Управление данными
Система политик для качества данных.
Data governance encompasses the overall management of data availability, usability, integrity, and security within an organization. It defines who can take what actions with what data, under what circumstances, and using what methods.
Key components include: data quality management (accuracy, completeness, consistency), data security and privacy (access controls, encryption, compliance), data lifecycle management (creation, storage, archival, deletion), and metadata management (data lineage, cataloging, documentation).
In blockchain contexts, data governance takes unique forms: on-chain governance for protocol changes, [DAO governance](/ru/terms/dao-governance) for collective decision-making, and considerations around immutability (data on-chain cannot be deleted). Off-chain data governance for dApps mirrors traditional practices but must account for decentralized architectures.
Regulatory frameworks like GDPR, CCPA, and industry standards (SOC 2, ISO 27001) drive data governance requirements. Organizations need data stewards, clear policies, automated enforcement, and regular audits to maintain effective governance.
graph LR
Center["Управление данными"]:::main
Rel_big_data["big-data"]:::related -.-> Center
click Rel_big_data "/terms/big-data"
Rel_blockchain_governance["blockchain-governance"]:::related -.-> Center
click Rel_blockchain_governance "/terms/blockchain-governance"
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🧒 Простыми словами
It's like the librarian for a library. They decide where books go, who can borrow them, and how to keep them safe.
🤓 Expert Deep Dive
In modern data mesh architectures, governance is becoming federated and automated ('Policy as Code') rather than centralized.