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Description
To protect sensitive information, including personally identifiable information (PII), organizations must implement techniques such as pseudonymization and anonymization for secondary purposes like comparative effectiveness studies, policy evaluations, and research in life sciences. This process is essential as businesses amass vast quantities of data to detect patterns, understand customer behavior, and foster innovation. Compliance with regulations like HIPAA and GDPR mandates the de-identification of data; however, the difficulty lies in the fact that many de-identification tools prioritize the removal of personal identifiers, often complicating subsequent data usage. By transforming PII into forms that cannot be traced back to individuals, employing data anonymization and pseudonymization strategies becomes crucial for maintaining privacy while enabling robust analysis. Effectively utilizing these methods allows for the examination of extensive datasets without infringing on privacy laws, ensuring that insights can be gathered responsibly. Selecting appropriate de-identification techniques and privacy models from a wide range of data security and statistical practices is key to achieving effective data usage.
Description
Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.
API Access
Has API
API Access
Has API
Integrations
AWS IoT SiteWise
Accenture Cloud Trade Promotion Management
Amazon Web Services (AWS)
AssetMetrics
CalendarAnything
Cognizant
Databricks
Decimal
Eviden MDR Service
Google Cloud Platform
Integrations
AWS IoT SiteWise
Accenture Cloud Trade Promotion Management
Amazon Web Services (AWS)
AssetMetrics
CalendarAnything
Cognizant
Databricks
Decimal
Eviden MDR Service
Google Cloud Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Fasoo
Country
United States
Website
en.fasoo.com/products/analyticdid/
Vendor Details
Company Name
Informatica
Founded
1993
Country
United States
Website
www.informatica.com/products/data-security/data-masking/persistent-data-masking.html