Predictive Analytics in Big Data-Driven Decision Making: A Framework for Intelligent Organizational Intelligence

Abstract

In the era of digital transformation, organizations generate massive volumes of heterogeneous data from diverse sources such as social media, IoT devices, enterprise systems, and transactional platforms. Predictive analytics, powered by big data technologies, has emerged as a critical enabler of intelligent decision-making. It leverages statistical modeling, machine learning, and artificial intelligence to forecast future trends and behaviors with significant accuracy. This paper explores the role of predictive analytics in big data-driven decision-making systems, focusing on architectures, methodologies, tools, and real-world applications. It further highlights challenges such as data quality, scalability, interpretability, and ethical concerns. The study proposes a conceptual framework that integrates big data pipelines with predictive modeling layers to enhance decision intelligence in organizations. Comparative analysis of predictive techniques and big data platforms is also presented. The paper concludes with future directions emphasizing explainable AI, edge analytics, and autonomous decision systems.

KEYWORDS: Predictive Analytics, Big Data, Machine Learning, Decision Making, Data Mining, Artificial Intelligence, Forecasting Systems