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One of the most common objectives for data migration that I see today among companies I work with is saving money . It often happens that businesses have been relying on licensed products to host their data , but after evaluating open source options they ’ ve decided that a free and open source alternative will allow them to meet their data needs at a lower cost .
You might need to invest a little more effort in management if you opt for an open source solution – but that work is often worth it for businesses looking to streamline data platform costs . migration as well . You might want to redeploy your applications using containers , for example , but because you store your data in a legacy platform that was not designed for cloud-native environments , you choose to migrate it so it integrates more seamlessly with your modernized application stack .
Taking the pain out of data migration
Again , determining why to migrate data is often the easy part . Figuring out how to do it is where things get tricky .
If you ’ re tied to a specific data platform , you may be wed to a particular vendor ’ s infrastructure or product ecosystem – this can make it hard to adopt a multicloud strategy . But if you migrate data to an open source , vendor-agnostic platform , it becomes easier to deploy workloads wherever you need .
A general goal of modernizing architectures and environments can become the motivator for data
So , how do you migrate your data without disrupting your business and depriving yourself of revenue ?
The answer is to approach data migration in a coherent , systematic way by following these steps .
Data assessment . Start by assessing the requirements that your data platform needs to support , then determining which configuration you ’ ll
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