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What is PHEMI Health DataLab?

In contrast to many conventional data management systems, PHEMI Health DataLab is designed with Privacy-by-Design principles integral to its foundation, rather than as an additional feature. This foundational approach offers significant benefits, including: It allows analysts to engage with data while adhering to strict privacy standards. It incorporates a vast and adaptable library of de-identification techniques that can conceal, mask, truncate, group, and anonymize data effectively. It facilitates the creation of both dataset-specific and system-wide pseudonyms, enabling the linking and sharing of information without the risk of data leaks. It gathers audit logs that detail not only modifications made to the PHEMI system but also patterns of data access. It automatically produces de-identification reports that are accessible to both humans and machines, ensuring compliance with enterprise governance risk management. Instead of having individual policies for each data access point, PHEMI provides the benefit of a unified policy that governs all access methods, including Spark, ODBC, REST, exports, and beyond, streamlining data governance in a comprehensive manner. This integrated approach not only enhances privacy protection but also fosters a culture of trust and accountability within the organization.

What is LeapYear?

Differential privacy serves as a robust framework designed to protect data, enabling analysis and machine learning applications without compromising the privacy of individual records. LeapYear's platform, which leverages differential privacy, safeguards some of the most sensitive datasets worldwide, including social media interactions, medical records, and financial transactions. This groundbreaking method empowers analysts, researchers, and data scientists to derive meaningful insights from a diverse range of data, including those from highly sensitive domains, while ensuring that the specifics of individuals, entities, and transactions are kept confidential. Unlike traditional techniques such as data aggregation, anonymization, or masking—which often reduce the data's utility and can create vulnerabilities—LeapYear's approach to differential privacy provides solid mathematical assurances that individual records remain unreconstructable. By preserving both the integrity and the utility of sensitive information, this innovative system not only upholds personal privacy but also amplifies the capacity for insightful reporting and deep analysis. Consequently, organizations can leverage their data with confidence, assured that privacy is maintained at every step. This assurance ultimately fosters a more responsible and ethical approach to data usage in various applications.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Apache Hive
Apache Ranger
Apache Spark
Cloudera
Hadoop
Microsoft Azure
Microsoft Power BI
Tableau

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Contact PHEMI to learn about our value-based pricing.

Pricing Information

Pricing not provided

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
Webinars
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

PHEMI Systems

Date Founded

2013

Company Location

Canada

Company Website

www.phemi.com

Company Facts

Organization Name

LeapYear Technologies

Date Founded

2014

Company Location

United States

Company Website

leapyear.io

Categories and Features

Big Data

Data Warehousing
High Volume Processing
Predictive Analytics

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Policy Management
Process Management
Roles Management
Storage Management

Data Lineage

Not specified

Data Management

Data Analysis
Data Integration
Data Security
Information Governance

Data Masking

Not specified

Data Privacy Management

Access Control
CCPA Compliance
Consent Management
Data Mapping
GDPR Compliance
Policy Management
Risk Management
Sensitive Data Identification

Data Security

Data Classification
Data Discovery
Data Masking
Data-Centric Security
Encryption
Identity / Access Management
Policy Management
Sensitive Data Compliance

Hybrid Cloud Storage

Not specified

Categories and Features

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