Data Warehouse Build Resource Plan
This is a practical guide to building a resource plan for a data warehouse build project — the people and resources needed, when, and how they are allocated, adapted to the realities of building a central data warehouse for analytics.
What a Resource Plan is
A resource plan is the people and resources needed, when, and how they are allocated. For the full concept and how it works in general, see Resource Planning. 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 resource 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
- Roles and skills needed
- Allocation over time
- Capacity vs demand
- Resource calendar
Data Warehouse Build-specific considerations
Tailor the resource 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 resource 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.