Friday, 11 August 2023
In the legal sector, where Document Management, Practice Management, Billing and Time Recording intersect, the digital transformation journey is reshaping the way legal enterprises operate, but it does make good quality testing even more important. Fee earners are the lifeblood of the legal and professional services sectors, which makes downtime very expensive very quickly. This ensures the role of test automation is vital to carrying out regular and meaningful regression testing while avoiding significant costs.
However, the efficacy of test automation pivots on the bedrock of quality and relevant test data. This is where test data management, in conjunction with anonymisation techniques, assumes critical importance. In this blog post, we delve into test data management and anonymisation to highlight their role in ensuring automated tests are meaningful, accurate and trustworthy to provide decision-makers with the right information before changes are implemented that could affect the firm.
Test data forms the canvas on which automated tests are crafted, enabling a simulated environment for applications and providing the necessary confidence to implement change in business-critical environments. The absence of authentic test data can potentially obscure software quality, leading to undiscovered issues and compromised outcomes.
Test data management ensures the continuity of data across testing phases and environments. This consistency is pivotal for the precise comparison of test outcomes, enabling swift identification of enhancements or regressions.
A robust test data management framework allows for efficient data reuse across varying testing scenarios, reducing redundancy and optimising the utilisation of resources. This reusability underpins comprehensive testing, ensuring diverse functionalities are thoroughly validated.
Data Privacy and Compliance:
In the era of stringent data privacy regulations, using sensitive information during testing is non-negotiable. Anonymisation techniques are used to strategically obscure or replace personally identifiable information (PII) while upholding data structure and authenticity, while today’s tools are able to maintain referential integrity links between tables, even once data has been changed, where production data is used as the source.
- Randomisation: Leveraging randomisation, actual values are replaced with meticulously structured simulated data. This approach ensures data integrity while safeguarding sensitive information such as names, addresses, and contact details.
- Data Masking: Data masking selectively veils sensitive data elements, providing an added layer of privacy. This technique obscures credit card digits or other identifiable segments without compromising data structure.
- Tokenisation: Tokenisation replaces sensitive data with secure tokens, ensuring original values are securely stored. This amalgamation of security and realism strengthens data protection while maintaining testing fidelity.
Data Generation Techniques:
The integration of authentic test data and test automation can be produced without using real data as a source, using data generated from scratch. Techniques include:
- Synthetic Data: Crafting fictional yet characteristic data mirrors real-world data, a valuable strategy when genuine data is scarce or privacy concerns are paramount.
- Data Subsetting: Data subsetting allows for precise extraction of relevant data from larger sets, honing in on specific legal scenarios pertinent to practice management, document handling, or time recording.
As legal firms increasingly entrust their critical operations to software, the fusion of test data and test automation becomes the cornerstone of software quality. Empowered by advanced test data management tools and anonymisation tactics, legal enterprise applications can elevate their performance, ushering in streamlined processes, fortified data privacy, and elevated user experiences. This strategic integration sets the stage for legal firms to navigate the digital landscape with confidence, ensuring efficiency, security, and excellence at every turn.
Prolifics have developed our own in-house Test Data Management tool: TiDiuM. Our tool is able to quickly generate or anonymise large quantities of data, which is a vital part of ensuring software testing and QA can run accurate and scaled simulations and generate meaningful results without having to rely on production data or compromising on lower volumes of test data, which may affect the quality of the tests.
Click here to connect with one of our Test Data Management experts for a no-obligation discussion and how we can help.
Jonathan Binks - Head of Delivery
Prolifics Testing UK