Metadata is a description of your dataset. It helps the library understand the type and format of your data, so that it can apply the correct metrics.
If the metadata is incorrect, this library may apply the wrong metrics to your data which leads to inaccurate scores.
Your metadata includes:
- The type of data that each column represents
- The primary keys and other identifiers of the table
- The relationships between the tables, if you have multiple tables
Write your metadata once and use it anywhere in the SDMetrics library.
If you used the SDV library to create your metadata, you can reuse the same file for SDMetrics.