Data migration is the process of transferring data from one application to another, and can take place due to the following reasons:
Data migration can be considered high risk due to the data being sensitive or in large volumes. In data migration testing, QA teams verify that the migration from a legacy system to the new system occurs without any data loss, thus maintaining data integrity. It also ensures that the features of the application are still working post-migration and that no sensitive data was lost during the migration.
Before starting data migration verification can take place, the following activities need to be completed, which are considered pre-migration testing techniques:
Below are the four primary approaches, also described as post-migration techniques, QA teams take when tasked with a data migration process.
This approach requires SQL knowledge as quality assurance team members need to prepare scripts based on the mapping document and requirements. The QA team has to create SQL queries in a way that covers every aspect of a table as well as defined scope. They then compare the number of records and data migrated corresponding to each attribute of the legacy database with the target database. The benefit of this technique is that the QA team can update the SQL scripts whenever they are required. Using this technique, one can verify the following elements of the migration:
Data comparison can also be done using Macros. In this method, the data from the source as well as target database is extracted into an excel spreadsheet and then compared. However, this approach is not favorable when dealing with a large quantity of data.
This technique is important in data migration testing because it checks how the migrated data will display in an application to an end-user. All the migrated data should retain its value and format unless it is specifically mentioned not to do so. In this technique, the data from the legacy application/database is compared with the target application to see if the data is populated in desired fields. QA engineers should always take the dataset that has values in all the fields and verify a few records from all migrated database tables. UI testing allows test teams to:
Automation scripts can also be used with test data from a legacy system and validated against target applications.
It is another self-scripted approach where the accuracy and quality of migrated data are checked. The following points will help you better understand this technique:
Validation testing decides whether the system functions as it was intended or not. An application with migrated data should work the same as it was working before data migration and should meet all specified business requirements. This technique verifies the stability of the application and ensures smooth running with migrated data. In this, a tester verifies an application’s core functionalities using migrated data and can check the following scenarios:
Data is an evaluative component for any business. A small miss in the verification of migrated data could result in a risk of failure at production. To avoid such risks, the above data migration testing techniques can help a tester in discovering any discrepancies in the migrated data. It leads to quality testing and a better user experience.
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