The enormous amount of data in circulation has allowed enterprises to automate, advance, or accelerate business development with the help of agile methodologies. The automation advancements require rigorous testing for business operations or software development. Thus, it is crucial to manage and streamline quality test data. This test data is used to build real-time scenarios and test data for building business operations or software development. The test data helps businesses make better and more informed decisions while developing software. It helps foresee any bugs in real time and improves the product’s performance. As the development or testing team usually spends the most time looking for reliable and quality test data, there is an obvious need for a practical test data management (TDM) strategy for ensuring testing completeness and coverage. Any good test data management solution can help to reduce operational business risk and maintenance costs by delivering updated and effective systems.

Due to various challenges, most enterprises fail to recognize the need for test data management in their software development initiatives. Failure to implement a seamless test data management strategy can significantly hinder automation advancement and business ambitions. To stay relevant in a competitive market and offer unmatched customer experience, it is crucial to emulate real-life conditions during the application or software testing cycles. In an attempt to make realistic data for development initiatives, but as a massive volume of diverse data is collected every day, the management of this volume can be revolutionized by the test data management solution. 

Test data management helps businesses create, design, store, and manage data sets that resemble or mimic the production data for developers to perform the test cycles. It ensures reliable and quality test data promptly to the testers – thus, giving control to the testing team on the data.

According to a report published on Verified Market Research, The test data management market was valued at $726.1 million in 2019 and is projected to reach $1,752.5 million by 2027, growing at a CAGR of 11.6% from 2020 to 2027. 

How to Implement a Successful Test Data Management Strategy

Some successful strategies for implementing test data management are discussed below:

Understand the Test Data Requirement 

The software development lifecycle has test data dependency; therefore, testers require timely quality data. Throughout the lifecycle, test data perform testing on different interfaces. Thus, various sources and types of test data are required in different formats and types depending on the sources. Analysis of the end-to-end business process and the associated data type for testing is a fundamental step for implementing test data management. Designing test cases helps to understand the test data ensuring ‘fit for purpose’ and timely data availability. The analysis involves awareness of the business domain that requires test data. For instance, developing an IoT mobile application would require more customer-centric test data. 

Create and Obtain Test Data

Once the analysis of the type of data is complete, the next step is to create or obtain test data. The process of creating test data can be done in several ways, involving creating unique synthetic data, or sourcing real-time data from the production environment, for example, from real users. A combination of both strategies can also be used to create test data.

Prepare the Test Data

After the test data is created, the data is prepared for all the designed test cases. The test data is prepared to ensure completeness and accuracy for its use. Data production and legislation compliance are also ensured when creating test data from the production environment. For example, personally identifiable or confidential data (like names, addresses, phone numbers, email addresses, and customer orders) or an organization’s sensitive information is always masked before using it as test data sets. Thus, protecting sensitive data from leaks and unauthorized access within test environments is critical. 

Data Maintenance and Refresh

Copying accurate production data creates and provides different data subsets for all the test data requirements. As the data subsets provide accurate, reliable, and consistent test data, this sensitive information must be masked and updated periodically. The maintenance of test data ensures that any obsolete or redundant data is removed and replaced with the most relevant test data for testing.

Pick Platform-Based Approach

Implementing a test data management solution that functions across different interfaces within a business domain is always challenging and cumbersome. An enterprise mainly involves heterogeneous data sources and thus requires a versatile platform to support data flow. Such platforms can help streamline test data management across the heterogenous environment even within a single business domain. The selection of the right platform for test data management helps faster delivery of test data for application development and more opportunity for innovation about the specific business requirement.

Conclusion

A test data management strategy helps administer test data for the test automation process with minimum human involvement, errors, and delays. Many test data management platforms offer capabilities to create and design quality test data. Thus, a platform providing a complete solution as per the business requirements is needed to make correct data more accessible for a variety of test cases.