Data Migration Quality Plan
This is a practical guide to building a quality plan for a data migration project — how quality will be planned, assured and controlled, adapted to the realities of moving data from legacy systems into a new platform.
What a Quality Plan is
A quality plan is how quality will be planned, assured and controlled. For the full concept and how it works in general, see Quality Management Plan. On a data migration project it plays the same role, tuned to this kind of work.
Why it matters for a Data Migration project
Data Migration projects live or die on moving data from legacy systems into a new platform. A well-built quality 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 migration projects drift into avoidable delay and cost.
What to include
- Quality standards
- Quality metrics
- QA activities
- QC / inspection approach
Data Migration-specific considerations
Tailor the quality plan to the risks that most often derail data migration projects:
- Data quality and lineage
- Field mapping errors
- Reconciliation and cutover
Example
On a real data migration project, the quality plan would be shaped by moving data from legacy systems into a new platform. In particular, it should explicitly account for the project’s biggest risks — data quality and lineage, field mapping errors, reconciliation and cutover — rather than treating them as afterthoughts.