Test data management is currently one of the most time-consuming and resource-intensive concerns in today’s testing environment. Every test project necessitates the collection of data. However, just about 31% of businesses today have a specific test data strategy. Furthermore, production data is stored and integrated across various legacy and new enterprise systems that are constantly changing. As a result, extracting, using, and concealing production data for testing is a significant difficulty. Teams struggle to maintain data integrity and comply with data privacy standards. How can we ensure that test data is managed consistently across business architectures during testing? What are the most successful TDM tactics for agile teams to use?

Test Data Management Strategies

Having an excellent test data management approach will help you release software faster and more efficiently. Most businesses rely on manually creating test data from start using excel, word, or test files, which is a time-consuming and labor-intensive procedure that inhibits agile delivery. Preparing test data can also be done automatically. This process can be automated to boost ROI and test automation efficiency. There are powerful TDM technologies available to help you mask or subset data from production or generate synthetic data. However, very few businesses automate test data – only 21% utilize some type of test data automation technology or method.

What exactly are you testing?

Gain a thorough understanding of the applications you’re evaluating across the business environment. What, for example, are the business requirements, the end-to-end flow of the applications under test, the user stories, or the test objectives? Having this knowledge allows you to plan ahead of time which test data you will require and which test data approach you will employ to ensure more efficient testing.

How are you going to prepare the test data?

Plan your test data preparation approach. In other words, how will you collect the data required for your testing? Copying production data, masking production data, or generating synthetic data are some common methods being applied today. Bear in mind, a good test data management tool can eliminate the need for users to create data manually, which can save costs and impact your speed to market. Also consider how you will ensure data privacy and compliance and prevent breaches of PII and sensitive data that can jeopardize your business.

How will you communicate test data while maintaining consistency across end-to-end flows?

Ensure that the test data is easily shared, retrieved, and managed across distributed teams or environments. This is critical for reducing data inconsistencies. As test data is used throughout business process testing, it is critical to maintain an effective approach for continuously updating and tracking the data.

Opkey’s Test Automation TDM Solution

Opkey uses patent-pending Test Mining technology to autonomously mine test data from the client’s environment and guarantee it is in the proper format.

Opkey’s test data management solution is especially useful when QA teams need to run several testing cycles during migration or when performing regression testing. To summarize, Opkey’s TDM solution saves businesses time and money by ensuring that their test data is always ready for ERP testing.