Data Governance vs. Data Management: : Where They Differ and Why It Matters

The text explores the nuanced distinction between data governance and data management, emphasizing that while they are interconnected, they serve different roles within an organization. Data governance is defined as the strategic framework that outlines policies, roles, and decision rights, essentially setting the standards for what constitutes "good data" and who is responsible for it. In contrast, data management involves the operational execution of these standards, focusing on the lifecycle processes of ingesting, storing, transforming, and maintaining data. The article highlights the importance of distinguishing between these disciplines to prevent directionless management practices and ineffective governance programs. It introduces the concept of data contracts as a bridge between governance and management, enabling governance policies to translate into actionable management tasks while allowing feedback from management to inform governance. The text argues that organizations should focus on establishing a clear boundary between strategy and execution, rather than conflating the two, to ensure efficient and reliable data handling, especially in light of increasing regulatory demands and AI readiness.