With the evolution of data security techniques and statistical methodologies, the fundamental principle of statistical confidentiality—which has always governed the relationship between producers and users of official statistics on one side, and data subjects on the other—has, over the past decades, evolved into a more comprehensive system of guarantees, embracing many of the fundamental rights and freedoms outlined in the General Data Protection Regulation (hereinafter GDPR) throughout the entire statistical process. This article specifically examines the principles underpinning the architecture of the GDPR in relation to those of the European Statistics Code of Practice (hereinafter Code of Practice), highlighting how many elements of data protection by design and by default are already integrated into the concept and practice of statistical quality. Furthermore, this analysis suggests that the transition of statistics from external privacy, concerning the dissemination and communication of statistical results, to input privacy, referring to data protection from collection to storage, can contribute to the improvement of statistical quality. The aim of this study is therefore to identify points of convergence between data protection and the quality of official statistics, while also highlighting aspects where a balance must be struck between the respect for individuals’ rights and freedoms and the statistical function as a public good serving citizens.