Test Data Sourcing Challenges

One of the areas in test data generation, the testers consider is data sourcing requirement for sub-set. For instance, you have over one million customers, and you need one thousand of them for testing. And this sample data should be consistent and statistically representing the appropriate distribution of the targeted group. In other words, we are supposed to find the right person to test, which is one of the most useful methods of testing the use cases.

Additionally, there are some environmental constraints in the process. One of them is mapping PII policies. As privacy is a significant obstacle, the testers need to classify PII data. The Test Data Management Tools are designed to address the mentioned issue.  These tools suggest policies based on the standards/catalog they have. Though, it is not very much safe exercise. It still offers the opportunity of auditing on what one is doing.

We believe that existing Test Data Management challenge is a profound blessing, which in their turn help in raising our testing standards, operation procedures and the use of effective tools to handle the pertaining issues existing along the process of quality product delivery. To keep up with addressing the current and even the future challenges, we should always ask questions like: When/where should we start the conduct of TDM? What should be automated? How much investment should the companies allocate for testing in areas of human resource on-going skills development and the use of newer TDM tools? Should we start testing with functional or with non-functional testing? And many more likely questions as them.

Some of the most common challenges of Test Data Sourcing are as below:

  • The teams may not have adequate test data generator tools knowledge and skills;
  • Test data coverage is often incomplete;
  • Less clarity in data requirements covering volume specifications during the gathering phase;
  • Testing teams do not have access to the data sources;
  • Delay in giving production data access to the testers by developers;
  • Production environment data may be not fully usable for testing based on the developed business scenarios;
  • Large volumes of data may be needed in short period of given time;
  • Data dependencies/combinations to test some of the business scenarios;
  • The testers spend more time than required on communicating with architects, database administrators and BAs for gathering data;
  • Mostly the test data is created or prepared during the execution of the test;
  • Multiple applications and data versions;
  • Continuous release cycles across several applications; and
  • Legislation to look after Personal Identification Information (PII).

On the white box side of the data testing, the developers prepare the production test data. That is where, QAs need to work touch base with the developers for furthering testing coverage of AUT. One of the biggest challenge is to incorporate all possible scenarios (100% test case) with every single possible negative cases.

In this section, we talked about test data challenges. You can add more challenges as you have resolved them accordingly. Subsequently, let’s explore different approaches of handling test data design and the management.

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