Throughout my professional career, I have found the need to place a special focus on data migration with the release changes of the systems that I managed.
The main objective of data migration is to have available the data that the system currently has in the new version. Additionally, the system must operate correctly with the migrated data.
Find out 10 AWS Cloud Migration tools companies need to conduct migration assessment, develop a plan, implement it, and manage it.
The importance of defining data migration as an essential milestone in a project originated from the need to ensure the integrity and operability in the company to:
- Inform national Government areas of the affiliate data of the clients. If we don’t comply with this requirement, we could receive a financial penalty fee or a criminal case.
- Guarantee the service provisioning processes once the systems update is performed.
- Guarantee the provision of the services.
- Guarantee the correct association of the charges generated by the use of the networks with the data of the customer’s billing accounts.
- Generate the record of the data transformation generated and preserve the evidence of the tests carried out on the system.
- Have the approval of the owner of the system on the data transformation carried out.
A data migration consists of moving data from a software solution installed on a customer to a new version through a process that includes extraction, transformation and loading into the new database.
Whatever the size of the database, the migration must be approached as a project in itself, which has its own life cycle (iterative and incremental) and a detailed work plan with an objective and a previously defined scope and in which each of the activities to be carried out is planned.
Data migration objectives
- Provide a detail of the tasks to be executed to transform the data from version A to version B, taking into account the documentation carried out by the product.
- Specify the necessary skills and knowledge that the work team must have to face a project of this type.
- Present the documents that must be prepared in each of the stages of the process.
Scope
- For data migration success, it must be carried out through a methodology that includes all the necessary activities to bring existing data in legacy systems to the new system.
These activities can be summarized as:
- Discovery: understand what data is available, the relationships between them, and the relevant data to migrate.
- Profiling: measuring and quantifying the quality of the data available.
- Extraction: it is the process by which data is taken from the source system or systems. The origin of the data can come from different platforms, they can be relational, files, non-relational, etc., and it must be possible to extract them from the different platforms.
- Data cleansing: analyze and define rules to clean the data and obtain reliable data
- Transformation: the extracted data can have different formats from the destination data. To load it, the necessary conversions are first made to adapt it to the new data model. The business rules are applied to convert it, adapt it and prepare it for the next step.
- Upload: once the data has been transformed and converted, it is uploaded to the new system, directly or in stages, depending on the type of connection available between the two.
Find out 10 AWS Cloud Migration tools companies need to conduct migration assessment, develop a plan, implement it, and manage it.
