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Course Outline
- Data Quality Governance
- Alignment of Data Quality Governance with the DAMA DMBoK Framework
- Strategic Objectives and Operational Drivers for Data Quality Governance
- Foundations of Data Quality
- Core Principles and Definitions
- Definition of Data Quality Governance
- Operational Contexts for Data Quality Management
- Consequences of Inaccurate Data Assets
- Comprehensive Knowledge Base for Data Quality Governance
- Strategic Approach to Data Quality Governance
- Framework for Enhancing Data Integrity
- Data Profiling and Measurement Methodologies
- Metrics for Evaluating Data Quality
- Evaluating Data Integrity Through Profiling
- Standard Outputs from Data Quality Profiling
- Validation-Based Monitoring Protocols
- Integrating Data Quality Monitoring Within the DQM Framework
- Implementation Tools and Techniques
- Distinguishing High-Quality from Low-Quality Data
- Data Quality Dimensions (per DMBoK)
- Strategies for Achieving Data Accuracy
- Principles of Data Correction
- Processes for Data Cleansing
- Determining Acceptable Levels of Data Quality
- Addressing Systemic Issues Beyond Data Correction
- Operational Impact and Quality Dimensions
- Economic and Operational Implications for Agency Mission
- Key Dimensions of Data Quality
- Data Quality Facets (DMBoK)
- DMBoK Defined Dimensions of Data Quality
- Application of Data Quality Dimensions in Federal Operations
- Regulatory and Policy Requirements for Data Quality
- The Relationship Between Data Governance and Data Quality
- Measurement Methodologies for Data Quality
- Strategies for Achieving Data Accuracy
- Attributes of Data Quality Indicators (DQI)
- Software Tools: Essential Functional DQ Capabilities
- Root Cause Analysis Methodologies
- Identifying Root Causes and Implementing Remediation Strategies
- Definition of Root Cause Analysis
- Contributory Factors in Root Cause Analysis
- The Root Cause Analysis Process for Government Applications
- Strategic Approaches, Assessments, and Roadmaps
- The 5-Why Analytical Method
- Application of Theory of Constraints
- Frequently Encountered Data Quality Errors
- Fiscal Implications of Data Quality Initiatives
- Developing a Data Quality Strategic Roadmap for government initiatives
- Overall Maturity Assessment of Data Quality Capabilities
- Summary and Conclusions
- Primary Takeaways
Requirements
Fundamental Principles of the CDMP Framework for government agencies
21 Hours
Testimonials (2)
The variety of the information shared and the clarity to explain terms in plain English.
Arisbe Mendoza - Fairtrade International
Course - GDPR Workshop
It's a hands-on session.