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In an accredited software testing business, the phrase test data strategy literally means data utilized for testing a specific software application. Every successful software tester understands that a product and test data are closely connected. If one cannot be obtained, the other is sure to fail. This statement is true even for test data management.

There are many advantages to implementing test data management strategy in your software development life cycle activities. First, it helps you obtain the test data in a fast, efficient, and effective manner. Second, this strategy helps you keep track of test data generation progress. Third, it can alert you to potential test data management problems before they happen.

The following paragraphs offer several common mistakes and other considerations to look out for when formulating a test data strategy. While these observations will not apply to every scenario, they do provide for an easy starting point. Keep in mind, these are simply meant as a working definition of test data management. They do not serve as the definitive definition for a testing professional. Rather, they are meant as a starting point for those interested in pursuing a career in software development.

One of the primary objectives associated with a test data strategy is to establish a clear path from the tester (you) to the data collector (the application). Effective test data strategies also allow the testers to maintain control over the data sources and to efficiently track their progress throughout the testing process. Often, a cleanup piece acts as the information conduit from the tester to the application and vice versa. Cleanup pieces also serve to provide information about test conditions and help the tester plot a roadmap for successful testing.

Another important element to consider when formulating a test data strategy is automation. Test automation enables a tester to automate various steps involved in the testing process. It can be a tedious task to manually create test data and then validating it against the end result. Test automation however, can simplify the testing process by removing the need for a tester to perform repetitive tasks. For first time testers, having automation in place simplifies the data gathering process and extends the time it takes testers to prepare data for a test run. Test automation in no way guarantees success, but by reducing the amount of time it takes testers to gather and validate test data, automation can be of significant benefit to the overall testing process.

So what do we mean by a working definition? Well, first and foremost we are talking about a definition that allows us to evaluate our current testing methodology. In other words, we want a definition that lets us know if we are on the right track! A working definition should be dynamic in nature and evolve along with your test projects. It should be a tool that enables you to see where you are doing well and where you need to improve. In the end, you want to be able to say "tested against" rather than "works with".