Migration and Data Validation Testing

Migration and
Data Validation

Migration and Data

In the world of data, the skillful application of migrated data, the data validation testing has taken an important position. Data migration is an integral component of system implementations, upgrades or consolidations. In order to have productive data migration, outcomes thorough validation are fundamental.

Since data accuracy is key in loading data from one source to a target system, we will need our data to be verified and consistent. Data migration testing is vital for:

  1. Checking if all required data was transferred.
  2. Validation the correct values in the destination tables.
  3. Verification that there is no data loss.

Here are 8 steps to follow in the data migration process.

1. Define the scope

Make a list with all the things you need to do, so you have a clear migration test scope.

2. Study requirements, business rules and mapping document

Make sure that the fields and data types in the original data source and the destination system coincide. Map each type of data, in the legacy system and destination system, in order to prevent data loss. A decent mapping document will represent all of the crucial details of both source and target fields including table, field names, data types and transformation logic, with business rules.

3. Dependencies and interactions

Get to know all of the dependencies and interactions with other systems.

4. Create test cases and queries to verify the data

When creating Test Cases, it’s worth to address the following:

Data Completeness with record count verification (by the way of record count for inserted records or record count for updated records) or comparing source and target data sets.

Data Quality is critical, in order to make sure that the data is correctly loaded into the destination tables/fields, that the application correctly rejects, substitutes default values, corrects, ignores, and reports invalid data.

Data Transformation and Data Integrity are comprised of checking to see if the data transformation is working in accordance to the requirements and business rules, if new tables are created, and if new columns are created with proper data types (as specified in the design), as wells as the referential integrity between tables.

5. Execute test cases

6. Compare the results

Compare your data after the migration. For huge data sets you may use the Red Gate, SQL Data Compare. Also you can use any tools like Total Commander, Excel to compare flat files.

Keep in mind that data validation shows that data migration was done with all business rules and mapping, but that does not mean everything works well in the destination environment; that is what next steps are for.

7. Non-functional testing

Non-functional testing includes:

  • Security testing – ensures that no security vulnerabilities are opened up.
  • Performance testing – perform load and stress tests to ensure the system’s stability.

8. Functional application test

At the end, run critical business processes in the destination environment. Often there are still some issues that should be fixed before the end of migration process.

Migrating data is not simply transferring information from one storage to another. It is the complex work of a QA team and it requires skill, expertise, tools, and resources. Next time you need to test migrated data, follow these 8 steps and check every important aspect of the migration.

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