While availing Testing-as-a-service[TaaS], benefits like Cost Reduction and Revenue Optimization seemed obvious but did you double check if the package is inclusive of Test Data Management? With Big Data the buzzword these days, we often sideline the test data management, in fact, experts believe that an effective Test Data Management could increase the quality of the product.
CloudQA being the pioneers in offering Testing-as-a-service[TaaS] stress on why Test Data Management is an integral part of your Testing-as-a-service[TaaS].
Boost TaaS with Test Data Management[TDM]
The Challenges faced by a QA/tester in test data management
What Test data is needed?
What is test data? For a numeric field fill in the value as 12345 and for a string ABCDE. Most of the test results do show such kind of screenshot where data was put in randomly. While testers argue that they were not performing data testing hence data could be random, experts believe each test case to mimic the real-life scenario. Simply, many testers are unclear on the experimental data to be used for a scenario in many cases.
Test Data Need Better Simulation, Masking, and Periodic Refresh
Put yourself in a financial trader/broker shoes, would he be able to make decisions based on simulated data? Or when the feed is delayed by 30 secs? That’s what happens for a tester/QA who tries to test a real-life scenario but fails may be because data is just the sample data or few weeks old or is given to you with a delay. Most of the testing teams would agree, that test data is close to real but NOT REAL!
Database Structuring, Relations, Keys, and linking is ambiguous to testers
A tester is well-aware of the full functionality, environment needs but very few know how and which tables get updated when hitting the submit button. What are the primary or unique keys in a table that could not be overridden? What’s linking of the data? Does submission of a record update multiple tables or just one? Ignorant on these issues, testers often override the data from backend to test a scenario or delete data leading in data getting corrupted.