Sap Se

Volker Lehnert

Carsten Pluder

Bjoern Christoph

Johannes Gilbert

Marco Valentin

Joerg Wiederspohn

An identifying data set is defined including semi-identifying attributes with semi-identifying attribute values corresponding to an entity. Descriptive records corresponding to the semi-identifying attributes are created. Based on the descriptive records, retention records with retention attributes are created. A composed retention attribute is generated based on applying cryptographic hash algorithms to the retention attributes stored in a database. A retention attribute description is generated with a category and payload corresponding to the composed retention attribute. The semi-identifying attributes with corresponding positions are stored in the retention attribute. Hashes corresponding to the retention attributes are computed based on a composing mechanism that includes logic to compute the hashes. The hashes are combined to generate the composed retention attribute. When a request is received to permanently delete the entity from the database, the entity may be permanently deleted from the database.

Data retention management in databases

A consent management system (CMS) manages a number of individual consent data records of data subjects. The CMS stores predefined consent templates to be instantiated when an individual consent data record is created. The CMS represents a centralized system for management of individual consent data records that are created, stored, and maintained in relation to provided consent by data subjects for purposes of operations related to stored personal data records by associated application systems. The CMS may run on an on-premise, cloud, or personal device computing platform.

Centralized consent management

A data information framework collects related data sharing characteristics (e.g., personal information, others) revealed by associated purpose information, and reports on that data. The location of the data is not restricted, and can be collected from various locations (e.g. different databases on different computer systems). An engine implements data creation defining links between different stored data structures (e.g., tables) using specific fields. A plurality of tables may be grouped into a smaller number of table clusters to facilitate constructing the data model. The model may be evaluated, enhanced, and/or corrected (e.g., by a user). The model may include fields reflecting the purpose information for the stored data, said fields accessible by the engine during data handling processes. The data model may include descriptions providing data storage location. Purpose information may be mapped to table fields. Field descriptions may be based upon purpose information, with some field values having intelligible text.

Data information framework

Various embodiments of systems and methods to determine data retention rules for data entities are described herein. In one aspect, the data entities are obtained. Usage statuses of the data entities are determined. One or more purpose of data corresponding to the one or more data entities is received. Further, legal entities corresponding to the one or more data entities are identified based on line organization attributes and the usage statuses. Process object attributes associated with the one or more data entities are identified based on the legal entities. Retention rules for the one or more data entities are determined based on the one or more purpose of data, the legal entities and the process object attributes.

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Schriesheim, Germany

Volker Lehnert