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Effective data management is essential for ensuring the quality, security, and usability of assessment data throughout the project lifecycle. Proper data management practices support reliable analysis, protect respondent privacy, and facilitate knowledge sharing within WFP and with partners.
Key Components of Data Management
Data Storage and Security: Store all data securely, using approved platforms and protocols. Limit access to authorized personnel and regularly back up datasets to prevent loss
Data Organization and Documentation: Maintain clear, consistent file naming conventions and folder structures. Use metadata and data dictionaries to document variables, coding, and changes throughout the process
Data Cleaning and Quality Assurance: Apply corporate systematic data cleaning procedures to identify and correct errors, standardize formats, and ensure completeness
Data Protection and Privacy: Adhere to WFP’s personal data protection and privacy standards, including anonymization and secure sharing practices
Version Control and Archiving: Track changes to datasets and maintain version histories. Archive final datasets and related documentation for future reference and audits
Data Sharing and Dissemination: Share cleaned and anonymized datasets with relevant stakeholders, following WFP protocols and data sharing agreements