Data Governance Defines How Organizations Leverage and Manage Data
Data Governance traditionally spans the practices of data quality, data management, data stewardship, and data ownership. With the growing focus on data use, governance may include compliance to data-centric regulations such as BCBS 239, and support for privacy compliance for GDPR and CCPA. In the context of data privacy, governance would include the management of cross border transfers.
With the recent ascent of the Chief Data Officer and the growing utilization of enterprise data, the focus on data governance has increased dramatically. Many organizations have embarked on creating catalogs of critical and personal data to help glean insights on opportunities for innovation and for assessing compliance readiness for privacy.
How are the goals and strategies of data governance determined?
Data governance councils set strategy, direction, and goals for the organization’s data utilization and management. This may be led by a CIO or CDO with participation by LoB leaders, data owners, data stewards, and IT executives responsible for data-centric technologies.
What are the functions of data governance?
- Data quality: ensuring data records are complete and accurate.
- Data management: managing the lifecycle of data and migrating and integrating data for new services and applications.
- Data cataloging: inventorying data assets across the enterprise to enable analytics, quality, and transformation.
- Master data management: consolidating records of customers, products, or services that have multiple instances across enterprise applications (e.g. creating a master record for customers and/or products).
- Data security: data is protected from unauthorized access, use, and transfer.