Test data management (TDM) is an integral part of the modern DevOps lifecycle. But shifting left Agile methodologies is the new normal in today’s development environment. That means pivoting away from traditional tools toward solutions that protect sensitive data, optimize processes, and speed up and streamline bug detection.
Is your test data management strategy lagging behind? Perhaps your time to market is hampered by the requirement of very specialized skills that not all of your development team has honed. The time-consuming nature of TDM is what makes modernizing it so critical in today’s testing automation-oriented software development life cycle.
Let’s cover the ins and outs of TDM processes, best practices, challenges, the best tools for the job, and how automated testing can optimize your software testing for better products, happier development teams, improved testing life cycles, and lower costs.
This blog will answer the following questions and more.
Shifting left puts ever more focus on decreasing time to market, cutting costs, data security, data privacy, and faster application uptime. So, let’s start with the basics: what is test data management?
TDM is how developers and testers craft, manage, and deploy test data for application teams. Quality test cases, test coverage, and test data management processes can contribute to Agile development. Moreover, automation tools can further help your team surmount test data requirements.
Managing test data requires three core elements in your approach.
The life cycle of any test data management process involves 5 key steps:
The term TEM stands for test environment management so it deals with the areas in which test data lives. The environment should be stable, validated, and able to be used for bug replication and test situations.
There are four main types of test data and developers must construct a set of strategies and tools that address all data types. The type of test data that teams encounter usually falls into one of the following categories.
Data testing requires the best test data management tools for the job. Finding the best one for your needs comes down to a few criteria such as:
Traditional TDM tools and testing approaches entail cloning a production base (including or excluding subsets). However, this risks data security and privacy, lacks parallelism and data collisions, doesn’t account for infrastructure costs like archiving data or complexity, and still requires a ton of specialized expertise or scripting with synthetic data generation.
Instead, leveraging data simulation with tools such as Parasoft Virtualize removes shared dependencies thus reducing complexity. It also enhances a team’s ability to address rare use cases and isolated test suites. You can read more about modern TDM approaches and data virtualization in this blog.
Regardless of data sources, good test data must be available when needed, of good quality, compliant, and realistic. Validation of data quality and more goes beyond expected results in the best data strategy.
While this might go without saying, the better quality ingredients you use, the better your meal will be at dinner time, right? The same applies to test cases, code, and testing. Furthermore, parallelizing testing improves speed. Getting better quality test results from better quality testing data is critical in Agile methodologies.
Maintaining the security of test data is just as paramount nowadays as obtaining actionable results, especially when it comes to government compliance. The GDPR dictates that you cannot use real data for testing which is why data masking has become a key strategy. Planning for your test environment, test standardization, and data security will improve project speed and quality.
But you can’t leverage this momentum without proper storage and maintenance. Test data audits must be done often to ensure accuracy, safety, and data integrity.
Leveraging the data you really need is pivotal when it comes to an Agile TDM. Think of it like this: if you just grab clothes from your closet and put them in your suitcase, you might not have the items you need for your trip to Chicago in December. In the same way, determining what kind of and how much data you need for your testing process matters when building test cases.
But performing a data refresh also affects its relevance. While you do need to reuse whenever you can, you don’t need to keep out-of-date or stale data that you can’t use anymore. Delete irrelevant data to make room for new data that can provide further insights.
The testing process doesn’t have to be a long, arduous slog. Automating repetitive processes can alleviate pressure from development and free up time to focus on other projects. By making use of automated testing, you can provision data faster, reduce human error occurrences, integrate into continuous integration/continuous delivery pipelines (CI/CD), and more.
Automating regression testing is an easy first step in the automation process. But testing teams can also look to automate things like test data production as well. No matter what your data needs or testing purposes might be, automated solutions for functional tests, performance tests, and more are must-haves in your test processes.
Common test data management challenges tend to involve the same kinds of things such as:
Parasoft Virtualize focuses on the A, B, C, and D of test environment destabilizers. A is availability, B is behavior, C is cost, and D is data. Attaining consistency in these areas is critical in the shift-left approach. But many issues with TDM relate to how time-consuming and knowledge-heavy it can be.
See how to create assets, manage test data, and monitor test environments with Virtualize.
Automation can’t replace human expertise, but introducing a proxy between the backend and any application under test enables the proxy to act as a traffic cop. What’s more, our user-friendly UI makes test environment managing a less daunting task, as well. The Continuous Testing Platform (CTP) works with Test Data Manager to visualize the data in a more accessible manner. You can even search with keywords and view results in text-based or tabular formats. In essence, service virtualization can be an optimizer for the whole workflow.
Jeff Peeples is a Senior Product Manager at Parasoft, leading the functional platform direction for SOAtest, Virtualize, and CTP. Jeff has extensive experience defining solutions and developing roadmaps for enterprise industries including energy, financial technologies, and travel/hospitality.