Template-Based Generation of Synthetic Data Sets

A non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a computing system, cause the computing system to perform operations comprising:

• obtaining a first plurality of data records associated with a first schema, wherein each respective data record of the first plurality of data records comprises a corresponding plurality of values of a plurality of fields;
• obtaining a mapping representing a transformation of one or more fields of the plurality of fields from the first schema to a training schema;
• selecting, based on the mapping and for each respective data record of the first plurality of data records, one or more corresponding values of the one or more fields from the first plurality of data records;
• generating a second plurality of data records by transforming, based on the mapping and for each respective data record of the first plurality of data records, the one or more corresponding values of the one or more fields from the first schema to the training schema;
• and
• training a machine learning model based on the second plurality of data records.

A system comprising:

• one or more processors;
• and
• memory, containing program instructions that, upon execution by the one or more processors, cause the system to perform operations comprising:
• obtaining a first plurality of data records associated with a first schema, wherein each respective data record of the first plurality of data records comprises a corresponding plurality of values of a plurality of fields;
• obtaining a mapping representing a transformation of one or more fields of the plurality of fields from the first schema to a training schema;
• selecting, based on the mapping and for each respective data record of the first plurality of data records, one or more corresponding values of the one or more fields from the first plurality of data records;
• generating a second plurality of data records by transforming, based on the mapping and for each respective data record of the first plurality of data records, the one or more corresponding values of the one or more fields from the first schema to the training schema;
• and
• training a machine learning model based on the second plurality of data records.