Published Paper Details:

The rise of digital technologies has led to the exponential growth of data, necessitating advanced analytical frameworks to manage, process, and derive meaningful insights. Big Data, characterized by its high volume, velocity, and variety, serves as a foundation for informed decision-making across sectors such as business, healthcare, finance, and e-commerce. Concurrently, decision trees have emerged as intuitive tools for classification and prediction, offering a transparent and structured approach to decision-making. This paper explores the fundamental concepts of Big Data, its classifications, and key applications, and demonstrates the construction and use of decision trees through practical case scenarios. Additionally, the study incorporates the use of EdrawMind, an open-source visualization tool, to develop clear and interpretable decision tree diagrams that enhance understanding and presentation. The study highlights how these tools collectively contribute to data-driven decisions and outlines their potential for academic and industrial applications.