GEODI 313 - Masking and Anonymization

Purpose

In this training, we’ll cover Masking and Anonymization using GEODI.

While these are two distinct concepts, they share a common technological foundation within GEODI. Despite serving different purposes, both processes follow similar operational workflows—making it efficient to learn them together.

That’s why this training includes both masking and anonymization techniques, their use cases, and how to implement them effectively within your data protection strategy.

Audience

Technical

Time

30 dk

Prerequsite

-

Scope

🔐 What is Masking?

Masking is the process of hiding sensitive data by replacing it with fictional but realistic values—while maintaining data format and usability.
🔗 Learn more about Masking

Common Use Cases:

• Displaying data to unauthorized users without exposing sensitive content

• Masking names, IDs, or contact information in reports

• Obscuring personal data in test environments

🕵️ What is Anonymization?

Anonymization removes or irreversibly alters personal data so it can no longer be linked to an individual.
🔗 Learn more about Anonymization

Common Use Cases:

• Compliance with GDPR, KVKK, or HIPAA

• Sharing data for analytics without violating privacy

• Public dataset publishing

🧩 Key Concepts in GEODI

• Permanent Masking:
  Alters data at the source for irreversible protection.

• Masking & Anonymization Rules / Profiles:
  Define how different data types (e.g., names, numbers, emails) are handled.

• Dynamic Masking:
  Data is masked in real time without changing the original source—ideal for UI-level security.

• Database Masking:
  Applies masking rules directly on structured data sources such as SQL or PostgreSQL.

• Bulk Masking via Actions:
  Automate large-scale masking operations across files, emails, SharePoint, databases, and more—integrated into GEODI Workflows.

Questions

Supporting Material