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

# Masking

> Hide sensitive column values in the Datachecks UI without modifying your underlying data.

Masking lets you conceal sensitive or personally identifiable information in the Datachecks interface. Masked values are hidden in report previews, dashboards, and comparison results — but the underlying data in your database is never modified or deleted.

Masking operates at the presentation layer only. Metadata-level monitoring (row counts, null rates, validation metrics) continues to work normally on masked columns.

## When to use masking

Masking is useful in collaborative environments where visibility must be restricted for compliance, auditing, or data governance purposes. Common use cases include:

* Customer names and contact details
* Account numbers
* Financial figures
* Any column containing confidential or regulated information

## How it works

When a column is masked:

1. The column's values are hidden in the Datachecks UI — report previews and dashboard views show masked placeholders instead of actual values.
2. Validations and comparisons still run against the column using the real data in your database.
3. No data is written back to the source — masking is a display control, not a data transformation.