Test Data Management
The software industry is constantly looking for optimization in testing efforts, and one such area is Test Data Management (TDM). It is crucial because testing completeness and coverage mainly depend on test data quality.
Efficient testing data management is essential to maximizing return on investment and supplementing testing efforts for the highest success and test coverage. If the data used fails to promote ease of use and adaptability, it adversely impacts the desired outcome and degrades the product quality. To balance the positive results and improve returns, consider the process, potential challenges and possible solutions involved in TDM.
The best data is always found in production, as this is where it is used. While using production data, creating a subset of this data is always advisable to reduce the effort involved in test planning, execution, and optimization. Depending on the business, privacy and legal concerns may surface when using production data. Hence, we recommend not using production data for testing purposes.
In the testing phase, the data is often incomplete; therefore, real-time scenarios are not being tested completely. Testing cycles are shrinking with the advent of Agile and DevOps practices. Creating quality data within that cycle, as well as performing software testing, becomes a challenge.
If you don’t have a TDM or are keen to make your test data more robust and production-like, this whitepaper will help you understand and implement TDM. It explains Infosys’ TDM strategy and solution encompassing data subsets and synthetic data that reduce cost, time, and effort in the testing cycle while establishing a cost-efficient software deployment process. The practice of not including TDM in the testing life cycle often leads to ignorance about TDM on the part of the software development team.
