Testing Data Quality with Synthetic Data is not only convenient for the test engineer but also helps the QA team to build trust. The two main purposes of Synthetic Data and Synthetic benchmarks are similar, but their use and application are different. While the former provides information about the test data so that the engineer can make informed decisions about design and implementation, the latter trains the developers to depend on the test data in the least possible time and at the highest possible level of accuracy. Thus, this tool makes it possible to implement test automation techniques. This article describes how Synthetic Data can benefit your development process.
With a large number of products and solutions deployed in the field today, data integrity is very crucial to product and system maintenance operations. However, testing and validating data recovery from these applications can be a daunting task. Many tools have been developed to solve this problem, but only a few are able to do so in a way that guarantees data integrity as well as execution reliability. SyntheticData makes it possible to develop quality test cases by simulating data recovery situations and then testing the quality of the recovery method.
The most common scenario for testing data recovery from an application is to test for consistency across multiple executions. The problem with consistent testing is that the results obtained are usually only aggregates and do not provide a meaningful picture of the end results. Hence, a good practice is to prepare and execute a series of tests to evaluate the consistency and validity of the application’s data-recovery method. This will help the developers in improving their application’s data-recovery capability, while also helping the testers to identify areas for improvement.
Similarly, some tests are useful for isolating and isolate specific data recovery issues. For instance, there might be a single database test that detects the presence of null values, and hence, validates the application’s user input validation code. However, there might be a series of tests that fail to detect a specific null value and hence, invalidate all the user input data in use with that particular database. In this case, the developer can easily isolate the problematic area by changing or eliminating the specific null value validation test in the software. By doing so, he can ensure better reliability of his application and hence, increase its ability to deal with data losses in real world scenarios.
Apart from regular testing of the application’s logic and data structures, developers also need to make sure that application performance is also tested using synthetic data. Often, performance testing is overlooked by the majority of the software engineers because they think of the application as being ‘black box’. The problem with this approach is that synthetic data helps identify areas where application’s performance can be improved, hence, increasing its reliability. Thus, regular data recovery audits help the designer to gain insight into the software’s actual problems and hence, shorten the time taken for application recovery.
In addition to regular tests of the application’s logical structure and data recovery procedures, a testing tool should also be able to automatically create a backup of the system prior to initiating any testing. This is because most applications do not initiate the test process until it is absolutely necessary to do so. Therefore, testing can be started only after the tester has ensured that a full backup of the system has already been made.
Apart from automated testing tools, manual testing should also be done using realistic data sets. It is recommended that testing should be done on a regular basis, say every six months. Regular testing helps identify the application’s weak spots and hence, can save considerable time and money spent on applications that are rarely used. Manual testing is important in other ways as well, because it helps in detecting bugs before a bug can get into the live environment and cause real-time problems. These bugs can then be fixed before they cause serious problems that can shut down an application permanently.
Synthetic data recovery tools are now available. They help data recovery professionals save time and money when recovering data. Hence, choosing these tools must be done carefully. Some of these tools are offered for free, while others require a fee. The cost of these tools depends on various factors such as the number of recovered documents and the amount of damage caused.
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