How to Implement Test Data Management

Test data management is essentially the creation of non-production virtual test data sets which reliably simulate organizations actual data sets so that software and systems engineers are able to do valid and robust systems testing. The term test data management, was first coined in 1986 by Bill Atkinson and Martin Seligman in their book The Cathedral and the Bully. The two conceptualized test data management models are similar in many ways however the actual test data management methodologies they describe are quite different.

In the case of the Cathedral and the Bully, the test data management methodology was modeled after the waterfall method which is an effective testing methodology. This model has proven to be very effective for software teams however as the number of projects to increase the level of stress on the team members increase. This is due to the increased number of user stories and the larger amount of change requirements which must be fulfilled before a release can be released to production. The increased stress on the team leads to a higher failure rate, which is a direct result of poor test data management practices.

The two major areas of test data management which the two authors described were manual and automatic testing. They then proceeded to describe the process of test data management in more detail. They concluded that there are five major principles that should be considered when designing a test data management plan. These are concurrency, parallelism, reproducibility, validation and consistency. These principles will guide the test team as they develop test cases.

Concurrent Testing – The test data management plan should include concurrency. This means that multiple test cases could be running concurrently in parallel on the same server. This is especially important for medium to large teams as even one single user could bring about hundreds of test cases onto the same test server.

Parallelism – The test data management plan should also include parallelism so that high-quality data can be obtained as and when necessary. Test automation software such as Monkey Talk or Team Centre will allow you to manage and run your test cases with ease by automating the entire testing process. Monkey Talk is one of the most popular testing automation tools used today and is highly recommended for high-quality software automation and data management.

Repretion – Test data management should also include a good testing policy as well as a good distribution policy so that a large chunk of test management resources can be dedicated towards validating business cases. This allows for the quick execution of even the most complex and critical testing requirements. For example, consider the following scenario. Your product is about to undergo a major transformation. You would like to make the testing process easier, thus you decide to automate it.

The automation of the test cases will make the test cases quite simple. This will also help in increasing the overall productivity of your team. In addition to that, the automated test cases are easier to deploy. They require no changes to your production environment and thus can be deployed without any glitches. While most of the modern test management tools have the capability of replicating the production environment, they also have the ability to create and save test data on a centralized server. This makes it easy for all the departments involved in the production environment to access the test data management system easily without compromising the production environment.

The implementation of test data management requires a comprehensive test data management strategy which consists of not only for test automation but also test data administration. The test data management policies must address the goals and the needs of your company. When properly implemented, test data management will help you gain more insight into the actual performance of the application and will help in the timely detection of bugs and security flaws. It will also help in the management of large amounts of test data in a secured and efficient manner.