Business data analysis focuses on extracting actionable insights from extensive datasets, which is crucial for informed decision-making and maintaining a competitive edge. It involves various techniques and methodologies to interpret data from different sources in structured and unstructured formats, ultimately supporting decision-making processes2.
Traditional rule-based systems struggle with modern data due to their inherent limitations in handling complex and dynamic datasets. These systems rely on predefined rules and lack adaptability, making it challenging for them to deal with ambiguity and bias in today's vast and ever-changing data environments1. As a result, they often need help to provide accurate and actionable insights for informed decision-making in contemporary business scenarios.
AI models like Large Language Models (LLMs) contribute to data analysis by recognizing patterns, making predictions, and understanding natural language in vast datasets. They enhance efficiency, accuracy, and utility in data science and analytics, enabling businesses to extract valuable insights from unstructured information, and make data-driven decisions more accurate.