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5 Steps To Create A Data Migration Strategy

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It requires great skills and knowledge to migrate data. Also will be essential a detailed plan if it is a complex data project. Data migration specialists tend to Leverage technology. They use a particular process to optimize project success and to mitigate risks. There are several stages involved in data migration something you need to be aware of.

Five steps to implement data migration strategy

1. Project Scoping:

Scoping exercise will prove to be useful if you are new to data migration or have unclear project parameters. Before starting of the project, develop a viable plan to establish the project structure’s critical areas. Include some elements stokeholds along with required deliverables, migration expertise, system expertise and business domain knowledge. Also will be essential setting deadlines, budget, reporting requirements and communication plans. Identify own dataset if external provider is hired to operate the project. Get to know the project scale and understand its scope. Review migration thoroughly to ensure functionally correct aspects.

2. Resource evaluation:

To derive well-managed, staged and robust approach towards data migration, there will be essential a clear methodology. Also will be essential cloud-based infrastructure. Proven methodology tends to include project evaluation along with core migration process. Incorporate standards within the project. Problem areas should be identified early on to avoid issues and disappointment at the latter stage. Also consider using ISO standards wherever possible to underpin data migration technology. Evaluate all available migration tools. Is the desired migration tool flexible? You will also require people with the right skills to manage the complex project.

3. Migration Design:

Migration design data migration strategy

It involves verification, extraction as well as conversion of data. Data migration and Landscape Analysis. Performing this task using cloud-based infrastructure allows uninterrupted data flow during migration. The latter depends upon key artifacts available during this stage. Migration design is to include how extraction, verification and storing are to be done of data. How data is to be loaded within the new system, mapping rules, action schedule to go live and recovery plans.

4. Testing Design:

This particular stage helps Leverage technology. It rather defines test plan to be conducted for all migration stages. Initial overview is to evaluate tools, constraints faced, structures, and reporting testing. Generally, overview includes how to test each stage at unit level. It needs to be followed by testing of whole migration right from scratch to finish. This ensures accurate data flow. Test groups are defined with unit test specifications. It comprises of individual tests meant for that specific migration area. Each test is to be then broken into component steps. It includes description as well as expected results.

5. Development and Execution:

An appropriate methodology is generally is used in different stages to create data migration project. Also is carried out Landscape Analysis. It has achieved significant success in those migrations involving several stakeholders. You may even adopt the Agile approach that other teams can view it clearly. It ensures risks get mitigated before it develops into major problems. Moreover, test data is offered much early during the process. Test framework should be developed to run test on a regular basis to unit level. It helps highlight all potential issues. Then perform dry runs to test go-live strategy. It enables proper adjustment of go-live plans. Once ready for going live, implement migration during weekend. Doing so help reduce work related issues of the organization. Otherwise, run concurrently both new/old systems to transfer data piece-by-piece. Parallel migration will be a better choice if business objectives permit. It helps enhance timescales and budgets. At the same time, the team will be able to address all issues as and when it occurs, experiencing minimal disruption.

Following the above steps will ensure coming out with proper data migration strategy to deliver the project successfully involving minimum risk.

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