What is Data Migration? Process, Types, Risks & Best Practices

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A professional-level summary covering key definitions, frameworks, and exam-relevant points.

Data Migration Process Phases

Phase	Activities	Key Risks
Discovery	Data profiling; source documentation; business rule capture	Undocumented data; unknown quality issues
Design	Target schema design; data mapping; transformation rules	Mapping errors; schema mismatches
Extract	Source data extraction; delta capture	Performance impact on source; incomplete extraction
Transform	Cleansing; standardisation; format conversion	Data loss; transformation errors
Load	Target load; constraint checking; error handling	Load failures; referential integrity violations
Validate	Record counts; data quality checks; business rule verification	Undetected errors; incomplete validation
Cutover	Go-live; parallel running; rollback planning	User disruption; data divergence

CDMP Exam Relevance

Data migration is tested in the Data Integration & Interoperability knowledge area (6% of the CDMP exam). Key exam topics include: the types of data migration, the migration process phases, the role of data profiling and data quality in migration success, common migration risks and mitigation strategies, and the difference between big bang migration (all at once) and phased migration (in stages). Data migration is also relevant to Data Architecture and Data Lifecycle Management questions.

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