Data Integrity
Data integrity garante que os dados sejam precisos, completos e consistentes ao longo do tempo, permanecendo confiáveis e protegidos contra modificação ou exclusão não autorizada.
Data integrity é a disciplina de preservar a precisão, completude e consistência dos dados em todas as fases do seu ciclo de vida. Abrange técnicas e controles que previnem, detectam e corrigem modificações não autorizadas, corrupção ou perda de dados. Mecanismos principais incluem: data validation e schema/constraint enforcement para prevenir estados inválidos; preservação de referential, entity e domain integrity para manter relacionamentos corretos e valores válidos; checksums, cryptographic hashes e digital signatures para detectar tampering; immutable storage, versioning e audit trails para permitir rastreabilidade e recuperação; data cleansing, reconciliation e anomaly detection para lidar com inconsistências; e robustos processos de access control, authentication, authorization e change management. Enquanto a criptografia protege a confidencialidade, a data integrity é primariamente alcançada através de hashing, signatures, validation e processos de mudança controlados. A integridade é avaliada através de métricas como validation success rates e error rates em data pipelines.
graph LR
Center["Data Integrity"]:::main
Rel_data_recovery["data-recovery"]:::related -.-> Center
click Rel_data_recovery "/terms/data-recovery"
Rel_data_obfuscation["data-obfuscation"]:::related -.-> Center
click Rel_data_obfuscation "/terms/data-obfuscation"
Rel_data_replication["data-replication"]:::related -.-> Center
click Rel_data_replication "/terms/data-replication"
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❓ Perguntas frequentes
What is data integrity?
Data integrity is the accuracy, completeness, and consistency of data throughout its lifecycle, ensuring trustworthiness.
What are the main types of data integrity?
Entity integrity (unique row keys), domain integrity (valid values), referential integrity (valid relationships), and transactional integrity (atomic operations).
How do you ensure data integrity?
Through validation, constraints, checksums, hashes, digital signatures, versioning, auditing, and controlled change management.
Is encryption part of data integrity?
Encryption protects confidentiality. Integrity relies on hashing and signatures; authenticated encryption can provide integrity guarantees when used appropriately.
What are common threats to data integrity?
Unauthorized modifications, data corruption, software bugs, data integration mistakes, and malware; mitigations include access controls, validation, and monitoring.
How does data integrity relate to data quality and security?
Data integrity is a core dimension of data quality and is essential for reliable security; they address different risk aspects but are interrelated.