This paper provides an overview of the *CCP4* programs *SCALA*, *POINTLESS*, and *CTRUNCATE* for data reduction through the *CCP4i* graphical interface. It covers key steps such as determining the point-group symmetry of diffraction data, examining systematic absences to infer the space group, scaling to adjust intensities for internal consistency, estimating the structure amplitude from intensities, and detecting crystal pathologies like twinning. The paper also discusses the scoring schemes used by *POINTLESS* to assign probabilities to possible Laue and space groups, and provides guidelines for making decisions during data reduction, including choosing the best resolution cutoff, detecting anomalous signals, and assessing data twinning. The appendix outlines the scoring algorithms used in *POINTLESS* for determining likely Laue groups and space groups.This paper provides an overview of the *CCP4* programs *SCALA*, *POINTLESS*, and *CTRUNCATE* for data reduction through the *CCP4i* graphical interface. It covers key steps such as determining the point-group symmetry of diffraction data, examining systematic absences to infer the space group, scaling to adjust intensities for internal consistency, estimating the structure amplitude from intensities, and detecting crystal pathologies like twinning. The paper also discusses the scoring schemes used by *POINTLESS* to assign probabilities to possible Laue and space groups, and provides guidelines for making decisions during data reduction, including choosing the best resolution cutoff, detecting anomalous signals, and assessing data twinning. The appendix outlines the scoring algorithms used in *POINTLESS* for determining likely Laue groups and space groups.