Data Projects

Data Projects focus on delivering data platforms, pipelines and analytics that the business can trust.

What makes these projects distinctive

Data Projects carry their own signature challenges. The ones that most often decide success or failure are data quality and lineage, source-system integration, governance and access control — so the plan should be built around managing exactly these.

Typical phases

1. Initiation — business case and charter
2. Planning — scope, schedule, budget, risks
3. Execution — building the deliverables
4. Monitoring & control — tracking against baseline
5. Closure — acceptance, handover, lessons learned

Sample WBS outline

• Initiation & business case
• Planning (scope, schedule, budget)
• Requirements & data model
• Pipelines & integration
• Quality & governance
• Reporting/analytics
• Handover
• Testing / quality assurance
• Deployment / handover
• Closure & lessons learned

Key deliverables

• Requirements & data model
• Pipelines & integration
• Quality & governance
• Reporting/analytics
• Handover

Top risks to plan for

• Data quality and lineage
• Source-system integration
• Governance and access control

Key roles

Typical duration

3–9 months, depending on scale and complexity.