Why The Quality Of Your Testing Is Highly Dependent On Your Test Data Management?

In this article, you will find what is Test Data Management (TDM)? The challenges related to TDM and why the right Test Data Management approach and tool are useful to ensure the quality of your testing process.

In a disruptive market, there is a constant pressure to release high-quality software in a short span of time. This has led the software testing industry to optimize the cost and efforts required for testing. One of the key areas for optimization is test data management. Let’s have a look at what is test data management:

What is test data management in software testing?

Any data that is used as an input to perform testing is called test data. The data can be static data such as containing currencies, countries, names, etc or transactional data. The testing team requires the right combination of static and transactional data sets to exhaustively test business features and scenarios.

Test Data Management is the process to ensure that the testing teams have the right quality test data in the right volume, in the right format with the proper environment at the appropriate time for testing.

The testing coverage mainly depends upon the quality of test data. The test data must resemble the actual production data for testing effectiveness.

Challenges in Test Data Management:

The clear data requirements along with the quantity specifications are neither gathered nor documented during the test requirements phase.
The testing team doesn’t have access to the sources of data.
The testing team may require test data from the development team which is usually busy in another priority task.
The data can be available in large chunks from the production dump which can be unsuitable for business scenarios that are to be tested.
There are no appropriate tools to manage a large volume of test data.
There is no process to review or reuse the data.
The same data may be used by multiple testing teams in the same environment that may result in corruption of data.
There is a lot of time wasted by the testing team in communicating back and forth with solution architects, database administrators, and business analysts rather than actual testing.
Gathering the test data turns out to be a hassle.
If the data related to a certain defect is missing during testing it could lead to a major risk at the time of production.

To address these challenges, you will need to test data management tools.

What are test data management tools?

The Test Data Management tools manage the test data that will be used by the testing team. These TDM tools help to implement the process of test data management. The key features of test data management tool are:

Data discovery & classification

TDM tool automates the identification of sensitive data and masking of the data classified as sensitive across the database.

Self-service data warehouse

TDM usually provides testers with a data warehouse to store, share and reuse test data to improve the efficiency of testing.

Providing data subsets

They also provision smaller datasets on the basis of test plan requirements.

Reporting

These tools also ensure compliance with data governance norms by monitoring the data and providing reports.

Advantages of implementing an effective TDM approach:

An optimum level of data coverage is achieved by employing TDM approaches.
Test Data requirements are effectively captured by the testing team to keep version controlled data requirements. This also helps in traceability and replication of data.
The detailed analysis of data requirements helps to identify any potential issues that may arise during testing.
Synthetic data can be easily created for the testing of new features.
Data security and safety policies can be implemented effectively.

Conclusion

The successful implementation of Test Data Management approaches will significantly improve testing effectiveness. It also ensures a large volume of data can be created efficiently and swiftly for the testing process.