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Data migration is the process of transferring data between computer storage systems. Data migration is holistic: selection, preparation, extraction, and transformation of your data all take place prior to transferring it to the new system. After transfer, migration concludes with the validation of migrated data, and the decommissioning of the old storage infrastructure.
An enterprise may want to migrate their data in order to:
- increase their data storage capacity or flexibility;
- move from one database vendor to another;
- upgrade an existing database's software or dependencies;
- address performance issues;
- implement disaster recovery;
- reduce the physical footprint of their data centers;
- relocate their data centers;
- adopt a new technology.
As a key part of system implementation, data migration is, when possible, automated in order to free up human resources for more strategic tasks.
The planning phase involves analyzing current and future storage environments and dependencies, while eliciting requirements, and creating tools and procedures to support the migration.
A plan is developed that does the following:
- defines the data and method of migration;
- assesses risk and impacts, and accounts for potential issues;
- documents new hardware and software architecture to be used;
- describes your migration and verification procedures;
- envisions a test plan for validating the migrations completeness.
In parallel with the plan, a team will typically create automated tools and scripts to support the migration and validation procedures.
Your migration phase will have your team using your tools and scripts to move your data to the new environment. Finally, your post-migration phase emcompasses running your validation scripts to ensure migration completeness.
When something doesn't work correctly during your migration process, it may be necessary to run your process iteratively, instead of in a single pass. This can make the validation phase more challenging as a result.
You will need to do root-cause analysis at each step to identify what's not working correctly, then restart the process.
Your legacy system may contain redundant or obsolete data, or there may be schema mismatches between your legacy and future systems. You may even experience hardware and software dependencies or version mismatches during your shift to the new system.
This isn't a comprehensive list — each migration has its own challenges — but it should give you a taste of what to expect.
While data migration can be daunting, Alooma's experts are here to help! We support the widest possible range of source formats and data destinations with low latency, massive scalability, and unparalleled accuracy.
Alooma can take the guesswork out of planning, execution, and validating your data migration, saving you time, money and trips back to the drawing board.