Enabling detailed query execution logs in Databricks allows for the capture of comprehensive information about each query's execution, including step durations, data shuffling, and resource usage. The built-in Spark UI facilitates the analysis of these logs, offering visual insights into query execution to easily identify bottlenecks like slow-running queries, inefficient data shuffling, or resource contention. This method enables the identification of stages with prolonged execution times, data skew issues, or suboptimal resource utilization, guiding targeted optimizations such as query rewriting, resource allocation adjustments, or data restructuring. This approach is superior as it harnesses Databricks and Spark's native monitoring and analysis features for detailed query performance insights, supporting real-time issue detection and resolution.