An effective data stewardship community elevates a Data Governance Program with a lens for proactive collaboration and striving for continuous improvement. Some key aspects include:
Data Collaboration: Foster collaboration between data stewards, data owners, and data users to facilitate data-informed-decision-making.
Continuous Improvement: Regularly review and refine data stewardship practices based on feedback and changing business needs.
Data Training and Awareness: Train data users to understand the importance of data governance and their roles in maintaining data quality.
Data Documentation: Maintain comprehensive metadata and data dictionaries to document data lineage, definitions, and usage, aiding in data understanding.
Data Access Control: Implement and manage access controls and permissions to ensure that only authorized users have access to specific data.
Data Privacy Compliance: Ensure compliance with data privacy regulations by applying proper data masking, anonymization, or encryption techniques.
Data Lifecycle Management: Oversee the entire data lifecycle, from data creation to archiving and disposal, ensuring data is retained and deleted as per policies.
Data Auditing and Monitoring: Continuously monitor and audit data to identify and rectify issues and track changes and access.
Data Quality Metrics: Define and measure key data quality metrics to track improvements and identify areas that need attention.
Data Classification: Categorize data based on sensitivity and importance, allowing data stewards to apply appropriate security measures and access controls.
Change Management: Adapt to evolving data governance requirements and technologies, ensuring data stewardship practices remain effective.
Communication: Communicate effectively with various stakeholders to align data stewardship efforts with organizational goals and strategies.