In an information-technology testing business, the word test data literally means statistical data used for technical analysis of a particular system. Every good information tester knows very well that a product and its database under test definitely have strong influences on each other. This is the reason why both of them have to be working with similar kinds of database, so as to get the most efficient results. It is not only important to test a piece of software in order to find out if it meets all of the expected conditions or not, but it is also very important to test the database in order to determine its stability. And the best way to achieve this is by using test data. This type of statistical data will enable you to check the results obtained from your software test against your own expectations.
The test data strategy of information technology testing is very important because it will help functional analysts to detect the defects in the software development process. Functional analysts are those people who are responsible for software development. They are supposed to check every aspect of the software development process including the business logic of the program, database, and user interfaces. If these aspects are found to be erroneous, then the software development team might be in deep trouble. In such a situation, it might be risky for the software developers to continue their work. Therefore, developing reliable test data strategy becomes a critical necessity.
For information technology testers, using test data will help them pinpoint areas that require further attention and fixing. The testers do this by identifying which areas need additional attention and by checking whether the problems they are faced with can be corrected easily. As they continue to improve their knowledge about test data, the testers will also become better at software testing itself. As a result, both functional analysts and testers will benefit from test data strategies.
The test data strategy is considered to be an essential element of the software testing process. It helps the testers to determine whether the automated tests which they are using are accurate or not. This is achieved because the testers can make use of the test data set which they have generated as well as the manual data sets that they have relied on. By following test data strategy, the testers can avoid making mistakes that may cost them the whole project. For instance, they might create a wrong specification for a complex piece of software and then have to recreate it from scratch.
Another important advantage of the test data strategy is that it enables the testers to test both static and dynamic data sets. Most of the testing tools nowadays support both kinds of sets of data. Hence, a tester can use the tool to test both synchronous and asynchronous data sets with the help of different tools. In the end, even the testing automation tool can help in the testing process and should be used correctly.
A test data strategy for large-scale testing environments like enterprise customers requires that the data be captured as quickly as possible. The faster the data capture, the better it is for the developers who have to convert it into functional and/or maintain it efficiently over time. Many of the test automation tools in the market today allow the user to specify the desired speed of data conversion. Therefore, it is easy to find the appropriate tools and select the most appropriate one for the testing environments.
Integration is another important aspect for Agile development. In order to integrate the test data strategy with the agile process, the developers use test automation technologies that support the development processes. These tools make it easy to construct and test the business cases as well as the code itself. For instance, in an Agile environment, it becomes mandatory to support integration of data from the customer database, the user stories, the test data, and the CI automation code itself.
Many testing strategies are available in the market to support the implementation of test data strategy. However, before using any of the strategies, a proper feasibility study should be carried out. For instance, an automated test’s implementation may not be suitable if the business process does not change in any significant way over the long term. Therefore, it is necessary to carry out a study on the business process in order to identify the areas which need modification. Once the business process is adjusted, then the developers can easily begin using the automated tests to validate the business process and the code itself.