National Statistical Agencies are responsable for collecting and disseminating data. The raw material are data collected from respondents. Due to the huge amount of data, several interesting and complex optimization problems appear. On the one side, errors can occur during the data collection process. The process of validating and correcting errors leads to an area known as Data Editing and Imputation. On the other side, individual data are subject to private confidentiality. Protecting private information leads to an area known as Statistical Data Confidentiality. This article presents and surveys some combinatorial problems arising in these two areas.
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