Metrics Glossary

Each metric in this section quantifies a different aspect of the synthetic data.

Browse by report

We recommend applying the metrics using SDMetrics Reports. Reports determine which exact metrics to use based on your data.

Diagnostic Metrics

These metrics are included in the Diagnostic Report.

• BoundaryAdherence, CategoryAdherence: measure the validity of statistical values

• KeyUniqueness: measure the validity of primary keys

• ReferentialIntegrity, CardinalityBoundaryAdherence: measure the validity of a connection between a foreign and primary key

• TableStructure: measure whether the overall structure of the data is the same

Quality Metrics

These metrics are included in the Quality Report.

• KSComplement, TVComplement: compare shapes (aka marginal distributions, histograms)

• ContingencySimilarity, CorrelationSimilarity: compare 2D distributions & pairwise correlations

• (Multi table only) CardinalityShapeSimilarity: compare parent/child connections

Other Metrics

These metrics are not yet included in any reports. You can still apply them manually on your data.

• MissingValueSimilarity, StatisticSimilarity: compare data using basic statistics

• CategoricalCAP: measure privacy against inference attacks

• CategoryCoverage, RangeCoverage: measure whether the overall synthetic data spans the possibilities

• NewRowSynthesis: measures exact matches between the real and synthetic data

Browse by data granularity

Different metrics compare data at various levels of granularity.

Single Column

These metrics compare single columns of data.

• CategoryCoverage, RangeCoverage: measure data coverage

• BoundaryAdherence, CategoryAdherence: measure whether the synthetic data is chosen from valid boundaries or lists of options

• KSComplement, TVComplement: compare shapes (aka marginal distributions, histograms)

• StatisticSimilarity, MissingValueSimilarity: compare data statistics

• KeyUniqueness: measures whether the primary keys are unique

Column Pairs

These metrics compare pairs of columns.

• ContingencySimilarity: compare 2D distributions

• CorrelationSimilarity: compare pairwise correlations

• ReferentialIntegrity: compute the validity of a connection between a foreign key and primary key

Single Table

These metrics compare a table of data.

• NewRowSynthesis: compute exact matches

• CategoricalCAP: measure privacy against inference attacks

Multi Table

These metrics compare multiple tables of data.

• CardinalityShapeSimilarity: compare parent/child connections

More Metrics

Can't find what you're looking for? Check out the Metrics in Beta for additional options.