Test Data Automation for Agile Development: Keeping Up with Your Sprints

Automation is everywhere and must for businesses to achieve high-quality results at a faster speed. That’s true in the case of test data management as well. The old and manual TDM practices not only restrict the QAs but also hinder the development speed and agility. The major challenge with these practices is compliance risk which can lead to some serious financial and legal problems.

Test data automation is one way to avoid these predicaments, especially when managing multiple test cases.

What is Test Data Automation?

The process of creating test data for a product, and then automating the creation of that test data is called test data automation. Various automation testing tools are available for this purpose, but one must carefully select the tool as success of software testing depends on the features of automation tools.

Selenium and Appium are the two popular automation testing tools in the market. For testing web applications on multiple browsers and OS, selenium is the best whereas Appium’s high compatibility make it the best tool for testing mobile applications.  

What is the Need?

The need for test data automation comes when you're writing tests for your applications. The more tests you have, the more time it takes to write and run them all. And if you're writing tests that are complex enough to warrant special attention, they can take an even longer amount of time to complete.

Test data automation helps solve this problem by creating new test data automatically as you run your tests. This means that all your tests can be run at once, saving time and energy on managing them all separately.

Another reason why automation testing makes sense is to reduce the waiting time for getting the right test data. On average, it takes more than a week or several weeks to get the right data. It is because either the process is not started or there is a problem with the test data refresh.  

Benefits of Automating the Test Data

Automating test data management brings several benefits to software development teams.

• Increase efficiency and productivity: Automation testing tools reduce the manual effort required to create, manage, and maintain test data. This leads to faster test execution and quicker feedback to developers, which can increase productivity and reduce time to market.

• Improved quality: It ensures that tests are performed consistently and accurately, reducing the likelihood of errors and defects in the software thus improving the overall quality of the product.

• Better data privacy and security: With the increasing focus on data privacy and security, automating test data management helps keep sensitive or confidential data protected. Creating and managing synthetic test data that does not contain sensitive information is the way to ensure the complete security of data.

• Cost-effective: Costs associated with manual test data management and maintenance are very high. This can include costs related to creating and maintaining test environments, storage costs, and labor costs. Automation reduces this additional expense making the entire process cost-effective.

• Scalability: As software development teams continue to scale, managing test data manually can become a significant bottleneck. Automating test data management allows teams to quickly create and manage test data at scale, ensuring that testing is not a bottleneck in the development process.

• Accurate test data: Accuracy of test data is a must when working with fast-changing systems. Automated test data ensures that every time system gets a unique combination of data to avoid any clashes during execution.  

• Faster test data provisioning: Manually creating and maintaining data leads to delays in providing the variety of data required for testing and development. A further problem arises when the test data is outdated or incomplete. Test data automation resolves this through integration with database orchestration and virtualization so that test data copies are available parallelly for testing and development.

• Rich synthetic test data: When doing rigorous testing, synthetic test data is very useful as it provides all the negative scenarios and data combinations that do not exist in production data. You can make this data even richer with test data automation without worrying about the risk of disclosing any sensitive information. Here, the metadata of production is used to create synthetic test data.

• Test data masking for compliance: Manually masking the test data consumes a lot of time and is also a complex process. But automation makes it quick and simple by making the masking rules reusable to transform the data across multiple sources in a consistent manner.

Best Practices for Automation of Test Data Management

Besides choosing the right automation testing tools, you must know the best practices as well. Here we have discussed a few of them.

It Should Always be Externalize

Keeping your test data externally in forms like .property or .csv will help you greatly in the future as data is never going to remain constant. It would keep evolving and changing with time. But this change should not affect your code.

Take Multiple Test Environments into Consideration

When testing an application, always consider multiple test environments so that you can easily manage the test data. Here, you can split the data into two different categories- common data for all environments and specific data for a particular test environment.

Avoid Using Excel as a Source of Test Data

The reason we don’t recommend using excel is the performance and maintenance issues. Reading and writing in excel is slow as compared to different file formats for test data sources such as .properties, and .csv. Furthermore, excel comes with the burden of maintenance as external APIs are used to read excel. This could lead to version incompatibility in the future causing you to spend time and effort on maintaining excel.

Conclusion

Each stage of the software delivery lifecycle is at risk with manual and outdated test data management practices. Legislative compliance is the major risk that businesses face because of it. Switching to test data automation not only avoids all these bottlenecks but also fulfils rapidly evolving data requests with ease and security.

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