Overview
Purpose: Understand the full lifecycle from requirements to reporting.
Who this page is for
| Audience | Why it matters to you |
|---|---|
| Product managers | Drive requirements |
| Implementers | Understand workflow |
EA · Delivery Lifecycle
Enterprise Analytics requires a disciplined workflow from business question to live reporting.
The lifecycle
- Business Requirements (Stakeholder input)
- Measurement Plan (Define metrics and segments)
- Solution Design Reference (SDR) (Implementation spec)
- Naming Conventions (Variable naming)
- Implementation (Build the code)
- QA & Validation (Test everything)
- Go-live (Deploy to production)
- Reconciliation (Verify accuracy)
Why follow this lifecycle?
Risk: Skip steps, break production data Benefit: Organized rollout, stakeholder alignment, quality data
Phase 1: Requirements
Question: "What do we need to measure?"
Deliverables:
- Business requirements document
- Success metrics
- Stakeholder sign-off
Owners: Product, Business, Analytics
Phase 2-3: Design
Question: "How will we measure it?"
Deliverables:
- Measurement plan (dimensions, metrics, segments)
- SDR (technical spec)
- Naming conventions (prop/eVar naming)
Owners: Analytics, Architects
Phase 4-5: Build
Question: "Build it"
Deliverables:
- Implementation code
- Data layer spec
- QA test cases
Owners: Developers
Phase 6-8: Launch
Question: "Does it work?"
Deliverables:
- QA sign-off
- Go-live plan
- Reconciliation report
Owners: QA, Analytics, Product
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Next: Writing business requirements