Published: 05 Feb 2018
4 Trends Driving an Effective Test Data Management Strategy
Last Updated: 10 Jan 2024
Test data management (TDM) is a critical activity in the testing lifecycle. And this is undergoing continuous refinement with constant changes in the technology landscape and application development process.
Contents
1. Effective Test Data Management Strategy
2. Big Data
3. Service Virtualization
4. DevOps Practices
5. Agile Methodology
6. Conclusion
TDM is highly critical in the testing lifecycle, as the quantum of data generated while testing is massive. Automating the test data helps in minimizing the time spent on processing the data, generating reports faster. However, some key trends have been empowering the TDM strategy. These key trends must be considered while creating an effective test data strategy to reduce time-to-market and improve efficiency. Let’s discuss these trends.
Effective Test Data Management Strategy
Big Data
Big data is a growing technology-driven program, and its strategic significance is growing gradually. With the rapid increase in the adoption of big data, test data architects need continuous data privacy and security solutions. Due to rising breach cases, IT organizations need to expand their data privacy and regulatory compliance initiative by including development and testing environments into the scope. In the current scenario, testing a big data application has become a challenge due to lack of proven test frameworks and toolsets. To set this right, test architects must manage test data and regulatory compliance in their test data strategy.
Service Virtualization
In the world of agile and DevOps, testing the applications need accurate, reliable, and comprehensive test environments. While this can be challenging, testers must execute integration tests on the application with various code versions and test data combinations. Therefore, test data architects need solutions to virtualize application behavior with predefined test data combination. Various organizations are leveraging service virtualization with proper test data configuration as a technique to minimalize costs in the non-production environment.
DevOps Practices
The implementation of DevOps practice promotes collaboration across teams involved in the software development lifecycle. The product, as well as test managers, deliver software in quick cycles and of high quality by continuous integration. A test data architect should leverage database virtualization in TDM for faster provisioning of non-production forms of databases virtually.
Agile Methodology
Agile delivery methods necessitate delivery within shorter delivery cycles with high quality. In every agile sprint, the test teams build, run, and automate tests for which the test data management teams execute data refresh and provide the test data needed to perform the tests. The ideal situation for a test data architect is to ensure optimal data sets with maximum test coverage. This solution helps in completing the testing on time.
Conclusion
Concisely, Test Data Management architects and consultants must be aware of the impact of these major trends on their existing test data strategy. Equipped with this information, they must modify their test data strategy with effective solutions, such as service virtualization, to integrate an ultramodern vision into their Test Data Management strategy. Test data is often generated using existing data. Therefore, the data must be kept confidential to protect the individual’s interest or business interests. Securing the test data is important based on the criticality of the application under test.
At TestingXperts, we have employed robust test data management practices for intricate enterprise platforms. Connect with our experts to improve test effectiveness by using accurate test data and institutionalizing the entire test data management process.