2 — Predict First & Build the Data Asset Inventory
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Predict first
Write your answers before detailed analysis. The purpose is to expose your current mental model.
- Which three Meridian data domains do you expect to create the most enterprise value? Why?
- Which three do you expect to create the greatest enterprise risk if poorly managed? Why?
- Which Meridian problem looks most technical at first glance but is actually broader than technology?
- If Elena Park can fund only two Data Management initiatives this quarter, what would you choose now?
- What evidence would make you change those priorities?
Do not fix yet. Preserve these predictions so you can compare them with your later evidence.
Lab A — Build Meridian's Data Asset Inventory
Select at least six assets/domains. Include Customer, Product, and Order, then choose at least three more.
For each asset record:
| Field | What to capture |
|---|---|
| Asset / domain | Business concept, not merely a table name |
| Business process | What creates/uses it |
| Key systems | Where the concept is represented |
| Primary consumers | Who depends on it |
| Value if well managed | Operational, analytical, customer, compliance, or other value |
| Risk if poorly managed | Quality, access, misuse, inconsistency, loss, bad decisions, etc. |
| Metadata/context needed | Definition, identifiers, source, owner, allowed use, grain, timestamps, etc. |
| Criticality | High / Medium / Low with a reason |
Starting context
Customer
Processes: Browse-to-Order; Campaign-to-Engagement; Customer-Issue-to-Resolution
Systems: WEB / CRM / POS / SERV
Consumers: Sales, Service, Marketing, Finance
Metadata/context examples: definition, identifiers, source, owner, allowed uses
Product
Processes: Product-to-Sellable-SKU; Order-to-Fulfillment
Systems: PIM / WEB / OMS / DWH
Consumers: Merchandising, Sales, Fulfillment, BI
Metadata/context examples: SKU meaning, category, lifecycle status, source/owner
Order
Processes: Browse-to-Order; Order-to-Fulfillment
Systems: WEB / OMS / DWH
Consumers: Operations, Finance, Service, BI
Metadata/context examples: grain, status meaning, timestamps, source rules
Decision questions
After completing the inventory, answer:
- Which assets are enterprise assets rather than merely “owned by one application”?
- Where does the same business concept have multiple representations?
- Which assets would be hardest to replace if lost?
- Which assets are easy to copy/share and therefore create control or privacy/security risk?
- Which assets cannot be interpreted correctly without stronger Metadata?
Evidence
Save as CH01-A — Meridian Data Asset Inventory and preserve enough reasoning that another person can understand why you classified each asset the way you did.