Data migration is more than moving data. Define the scope, validate quality, rehearse the move, cut over to production, and hand operations over as one connected body of work.
Each step overview explains why the stage matters and which risks commonly arise. Use the linked pages to review work, tools, failure patterns, checklists, and deliverable templates.
STEP 1
Objective
Align the migration objective, investment decision, governance, and overall schedule before the project starts.
Goal
Decision makers have approved the objective, success metrics, budget, organization, and key milestones.
View details →STEP 2
Objective
Define the migration scope and data mapping, then design a repeatable runbook.
Goal
Stakeholders have agreed on the data scope, mapping, transformation and exception rules, and runbook.
View details →STEP 3
Objective
Implement the extraction, transformation, loading, and validation processes and prepare the migration environment.
Goal
The migration programs, environment, monitoring, logs, and rerun procedures have been built and reviewed.
View details →STEP 4
Objective
Validate the migration under production-like conditions for quality, duration, business impact, and open issues.
Goal
Results meeting the pass criteria and measured duration are recorded, with remediation approved for open issues.
View details →STEP 5
Objective
Cut over to the new system and load the final data safely according to the approved runbook.
Goal
Cutover, final loading, initial validation, and the go/no-go decision are complete and recorded.
View details →STEP 6
Objective
Confirm integrity and business impact after migration, address incidents, retire the legacy system, and hand over operations.
Goal
Business approval, integrity validation, open-issue handover, and the legacy-system retirement decision are complete.
View details →