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What is Tumult Analytics?

Created and consistently enhanced by a skilled team of experts in differential privacy, this innovative system is currently in use by organizations like the U.S. Census Bureau. Built on the Spark framework, it effectively manages input tables containing billions of records. The platform features a wide and growing selection of aggregation functions, data transformation operations, and privacy frameworks. Users have the capability to perform public and private joins, implement filters, or use custom functions on their datasets. It allows for the calculation of counts, sums, quantiles, and more while adhering to various privacy models, with differential privacy made accessible through easy-to-follow tutorials and thorough documentation. Tumult Analytics is developed on our sophisticated privacy architecture, Tumult Core, which governs access to sensitive information, guaranteeing that every application and program comes with an embedded proof of privacy. The system is engineered by combining small, easily verifiable components, ensuring robust safety through reliable stability tracking and floating-point operations. Additionally, it incorporates a versatile framework rooted in peer-reviewed academic research, making certain that users can have confidence in the security and integrity of their data management practices. This unwavering dedication to transparency and security establishes a new benchmark in the realm of data privacy and encourages other organizations to enhance their own privacy practices.

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.

Media

Media

Integrations Supported

Java
Python
SPARK

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Contact PHEMI to learn about our value-based pricing.

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Tumult Analytics

Date Founded

2019

Company Location

United States

Company Website

www.tmlt.dev/

Company Facts

Organization Name

PHEMI Systems

Date Founded

2013

Company Location

Canada

Company Website

www.phemi.com

Categories and Features

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

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