Mask Personal Data in a Parquet File, No Code

Parquet files often hold customer data. Masking them usually means writing code. Here it takes a few clicks.

Open the Data Masking

Open Data Masking and drop the Parquet file. The tool looks for emails, phone numbers, names and similar columns and suggests a rule for each, such as hashing or replacing with fake values. Review each rule and change it if needed.

Download the masked file as Parquet to keep the column types, or as CSV, JSON or Excel. Turn on consistent masking if the same person must get the same value in several files, so joins still work.

Check the result: search the masked file for a few real values from the original. A masking tool finds common patterns, but it cannot know every sensitive field, so look at the column list yourself.

Everything runs in your browser and nothing is uploaded.

Open the Data Masking

Related tool pages

  • Mask Emails in a CSV File: Hide email addresses and phone numbers in a CSV file before you share it. Detects personal columns for you. Free, in your browser.
  • Anonymize CSV Data: Anonymize a CSV before sharing it: hide names, emails, phones and card numbers with the method you choose. Free, in your browser.
  • Mask PII in Excel Files: Find and hide personal data in an Excel file before you share it, such as emails, phone numbers and names. Free, in your browser.
  • Mask Phone Numbers in a CSV: Hide phone numbers in a CSV, Excel or JSON file before you share it. Keep the country code or last digits, or replace with fake numbers. Runs in your browser.
  • Mask Credit Card Numbers in a File: Find card numbers in a CSV or Excel file and mask them, keeping only the last 4 digits. Free, private, no upload.
  • Mask Names in a CSV File: Replace real names in a CSV, Excel or JSON file with fake names or initials, so you can share the data safely. Free, in your browser.

How to use the Data Masking: step by step

  1. Open Data Masking and drop the Parquet file.
  2. Review the suggested rule for each column.
  3. Download the masked file.
  4. Search it for original values.

When to use the Data Masking

  • Share a dataset with a partner
  • Make a safe copy for testing
  • Remove emails before analysis
  • Prepare data for a vendor

Example

Input: ada@example.com, +1 555 0100

Output: a**@example.com, +1 *** ****

Frequently asked questions

What is data masking?

Hiding or replacing sensitive values, such as emails, phones and names, so a file can be shared or tested without exposing real people.

Which masking methods are available?

Fake data, partial masking, hashing and noise for numbers, with consistent masking so the same input gets the same result.

Is my file uploaded?

No. Masking runs in your browser, so the real values never leave your device.

Is masking the same as anonymizing?

Not always. Combined details can still identify people, so review before sharing.

Tip: Search the masked file for a few real values from the original before you share it.