Big Data Concept

Introduction In the era of big data and advanced analytics, dependency modeling has emerged as a critical tool for understanding and quantifying relationships between variables in complex systems. Dependency modeling refers to statistical and computational methods used to capture and analyze the interdependencies among multiple variables, enabling more accurate predictions in uncertain environments. This approach is particularly vital in predictive analytics, where it helps forecast outcomes by accounting for how changes in one factor influence others, moving beyond simple correlations to model joint distributions and tail dependencies. In finance, it aids in risk assessment and portfolio management, while in healthcare, it supports patient outcome predictions and resource allocation. As data volumes explode, dependency modeling unlocks actionable insights, driving efficiency and innovation in these high-stakes sectors. This chapter delves into the fundamentals, processes, techniques...