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What is Trūata Calibrate?

Elevate your data management strategies with software solutions that prioritize privacy. Trūata Calibrate empowers organizations to harness their data while turning privacy into a strategic advantage. Our user-friendly, cloud-based platform facilitates the rapid implementation of privacy-compliant data pipelines, enabling teams to manage data responsibly and confidently. Leveraging intelligent automation, Trūata Calibrate simplifies the processes of risk assessment and mitigation through a comprehensive dashboard. This platform provides a refined and standardized method for addressing privacy risks, ensuring that data can be safely transformed for use throughout your business ecosystem. Users benefit from real-time insights for data transformation and can assess the implications of privacy-utility simulations prior to executing focused de-identification measures to minimize risks. By transforming their data, organizations can develop privacy-enhanced datasets that can be securely shared, transferred, and ethically utilized by their teams, ultimately cultivating a culture centered around privacy-conscious data governance. Moreover, this powerful tool not only strengthens compliance but also encourages innovation, enabling businesses to derive data insights while maintaining stringent privacy standards. These capabilities position organizations to thrive in an increasingly data-driven world where privacy and innovation go hand in hand.

What is Informatica Persistent Data Masking?

Ensure the core message, format, and precision remain intact while prioritizing confidentiality. Enhance data security by transforming and concealing sensitive details through the implementation of pseudonymization techniques that comply with privacy regulations and facilitate analytical needs. The transformed data retains its contextual relevance and referential integrity, rendering it appropriate for use in testing, analytics, or support applications. As a highly scalable and efficient data masking solution, Informatica Persistent Data Masking safeguards sensitive information such as credit card numbers, addresses, and phone contacts from unintended disclosure by producing realistic, anonymized datasets that can be securely shared both internally and externally. Moreover, this approach significantly reduces the risk of data breaches in nonproduction environments, improves the quality of test datasets, expedites development workflows, and ensures adherence to various data privacy standards and regulations. By incorporating such comprehensive data masking strategies, organizations not only secure sensitive information but also cultivate an environment of trust and security, which is essential for maintaining stakeholder confidence. Ultimately, the adoption of these advanced techniques plays a crucial role in promoting an organization's overall data governance framework.

Media

Media

Integrations Supported

Microsoft Azure

Integrations Supported

Microsoft Azure
AWS IoT SiteWise
Accenture Cloud Trade Promotion Management
Amazon Web Services (AWS)
AssetMetrics
CalendarAnything
Cognizant
Databricks
Decimal
Eviden MDR Service
Google Cloud Platform
HCL Accelerate
Hadoop
Microsoft 365
Peromnes
Salesforce
Snowflake
Tableau

API Availability

API Availability

Pricing Information

$5,000 per month

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Trūata

Date Founded

2018

Company Location

Ireland

Company Website

www.truata.com/products/truata-calibrate/

Company Facts

Organization Name

Informatica

Date Founded

1993

Company Location

United States

Company Website

www.informatica.com/products/data-security/data-masking/persistent-data-masking.html

Categories and Features

Categories and Features

Data Masking

Not specified

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