In today’s digital landscape, data is considered the new gold. Companies and individuals are collecting, analyzing, and using data to make informed decisions and develop innovative solutions. But while data collection takes center stage, it is often overlooked that deleting data that is no longer needed is just as important.
The obligation to erase data is a principle enshrined in law, which is set out in Art. 17 GDPR and § 35 BDSG. It obliges companies and individuals to delete data that is no longer required and whose purpose has ceased to exist, provided that this no longer conflicts with statutory retention periods. This also serves to minimize the risk of data breaches and data loss. In the past, deleting data made economic sense due to expensive storage media. Nowadays, the focus is on reducing both the risk of losing unneeded data and the risk of using unwanted data to avoid penalties.
The penalties for breaches of the deletion obligation can be significant, amounting to up to 4 % of the previous year’s gross annual turnover. This applies in particular in the area of data protection for natural individuals. Sensitive data, as defined in Art. 9 GDPR, so-called special categories of personal data, include a variety of information, including personal characteristics such as gender, sexual orientation, and health data. This data must be protected by technical and organizational data in accordance with Art. 32 GDPR are specially protected and deleted in accordance with the legal requirements as soon as their processing purpose has been fulfilled and there are no longer any legal storage obligations, such as for patient files in accordance with § 630f BGB.
The solution: a deletion concept
An effective deletion concept is therefore essential. It requires careful data categorization to ensure that unnecessary data can be identified and properly removed. Possible backups must also be integrated into the deletion concept. For this purpose, deletion classes are formed and the data categories formed are assigned to the deletion classes. All data categories with the same start time and the same deletion period are combined into one deletion class. The start time can either be when the data is collected or at the end of a process or relationship. The next step is to define the deletion rules to be applied for each deletion class. Before the final deletion, a check of the exceptions/deviations must be carried out.
The implementation of such a concept enables companies and individuals to optimize the data inventory, minimize risks and ensure compliance with legal regulations.
Data categorization plays a central role in this process. It allows data to be classified according to its level of protection and protection requirement class.
In the healthcare sector in particular, where different retention periods apply to different types of data, precise categorization is essential.
Overall, erasure compliance is a crucial aspect of data protection and requires careful planning in order to both meet legal requirements and minimize the risk of data breaches.
Source cover image: KI