This chapter explains that before researchers can proceed with the next stages of data analysis, the data need to be prepared by checking questionnaires or other instruments of data capture for usability, editing responses for legibility, completeness and consistency, coding any responses that are not pre-coded, and assembling the data together by entering all the values for all the properties for all the cases into a data matrix. Data entry into the survey analysis package SPSS is explained in some detail. Once data are entered, some of the properties may need to be transformed in various ways. For properties as variables, the transformations may involve one or more of a number of activities, including regrouping values on a nominal or ordered category measure to create fewer categories, creating class intervals from metric measures, computing totals or other scores from combinations of several variables, treating groups of variables as a multiple response question, upgrading or downgrading measures, handling missing values and ‘Don’t know’ responses, or coding open-ended questions. For properties as set memberships, transformations may entail creating crisp sets or fuzzy sets from existing variables.

The careful preparation of data ready for analysis should never be neglected. If poor-quality data are entered into the analysis, then no matter how sophisticated the statistical techniques applied, a poor or untrustworthy analysis will result. Handled with care, data preparation can substantially enhance the quality and usefulness of data analysis; paying inadequate attention to it can seriously compromise the validity of the results.