What's included?
Last updated
Last updated
The quality report captures the Column Shapes, Column Pair Trends and Cardinality. This guide contains some technical details about each property.
Does the synthetic data capture the shape of each column?
The shape of a column describes its overall distribution. The higher the score, the more similar the distributions of real and synthetic data.
This property applies metrics based on the column types.
numerical
datetime
boolean
categorical
This yields a separate score for every column. The final Column Shapes score is the average of all columns.
Does the synthetic data capture trends between pairs of columns?
The trend between two columns describes how they vary in relation to each other, for example the correlation. The higher the score, the more the trends are alike.
This property applies a different metric metric based on the type of data
numerical (or datetime) with another numerical (or datetime)
categorical (or boolean) with another categorical (or boolean)
numerical (or datetime) with a categorical (or boolean)
This yields a score between every pair of columns. The Column Pair Trends score is the average of all the scores.
This property is only available for multi table datasets. (In older versions of SDMetrics, it was known as "Table Relationships".)
Does the synthetic data capture the number of connections between parent and child tables? This is also known as the cardinality of the tables.
This property is only available for multi table datasets.
Does the synthetic data capture trends between columns across different tables?
This is similar to the Column Pair Trends property, but it is applied across parent/child tables. For example, a column in a parent table might be correlated with a column in the child.
This property denormalizes the parent and child table into a single, flat table. Then, it applies the same metrics as the Column Pair Trends property.
numerical (or datetime) with another numerical (or datetime)
categorical (or boolean) with another categorical (or boolean)
numerical (or datetime) with a categorical (or boolean)
This yields a score between every pair of columns. The Intertable Trends score is the average of all the scores.
Discretize the numerical columns into bins, then apply
This property applies the metric for every set of connected tables: parent table and child table.
Discretize the numerical columns into bins, then apply
Higher order distributions of 3 or more columns are not included in the Quality Report. We have found that very high order similarity may have an adverse effect on the synthetic data usability; after a certain point, it indicates that the synthetic data is just a copy of the real data. (For more information, see the metric.)
If higher order similarity is a requirement, you likely have a targeted use case for synthetic data (eg. machine learning efficacy). Until we add these reports, you may want to explore other .