Introduction to Data Governance
Data Governance (DG) refers to exercising authority and control over managing data assets, involving planning, monitoring, and enforcement. Implementing a formal DG program helps organizations gain more excellent value from data by ensuring proper management according to policies and best practices.
Key Goals and Principles
The primary goals of DG are to manage data as a valuable asset, define and communicate data management principles, and monitor compliance. A successful DG program must be sustainable, embedded within organizational processes, and measurable. Leadership commitment and alignment with business strategy are crucial for its success.
Implementing a Data Governance Program
DG programs typically start by defining a strategy that includes a charter, an operating framework, an implementation roadmap, and a plan for sustained success. Assessing readiness, performing discovery, and aligning business is essential to tailor the DG strategy to organizational needs.
Developing Policies and Procedures
Organizations need to establish clear data policies, standards, and procedures that define the rules for data management. Developing a comprehensive business glossary and coordinating with architecture groups are critical to ensure consistent terminology and alignment with the enterprise data model.
Sponsoring Data Management Projects
Underwriting and coordinating data management projects, such as Master Data Management (MDM), are vital for improving data management practices. These initiatives often require cross-functional sponsorship and alignment with overall business strategy.
Engaging Change Management
Organizational Change Management (OCM) drives the cultural and behavioural changes necessary for DG success. Effective communication, continuous training, and strong leadership support are critical components of OCM.
Issue Management and Regulatory Compliance
DG programs must include robust issue management processes and ensure regulatory compliance. The DG team’s ongoing responsibilities include identifying, prioritizing, and resolving data-related issues and monitoring compliance with relevant regulations.
Tools and Techniques
While DG is fundamentally about organizational behaviour, specific tools can support its processes. These include online presence via websites, business glossary tools, workflow management tools, document management tools, and data governance scorecards. These tools help manage DG activities and measure their effectiveness.
By highlighting these aspects, the article underscores the significance of a structured, comprehensive approach to data governance. This approach ensures that large firms and institutions can maximize the value of their data assets while maintaining compliance and operational efficiency.
Resource
DAMA-DMBOK2 Data Management Framework Chapter 3
