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 — 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.
Tutorials that teach this
- Tutorial Create Anonymized Views Using Differential Privacy
- Tutorial Create an Anonymized View Using K-Anonymity
- Tutorial Understand How Data Anonymization Works in SAP HANA Cloud, SAP HANA Database
- Tutorial Create an Anonymized View Using L-Diversity
- Tutorial Understand Why Data Anonymization is Important
- Tutorial Create a Calculation View with K-anonymity (XS Advanced)
- Tutorial Monitor and Share Anonymized Data
Prerequisites
- Concept Data governance and transparency The concept name was not provided (marked as "undefined"), and the supplied source snippets cover SAP BTP audit logging, security events, and data privacy configuration but do not define a specific named developer concept. Without a concept name or sufficient source detail to identify and describe a discrete concept, a grounded definition cannot be produced. Please provide the concept name and relevant source snippets so an accurate definition can be written.
- 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 LLM orchestration across multiple models The concept name is missing or undefined, and the provided source snippet does not contain enough detail to construct an accurate, grounded definition. A valid concept name and sufficient source content are required to produce a reliable reference definition.
- Concept SAP HANA Cloud fundamentals The concept name was not provided, and the available source snippets do not contain enough detail to define a specific SAP developer concept with accuracy. The sources reference topics such as [setting up database artifacts](https://help.sap.com/docs/btp/sap-business-technology-platform/3cd69547217949e098fb4f2a88aa6d33?locale=en-US&state=PRODUCTION&version=Cloud) in SAP HANA, connecting via JDBC, spatial data visualization, and migrating to SAP HANA Cloud, but no specific concept name or substantive explanatory content was supplied to ground a precise definition.
- Concept Large Language Models (LLMs) The concept provided is **undefined**, and the supplied sources do not describe a specific, identifiable SAP developer concept by that name. Based on the available snippets — which cover topics such as [Retrieval Augmented Generation (RAG)](https://architecture.learning.sap.com/docs/ref-arch/RA0005/3-retrieval-augmented-generation/readme), prompting LLMs in the generative AI hub, and using custom or small language models on SAP AI Core — no definition can be responsibly constructed for an unnamed or undefined concept. Please provide a valid concept name so that an accurate, source-grounded definition can be written.
Concepts that build on this
- Concept Differential Privacy Anonymization
- Concept K-Anonymity for Quasi-Identifier Protection
- Concept SAP HANA Anonymized Views
- Concept Data Anonymization in SAP HANA Cloud
- Concept PII Data Masking for AI Applications
- Concept Quasi-Identifier Generalization Hierarchies
- Concept L-Diversity for Sensitive Data Protection
- Concept Sensitive Data Field Masking