> For the complete documentation index, see [llms.txt](https://academy.pentaho.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.pentaho.com/pentaho-data-catalog-en/data-catalog/data-processing/pii-detection.md).

# PII Detection

{% hint style="info" %}

#### Overview

The PII Detection feature in Data Catalog uses Machine Learning (ML) and Large Language Models (LLMs) to analyze data in JDBC tables and identify Personally Identifiable Information (PII). This feature is specifically trained for Korean and Japanese datasets and automatically detects and classifies sensitive data, such as names, addresses, and ID numbers. It helps you to streamline compliance with privacy regulations by automatically identifying and classifying personally identifiable information (PII) in datasets.
{% endhint %}

{% hint style="warning" %}
This feature currently supports only JDBC data sources with Korean and Japanese content.
{% endhint %}

<figure><img src="/files/XGFmAw9edd5CTRT8vr55" alt=""><figcaption><p>PII Detection</p></figcaption></figure>

{% hint style="info" %}
When you start PII Detection, Data Catalog scans the selected JDBC table for column names that contain PII entities. Once the process is complete and if PII data is identified:

* A new glossary titled **ML\_PII** is automatically created (if not already present). If the **ML\_PII** glossary already exists, newly identified PII terms are added to it.
* Detected PII entities are tagged with relevant business terms from the **ML\_PII** glossary.

These tags appear in the Business Terms panel of the respective columns.
{% endhint %}

***


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