Data Warehouse Build Test Plan
This is a practical guide to building a test plan for a data warehouse build project — the approach, scope and schedule for testing the deliverables, adapted to the realities of building a central data warehouse for analytics.
What a Test Plan is
A test plan is the approach, scope and schedule for testing the deliverables. For the full concept and how it works in general, see Test Plan. On a data warehouse build project it plays the same role, tuned to this kind of work.
Why it matters for a Data Warehouse Build project
Data Warehouse Build projects live or die on building a central data warehouse for analytics. A well-built test plan gives the team a shared, explicit reference for exactly that — reducing ambiguity, aligning stakeholders, and making problems visible early enough to act. Skipping it, or doing it generically, is how data warehouse build projects drift into avoidable delay and cost.
What to include
- Test scope and objectives
- Test cases/scenarios
- Environments
- Entry/exit criteria
- Defect management
Data Warehouse Build-specific considerations
Tailor the test plan to the risks that most often derail data warehouse build projects:
- Source-system integration
- Data modelling decisions
- Governance and access control
Example
On a real data warehouse build project, the test plan would be shaped by building a central data warehouse for analytics. In particular, it should explicitly account for the project’s biggest risks — source-system integration, data modelling decisions, governance and access control — rather than treating them as afterthoughts.