Big, personal, depersonalized data: problems of industry regulation

The development of Russia's digital economy faces a contradiction between the need for free big data exchange and increasing control over personal data. The introduction of «Data Economy» national project and new federal laws on personal and depersonalized data has intensified regulatory problems in this sphere. The research aims to identify economic problems in big data field arising from regulatory gaps and new personal information protection norms. The methodological foundation is new institutional theory, particularly O. Williamson's transaction cost economics. The author applies comparative institutional analysis and economic-mathematical modeling methods to assess the effectiveness of penalty sanctions. Differences in the specificity of big data and personal data as resources were established, justifying the need for a differentiated regulatory approach. Structural regulatory alternatives were identified: from complete state control to market mechanisms with intermediate hybrid forms. The main obstacles to big data market development are uncertainty regarding anonymized data status and the absence of reliable depersonalization methods. Modeling showed that introducing turnover-based fines creates excessive burden on small and medium-sized enterprises that previously invested in cybersecurity. Ensuring digital industry development requires mandatory public-private partnership in rulemaking through self-regulatory organizations that account for a high pace of technological changes.