The Importance of Data migration Testing

 If you're considering migrating your data from one database to another, you should perform pre-migration testing to ensure that the data migration will be successful. These tests may include Application Level Validation and Test automation. Data migration testing is an important part of any migration process, and the data you're moving should be consistent and accurate. Before you begin data migration testing, it's important to gather as much information as possible.

Pre-Migration testing

The key to successful data migration is thorough testing of the pre-migration process. In this phase, you need to pull down all environment components and perform a test run, ideally during the downtime of the actual migration. The downtime should be the same as the migration itself, and you should document the test results both in the white box and backend. If you are using a script to migrate the data, ensure that you pull it from the version control repository.

For each data type being migrated, conduct validation tests against the subset of data. Use the data sheets to reference validation rules to make sure the data matches the database. You should also test for boundary values analysis and equivalence partitioning. You can also perform field-level validation tests to validate if the data is consistent. Invalid data is a major red flag and should be treated as a defect.

Application Level Validation Testing

Application Level Validation Testing (ALVT) is an essential part of data migration. This testing is done to make sure that the data that migrate from one system to another is complete without errors. It can involve sampling, data verification, and entitlement checking. Performing this testing prior to data migration will help to avoid a major disaster down the line. Regardless of which type of data migration you perform, you should follow the best practices for application-level validation testing to ensure that your data migrate successfully.

When evaluating the quality of data migration, you should first consider the security measures that are in place. For example, if you plan to migrate sensitive data, this step is essential. Once this is done, you can proceed with the migration using the style that you defined in the data migration plan. Lastly, when performing this testing, you should also consider the quality of the data that is being migrated.

Test automation

Performing extensive testing prior to implementing migration is vital to ensure a successful migration. It frees up your physical body from tedious tasks. Data migration is not seamless and requires thorough testing. Before migration, identify the data to be migrated and decide on a data integrity check. Data integrity check ensures that the migrated data will be accurate and not contain duplicates. Also, it validates business rules for data fields. Once you have determined which data migrate, run a series of integration test cases to validate the integrity of the data.

The migration process must be tested for throughput, the number of records migrated per unit of time. The downtime must be sufficient to complete the testing. In addition, the testing process can also determine if the planned downtime is sufficient. If not, it is recommended to run a manual test before the migration. In addition, you may want to use an automated tool to automate this process. If you have to perform manual testing, you should make sure to document every step of the migration process.