Datahandling

Data handling refers to the collection, storage, processing, distribution, and disposal of data across its lifecycle. It encompasses the technical methods used to manage data as well as governance practices that ensure privacy, security, and quality. In computing and information systems, data handling includes entering data, validating and transforming it, storing it in databases or file systems, transmitting it between systems, and producing outputs or reports.

Key components include data collection, data storage, data processing, data sharing, and data retention and deletion. Data pipelines and ETL processes move data from source to target systems, often through cleaning, normalization, and enrichment. Metadata and data lineage document the origin and transformations of data, supporting quality control and reproducibility.

Quality and governance are central to data handling. Data quality dimensions such as accuracy, completeness, validity, consistency, timeliness, and uniqueness are used to assess data. Data integrity and access controls protect against corruption and unauthorized use. Data governance assigns roles like data owner and data steward and establishes policies for data retention, privacy, and compliance with regulations such as GDPR, HIPAA, and industry standards. Privacy-preserving techniques, including anonymization and encryption, may be applied to protect sensitive information.

Risks include data loss, corruption, leakage, and biased or inaccurate analyses. Effective data handling balances utility with protection, enabling reliable decision-making, reproducibility in research, and regulatory compliance.