Generators transform the data in a source database column.
Generators allow you to assign a transformation to sensitive data.
Tonic offers a variety of generators suited for handling different types of data.
Privacy Hub, Database View, and Table View all provide options to assign a generator to a column.
These are some common generator characteristics that you should be aware of:
- Consistency - Consistency ensures that the same input value maps to the same output value across multiple columns, tables, and databases, even columns and databases of different types. For more information, see Making a generator consistent.
- Linking - Linking allows you to identify columns that use the same generator and that have an inter-dependency or correlation that should be maintained in the output. For example, your data has a city column and a state column. You apply the Categorical generator to both columns and link them. This ensures that the city and state pairings are always valid. For more information, see Linking generators.
- Differential privacy - Differential privacy ensures that the output does not reveal anything that is attributable to a specific member of the source data. For more information, see Differential privacy.
- Data-free - Some generators can be data-free. When a generator is data-free, it means that the output data is completely unrelated to the source data. There is no way to use the output data to uncover the source data. Data-free generators implicitly have differential privacy. A generator is not data-free if consistency is enabled.
Some data values require custom processing before or after the generator is applied.
The most common use case for custom processing is encrypted source data. A custom value processor might decrypt the data before the generator is applied. Another custom value processor might encrypt the generator results.
If you require custom processing for data values, Tonic can work with you to develop and deploy custom value processors for your instance. Once a custom value processor is deployed, you can select the processor as part of the generator configuration for each column.