Advancing Business Insights with Data Science and Machine Learning
EOI: 10.11242/viva-tech.01.08.038
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Citation
Prashik Ubale, Greeshma Raut, Janhavi Morajkar, Bhaumik Mhatre, Nivedha Raut " Advancing Business Insights with Data Science and Machine Learning ", VIVA-IJRI Volume 1, Issue 8, Article 29, pp. 1-8, 2025. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.
Abstract
" The combination of data science, machine learning, and business analytics has transformed the way organisations use data for decision-making and operational optimisation. This paper explores the transformative role of data science and machine learning (ML) in driving innovation and enhancing decision-making across industries. Machine learning applications, such as deep learning for customer segmentation and predictive maintenance powered by IoT, demonstrate the ability to optimize business operations and improve customer experiences. Key advancements include anomaly detection, fraud prevention, and supply chain logistics optimization using supervised, unsupervised, and reinforcement learning techniques. The review also emphasizes the importance of explainable AI (XAI) in promoting transparency and ethical AI adoption within businesses. Moreover, the integration of AutoML, natural language processing, and scalable cloud computing platforms is making advanced analytics accessible even for small and medium enterprises. Despite its potential, challenges like biased datasets, computational demands, and the complexity of models are highlighted as barriers to implementation. The paper concludes by discussing future opportunities in predictive modeling, real-time analytics, and ethical AI development to sustain competitive advantage in data-driven economies."
Keywords
- business analytics, data science, machine learning, operational optimization, predictive modelling.
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