4 key test data management techniques to empower software testing
Whether it is a gaming application or a functional CRM or ERP software application, organizations need to ensure that the software product is tested thoroughly before deployment and release. Quality assurance is the most heard word in IT organizations and has the utmost importance to let your customers enjoy your products without any functional or operational issues. However, when it comes to testing these software products, test data management is highly crucial for organizations during the testing lifecycle. During the testing lifecycle, assessing the application under test is required and for this, test data sets are needed too.
When testers test any particular application, a massive quantum of data is generated. What the test data management technique does is that it helps quality analysts to process this data in lesser time and generate reports that can be used for overall application or software development and release. Also, there are some other benefits of test data management. It helps developers in the integration of sensitive data discovery, business classification, and policy-driven data masking. Here, test data management also identify common test data elements, mask, and archive test data, prioritize and allocate test data and generate reports and dashboards and create old data versions.
What are the key TDM techniques that empower application testing? Let’s discuss this in detail.
Exploring the Test Data
Developers and other stakeholders need to search for the right data sets that can be used for testing the software product. Now, data might be present in cluttered, diverse forms and formats and might be spread across multiple systems. Locating and choosing the right data in the needed format within the time is very vita. Hence, you will need a solid test data management tool that can help you to achieve this objective. Now, it is a very tedious and annoying task to do it manually. It also affects the efficiency of the process. The right test data management solution can address this issue perfectly. To establish an efficient and effective test data management approach is very critical in the software test lifecycle.
Validating your test data
Validating data is another thing that you need to work on. In the era where agile methodologies are used for software and application development, testers, sometimes, get data from actual users that come from the application. Now, you need to protect this sensitive data against any security breaches during the development process. Some of the sensitive test data might be names, addresses, financial information of customers, and contact details must be secured by organizations against any data breaches.
Test data management ensures that the data is validated first and then used for testing purposes. Only validated data can show you a real picture of the production environment when you deploy the software product in the live environment.
Building test data for Reusability
Can you reuse the available data for testing other applications? If not, the cost of your software development will touch the sky. If you want cost-effectiveness, you need to ensure that you have the test data that can be used in different testing practices. You need to ensure that the data is built and segmented for reusability. Stored and accessible from a central repository, it must be used multiple times to optimize the testing practices.
When you make data reusable, you will get some key benefits. First, the bottlenecks and other issues will be removed from the data and can be accessible to various teams as and when they want it.
Automation can accelerate the process
Some of the key elements of test data management are scripting, data masking, generation, data cloning, and data provisioning. When you automate all of these elements, it will make the whole process more efficient and error-proof. During the development and software testing process, data automation ensures that the developers and quality analysts get the best quality data in the needed format. Not just that, you can also automate test data production. It will reduce the time and efforts you spend on software testing and help to identify and address any errors or issues with the data. The QA team would be in a better position to streamline its test data management practices.
Conclusion
Data is new knowledge and the best test data management practices can help you build your brand in the most meaningful manner. It helps to build the test environment with the required data sets and also ensures that the software product you release performs excellently without any functional issues. All the aspects of the application from functionality, performance, security, and other aspects are tested perfectly with the help of test data management practices.
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