Data Quality Framework

Table of Content

• 1. Introduction
  • Executive summary
  • What is Data Quality ?
    • Market case studies
    • Data Observability vs Data Quality
    • Data Quality Investment benchmarks
  • Why a Data Quality Framework ?
  • Intended Audience & Scope
  • How is DQ framework aligned with DG policies?
  • Guiding Principles
  • Key capabilities
  • Data Quality Governance
    • Central Data Office
    • Business Lines Data Office
    • Other roles
  • References
  • Key Terms & Abbreviations
• 2. Prioritization
  • Objectives & Benefits
  • Methodology
  • Standards
  • Tools
  • Progress Monitoring
• 3. Data Profiling
  • Objectives & Benefits
  • Methodology
  • Standards
  • Tools
  • Progress Monitoring
• 4. Controls
  • Objectives & Benefits
  • Methodology
  • Standards
  • Tools
  • Progress Monitoring
• 5. Monitoring
  • Objectives & Benefits
  • Methodology
  • Standards
    • Operational monitoring standards
    • BDO monitoring standards
    • ADO monitoring standards
    • DG Advisory monitoring standards
  • Tools
  • Progress Monitoring
• 6. Remediation
  • Objectives & Benefits
  • Methodology
  • Standards
  • Tools
  • Progress Monitoring
• 7. Sustainability
  • Objectives & Benefits
  • Methodology
  • Standards
  • Tools
  • Progress Monitoring
• 8. Self-Assessment
  • Objectives & Benefits
  • Methodology
  • Standards
    • CEDO self-assessment standards
    • BLDO self-assessment standards
  • Tools
  • Progress Monitoring
• 9. DQF Resource Center
  • 1. Introduction to Data Quality Framework
    • Cost of poor Data Quality
  • 2. Data Quality Governance roles
    • Data Governance roles
      • Central Data Office (CEDO)
      • Business Lines Data Officer (BLDO)
      • Data Owner (DO)
      • Data Steward (DS Tech)
      • Data Consumer
    • Other roles
      • R&D Team
      • Data Quality Analyst
      • Business Process Owner
  • 3. Prioritization
  • 4. Profiling
  • 5. Controls
  • 6. Monitoring
  • 7. Remediation
  • 8. Sustainability
  • 9. Self-Assessment
• 10. Implementation
  • Conceptual model
  • Data Logical model
  • Process
  • Controls
  • Architecture
  • Reports
  • Software architecture