Best Practices for Developing a Data Migration Strategy


October 17, 2017

When IT environments purchase new infrastructure, particularly storage, they must migrate their existing data from the old hardware onto the new. To do so require planning and a definitive strategy, and there are a number of factors that can influence how the migration is conducted. Furthermore, there are different kinds of migrations that each require a different approach. Most of this is fairly straightforward, but there are a few pitfalls to avoid and best practices to follow when developing a data migration strategy.


Data Migration Strategy


Project Scoping and Data Discovery

The first step to any IT project is an exploratory planning session. Stake out the goals, requirements, and resources available for your migration project and attempt to anticipate complications that may arise during the migration. Does your team have the skills and experience in the right areas to conduct the migration successfully? Are there any version or format complications that may arise? Leave no stone unturned and map out any data dependencies, permissions, users groups, network configurations, and so on.

For example: when migrating a virtual environment, not all VMs are written in the same format. Microsoft Hyper-V VMs are in VHDX, while VMware VMs are in VMDK format. This will cause a significant issue in the migration.


Choose Your Migration Strategy:


Big Bang

The Big Bang strategy is just what you would expect. It requires the IT team to deploy the new infrastructure and transition data from the old to the new in one fell swoop. This is a useful strategy, because it spares the business from having to run two environments simultaneously, even if for only a short while. That may sound trivial, but it would require the IT department to keep two environments up to date at all times during the transition period.

One of the key drawbacks for this strategy is that you need a window of time where the business can shut down. Typically, most businesses would do this overnight at two or three in the morning when there is the least amount of network activity. Internet businesses and 24 hour service companies don’t have such a window to utilize. In addition, should the migration run long for any business, it risks impacting the normal work day.


Trickle / Incremental Cutover


If one strategy is to migrate everything all at once, the logical alternative is to perform the migration in segments. For some businesses with multiple branches in different geographic areas, the Incremental Strategy will make a lot of sense. You can move over one service or region at a time. This can also be useful if something goes wrong along the way. The IT department can roll back a small portion of the data much more easily. In IT, any strategy that reduces risk for the business is an attractive path to follow, yet it is not without its drawbacks as well.

Businesses are complex, and their applications and data is often a tangle of interdependencies. If you pull one thread, it unravels large portions of the environment. The Project Scoping and Data Discovery phases are critical with this strategy to avoid this exact scenario.


Parallel Migrations

A Parallel Migration can greatly reduce the risk of the migration, but it can be significantly more expensive than other options. In this this strategy, the data is migrated to the new environment, but both systems are run in full with all data kept current. This can be done as a Big Bang or an Incremental migration, and it allows the IT team to verify that everything is migrated successfully before shutting down portions of the old environment.


Pick the Strategy that Makes the Most Sense for You


Of course, every business is going to have factors that influence which strategy makes the most sense. Single-location businesses may find a Big Bang strategy attractive, while sprawling multi-state enterprises may take a different approach, or vice versa. They key is to understand your own environment and anticipate the problems that you may face.

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