Effective test data management is crucial for successful automation testing. Key strategies include creating data sets that mimic real-world scenarios, ensuring data consistency and reliability across test cases, and using data-driven testing to cover various input combinations. It’s also important to implement reusable test data, optimize the test environment, and ensure proper data privacy and security. Version control for test data, data masking for sensitive information, and continuous monitoring of test data quality are additional best practices that ensure the robustness and accuracy of automation tests, minimizing errors and enhancing test efficiency.
