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

# FuzzyMatch gem for Data Analysis

> Match records that are not exactly identical

export const gemName_0 = "FuzzyMatch"

export const execution_engine_0 = "the SQL warehouse"

<Info>This gem runs in {execution_engine_0}.</Info>

## Overview

Use the FuzzyMatch gem to identify non-identical duplicates in your data.

<Tip>
  The {gemName_0} gem has a corresponding interactive gem example. See [Interactive gem
  examples](/data-analysis/gems/gems#interactive-gem-examples) to learn how to run sample pipelines
  for this and other gems.
</Tip>

## Prerequisites

* Add `prophecy_basics` package version 1.0.0 or higher to your project.

## Input and Output

| Table   | Description                                                                                           |
| ------- | ----------------------------------------------------------------------------------------------------- |
| **in0** | Includes the table on which duplicates will be checked. <br />Note: FuzzyMatch only allows one input. |
| **out** | Generates one record per fuzzy match.                                                                 |

## Parameters

### Configuration

| Parameter                  | Description                                                                                                                                                                   |
| -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Merge/Purge Mode           | Records are either compared from a single source (Purge) or across multiple sources (Merge). <br /> Merge mode assumes that multiple sources exist in the same table **in0**. |
| Source ID Field            | Unique identifier for each source when using **Merge** mode. <br />This is necessary because the different sources exist in the same table **in0**.                           |
| Record ID Field            | Unique identifier for each record.                                                                                                                                            |
| Match threshold percentage | If the match score is less than the threshold, the record does not qualify as a match.                                                                                        |
| Include similarity score   | Checkbox to enable for an additional output column that includes the similarity score.                                                                                        |

### Match Fields

| Parameter      | Description                                               |
| -------------- | --------------------------------------------------------- |
| Field name     | Name of the column that you want to check for duplicates. |
| Match function | The method that generates the similarity score.           |

## Example

One common use case for the FuzzyMatch gem is to match similarly spelled names. Here's a table with two entries for `Alex Taylor`, whose phone number was updated.

<div class="table-example">
  | `id` | `email`               | `phone`      | `first_name` | `last_name` | `date_added` |
  | ---- | --------------------- | ------------ | ------------ | ----------- | ------------ |
  | 1    | `alex.t@example.com`  | 123-456-7890 | Alex         | Taylor      | 2023-01-01   |
  | 2    | `alex.t@example.com`  | 123-456-9542 | Alex         | Ttaylor     | 2023-07-01   |
  | 3    | `sam.p@example.com`   | 987-654-3210 | Sam          | Patel       | 2024-03-15   |
  | 4    | `casey.l@example.com` | 555-111-2222 | Casey        | Lee         | 2024-05-01   |
</div>

You can use the FuzzyMatch gem to find the closely spelled name. In the gem configuration:

1. Set the Merge/Purge Mode to **Purge mode**.
2. For the Record ID, use the **id** column.
3. Keep the threshold at `80` percent.
4. Enable the **Include similarity score column** checkbox.
5. In the Match Fields tab, add a match field for the **last\_name** column.
6. Set the Match Function to **Name**.
7. Save and run the gem.

### Result

The output includes the Record IDs of the records with fuzzy matches above the defined threshold.

<div class="table-example">
  | `id` | `id2` | `similarityScore`  |
  | ---- | ----- | ------------------ |
  | 1    | 2     | 0.9111111111111111 |
</div>

<Info>
  Depending on your SQL provider, you might see different similarity scores based on the algorithm
  that runs under the hood.
</Info>

<Tip>
  To view the names per record, [join](/data-analysis/gems/join-split/join) the FuzzyMatch output
  with the original dataset.
</Tip>