Program Mission, Learning Architecture & Lab Types
Program mission
Create durable CDMP understanding by repeatedly converting theory into observable work. The applied lab must prevent both shallow recognition and blind tutorial-following; conceptual explanation and practical evidence are both required.
Learning architecture
| Layer | Question it answers | Primary outputs |
|---|---|---|
| DMBOK Mastery Lab | What does DAMA mean? What must I distinguish and retrieve? | Guides, maps, Battle Cards, scenarios, MCQs, recall. |
| Technology Training & Competency Roadmap | Can I use the underlying tools without copying blindly? | Competency roadmap, target depth, readiness gates, learner-selected training; lab scripts are scaffolding, not technology training. |
| Meridian Casebook | What company am I managing and why does the data exist? | Processes, systems, domains, roles, defects, incidents. |
| Chapter Applied Labs | Can I make this chapter concept happen in a real environment? | SQL/Python, diagrams, policies, registers, decisions, metrics. |
| Cross-Chapter Capstones | Can I reason when several Knowledge Areas are simultaneously relevant? | Integrated investigations and staged remediation. |
| Evidence & Journal | Can I prove and explain what I did? | Screenshots, artifacts, reflections, before/after results. |
Lab types
| Lab type | Best for | Examples |
|---|---|---|
| Technical build | Concepts clearer when an object is created. | Model → PostgreSQL schema; warehouse star schema; roles/views. |
| Diagnostic / break-it | Concepts whose importance is felt when something fails. | Orphan rows, broken source format, wrong access, duplicate masters. |
| Management artifact | Concepts expressed through decisions, accountability, documented rules. | Governance charter, retention schedule, maturity assessment. |
| Decision / dilemma | Concepts where judgment matters more than code. | Ethics, governance escalation, change resistance. |
| Observation / trace | Relationships, movement, context. | Architecture, lineage, Metadata, source-to-target mapping. |
| Cross-domain incident | Several Knowledge Areas must coordinate. | Untraceable KPI, Customer 360 conflict, sensitive-data exposure. |
Lab-design rule
Do not force every chapter into code. Choose the medium that makes the DMBOK concept concrete with the least unnecessary technology.
Source boundary
DMBOK concept scope for Chapters 1–17 is controlled by Main 00A and the relevant DMBOK source PDF. Meridian scenarios, software selections, schemas, and synthetic datasets are instructional implementation designs; they are not DAMA-prescribed architectures.
Related links
Source: Applied Laboratory Master Program Guide, Sections 1–3.