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By Mariann Utrosa • July 29, 2020

Test Data Management - Simplified

test-data-managementData is the heartbeat of every business application and having a proper testing strategy is essential.  Data is, after all, a business’s most valuable asset, data breaches bring Enterprises to the ground!

Protecting real data and managing how data moves from non-production to production or vice versa is critical.

Test Data Management (TDM) is gaining a fast traction of importance in the Enterprise, especially when non production environments require meaningful data that represents a production quality.  Whether you’re rolling out new features, performing software updates, or validating data to ensure quality testing, using real time data is often very dangerous.

The Challenges

High quality data can provide an abundance of useful information to businesses, this often involves the use of different tools and procedures that come with associated risk and business challenges. It’s important to take these into consideration and plan accordingly. Some challenges of TDM are;

Data Validity and Consistency

Over time data ages; it can become stale. Proper versioning of data is important to maintain accurate data sets. You also need traceability at an end-to-end level, from inception all the way through the data exchange life cycle. The integrity of your data must be maintained. If you allow data to age you may not be able to trace the data and validate its integrity, and could prove to be very difficult to troubleshoot any issues that arise. For example, in order to successfully capture an audit trail, the above observations must be considered, and in most cases, all should be met.

Data Privacy

Many applications contain sensitive Personally Identifiable Information (PII). There may be government mandates and regulations in place that stipulate the data must be masked, de-identified, or encrypted. Without a solid process to protect that data there's a real risk that valuable and personal information could be leaked and used in a malicious manner. A data breach can be extremely expensive to recover from; it can damage reputations and often results in lawsuits and punitive fines.

Data Selection and Sub-setting

You need data that is relevant to the context of what you're testing, but how do you manage datasets effectively? You'll want to use a smaller subset of data in a scaled-down, non-production environment, while mimicking the production environment. If you don't get your selection right, test coverage won't be as good as it should be. Ensuring you have the minimal viable subset to meet the application quality requirements is a must.

Compliance and Privacy Laws

The European Union’s (EU) General Data Protection Regulation (GDPR) came into effect May 2018 and requires companies to delete all instances of the EU's Personally Identifiable Information at the consumers request, otherwise known as, “The right to be forgotten”.  The GDPR also requires consumer consent to use their data for any purpose, including application testing.  This means that if organizations use: real and unmasked customer data in their testing they are now violating the GDPR which results in hefty fines.

It’s not just the European Union that needs to be mindful, any company that possesses data on EU based consumers need to comply – including all North American companies.

Best Practices and Essential Steps

When implementing a secure Test Data Management solution, following a few steps can help simplify the testing process by applying these 5 best practices to Test Data Management before going to production:

  • Discover and understand your test data,
  • Extract a subset of production data from multiple data sources,
  • Mask or de-identify sensitive test data,
  • Automate expected and actual result comparisons,
  • Refresh test data.

Wrapping it All Up

Test Data Management is a challenge for most organizations and creating a process to manage your data is quite the undertaking. 

Implementing a network-based solution like DataStealth enables companies to adopt a secure TDM approach that facilitates a self-serve model for developers and testers to access new test data sets, remove manual intervention, and eliminate any infrastructure requirements of master 'golden copy' and / or derivative test data sets.

Enable the convenience of automated Test Data Management while ensuring the highest degree of security and compliance in your organization, globally.