In the digital society, individuals play different roles depending on the situation they are placed in: they are consumers when they purchase a good, citizens when they vote for elections, content providers when they post information on a platform, and data subjects when their data is collected. Public authorities have thus far regulated citizens and the data collected on their different roles in silos (e.g., bankruptcy registrations, social welfare databases), resulting in inconsistent decisions, redundant paperwork, and delays in processing citizen requests. Data silos are considered to be inefficient both for companies and governments. Big data and data analytics are disrupting these silos allowing the different roles of individuals and the respective data to converge. In practice, this happens in several countries with data sharing arrangements or ad hoc data requests. However, breaking down the existing structure of information silos in the public sector remains problematic. While big data disrupts artificial silos that may not make sense in the digital society and promotes a truly efficient digitalization of data, removing information out of its original context may alter its meaning and violate the privacy of citizens. In addition, silos ensure that citizens are not assessed in one field by information generated in a totally different context. This chapter discusses how big data and data analytics are changing information silos and how digital technology is challenging citizens’ autonomy and right to privacy and data protection. This chapter also explores the need for a more integrated approach to the study of information, particularly in the public sector.