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Multiple tables synthetic data generation **

** YData's Enterprise feature

This feature is only available for users of YData Fabric.

Sign-up Fabric community and try synthetic data generation from multiple tables or contact us for more informations.

Multitable synthetic data enables the creation of large, diverse datasets crucial for training robust machine learning models, algorithm testing, and addressing privacy concerns. It can be crucial to enable proper data democratization within an organization.

Nevertheless, the process of generating a full database or even several tables that share relations, can be particularly challenging due to the necessity of preserving referential integrity across diverse tables and scale. This involves maintaining realistic relationships between entities to mirror real-world scenarios accurately while being able to process large volumes of data.

YData Fabric offers a cutting-edge Synthetic data generation process that seamlessly integrates with your existing Relational databases. By replicating the data's value and structure to a new target storage, Fabric delivers a wide range of benefits and use-cases. These include reducing risk and improving compliance by substituting operational databases with synthetic databases for tests and development. It also enables QA teams to create comprehensive and more flexible testing scenarios.

Explore Fabric multi-table synthesis capabilities:

From what sources am I able to train a multi-tables synthetic data generator?

  • From a relational database
  • From the upload of multiple files