Production data Vs. Synthetic data for software testing is one of the most common debates amongst the quality assurance managers in a software testing company. Keeping this scenario in mind, they consider six factors to make choice between the utilization of synthetic and production test data. All factors play a significant role in eliminating the hurdles related to test data and elevating the risk of the security data breach.
Adaptability
The test data must be sufficiently adaptable to be utilized by any technology or testing tool. The test data provisioning procedure should be versatile to all sorts of testing environments, for any sector or size. It must have the capacity of performing with huge databases with various apps. Synthetic data is famous for its adaptability and can provide services for huge databases on demand.
Easiness
While selecting a source of provisioning test data, quality assurance managers must guarantee that it is simple for the testers to attain the data they require for their assessment. It must be the simple framework that makes bets quality test data obtainable for anyone at any time. Synthetic test data production makes the procedure very easy with platforms that permit actual test data to be produced on-demand by the quality assurance teams.
Security
Quality assurance teams are required to consider the confidentiality of the test data sources. Test data must remove all PII, to alleviate the increased data breach cost. Production data needs data masking. However, the masking process is not guaranteed. Nevertheless, synthetic data guarantees complete compliance with every security regulation in the testing cycle.
Quality
Production test data have very less control over the quality of data considering the factors like data value, variety, accuracy, and age. They are required to copy, subset and mask. A software testing company needs various permutations of information along with undesirable test data. Perhaps, testers are forced to manually customize the production data into the practical test values. Nevertheless, synthetic test data eliminates the effort that is allocated to develop a data subset. It is developed on a test data situation and is able to rapidly produce data with a difficulty that cannot be executed manually.
Cost
Cost is very important whenever we have to develop, manage and archive test data. The production data is required to be created, managed, and saved; teams require a Test Data Management system. Therefore, they are required to buy a test data management system and also tolerate its maintenance costs. Nevertheless, if synthetic data is produced on demand, and there are more cost-effective tools and solutions available in comparison to a few years earlier. This plays an imperative role in decreasing the cost of providing test data.
Speed
The quality assurance managers must take into consideration the time required for test data provisioning prior to starting a test project. Generally, it takes very less time to complete a request for test data for supporting some test environments. Synthetic test data copy the actual world data and produce it at a percentage of thousands of rows per second. This framework permits the testers to offer their own information whenever they require it and dispose of it after test completion.
Conclusion
QA specialists in software testing companies are still worried about the trade-offs. They are required to construct the approach that is the better and correct selection for their testing environment. These apprehensions cause a great debate regarding the consumption of synthetic test data or production test data in continuous assessment environments. The points mentioned above can assist quality assurance teams performing for an outsourced software testing company to have an enhanced choice.
