This study aims to examine the impact of Big Data Analytics on Audit Quality using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) approach. The research involved 120 respondents consisting of auditors from Big Ten public accounting firms in Indonesia. The Big Data Analytics variable was measured based on five main dimensions: volume, velocity, variety, veracity, and value. The results indicate that Big Data Analytics has a positive and significant effect on Audit Quality. This relationship is demonstrated by a path coefficient in the moderate category, with a significance level below the five percent threshold. The coefficient of determination shows that nearly half of the variation in Audit Quality can be explained by Big Data Analytics. These findings confirm that effective implementation of Big Data Analytics can enhance the effectiveness, efficiency, and reliability of the audit process. The study also supports the application of the Technology Acceptance Model framework, where perceived usefulness and ease of use of technology contribute to improved audit quality. The practical implications of this research highlight the importance of data-driven strategies in enhancing audit quality in today's digital era.
                        
                        
                        
                        
                            
                                Copyrights © 2025