Data Governance Framework
A comprehensive framework for managing data as a strategic enterprise asset with accountability, quality, and compliance
Data Governance Framework
A comprehensive framework for managing data as a strategic enterprise asset with accountability, quality, and compliance
WHAT IS IT?
Data Governance is the system of decision rights and accountabilities for data-related processes, executed according to agreed-upon models.
- Policies, standards, and procedures
- Roles and responsibilities matrix
- Data quality management
- Regulatory compliance framework
WHY IS IT IMPORTANT?
Without governance, organizations face data chaos, compliance risks, and poor decisions. Gartner reports that poor data quality costs organizations an average of $12.9 million annually.
- GDPR, CCPA, HIPAA compliance
- Trust in analytics and AI models
- Reduced data breach risks
- Faster time to data insights
HOW DOES IT WORK?
Governance operates through a federated model with central coordination. A Data Governance Council sets policies, Data Owners define rules, Data Stewards enforce standards.
- Policy definition and enforcement
- Automated quality monitoring
- Access control and audit trails
- Continuous improvement cycles
Data Governance Reference Architecture
Multi-layered governance framework with people, process, and technology integration
Core Components
Data Strategy
Aligned business objectives with data initiatives
Master Data Management
Single source of truth for critical data
Data Quality
Accuracy, completeness, consistency
Information Lifecycle
Data retention and archival policies
Metadata Management
Context and lineage tracking
Data Security
Access control and protection
2024-2025 Governance Trends
AI Governance & Ethics
Frameworks for responsible AI, model governance, bias detection, and explainability requirements
Data Contracts & Products
Formal SLAs between data producers and consumers with automated quality guarantees
Automated Policy Enforcement
Real-time policy engines that automatically enforce governance rules at query time
Business Value
DaasLabs Governance Implementation Approach
Assess Current State
Evaluate existing policies, identify gaps, benchmark against industry standards
Design Framework
Define policies, roles, processes, and tool requirements aligned to business goals
Implement Controls
Deploy governance tools, train stewards, establish monitoring dashboards
Operationalize & Mature
Run governance councils, measure KPIs, continuously improve based on feedback
Ready to Implement Data Governance?
Schedule a consultation to discuss how our governance framework can improve your data quality and compliance.