Cybercrime, GDPR, and data anonymization. These topics are also becoming increasingly relevant to non-production systems. And software tests should also be as meaningful as possible with anonymous data. Finding a suitable answer for this is complex, and the complexity of the topic means that many projects almost fail. Our expert shows you his three main challenges in data anonymization projects in non-production systems and explains how to master them successfully.
Challenge 1: Stakeholders underestimate the problem of data anonymization
One project, many stakeholders, different perspectives: During my career at Libelle, several stakeholders’ efforts to anonymize data were fraught with problems from the start. For example, the stakeholders disagreed on data anonymization in non-production systems. While it was essential to some that the addresses are logically correct after anonymization, others have entirely different priorities. Therefore, before starting a data protection project, define clear goals with everyone involved and ensure a consistent level of knowledge.
Challenge 2: Project management too complex
Do you want to successfully chief your data protection project? Our recommendation: be pragmatic. Define one (!) project manager and only identify the relevant systems for data anonymization. Divide the personal data into profiles (names, addresses, bank details, etc.) to receive a structured description. In times of big data and IT becoming increasingly complex, a procedure that is as simple and structured as possible is essential.
Challenge 3: A non-iterative implementation
Once you have chosen a provider for data anonymization on non-production systems, it is vital to take an iterative approach to implementation. The project does not end with the final decision; every plant scenario is different. Therefore, iterative validation of test systems, anonymized data, etc., is necessary for the project’s success.
Are you also thinking about optimizing data anonymization in your non-proactive systems? Then our experts, Miroslav Jakovljevic and Michael Schwenk, will be happy to help you anytime. Feel free to contact them for an individual consultation. For optimized data anonymization and the best possible project success: Libelle DataMasking.