Test data management is essentially the generation of non-production test data sets which consistently simulate an enterprise s real data in order to enable software and systems developers to perform robust and accurate system tests. Most people think that test data management is similar to test automation, which in fact is not the case. Test automation involves designing and implementing automated test cases that verify whether a specific software solution meets specified requirements. While it certainly is possible to generate test data manually, without the automation approach, it would be very difficult to achieve an effective level of test coverage.
Such testing aims to reduce the risk of software bugs, defects and performance issues which may lead to severe financial loss, operational disruption and business failure. It helps businesses ensure that the most important and critical applications are bug free and deliverables meet delivery commitments and specifications. It helps make the systems more robust and reliable for a variety of software and hardware scenarios and reduces the risk of system downtime, network issues and data loss. The ultimate objective of test data management therefore, is to protect sensitive data from potential risk and failure.
The process of test data management entails several steps which start by collecting actual test data sets. This initial set of test data sets are commonly comprised of a collection of user stories, acceptance tests, infrastructure requirements, and software/hardware issues. The developers then use test data management tools to merge these into a final test data set which ultimately becomes the production data. The test data management tool further applies various optimization techniques and code cherry-picks to address problems specific to each scenario that is being tested. Once test data management is complete, the test data sets are deployed for live testing.
While time is generally utilized to simplify the collaboration among testers, it does have limitations. For example, when using them to automate the generation of test data sets, all testers must have access to the development environment in order to make any changes to the underlying code. Similarly, it is important for testers to be able to easily collaborate and work across different platforms and operating systems. In addition to that, a wide variety of inputs is needed in order to test a large array of software and hardware configurations. As an example, it would be very tedious to test a large number of network adapters and OS flavors on one OS. Similarly, testers need to test data from many networking locations and in many different networking environments.
Another limitation of test data management is that it only contains test data that is generated at the time of testing and hence cannot be reused afterwards. Hence, it can be used as a control or validation tool. By validating a particular input value, tDM can enforce compliance with test policies and thus provide a useful reference point for QA professionals to validate and control the quality of the software development methodology itself. Also, this tool enables quick and easy collaboration among testers since there are no geographical boundaries and everyone can access the repository at the same time.
Another limitation of the tdm implementation is that it contains only text, hence is not capable of storing any metadata or other sensitive data. Hence, it proves useful only for simple text selection activities. To ensure that sensitive data is appropriately stored and maintained, the tDM should provide for encryption of data. This encryption should be periodically reviewed and re-licensed to comply with international standards such as the ISO 9000.
The last major limitation of the use of the test data management (TDM) tool lies in the speed of reporting. Since TDM is intended to act as a reference point for QA professionals when they look for a pre-requisite for a particular test, its reports must be extremely fast. If the data has to be analyzed further, then it has to take a long time to generate the reports. Moreover, if the user is looking for quick results, he/she might be inclined to opt for a slower time rather than a faster one.
However, this last point is also a limitation. Some test data management (TDM) tools are capable of generating quick results. They can be designed so that the user gets instant information on all the test data management activities that have been performed across the test environment. This allows QA professionals to make informed decisions about various aspects of the testing environment.