The raw data have to be processed before they can be analyzed. Data processing includes the inspection of the datasets and the way how they were generated. It is to be checked if the datasets were assembled in a technically correct way. In addition, a plausibility check has to be performed in order to validate that the datasets are credible. Furthermore, the completeness of the datasets has to be verified. Found errors are to be corrected. Another important issue is data quality. Do the datasets provide the desired or required accuracy?

Apart from these checks, this step also includes the preparation of the data for further processing. Existing tables are assembled in such a way so that they can be used for data analysis. For example, some features may be combined or reclassified to ease their evaluation. The different aspects of data processing can be showed by using the example of a questionnaire.