Scholarly record

GDPR COMPLIANT METHODS OF DATA PROTECTION

T. Pikulik, P. Starchon

Abstract

(CRM, Customer Relationship Management) and solutions for data storage that are usually set and implemented by their headquarters. Need to maintain large stores of data and personal data not excluded are managed by IT, multiple-used in terms of time and aim by analytics (DA, Data Analytics) - e.g. for profiling, data mining, segmentation and other specialists (PDPs, Personal Data Protection Specialists / DPO, Data Protection Officer etc.), performed and controlled by internal controlling department (BI, Business Intelligence). Big Data Management set usually three main principles (i) to secure the dataset (ii) to manage the quality of large stores of data (iii) to ensure the accuracy without redundancy. These main principles have also opposite meaning in possible consequences (i) to secure data protection (ii) to manage standardization and utilization of dataset (iii) to eliminate inaccuracy in large stores of data. All that principles in one eligible to use one of two GDPR-compliant methods - Standard encryption or Pseudonymization. These techniques allow and play a significant role in data privacy (PDP, Personal Data Protection). Furthermore, we pinpoint selected “white spots” in potential of pseudonymization/anonymization in big data (BDM - Big Data Management) and draw attention to promising areas for future research and directions of future development of these methods.

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DOI resolver: doi.org/10.5593/SWS.ISCSS.2019.2/S05.069

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