Test data management streamlines the software development process by improving speed, quality, and security. It also reduces costs and risks by improving compliant data access throughout the SDLC.
Effective TDM includes the processes of scripting, generating, masking or obfuscating, cloning, and provisioning data. Automation of these tasks significantly expedites and makes them considerably more proficient.
Automation
A good test data management process automates the creation of test data, allowing QA teams to quickly access a set of reusable data according to their needs. This saves time, helps the team focus on more productive tasks, and eliminates issues with faulty or insufficient test data.
It also reduces the time needed to prepare the test data, enabling IT operations teams to better fulfill ticketed requests. This is important because stale data can impact the quality of test results and lead to costly late-stage defects.
It also provides immediate feedback to developers and testers, helping them detect errors sooner in the testing cycle. This can help them resolve issues before a product goes live and ensure that the application performs as expected. It also increases the accuracy of the tests, which leads to more accurate and reliable software deployments.
Scalability
Scalability is the ability to accommodate growth and handle increased load without impacting performance. This is a crucial feature for any business that plans to expand, or that wants to remain competitive with its competitors.
The scalability of software depends on the quality of its architecture and the management processes that support it. Businesses should focus on building a scalable system from the ground up to avoid expensive refactoring and to ensure that it is reliable.
Test data management (TDM) is a valuable tool for all software development projects. By copying accurate production data and providing different data subsets for testing, it allows developers to create realistic workload models and perform granular tests. It also enables teams to mask data to maintain compliance with CCPA, HIPAA and GDPR regulations.
Security
A secure test data management process is critical. It’s especially important now as the GDPR comes into effect and companies are on high alert for security breaches that could be costly.
Ideally, the data used for testing purposes is not production data. Instead, it’s nonproduction data that meets the quality requirements of software quality-testing and safeguards privacy with de-identification techniques.
Modern DevOps teams are focused on speeding up their development processes, improving code quality and security while also lowering costs. However, they face challenges ensuring that test data is available for environments throughout the SDLC. This can result in a longer time to market and increased project costs without an effective test data management strategy. TDM solutions ensure timely and accurate test data while providing security controls.
Reusability
Testing teams spend a lot of time searching for reliable and accurate test data. Stale and outdated data can invalidate test results, leading to application features going live with defects.
Ideally, organizations would like to make their existing data sets as reusable and as possible for new test cases. However, this is not always possible. A lot of test data is not reusable because it contains confidential aspects and cannot be manipulated or changed without the risk of breaching compliance regulations.
A solution’s reusability is determined by how many purposes it can serve. This is known as its reusability potential. To maximize reusability, solutions are usually broken down into modules that can work independently from one another. However, these modules should be compatible in terms of design and functionality.
Tracking and Traceability
The most efficient way to test an application is through a forward and backward traceability matrix. This allows you to check whether the test cases cover all the requirements, avoids omissions, and ensures that any changes in requirements are reflected in linked tests.
Test data consists of nonproduction datasets that leverage production-like values for quality-testing purposes while protecting user privacy. Test data management tools implementation helps you comply with CCPA, GDPR, HIPAA and other data privacy regulations thanks to masking techniques.
Typically, QA teams or project managers are responsible for producing test data. But with a dependable TDM solution, you can provide self-service capabilities to create and refresh ephemeral datasets on-demand without waiting for IT tickets or involving the IT operations team. This improves developer productivity, boosting their time-to-delivery.
