6 steps of a real-time data migration plan

Have a good data migration plan avoiding headaches in the IT department is essential. Without a carefully prepared and executed real-time data migration plan, migration can involve too much downtime. with the consequent loss of income.

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Many companies already use mobile applications or a web portal to carry out daily tasks, hence It is essential that data is consistent across all channels and available in real time..

Despite this, based on IDC data, “only the 60% of data migrations are completed on time”. One of the main reasons for migration delays is that there is no reliable data migration plan that contains detailed analysis of existing infrastructure to understand nuances and drill down into potential issues. If companies had a real-time data migration plan, they would have a great understanding of the complexities that may be encountered and could plan any action prior to the migration procedure.

How to create a real-time data migration plan?

To catch up with the current needs of your organization, must continue the following 6 Steps, ensuring a consistent data migration plan in real time:

1. Planning: define what is feasible and what is not, based on what data sources support and what is reasonable. Once the scope has been determined, you can continue with the data migration plan, setting deadline and specifying available resources and budget, taking into account that material and time costs will need to be included in these calculations to audit and profile data, develop mapping specifications, write migration code, build data cleansing and transformation rules, and load and test data. To reduce the complexity of the project, it is essential to try to migrate the least amount of data necessary to run the target system efficiently. The selection of the data to extract, transform and upload should be done in collaboration with the data owners, since These business users have a better understanding of business circumstances and their current and future data needs.. Y, after all, they are the ones who will be directly affected by the immigration procedure.
2. Analysis of data: before migrating, you must understand your data, prioritize down and determine goals. Each type of data involved in a migration is related to a cost and a benefit. The more data is migrated, the higher the total cost of the project, so it will be necessary to make strict decisions about the level of source information to include or exclude from the migration package. Historical data, as an example, can greatly inflate project costs, so it may be convenient to leave them out of the migration plan.
3. Project design: obtained the results of the data audit, it is feasible to develop a series of rules that allow the transfer of all designated source data and guarantee its adequate transformation to guarantee compliance with what is marked in the plan's objectives. It is necessary to develop mapping specifications and, once they have been converted to migration code, must be independently verified against the rules. This procedure will help identify errors in test environments. Y, therefore, simplify the key decision-making process for the implementation of migrated data. For this, ETL tools compatible with data quality tools can be used.
4. Execution: It is time for what was established in the data migration plan to be transformed into specific actions. Data is extracted from the source system, they transform, are cleaned and uploaded to the target system, applying migration rules.
5. Tests: unit testing, systems, volumes, Online applications and batches must be completed before the company can finalize the project.. It is advisable not to wait for the end and to start the tests before the main milestones.
6. Monitoring: continuous use of data quality tools helps preserve and maintain data quality., that simplifies future migrations and benefits the organization's ongoing operations.