Test data management is highly critical for analysis of previous test data and making amendments or upgrades based on that data. They are also important in testing life cycles when the required data sets are needed for assessing the application under test (AUT).
It is important to note here that the data generated while testing an application is huge and TDM helps in monitoring them and minimizing the time spent for processing the data. TDM also helps in generating reports that add value to the overall application software. It also enables integrating sensitive data discovery, business classification, and policy-driven data masking for de-recognition and state-of-art implementation of production data within the development ecosystem.
The best part about TDM is it cannot only be launched in the premises but can also be implemented on the Cloud or via any hybrid cloud configurations. Some of the key functions of TDM are:
- Identifying common test data elements
- Masking and archiving test data
- Prioritizing and allocating test data, generating reports and dashboards
- Establishing business rules
- Developing automation suite for master data preparation
- Eventually creating versions of old data
The importance of TDM is widely felt and therefore enterprises are opting to set up centralized test data management teams to procure test data in time and cater to the needs of both the tester and the developer.
Here are the four TDM techniques that empower software testing:
- Exploring the test data: Data can be present anywhere in a given system, in any form. Finding a data in thousands of files is a tedious job. TDM helps manage the files and traces the given requirement. Locating the right data in the right format is an important requirement. In such a case, manually locating the data and retrieving it is a big task, which is easily done by TDM.
- Building test data for Reusability: Reusability is the key to a successful business. It not only reduces cost, but also maximizes testing efforts. Test data must be built and segmented to make it reusable. It should be accessible from a central repository and should be used as much as possible to optimize the work that has been done. By making the data reusable, the bottlenecks and the issues within the data are removed and it is fully versioned. No time is wasted in retrieving or protecting the data. These data can be used for building test cases within no time and at ease.
- Validating test data: In this age of organizations implementing agile methodologies, data can be sourced even from actual users. The data gets transferred mostly via the application, which is followed as a practice for generating and exploring existing data. It is to be noted that the data must be protected against any breach in the development process. The test data is then validated, and the resulting test case gives a real picture of the production environment when the application is launched.
- Automating TDM tasks to accelerate the process: TDM enables scripting, data generation, data masking, cloning and provisioning. Automation of all these activities can take the process a little further ahead in time. During the Data Management process, the test data is linked to a specific test that is then fed into an automation tool. This tool ensures that the data is available at the required format. Automating the process ensures quality of the test data during the development and the testing process.
This blog shared by the QualiTest Group , World’s largest software Testing company.