Anonymization
GEODI DSPM enables anonymization by transforming sensitive data into realistic but non-identifiable values, allowing organizations to safely use, share, and analyze data without exposing original identities. By preserving data structure and context, anonymization supports testing, analytics, and collaboration workflows while maintaining compliance with privacy regulations.
Integrated with GEODI’s discovery and classification capabilities, anonymization can be applied consistently across structured and unstructured data sources, ensuring scalable and policy-driven data protection.
Difference from Masking:
Masking in GEODI hides data and makes it unreadable, whereas anonymization replaces sensitive values with realistic alternatives, keeping the data usable but no longer linked to real individuals.
In Anonymization, each value is replaced with a compatible alternative. For example, a name is replaced with another name, a phone number with another phone number, and so on. The ready-to-use values are listed below.
Name → Name
Money → Money
Dictionaries(Placename, part number or other) → random value from the same dictionary
Creditcard → Creditcard
IBAN → IBAN
Tel → Tel
e-Mail → e-Mail
Date → Date
Anonimization has 2 mode. In the Default mode, the same value takes the same value. A name (John Smit) is converted to the same name everywhere. In the other mode, conversion is always random, and you can not even see the same results in a single session.
Set ANO.SameToSame:False in the project generic settings for the second mode.
Profiles
Profiles define which findings are to be anonymized. You may anonymize all PII or Financial data. The functions ask you to choose from existing profiles.
Anonymization in content can be applied in several ways:
Persistent File Anonymization: The identified discovery layers are modified permanently or as a copy in file-based data. An anonymous copy of the original file is created, or the original file is altered.
Dynamic Anonymization: The selected discovery layers change dynamically for selected groups/users. For Example, one user can see the complete document, while another user sees it with hidden monetary fields or personal data.
Database anonymization creates a masked or anonymized copy of a given database. This allows software development teams to work with a masked version of the database.
Persistent File Anonimization
GEODI creates a copy of the content undergoing masking to perform the process. The operation functions in the "Mask and Download" manner.
You can also perform this process in bulk using workflows and mask action. Please refer to Automation&Workflow pages.
Masking operates in the following formats:
Word (*.doc, *.docx, *.rtf)
Excel (*.xlsm, *.csv, *.xlsx, *.xls)
PDF (*.pdf)
Powerpoint (*.ppt, *.pptx, *.ppsx)
LibreOffice (*.odp, *.odt, *.ods)
Download as masked tools is under the button in the viewers.
Masking profiles allow you to create templates to mask all or just PII.
For example, with masking, a name like "Hasan Hüseyin" can be masked as "[NAME]" or "****". Different masking formats can be defined based on different identifiers using definitions. This means that names, IBANs, and currency expressions can all be masked differently.
Database Anonymization
Database masking performs permanent masking on the given database. You can also work on a copy if you want the original data to remain intact.
Database masking provides several use cases:
When you need to share your database with software or testing teams, masking permanently removes sensitive data from your database for this use case.
When you share your database for data analysis, sensitive data is permanently removed, allowing you to share the database safely.
You can also perform this process in bulk using workflows and mask action. Please refer to Automation&Workflow pages.
Permissions
The authorization for masking is the same as the document download permission. Those with download permission can use masking.
Dynamic masking allows authorization at the user and discovery layer levels.
License
A mask and DISCOVERY license is required for anonymization.
The number of users is equal to the number of GEODI users.
Special Situations
All limitations related to masking also apply to anonymization.
Unlike masking, numeric and float fields can be anonymized at the column level without prior discovery. To do this, define the column names in the database source connection under Advanced Settings → Anonymize Float Columns.
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