Quasi-Identifier Generalization Hierarchies
The concept name was not provided (marked as "undefined"), and the supplied sources do not contain enough grounded detail to produce a precise, accurate definition without risking unsupported claims. A valid concept name or additional source snippets are required to generate a reliable reference definition.
Tutorials that teach this
- Tutorial Understand How Data Anonymization Works in SAP HANA Cloud, SAP HANA Database
- Tutorial Understand Why Data Anonymization is Important
- Tutorial Create an Anonymized View Using L-Diversity
- Tutorial Create an Anonymized View Using K-Anonymity
- Tutorial Create a Calculation View with K-anonymity (XS Advanced)
Prerequisites
- Concept Data Protection and Privacy for Personal Data The concept name was not provided, so a best-effort definition is constructed from the available sources on Data Protection and Privacy in SAP contexts. **Data Protection and Privacy** in SAP development refers to the set of technical and organizational measures developers must implement to comply with legal requirements around the handling of personal data. Developers use capabilities such as [Read Access Logging (RAL)](https://help.sap.com/docs/btp/sap-business-technology-platform/5688c3a63f4e400e841a4c7afc2bee8b?locale=en-US&state=PRODUCTION&version=Cloud) to monitor and log read access to sensitive data, and change logging to record modifications to personal data. SAP platforms also provide mechanisms for the [deletion of personal data](https://ui5.sap.com/#/topic/76c2124562b143a9a3a06e431242cf72) to support data subject rights such as the right to erasure.
- Concept Data Protection and Privacy Compliance The provided sources do not contain enough information to write a grounded definition for an undefined concept. Please provide a valid concept name and sufficient source material to support a definition.
- Concept Data Privacy and Anonymization Techniques A technique used in SAP HANA Cloud, SAP HANA Database to protect sensitive personal data by transforming it so that individuals cannot be identified from a dataset. Developers use it to create **anonymized views** — using methods such as [K-Anonymity, L-Diversity, or Differential Privacy](https://developers.sap.com) — that allow data to be shared and analyzed while reducing the risk of re-identification. These anonymized views can then be monitored and shared with consumers who need access to the data without exposing personally identifiable information.