---
title: "Set up duplicate check - Fuzzy matching"
slug: "set-up-duplicate-check-fuzzy-matching-general"
description: "Set up a fuzzy duplicate check to identify similar records in your database, ensuring data quality with customizable thresholds and field weightage."
tags: ["Task topic"]
status: "update"
updated: 2026-09-23T08:28:37Z
published: 2026-09-23T08:28:37Z
canonical: "docs.staedean.com/set-up-duplicate-check-fuzzy-matching-general"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.staedean.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Set up duplicate check - Fuzzy matching

Use a fuzzy duplicate check to ensure that no (almost) similar records exist in a table.

To set up a fuzzy duplicate check rule, use a duplicate check of type **Fuzzy matching**. If the desired **Fuzzy matching** duplicate check does not exist, set up a new **Fuzzy matching** duplicate check.

A **Fuzzy matching** duplicate check checks for duplicates applying fuzzy logic. A **Fuzzy matching** duplicate check compares, for a selected record, several field values with the values of the same fields of other records. Based on the comparison, a duplicate score is calculated.

### Duplicate check definition

On the duplicate check, you define:

- Which dynamic query is used. The dynamic query defines the records that are checked for duplicate values and the fields that can be checked for duplicate values. In the dynamic query, the first defined table must be the main table, on which you want to check for duplicates. This is the same table as defined in the duplicate check header, in the **Table name** field. A form can use several related tables. In this case, in the dynamic query, use data entities for the next table records. For each of the data entity table records, define the applicable parent. Use the data entities to select the fields that you want to check for duplicates.
- The fields which values are checked for duplicates. You can only use fields that are defined in the dynamic query.
- For each field, the weightage. The weightage expresses the importance of a duplicate value. Express the weightage in a number (with or without decimals). Define the weightage number in such a way that the importance is expressed compared to the other fields. If you do not define a weightage for a field, the field value is not checked for duplicates.
- The threshold that is used to indicate if a record is a possible duplicate. The threshold is expressed in a percentage. Only if the calculated duplicate score for a record is equal to or higher than the threshold, a record is marked as possible duplicate. The duplicate score is calculated in this way: [Weightage sum of fields with duplicates] / [Total weightage sum] * 100%

### Example:

Duplicate check on CustTable

Threshold: 50%

| Table name | Datasource name | Field | Field label | Weightage |
| --- | --- | --- | --- | --- |
| CustTable | CustTable | AccountNum | Customer account |  |
| CustCustomerV3Entity | CustCustomerV3Entity | AddressStreet | Street | 1 |
| CustCustomerV3Entity | CustCustomerV3Entity | AddressZipCode | ZIP/postal code | 1 |
| CustCustomerV3Entity | CustCustomerV3Entity | OrganizationName | Organization name | 6 |
| CustCustomerV3Entity | CustCustomerV3Entity | PrimaryContactEmail | Primary email | 3 |
| CustCustomerV3Entity | CustCustomerV3Entity | PrimaryContactPhone | Primary phone | 3 |

Calculation examples:

- Duplicate values exist in the Primary email field and in the Primary phone field. The duplicate score is: 6 / 14 * 100 = 42,86. The record is not reported as possible duplicate.
- Duplicate values exist in the Organization name field and the ZIP/postal code field. The duplicate score is: 7 / 14 * 100 = 50. The record is reported as possible duplicate.

> [!NOTE]
> Note
> 
> A duplicate check can be used in multiple data quality policies. Therefore, changes may impact other data quality policies.
> 
> To review the dependencies and assess the potential effect, first check where the duplicate check is used:
> 
> 1. On the **Duplicate check** page, select a duplicate check.
> 2. On the **Action Pane**, click **Where used**.
> 3. Review the dependencies.
> 
> If the desired changes have an unintended impact on other configurations, you can create a copy of the duplicate check:
> 
> 1. On the **Duplicate check** page, select a duplicate check.
> 2. On the **Action Pane**, click **Where used**.
> 3. On the dialog, enter a new name and click **OK**.
> 4. Make the changes to the copy.

