Anyone working with test data, analytics or data provisioning will quickly come across terms such as masking, de-identification, pseudonymization and anonymization. In day-to-day project work, these terms are often used loosely, even though they describe different protection approaches. For IT teams, the distinction matters when data needs to remain usable
Data masking is a crucial process in software testing, particularly in the procurement of test data (TDM). It involves altering data to protect sensitive information while maintaining the data’s usability for testing purposes. Here is a look at how effective data masking can improve software testing.
To optimize the user interface (UI) for XDM, UBS Hainer recently conducted a comprehensive usability survey with several of its customers. The interviews provided valuable insights into user experiences and identified potential areas for improvement.
Digital technologies have introduced new business models that pose strategic challenges for companies, particularly in the field of Data Governance. Procuring and maintaining high-quality test data, as well as meeting software testing requirements, are critical factors in this context.
Company management must comply with mandatory regulations, such as GDPR and others. Our customers look at such externally mandated projects as a chance to enhance efficiency in software development.
This article outlines the benefits of utilizing an automated test data provisioning tool like XDM from UBS Hainer and highlights the key requirements necessary for maximizing its effectiveness.
The need for continuous deployment also emphasizes the importance of continuous testing. In an interview with Christoph Stock, Product Development Manager at UBS-Hainer, we asked if the implementation of this process can be achieved without test data automation?
