# Data Quality Rules Reference

This section contains reference information on the data quality rule types and input types that are available in Designer Cloud.

Data quality rules can be applied to your dataset through the Transformer page.

Input types identify the calculated metric types that can be used as inputs for a data quality rule.

## Rule Types

name | description |
---|---|

## Unique | Column values must be unique. |

## Implies | Source column values imply the values of a target column. For each unique source value, there should be exactly one implied target value. |

## Not Missing | Column values must not be missing. Null values and empty strings are not allowed. |

## Not Null | Column values must not be null. Empty strings are allowed. |

## Valid | Column values must be valid instances of a data type. |

## Match | Column values must match a pattern. |

## Not Match | Column values must not match a pattern. |

## Starts With | Column values must start with a pattern. |

## Ends With | Column values must end with a pattern. |

## Equal | Column values must equal a provided value. |

## Not Equal | Column values must not equal a provided value. |

## In Range | Column values must lie between provided minimum and maximum values. |

## Greater Than | Column values must be greater than a minimum value. |

## Less Than | Column values must be less than a maximum value. |

## In Set | Column values must be one of a set of acceptable values. |

## Not In Set | Column values must not be one of a set of unacceptable values. |

## Formula | Apply a custom data quality rule formula. |

## Metric Input Types

The following metric input types can be selected as the source of a data quality rule.

**Note**

These input types are available for selection from the Column drop-down.

Metric input types are supported for the following rules:

In Range

Greater Than

Less Than

Equals

Not Equals

In Set

Not In Set

name | description |
---|---|

## Average | The average column value. |

## Count Distinct | The number of unique column values. |

## Maximum | The maximum column value. |

## Minimum | The minimum column value. |

## Sum | The sum of column values. |

## Standard Deviation | The sample standard deviation of column values. |

## Variance | The sample variance of column values. |

## Count | The number of rows. |

## Correlation | The Pearson correlation coefficient between two columns. |

## Z-Score | The distance from the mean, in units of standard deviations. |