Presidio Tabular Referential integrity

[zahycs]

**Is your feature request related to a problem? **
Yes, it is. During a recent engagement with a customer, we encountered a challenge related to preserving referential integrity when anonymizing tabular and structured data. The issue lies in the need to balance between maintaining data usability (especially in ML and AI contexts) and adhering to data privacy regulations such as GDPR.

Describe the solution you'd like
We propose introducing a feature to Presidio that ensures the preservation of referential integrity during the anonymization process of tabular data. We've successfully used a solution in a recent project which we believe can be integrated into Presidio. This feature should effectively anonymize data while maintaining relationships between tables or data structures, making sure that the anonymized data keeps its utility for development, testing, ML, and AI applications.

Describe alternatives you've considered
An alternative we considered involved developing separate tooling for handling referential integrity outside of the Presidio framework. However, integrating this solution directly into Presidio simplifies the process for end-users and aligns with the tool's vision of being a comprehensive data anonymization solution.

Additional context
Preserving the referential integrity of structured data during the anonymization process is key to creating 'real-like' data sets that can be used for development and testing without violating data privacy regulations. By enhancing Presidio with this feature, we will make it possible for organizations to build and test on robust, anonymized data sets, which could significantly improve their development practices, especially in the realms of machine learning and artificial intelligence.