Managing Test Data Environments

Data teams must ensure that the data they use for testing is safe and complies with privacy regulations. It’s also critical to ensure that masked test data maintains referential integrity.

Managing a high-quality testing environment can be challenging. It requires ensuring that the test environments mirror production systems, but aren’t too restrictive.

Requirements Analysis

A key component of a successful project is understanding stakeholder requirements. Having these documented prevents scope creep. Stakeholders should be asked to sign off on the requirements document, as this makes it difficult for them to change their minds later. This ensures that the final product meets their needs.

QA environments must mimic real user conditions as closely as possible. This includes the same hardware (like smartphones and desktops), browsers, and networks that users will encounter. This helps development and testing teams find bugs before they reach production.

This requires a centralized repository for data that’s easy to update. A streamlined test data management (TDM) process uses automation to provide an ephemeral data environment that’s ready for testing. This is typically done using continuous integration tools like Jenkins. It also unifies technologies for target database initialization, configuration steps, and synthetic data creation so that they’re all automated. Having this low touch approach reduces the time it takes to refresh an environment.

Data Sources

Often, companies struggle to find or create large volumes of accurate test data. This can delay testing and negatively impact application performance.

When it comes to testing, it’s crucial that your test data represents real-life operating conditions and is accurate. Moreover, the data must be securely masked to ensure privacy and regulatory compliance.

With the growing reliance on digital channels, businesses want their applications to offer seamless and uninterrupted customer experiences. This can only be accomplished by strict QA checks, which depend on a reliable and robust testing environment.

Using the TechArcis TDM and TEM services, your business can streamline the processes of creating, preparing, and managing data sets to test applications. This allows for the quick fulfillment of ticketed demands and the creation of new environments as demand changes. The centralized repository also reduces manual work for operations teams to minimize data management costs. In addition, a centralized repository helps to ensure that all data is consistent with the production environment.

Data Masking

Data masking replaces sensitive production data with fictitious values in nonproduction environments for development and testing purposes. The process must be repeatable and as automated as possible to reduce risk and enable speedy development.

Depending on the type of data, there are several masking techniques to choose from. Substitution involves replacing a value in the database with another, for example replacing “Adam” with “James.” Nullification, on the other hand, encodes the original data by removing its distinctive attributes, such as zip code or bank account number, while retaining its characteristics.

For example, Independence Health Group uses Informatica Dynamic Data Masking to mask member names, birthdates and social security numbers in real time as developers pull down data sets. This ensures that the masked data is not easily reverse engineered and that referential integrity is maintained across databases.

Refreshing

A refresh of a test environment involves updating the test system with fresh data so that developers can see how the system works with real-world information before it’s released to the public. This ensures that the system can handle updates, and that the software is accurate before it’s deployed.

Whether a test environment is long-standing and permanent, or ephemeral (spun up for a specific code branch), it must be refreshed regularly to maintain accuracy. If a refresh is not performed, the system will become out of date and tests may fail with errors as well as Synthetic Data.

Refresh processes are complex, and research on optimal refresh policies is ongoing. The key to a successful refresh strategy is based on understanding the goals of your test team, and aligning them with the continuous delivery methodology your team is using. This includes assessing the impact of refreshing test environments on teams’ ability to deliver code quickly and reliably. This will allow you to make the best decisions about how to refresh your landscape.