03 — Visual Memory Map & Framework Atlas
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Use these as redraw-from-memory structures. The relationships matter more than artistic appearance.
Map 1 — Chapter 1 mental skeleton
Business Strategy
↓
Data Strategy
↓
Data Management Program Strategy
↓
Data Management Capabilities
↓
Enterprise Value
Capability groups include:
- Governance / leadership
- Lifecycle management
- Data Quality / Metadata / Security / risk
- Broader Data Management Knowledge Areas
Rebuild: Draw the five-stage chain and add at least four capability groups.
Map 2 — Principles in five memory buckets
1. DATA IS VALUABLE
├─ unique asset properties
└─ economic value
2. BUSINESS / DATA REQUIREMENTS LEAD
├─ Data Quality
├─ Metadata
├─ planning
└─ data requirements drive IT decisions
3. DIVERSE SKILLS + ENTERPRISE PERSPECTIVE
├─ cross-functional
├─ enterprise view
└─ multiple perspectives
4. LIFECYCLE + RISK
├─ lifecycle management
├─ data types differ
└─ data-related risk
5. LEADERSHIP
└─ sustained commitment
These five buckets are a Mastery Lab memory aid, not an official DAMA grouping.
Map 3 — Data lifecycle, lineage and cross-cutting controls
Plan
↓
Create / Obtain
↓
Store / Maintain
↓
Use
↓
Transform / Enhance
↓
Share
↓
Dispose
Use/enhancement can create new data, so the lifecycle may loop.
Across the entire lifecycle:
Data Quality | Metadata Quality | Data Security / Risk
Lineage: the pathway a particular data set follows from origin through movement and transformation to use.
Memory hook: life = stages; line = path.
Map 4 — Strategy to execution artifacts
Business Strategy
↓
Data Strategy
↓
Data Management Program Strategy
↓
┌───────────────┬───────────────────┬───────────────────────────┐
│ Charter │ Scope Statement │ Implementation Roadmap │
│ mandate / why │ what/who/horizon │ how/when │
└───────────────┴───────────────────┴───────────────────────────┘
- Charter: vision, business case, goals, principles, measures, risks, operating intent.
- Scope Statement: planning-horizon objectives and accountable roles/organizations/leaders.
- Roadmap: programs, projects, assignments and milestones.
Map 5 — Framework purpose map
BUSINESS / IT ALIGNMENT
• Strategic Alignment Model (SAM)
• Amsterdam Information Model (AIM)
KNOWLEDGE AREA TAXONOMY
• DAMA Wheel
KNOWLEDGE AREA OPERATING CONTEXT
• Environmental Factors Hexagon
• Knowledge Area Context Diagram
CAPABILITY PROGRESSION / DEPENDENCIES
• Aiken DMBOK Pyramid
• Functional Area Dependencies
LIFECYCLE / FOUNDATION / OVERSIGHT
• Data Management Function Framework
• DAMA Wheel Evolved
One-sentence chooser
- SAM: use when you need four-domain business/IT strategy and infrastructure/process alignment.
- AIM: use when you need Business, Information and IT across Strategy, Tactics/Structure and Operations.
- Wheel: use when you need the 11 Knowledge Areas and Governance's central coordinating role.
- Hexagon: use when you need recurring factors surrounding Knowledge Area work.
- Context Diagram: use when you need one Knowledge Area's detailed operating anatomy.
- Aiken Pyramid: use when you need capability progression/dependencies toward advanced use.
- Functional Dependencies: use when you need upstream foundations for downstream capability.
- Function Framework: use when you need to separate governance oversight, lifecycle work and foundational activities.
- Wheel Evolved: use when you need core, lifecycle/usage and governance relationships concentrically.
Map 6 — How to read a Knowledge Area Context Diagram
Suppliers / Inputs
↓
Activities
↓
Deliverables / Consumers
Activities are classified:
PLAN | CONTROL | DEVELOP | OPERATE
Supporting relationships:
- Participants perform, manage or approve activities.
- Tools and Techniques support the work.
- Metrics evaluate performance, progress, quality, efficiency, improvement or value.
Rebuild: Draw the left-to-right flow, add Participants under Activities, then write Tools/Techniques/Metrics across the bottom.
Map 7 — The 11 DAMA Knowledge Areas
DATA GOVERNANCE
direction + oversight
+ decisions
Data Architecture Data Modeling & Design
Storage & Operations Data Security
Integration & Interop Document & Content
Reference & Master Data DW / Business Intelligence
Metadata Management Data Quality
Governance is central because it coordinates and oversees. The other ten Knowledge Areas remain distinct functions.
Final blank-page challenge
On one blank sheet, reconstruct Chapter 1 using only these seven anchors:
- Data Management definition + business driver
- Five principle memory buckets
- Thirteen challenge themes
- Lifecycle + lineage distinction
- Strategy → Charter / Scope / Roadmap
- Framework purpose map
- 11 Knowledge Areas + Context Diagram structure
If you can rebuild these and explain them in plain language, you have the mental scaffolding Chapter 1 is intended to provide.