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Google Cloud Data Loss Prevention Reviews

Vendor: Google
4.5 out of 5

What is Google Cloud Data Loss Prevention?

Google Cloud Data Loss Prevention mindshare

As of May 2026, the mindshare of Google Cloud Data Loss Prevention in the Data Loss Prevention (DLP) category stands at 1.0%, up from 0.8% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Data Loss Prevention (DLP) Mindshare Distribution
ProductMindshare (%)
Google Cloud Data Loss Prevention1.0%
Microsoft Purview Data Loss Prevention6.7%
Forcepoint Data Loss Prevention5.1%
Other87.2%
Data Loss Prevention (DLP)
 
 
Key learnings from peers

Valuable Features

Room for Improvement

Top industries

By visitors reading reviews
Comms Service Provider
12%
Financial Services Firm
10%
University
9%
Manufacturing Company
7%
Construction Company
7%
Insurance Company
7%
Media Company
7%
Government
6%
Outsourcing Company
6%
Logistics Company
3%
Energy/Utilities Company
3%
Non Tech Company
2%
Performing Arts
2%
Real Estate/Law Firm
2%
Retailer
2%
Computer Software Company
2%
Transportation Company
2%
Wellness & Fitness Company
1%
Recreational Facilities/Services Company
1%
Religious Institution
1%
Leisure / Travel Company
1%
Security Firm
1%
Marketing Services Firm
1%
Educational Organization
1%
Non Profit
1%
Hospitality Company
1%
Healthcare Company
1%

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Google Cloud Data Loss Prevention Reviews Summary
Author infoRatingReview Summary
Security Consultant at HCLSoftware4.0I find Google Cloud Data Loss Prevention useful for identifying and managing sensitive data efficiently, though it lacks plug-and-play integration and better documentation, making it somewhat challenging for seamless deployment in large-scale or on-premises environments.
Cloud Senior lead at a financial services firm with 10,001+ employees5.0I find Google Cloud Data Loss Prevention user-friendly with easy integration. It meets client requirements with constant improvements. Despite considering other solutions, we chose it for its ability to manage encryption and tokenize sensitive data effectively.