Protecto
February 16, 2022
There can be many reasons why you might want to do this, ranging from changing or upgrading servers, moving from an on-premise framework to the cloud, or migrations related to application versions. No matter your needs, data migration is a high-risk project that needs to be planned meticulously.
Let us take an in-depth look at some of the most important facets of the process and how you can structure your plan for the best results. Here are a few critical considerations.
Any data migration must have the right data migration strategy. You want to prevent any corruption of the source data or any incremental amplification of any issues in the source data. You want to prevent missed deadlines, budgets spilling over, or massive downtime that affects important areas of the business. Therefore, data migration needs to be a complete project that merits attention to detail.
Ideally, a solid data migration plan needs to include the following components.
In addition, you should put a lot of thought into your destination platform and figure out a data migration plan that suits your use case. Figure out the right tools for the project, set a reasonable timeline, and then you can proceed with the actual migration.
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Depending on your use cases, one of the two popular approaches might be a good idea. In many cases, businesses use the 'big bang' approach for data migration. This approach requires the company to carry out the complete data migration process to the new platform within a set time window. Then, the data undergoes ETL processing and gets transitioned to its new home, during which time all live systems may face downtime.
The advantages of this method include the fact that the migration can happen quickly, and you can straightaway start to enjoy any benefit you might have from your new data platform. For time-sensitive migrations, this might be the best way forward. On the flip side, the downtime involved can hurt the business. Due to the critical nature of the downtime, the migration can feel rushed, and there can be great pressure on the team. The quality of the migration can also get compromised.
The other approach is the 'trickle' approach. The trickle approach involved dealing with the migration process in small batches. The previous and newly migrated systems run parallel during the migration process. The migration takes place in small increments over an extensive period. There are many benefits to this approach. Since the migration is done in phases, there is no downtime involved. Regular business operations do not need to get interrupted. A gradual migration also lets you test the characteristics and limitations of the new platform for your data and create workflows and workarounds that allow you to make the best use of this new platform. On the flip side, trickle migration can be slow and extremely complex to pull off. You would also not be able to leverage the total benefits of your new data platform until the entire process is complete.
No matter which technique you prefer, it is always good to create a complete backup of the data you are migrating. Then, create a comprehensive strategy, drive it throughout the process, and conduct thorough testing to ensure the migration will go as planned.
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While the steps might vary based on the technique of data migration and the idiosyncrasies of the platforms involved, these general steps tend to be common across all forms of data migration.
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The most important thing with data migration is to understand the high stakes. Data migration is a critical process, and there is little room for error. Any misstep can result in disastrous consequences for your organization. Therefore, it is crucial to have a concrete data migration plan, double-check frequently, and follow the plan down to the last detail while carrying out the migration.
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