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What is Data Migration?
Data migration is a process performed for the purpose of moving data between different environments. Data can be migrated across cloud vendors, storage tiers, computer systems, and data center locations.
Organizations migrate data for a number of reasons. For example, you can shift data from one cloud vendor to another, and gain different capabilities. You can move data from warm storage to cold storage tiers, to reduce costs. Additionally, you can shift data from on-premise data centers to cloud environments, and gain access to managed services.
This is part of our series of articles about data management .
In this article, you will learn:
- What is Data Migration?
- Types of Data Migration
- Data Migration Challenges
- Data Migration Best Practices
Types of Data Migration
Here are four common types of data migration:
- Storage migration—involves moving storage blocks and files between storage systems. During this process, you can identify corrupt and obsolete data and remediate storage inefficiencies.
- Database migration—involves moving a database between vendors, upgrading database software, or moving a database from on-premise data centers to the cloud. During this process, underlying data changes may occur and impact the application layer.
- Application migration—involves moving applications between vendors or platforms. During this process, the application typically needs to undergo changes that ensure all components are compatible with the new environment. This typically requires the use of middleware solutions, which help closing technology gaps.
- Cloud migration—involves moving data from on-premise data centers to cloud environments or moving data between cloud vendors. During this process, data schemas may need to be changed to ensure compatibility.
Data Migration Challenges
Data migration is an important process that requires careful planning and consideration, to ensure business continuity during the process and avoid data loss. Here are key challenges to consider before migrating your data:
- Confusion and disorganization—data is a critical component that should be properly managed. Migration processes are complex and require careful planning. A solid plan can help prevent data loss or incompatibility issues, and ensure continuity during disasters.
- Data loss—data should be inventoried, categorized, organized, and prioritized before it is migrated. Prioritizing data helps you determine which data should be backed up for recovery purposes, and what is the scope of damage if certain data is lost. You can then set an appropriate backup and recovery strategy for the migration process.
- Compatibility issues—each environment comes with its own set of requirements. In some cases, the compatibility between environments matches and enables you to simply lift and shift your data. In other cases, you might need to re-architect your systems before migrating them to a new environment.
- Hardware challenges—different environments come with different capacity. Before migrating, you need to properly determine the changes in capacity, and ensure that the hardware utilization of the new environment meets your system requirements. Otherwise, you might incur overhead in capacity fees or experience failures.
Related content: read our guide to data classification (coming soon)
Data Migration Best Practices
Here are key best practices to help you successfully migrate data:
- Backup your data—data migration is a complex process and issues may occur during any stage. To prevent data loss, you should create a backup and recovery plan that maintains copies of your data before, during and after the migration process.
- Verify data complexity and quality—before migrating data, you should assess it for complexity and quality. Complex data that require modification should be properly edited or otherwise kept in its current location. Once you decide which data to migrate, you should clean, organize, and prepare it for compatibility with the new location.
- Create a data migration strategy—there are several data migration strategies that are useful for different purposes. For example, the “big bang” migration strategy can help you migrate all data within a specific period of time. A “trickle” strategy, on the other hand, migrates data in stages to ensure there is no downtime during the process.
- Choose the right data migration tools—a data migration tool can help you move data quickly and efficiently. There are many tools available. Some tools offer dedicated capabilities, like data profiling and discovery. Other products offer end-to-end migration solutions. After creating a migration plan, choose the tools relevant to your implementation.
- Implement a risk management strategy—list all the issues that may occur during the migration process and then define proper measures to mitigate and prevent disasters. Consider security issues, application dependencies, and user testing when creating your risk management strategy.