---
title: Column Uniqueness Check
description: Validates that values in a specified column are unique.
group: Uniqueness
---

# Column Uniqueness Check

The **Column Uniqueness Check** rule ensures that all values in a specified column are distinct within a dataset.  
This rule is commonly used to:

- Validate primary key or identifier columns  
- Ensure unique fields like email addresses, SKUs, or serial numbers are not duplicated  
- Maintain data integrity for critical business attributes  

**Example Usage**:  
- Ensure all `ProductCode` values are distinct  
- Verify `SerialNumber` is unique for each product entry  
- Confirm `Email` addresses have no duplicates in a user database  

## Configuration Fields  

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### Success Criteria Configuration  

This section defines how the rule’s outcome is measured against expected thresholds.

| Field Name        | Description                                                 | Required   | Options / Format                                                     |
|:------------------|:------------------------------------------------------------|:-----------|:----------------------------------------------------------------------|
| **Operator**        | Comparison operation for the unique value count             | Yes        | `GreaterThan`, `LessThan`, `EqualTo`, `Between`                      |
| **Threshold Value** | Value for comparison (single value for most operators)      | Conditional| Number                                                               |
| **Threshold Min**   | Minimum value (for `Between` operator)                      | Conditional| Number                                                               |
| **Threshold Max**   | Maximum value (for `Between` operator)                      | Conditional| Number                                                               |
| **Is Percentage**   | Whether the threshold represents a percentage of total rows | No         | `true` / `false` (default: `false`)                                  |
| **Allow Nulls**     | Whether null values should count as unique                  | No         | `true` / `false` (default: `false`)                                  |

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## Sample Input Data  

| ID | ProductCode | SerialNumber |
|:----|:-------------|:--------------|
| 1  | PC-100      | SN-001       |
| 2  | PC-101      | SN-001       |
| 3  | PC-100      | SN-002       |
| 4  | PC-102      | NULL         |
| 5  | PC-103      | NULL         |
| 6  | NULL        | SN-003       |

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## Sample Configurations  

### Example 1: Strict Uniqueness Check  



| Configuration Field | Value       |
|:---------------------|:-------------|
| Column                | ProductCode |
| Operator              | EqualTo     |
| Threshold Value       | 4           |
| Is Percentage         | false       |
| Allow Nulls           | false       |

**Explanation**:  
Validates that the `ProductCode` column contains exactly 4 unique values (PC-100, PC-101, PC-102, PC-103). Null values are treated as non-unique.

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### Example 2: Percentage-Based Uniqueness Check  


| Configuration Field | Value       |
|:---------------------|:-------------|
| Column                | SerialNumber|
| Operator              | GreaterThan |
| Threshold Value       | 50          |
| Is Percentage         | true        |
| Allow Nulls           | true        |

**Explanation**:  
Ensures that over 50% of `SerialNumber` values are unique, with null values being considered unique.

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## Sample Output  

| Column Name   | Rule Name            | Success Count | Failure Count | Null Count | Within Threshold |
|:---------------|:----------------------|:---------------|:---------------|:------------|:------------------|
| ProductCode    | Column Uniqueness Check | 3             | 2             | 1          | No               |
| SerialNumber   | Column Uniqueness Check | 4             | 2             | 0          | Yes              |

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