### Steps

1. Click **Data quality management**.
2. Click **Duplicate checks**.
3. Click **New**.
4. In the **Duplicate check name** field, type a value.
5. In the **Duplicate check type** field, select '**Fuzzy matching**'.
6. Use a dynamic query to define the records that are checked for duplicate values and the fields that can be checked for duplicate values.

In the **Query** field, enter or select a value.
7. Define the threshold that is used to indicate if a record is a possible duplicate. The threshold is expressed in a percentage. Only if the calculated duplicate score for a record is equal to or higher than the threshold, a record is marked as possible duplicate.

In the **Threshold %** field, enter a number.
8. Sub-task: Select the fields to be checked on duplicate values.
  1. In the **Constraints** section, click **Add**.
  2. In the **Select fields** dialog, in the available grid, select the desired fields.
  3. Click **Add**.
  4. Click **OK**.
  5. You can use a phonetic search algorithm to check on duplicate names that sound similar, for example, John and Jon.

Select the **Use phonetic search** check box.
  6. If you have selected the **Use phonetic search** check box, define the applicable phonetic search rule.

In the **Phonetic search rule** field, enter or select a value.
  7. The weightage expresses the importance of a duplicate value. Express the weightage in a number (with or without decimals). Define the weightage number in such a way that the importance is expressed compared to the other fields.

In the **Weightage** field, enter a number.

> [!NOTE]
> Note
> 
> If you do not define a weightage for a field, the field value is not checked for duplicates.
  8. You can hide a field and its duplicate check results from the **Duplicate records found** page. For example, if a field shows sensitive data, you can check the field for duplicate values but hide the results of the check.

Select the **Hide in results** check box.
  9. You can exclude a field from the duplicate score calculation when its value is blank in the evaluated record. This prevents blank values from affecting the duplicate score. Especially for fields where an empty value should not be considered for the duplicate score. Select the **Ignore blank** check box.
9. Sub-task: Select product attributes to be checked on duplicate values.
  1. Instead of a standard field linked to a table and datasource, you can check a product attribute for duplicate values. Add product attributes as virtual fields.

In the **Constraints** section, click **Add virtual field**.
  2. In the **Virtual field type** field, you can select these options:

Select **Product attribute**.
    - **None**: No virtual field is used. This is the default value.
    - **Product attribute**: The field is a product attribute of the entity used in the query.
  3. The available product attributes depend on the entity used in the query.

In the **Virtual field identifier** field, select the desired product attribute.

> [!NOTE]
> Note
> 
> - A virtual field supports the same phonetic search, weightage, hide in results, and ignore blank options as a standard field (see steps 8e -8i).
> - Virtual field setup on a duplicate check only applies to the fuzzy duplicate check in Data Entry Workflow.
10. Sub-task: Select the fields that can be merged for a duplicate record.
  1. In the **Merge fields** section, click **Add**.
  2. On the dialog, in the list, find and select the desired fields.
  3. Click **Add (->).**
  4. Click **OK**.
11. Sub-task: Add a product attribute as a virtual field to the Merge fields section.
  1. Instead of a standard field linked to a table and datasource, you can merge a product attribute value. Add product attributes as virtual fields.

In the **Merge fields** section, click **Add virtual field**.
  2. In the **Virtual field type** field, you can select these options:

Select **Product attribute**.
    - **None**: No virtual field is used. This is the default value.
    - **Product attribute**: The field is a product attribute of the entity used in the query.
  3. The available product attributes depend on the entity used in the query.

In the **Virtual field identifier** field, select the desired product attribute.
12. Sub-task: Activate duplicate check.
  1. If the duplicate check setup is finished, you can make it available for selection on the duplicate check rules.

Select **Yes** in the **Active** field.

> [!NOTE]
> Note
> 
> - If active, you cannot edit the duplicate check.
> - If active and used in an active data quality policy version, you cannot make the duplicate check inactive.
13. Close the page.

## Related

- [Check for, review, and merge duplicates - Fuzzy matching](/check-for-review-and-merge-duplicates-fuzzy-matching.md)
- [Set up duplicate check](/set-up-duplicate-check-general.md)
- [Set up dynamic queries - Data Entry Workflow](/set-up-dynamic-queries.md)
- [Product attributes in fuzzy duplicate check](/product-attributes-in-fuzzy-duplicate-check.md)