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About DataVeil

DataVeil is a data masking software from DataVeil Inc. [designed for protecting sensitive information]. It combines data discovery, masking techniques, and reporting tools so organizations can ensure compliance and safeguard their data. DataVeil specializes in creating realistic, yet fictitious, data to be used in non-production environments without exposing confidential information. With its ability to integrate with various databases and systems, DataVeil helps businesses maintain data privacy while still enabling development and testing activities. Key capabilities: data discovery data masking reporting tools integration support compliance management Best for: organizations that need to protect sensitive data in development and testing environments.

DataVeil Details

Vendor
DataVeil Inc.
Year Launched
2002
Location
Melbourne, Australia.
Deployment
cloud
Training Options
demo, account manager, community
Countries Served
All Countries
Languages
English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean
Users
Data analysts, Data protection officers, IT administrators, Compliance officers, Database administrators.
Industries Served
Healthcare, Education, Finance, Retail, Manufacturing, Government, Technology
Tags
GDPR Compliance, Data Masking, Data Privacy, Data Security, Compliance, Data Protection

DataVeil's In-App Market Place

Does DataVeil have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), AUD ($), CAD ($), CHF (Fr), CNY (¥), JPY (¥)

Pros & Cons

  • Masks sensitive data securely while keeping realistic data structure.
  • Supports major SQL databases including Oracle and SQL Server.
  • Format-preserving masking keeps databases usable for testing teams.
  • Referential integrity maintained automatically across connected tables.
  • Deterministic masking ensures repeatable consistent masked outputs always.
  • Full version pricing may challenge smaller organizations with budgets.
  • No dynamic masking available for real time needs.
  • Complex database schemas require long configuration before masking.
  • Permanent masking mistakes cannot be undone after commit.
  • Schema changes often require new masking setups again.

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