Data Warehouse Build Work Breakdown Structure
This is a practical guide to building a work breakdown structure for a data warehouse build project — a deliverable-oriented decomposition of the whole scope into manageable work packages, adapted to the realities of building a central data warehouse for analytics.
What a Work Breakdown Structure is
A work breakdown structure is a deliverable-oriented decomposition of the whole scope into manageable work packages. For the full concept and how it works in general, see Work Breakdown Structure. 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 work breakdown structure 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
- Top-level deliverables
- Sub-deliverables
- Work packages (8–80 hours)
- WBS numbering
- WBS dictionary entries
Data Warehouse Build-specific considerations
Tailor the work breakdown structure 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 work breakdown structure 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.