Data Privacy and Compliance: Adhering to relevant data privacy regulations (e.g., GDPR, CCPA) and industry-specific compliance requirements. This necessitates careful management of personal and sensitive data within databases.
Data Stewardship: Assigning responsibility for specific data assets to individuals or teams who understand the data's meaning, usage, and quality. Data stewards act as guardians of the data within their domain.
Metadata Management: Documenting and managing metadata – data about data. This includes technical metadata (e.g., table schemas, data types) and business metadata (e.g., definitions, business rules), which are crucial for understanding and using data effectively.
Data Lifecycle Management: Managing accurate cleaned numbers list from frist database data from its creation to its eventual archival or deletion, defining policies for retention, backup, and recovery.
Implementing data governance in a database landscape involves several key components:
Organizational Structure: defining roles and responsibilities for data owners, data stewards, and data custodians. This provides the necessary leadership and accountability.
Policies and Standards: Developing clear, documented policies and standards for data definition, data entry, data storage, data access, data sharing, and data retention. These policies serve as the guiding principles for data management.