The paper discusses the process of data reduction in X-ray crystallography, focusing on the scaling program AIMLESS, which is designed to improve the quality of the data set by correcting for experimental variations and estimating the structure amplitude. The authors describe the scaling process, including the minimization of a function that accounts for measurement errors and the correction of these errors. They also discuss the analysis of data quality, including the use of $R$ factors and correlation coefficients to assess internal consistency and signal-to-noise ratio. The paper explores the resolution cutoff for data sets, comparing the measured data with simulated data and testing the impact of extending the resolution beyond conventional limits. The results suggest that adding weak high-resolution data may improve structure determination without causing harm. The authors conclude that the exact resolution cutoff is less important than ensuring that the data set is as complete as possible, and that merging data from multiple sources can enhance the weak anomalous signal.The paper discusses the process of data reduction in X-ray crystallography, focusing on the scaling program AIMLESS, which is designed to improve the quality of the data set by correcting for experimental variations and estimating the structure amplitude. The authors describe the scaling process, including the minimization of a function that accounts for measurement errors and the correction of these errors. They also discuss the analysis of data quality, including the use of $R$ factors and correlation coefficients to assess internal consistency and signal-to-noise ratio. The paper explores the resolution cutoff for data sets, comparing the measured data with simulated data and testing the impact of extending the resolution beyond conventional limits. The results suggest that adding weak high-resolution data may improve structure determination without causing harm. The authors conclude that the exact resolution cutoff is less important than ensuring that the data set is as complete as possible, and that merging data from multiple sources can enhance the weak anomalous signal.