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The software development environment is evolving so rapidly that it’s hard for businesses to keep afloat. It is important to have a proper testing plan in place in this highly competitive scenario. And there are several components to a sound testing approach, one of which is test data management. And that’s exactly what the post today is about: what, why, and how to handle test results.
We begin by addressing test data management (TDM) and then proceed to explain why it is so relevant. After that, we’re giving some basic guidance on how to implement Test data management strategy, showing the usual stages of the test data management process, and describing the activities performed in each of them.
Let’s start with the concept of test data management (TDM). Test data management is the process of managing the data required to satisfy the needs of automated tests, with zero (or as little) human involvement. This means that the test data management services are responsible for generating the necessary test data according to the needs of the tests. It should also ensure that the data are of the highest quality possible.
Bad quality test data is worse than no data at all because it will yield results that cannot be trusted. Fidelity is another essential criterion for test data. In other words, it should be as similar as possible to the actual data contained on the production servers. Finally, the TDM process must also ensure the availability of test data. It’s not a good idea to provide high-quality data that is as practical as possible but doesn’t get to test cases when it’s needed. We may therefore conclude that the test data management process has three key objectives: to provide high-quality, practical, and usable test data.
Also Read: What Is Test Data?
In the previous section, we described the management of test data and briefly covered the motivation behind its use. We’re going to cover those motivations in greater detail now.
If you feed bad feedstock to any industrial process, the result will be subpar. If you supply bad materials to a skilled craftsman, they will probably get a better result than a less talented worker, but they can only go so far. The same is true for research. It doesn’t matter how brilliant your test plan is. If you feed it with bad data, you’ll get bad results every time. Not taking care of the accuracy of your test data is throwing money away. All the investments made in your research plan will have been for nothing.
Another main duty of TDM is to ensure the availability of test data. Your data may be of the best standard quality imaginable, but if it’s not there when it’s needed, it’s worthless. The only thing that would certainly be worse would be to have low-quality but readily available data. So, high-quality, high-availability data is the only outcome we can settle for.
The previous section ended by discussing the possibility of disclosure of confidential client data. This is not something you’re going to take lightly. On the contrary: the disclosure of sensitive data may result in catastrophic damage to the company.
The faster you find a flaw, the cheaper it will be to patch it. Having a solid test data management process means that the whole automated testing process is running smoothly, this improves the possibility of finding more bugs sooner.
Here is a list of the Popular Test Data Management Software:
In this article, you’ve seen what the management of test data is, why you should take care of it, and how to take care of it. We began by defining the word. Then we covered the reasons behind the adoption of the test data management. After that, we’ve shown you the basics of how to apply TDM by explaining its basic steps.
Also Read: 6 Test Data Management Strategies