bkjohn2018 Data Management Foundations
When to Use
- Establishing or resetting enterprise data management scope.
- Defining how governance, architecture, quality, metadata, and security connect.
- Building a phased data management roadmap and target operating model.
DMBOK Knowledge Areas Anchor
Use these anchors to organize recommendations:
- Data Governance
- Data Architecture
- Data Modeling and Design
- Data Storage and Operations
- Data Security
- Data Integration and Interoperability
- Reference and Master Data
- Data Warehousing and BI
- Metadata Management
- Data Quality Management
- Data Management Maturity Assessment
Workflow
- Define business drivers and data management outcomes.
- Assess current-state capabilities and pain points by knowledge area.
- Define target operating model (owners, stewards, councils, controls).
- Prioritize initiatives by risk, value, and feasibility.
- Build a phased roadmap with metrics and governance checkpoints.
Output Template
# Data Management Foundation Blueprint
## Business drivers
- ...
## Current-state assessment
| Knowledge area | Current capability | Risk | Priority |
|---|---|---|---|
## Target operating model
- Governance structure:
- Key roles:
- Core controls:
## 12-month roadmap
- Quarter 1:
- Quarter 2:
- Quarter 3:
- Quarter 4:
## Success metrics
- ...
Quality Checklist
- Recommendations map to explicit DMBOK knowledge areas.
- Roles distinguish accountability from stewardship.
- Roadmap balances quick wins and structural fixes.
- Success metrics measure business value and control effectiveness.