Test data management best practices assure thorough testing, guard sensitive data, comply with regulations, improve test results, and reduce testing costs.
Table of Contents
1. Start with the Test Data Strategy
2. Discovering Test Data
3. Protecting Private Data
4. Refreshing Test Data in Real Time
5. Ensuring Test Data Relevancy
6. Maintaining Test Data
7. Automating the Test Data Management Process
Speeding Up Software Delivery Cycles
As the need for relevant production-grade test data grows, enterprises operating increasingly spend too much time and effort in provisioning test data, leading to inefficiencies and slowdowns in software delivery.
That’s why it’s important to establish and follow test data management best practices. The following 7 guidelines bring much-needed structure to test data management and ensure that all the key components are considered.
1. Start with the Test Data Strategy
The very act of building a comprehensive test data management strategy forces you to understand your test data landscape, and the different teams across the organization that will use the test data and contribute to it. Your plan should support your test data needs, testing environments, your company's data governance policies, and relevant data privacy regulations that impact test data handling. Starting with the test data management strategy will save time, overhead costs, and rework.
2. Discovering Test Data
The first test data management best practice is to discover, integrate, and organize test data from multiple source systems and IT environments, across the organization. To achieve this, enterprises should identify all the relevant data sources early on in the process. This includes discovering and categorizing all sensitive data and Personally Identifying Information (PII) according to relevant data protection regulations (e.g., GDPR and CCPR), and industry legislation (e.g., HIPPA and PCI).
3. Protecting Private Data
Today, PII is a sensitive topic as consumers and authorities become more aware of the dangers of collecting and using people’s private information. Your test data management tools must support specific compliance rules, such as those included in GDPR or CCPR, that often demand the highest data masking standard.
When sensitive data is involved, data masking keeps it protected. When data masking tools are able to anonymize data in a lifelike way – without exposing the real data – both authenticity and compliance are assured. Another security aspect to consider is how the test data is stored and managed. Keeping test data accessible only to authorized personnel, and maintaining security protocols, even for apps under development, are essential.
4. Refreshing Test Data in Real Time
Perhaps the most important factor in test data is keeping it adequately fresh. Due to the sheer volume of enterprise data, many enterprises refresh their test data only periodically, such as once a quarter. Since extracting and provisioning test data is time-consuming, testing teams often reuse old data, over and over again. To maintain the relevance and trustworthiness of test data, a real-time synchronization mechanism is needed that doesn't require bulk database copying. Another important factor is ensuring that production system performance is not adversely impacted by frequent access.
5. Ensuring Test Data Relevancy
Time isn’t the only factor impacting the relevancy of test data. Testing quality relies on the ability of the testing teams to source relevant test data to the use case at hand. Due to the complexity of this task, traditional test data management solutions discourage testers from parameter-based subsetting, especially across multiple source systems. Testing teams should be able to define which data is needed for their particular test scenarios, and build the test data subsets accordingly. Not only will the test datasets be relevant and focused, but they will also improve test data quality and accelerate software delivery through continuous testing.
6. Maintaining Test Data
Keeping your data fresh and relevant over time leads us to the next test data management best practice, which is ongoing maintenance. In addition to relevancy and accuracy, your team would need to ensure that the data is adequately stored, remains consistent, and error-free. This level of quality should be maintained as multiple testing teams use the data and refresh it at different times. Enabling test data reservation, versioning, and rollback, at the individual tester level, is critical for maintaining data quality. Provisioning test data at scale is challenging, so this is one area where the importance of test data management stands out. Be sure to monitor the cost efficiency of your test data storage solution, and perform regular audits to examine the integrity, quality, and compliance of your test data.
7. Automating the Test Data Management Process
By now, you’re probably concerned about the many tedious tasks related to test data management best practices. Worry not, because many test data steps can, and should, be automated. Automation makes test data provisioning faster, and helps minimize human error. Agile software development and a shift-left testing approach demand test data automation for integration into CI/CD pipelines. Best practices for data testing have become increasingly automated over the past years. The entity-based test data management approach makes this possible.
