and decision-making speed and operational efficiency and challenges faced.
Results: The results show that 86% of participants have implemented BA-ML systems in partial or complete form. Survey participants showed substantial enhancements in both forecasting accuracy and decision speed and operational efficiency. The main challenges to ML model implementation stem from poor interpretability (48% of respondents) and data privacy problems (42%) and insufficient skilled workforce (37%). This research establishes a real-time decision-making framework consisting of five stages which combines BA and ML to improve organizational performance.
Conclusion: The study demonstrates both business benefits and technical difficulties which organizations need to overcome for successful BA-ML integration. The framework sets a clear path for organizations to achieve operational efficiency and market agility in competitive business environments.
Keywords: Business Analytics, Machine Learning, Real-Time Decision-Making, Predictive Analytics, Data Strategy
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