What is data migration?
Data migration is the process of moving data from one system, storage location, or format to another, typically as part of a system upgrade, platform change, or consolidation effort.
Understanding data migration
Data migration is a one-time (or infrequent) transfer of data between systems. Common scenarios include:
- Platform migration: Moving from one SaaS product to a competitor - System upgrade: Migrating to a new version of your database or application - Consolidation: Merging data from multiple systems into one - Cloud migration: Moving from on-premise to cloud infrastructure
Data migration projects are notoriously risky. Studies show 38% of data migration projects go over budget, and 83% experience issues. The challenges include data quality problems, schema mismatches, downtime requirements, and validation complexity.
Successful migrations require careful planning, data mapping, validation at every stage, and rollback capabilities.
Key points
One-time transfer of data between systems
Common during platform changes, upgrades, or consolidation
High-risk: 83% of projects experience issues
Requires careful planning and validation
Should include rollback capabilities
Frequently asked questions
What is the difference between data migration and data integration?
Data migration is typically a one-time move of data from one system to another. Data integration is an ongoing process of keeping data synchronized between multiple systems.
What are the biggest risks in data migration?
Key risks include: data loss, data corruption, extended downtime, schema mismatches, performance issues with large datasets, and incomplete validation leading to bad data in the new system.
How do I validate data during migration?
Validate at multiple stages: before migration (source data quality), during migration (transformation correctness), and after migration (data integrity in target). Use checksums, row counts, and sample comparisons.