Data Quality Metrics

The Data quality assessment is a key indicator to evaluate datasets used during the whole AI system building.

DQM-ML incorporates more than a dozen methods divided into inherent metrics which evaluate intrinsically the data knowledge by assessing the connection between data and its application domain such as representativeness, diversity and completeness, and system- dependent metrics which integrates in the assessment the system behaviors such as coverage and domain gap metrics.

It could be used by Data Engineers or ML-Algorithm Engineers during the specification or the development of the ML Component or its models,and the monitoring during the deployment. It can also be used along all the data engineering life cycle