Data administration
Data administration
(also data security management)
Data administration definition
Data administration refers to managing an organization’s data to ensure reliability, usefulness, and consistency. Various stakeholders across the organization, including IT, business units, and legal and compliance teams, can contribute to data administration. Key responsibilities include data modeling, database management, governance, security, and quality management. Effective data administration enables informed decision-making and ensures compliance with applicable regulations and standards. Data administration also helps organizations respond quickly to data security risks, such as data breaches, data loss, data theft, and other malicious activities.
See also: access control entry, endpoint security
Data administration strategies
- Data governance. Establishing a formal framework ensures that the organization consistently and effectively manages data. The framework includes policies and procedures for data quality, security, privacy, and lifecycle management.
- Data modeling. Designing and creating data models helps the company structure and effectively organize data for its needs. It also helps detect potential data quality issues and facilitates establishing relationships between different data entities.
- Data integration. Combining data from various sources and systems helps the organization create a comprehensive and accurate view of its data assets.
- Master data management. MDM helps ensure data consistency across the organization and can help improve data quality.
- Data security. Implementing security measures helps the organization protect data from unauthorized access, theft, or loss. It includes establishing access controls, encryption, and data backup and recovery procedures.
- Data quality management. Establishing data quality standards, monitoring data quality metrics, and implementing processes to identify and correct data quality issues, ensures the data is accurate, complete, and consistent across the organization.