Original Article by Jeffrey Hughes

Finding proper test data for testing the software you’re developing for can be a challenge most of the time for a variety of reasons. In his article, Jeffery Hughes goes over why test data management is important and lists four main ways of how to improve your management of test data.

Hughes states that test data management is important because it can help address challenges that occur in providing test data quickly and continuously for the application you’re working on. The main three challenges that he touches on are test data compliance, availability, and freshness.

After that, Hughes addresses what the four keys to better test data management are. The first key is how to properly discover and analyze test data. Hughes states that your test data may be spread across multiple platforms and could be extremely time consuming if you tried to access it all manually. He suggests that using a tool that can make sure that the right test data is being tested and to come up with a “solution that provides complex coverage analysis and data visualization is a better approach.”

The second key that Hughes talks about is protecting sensitive data. In this section, he points out that is important make sure that sensitive data is being properly secured (even when just in testing), and to make sure that you use “inconsistent data to test for anomalies that are sure to occur with end users.”

The third key is make sure that you’re able to deliver test data on demand. Hughes points out that it is a great advantage to have your data stored on a central repository so that all test data is in one place and can be easily shared. The hope is to make sure that there are no more bottlenecks for testers that are “waiting for data” when running tests.

Finally the fourth key is to make sure that you try to automate as many steps as you can. Hughes suggests severally tools that can make automating your testing easier for your and your team. He states that this kind of “stabilized automation framework guarantees that data will be provisioned in the right state when needed by your testers.” This also makes it easier to trace your data and test cases back to their requirements, and also means that if your “requirements change, the data can be updated automatically.”