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What is FedEHR?

By redefining the traditional data value chain, we provide solutions that prioritize risk awareness when it comes to de-identifying sensitive data, facilitating its further processing. Whether you opt for on-premises management to maintain total control or choose a secure external service, FedEHR stands as your comprehensive solution that adheres to GDPR and HIPAA standards. As technological advancements progress, the characteristics of our data evolve, with a remarkable increase in IoT devices producing extensive amounts of information, reflecting our deeply interconnected and pervasive society. This evolution brings forth critical questions regarding the concept of our "quantified self." Yet, what are the broader implications and potential hazards associated with data sharing? Who has the right to access this data, and for what ends? What is the actual value of data, and who claims ownership over it? Although this wealth of personal and sensitive information offers remarkable opportunities for individual insight, it also creates substantial challenges for societies aiming to establish effective governance frameworks that can manage this data responsibly. As we confront these intricate challenges, the necessity for transparency and accountability in data management becomes increasingly vital, highlighting the need for ongoing conversations about ethical data practices.

What is AnalyticDiD?

Safeguarding sensitive information, particularly personally identifiable information (PII), through strategies such as pseudonymization and anonymization is crucial for secondary applications like comparative effectiveness research, policy assessments, and studies within the life sciences. As organizations gather large amounts of business data to discern patterns, gauge customer preferences, and stimulate innovation, the significance of this process grows. Adherence to legal frameworks like HIPAA and GDPR requires that data be stripped of identifying details; however, many current de-identification solutions focus primarily on eliminating personal identifiers, which can compromise the usability of the data. Transforming PII into formats that preclude identification while ensuring privacy is essential, and effectively utilizing data anonymization and pseudonymization techniques is key to this endeavor. This approach facilitates thorough data analysis without violating privacy laws. It is crucial to carefully choose suitable methods and privacy models from the broad domains of data de-identification and statistics to achieve effective data de-identification. Additionally, ongoing assessment of the evolving landscape of privacy standards is necessary to maintain compliance. Ultimately, achieving an equilibrium between data usability and the protection of privacy is essential for ethical data management practices.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

GNUBILA

Company Location

France

Company Website

gnubila.fr/

Company Facts

Organization Name

Fasoo

Company Location

United States

Company Website

en.fasoo.com/products/analyticdid/

Categories and Features

Data Security

Alerts / Notifications
Antivirus/Malware Detection
At-Risk Analysis
Audits
Data Center Security
Data Classification
Data Discovery
Data Loss Prevention
Data Masking
Data-Centric Security
Database Security
Encryption
Identity / Access Management
Logging / Reporting
Mobile Data Security
Monitor Abnormalities
Policy Management
Secure Data Transport
Sensitive Data Compliance

Categories and Features

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