---
title: Distinct Record Check
description: Validates the number of distinct values in a specified column.
group: Uniqueness
---

# Distinct Record Check

The **Distinct Record Check** rule verifies that a column contains the expected number of unique values.  
This rule is commonly used to:

- Validate expected cardinality in categorical or lookup fields  
- Ensure proper distribution of distinct values in key columns  
- Maintain data quality standards for reporting and analysis  

**Example Usage**:  
- Check that a `Country` column contains exactly 25 unique country codes  
- Verify that a `Product Category` column has between 5 and 10 distinct values  

## 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 distinct 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 be counted as distinct values    | No         | `true` / `false` (default: `false`)                                  |

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## Sample Input Data  

| ProductID | Category    | Region  |
|:-----------|:-------------|:---------|
| 1001      | Electronics | East    |
| 1002      | Furniture   | West    |
| 1003      | Electronics | East    |
| 1004      | Apparel     | North   |
| 1005      | Electronics | NULL    |

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## Sample Configurations  

### Example 1: Exact Distinct Count  



| Configuration Field | Value       |
|:---------------------|:-------------|
| Column                | Category    |
| Operator              | EqualTo     |
| Threshold Value       | 3           |
| Is Percentage         | false       |
| Allow Nulls           | false       |

**Explanation**:  
Validates that the `Category` column contains exactly 3 distinct values (`Electronics`, `Furniture`, `Apparel`).

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### Example 2: Range-Based Distinct Count  



| Configuration Field | Value       |
|:---------------------|:-------------|
| Column                | Region      |
| Operator              | Between     |
| Threshold Min         | 2           |
| Threshold Max         | 4           |
| Is Percentage         | false       |
| Allow Nulls           | true        |

**Explanation**:  
Validates that the `Region` column contains between 2 and 4 distinct values, counting `NULL` as a distinct value if present.

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## Sample Output  

| Column Name | Rule Name             | Success Count | Failure Count | Null Count | Within Threshold |
|:-------------|:-----------------------|:---------------|:---------------|:------------|:------------------|
| Category    | Distinct Record Check   | 3             | 2             | 0          | Yes              |
| Region      | Distinct Record Check   | 3             | 1             | 1          | No               |

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