This article discusses the differences between thin and thick X-ray diffraction data collection using two-dimensional position-sensitive detectors. Thin data sets, with small rotation-angle increments, result in more spatial overlaps, lower X-ray background, and fewer saturated pixels, but may have higher detector noise and issues with underscan and overscan. Thick data sets, with larger rotation-angle increments, have more fully recorded reflections, higher X-ray background, and more saturated pixels, but fewer images are needed to cover the rotation range. The processing of thin and thick data sets requires different approaches, with thin data sets requiring three-dimensional integration and thick data sets requiring two-dimensional integration. The software package d*TREK is introduced for processing diffraction images and is compared with other popular packages. The article also discusses the importance of minimizing potential problems in data collection to achieve better results. Results from three different experiments are presented, showing that thin-sliced data sets can yield better results in terms of I/σ(I) and R_merge values. The article concludes that the optimal rotation start, end, and increment, as well as exposure time, should be chosen based on the specific experimental conditions and the desired precision of the results.This article discusses the differences between thin and thick X-ray diffraction data collection using two-dimensional position-sensitive detectors. Thin data sets, with small rotation-angle increments, result in more spatial overlaps, lower X-ray background, and fewer saturated pixels, but may have higher detector noise and issues with underscan and overscan. Thick data sets, with larger rotation-angle increments, have more fully recorded reflections, higher X-ray background, and more saturated pixels, but fewer images are needed to cover the rotation range. The processing of thin and thick data sets requires different approaches, with thin data sets requiring three-dimensional integration and thick data sets requiring two-dimensional integration. The software package d*TREK is introduced for processing diffraction images and is compared with other popular packages. The article also discusses the importance of minimizing potential problems in data collection to achieve better results. Results from three different experiments are presented, showing that thin-sliced data sets can yield better results in terms of I/σ(I) and R_merge values. The article concludes that the optimal rotation start, end, and increment, as well as exposure time, should be chosen based on the specific experimental conditions and the desired precision of the results.