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Getting Personal in Application Development

In this blog, we explain how the new GDPR legislation will potentially impact the testing and development of new systems, threatening to put the brakes on digital transformation. With proven solutions for the creation of consistent, reliable, right-sized fictitious data sets, Northdoor can accelerate and simplify data masking, enabling speed and GDPR compliance to go hand in hand.

The General Data Protection Regulation (GDPR) brings far-reaching changes to how businesses and public bodies store, process and manage personal data. Specifically, the regulation requires organisations to protect personally identifiable data on EU citizens, on pain of multi-million Euro fines for non-compliance.

For software testers and developers, the best way to ensure that a new application will perform as expected is to use real data. Generally speaking, existing data protection laws in the UK already restrict the use of genuine personal data, such that all software development teams already (or should already) use either fictitious or masked data.

However, in light of greater stringency imposed by the GDPR, and given growing expectations about time-to-market for new or updated applications, most organisations should review how they currently manage the creation of fictitious or masked data. For dummy data, they will need to ensure that creation is accurate and highly automated. And for masked data, they will need to ensure that the process is reliable (read: irreversible) as well as fast and easy. Speed is especially important in organisations that follow DevOps principles, where near-continuous cycles of testing demand rapid handling and low costs.

Equally, as organisations add new sources of data at an increasing rate, software testing and development teams need reliable, automated ways in which to create or mask new data sets for use in applications.

Fast, Reliable, Low-cost

Using tried-and-trusted technologies, Northdoor provides a comprehensive range of solutions that make it easy to mask data from any variety of structured data source, automatically creating new and unique reference codes for each masking run. In-built custom routines enable organisations to mask, blank, anonymise or pseudonymise personal data precisely as required. The solutions also enable the easy generation of valid sample data for use in system development or training, significantly reducing both the cost and the potential for error.

For more information on how your organisation can meet the internal appetite for data from testing and development groups while remaining GDPR-compliant, click here for more information.

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