Exploring Hybrid Data Models for Effective Business Intelligence

Abstract

Business Intelligence (BI) has become an indispensable tool for organizations aiming to derive actionable insights from data. Traditional data models often fall short in addressing the complexities of modern data landscapes characterized by structured, semi-structured, and unstructured data. This paper explores hybrid data models as a solution for enhancing BI effectiveness. By integrating relational databases, NoSQL systems, and data lakes, hybrid models provide flexibility, scalability, and real-time analytics capabilities. This study evaluates the implementation of hybrid data models in diverse industries, highlighting their advantages, limitations, and impact on decision-making processes.