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What is Harbr?

Quickly generate data products from multiple sources without transferring the data, ensuring they are readily available to all while maintaining complete oversight. Create meaningful experiences that uncover value, while also strengthening your data mesh through smooth sharing, discovery, and governance across different areas. Promote teamwork and accelerate innovation by granting unified access to premium data products. Provide controlled access to AI models for each user, guaranteeing that data interactions with AI are managed to protect intellectual property. Optimize AI workflows to swiftly integrate and improve new features. Users can access and create data products directly within Snowflake, eliminating the complexities associated with moving data. Benefit from the ease of maximizing your data's potential, making it available for analysis without the need for centralized infrastructure or tools. Data products are designed to work seamlessly with various tools, ensuring governance is maintained while speeding up outcomes, thus creating a more productive data environment. This approach not only boosts collaboration but also empowers users to utilize data in more impactful ways, ultimately leading to enhanced decision-making across the organization. By fostering a culture of accessibility and innovation, organizations can stay ahead in a rapidly evolving data landscape.

What is Apheris?

Apheris serves as a platform that enables organizations to securely and privately collaborate on distributed datasets while remaining compliant with regulatory frameworks. By utilizing the Apheris Compute Gateway, users can conduct machine learning and analytical tasks directly where the data resides, ensuring that it is never exposed or relocated, which helps maintain its intrinsic value. This innovative approach addresses common issues associated with data being confined due to geographical limitations, regulatory constraints, or internal organizational policies, as well as the difficulties that arise from transferring sensitive or costly data. Unlike alternative methods such as synthetic data generation, encryption, or data clean rooms—which can compromise result accuracy, introduce security risks, or lack the capacity to scale effectively—Apheris adopts a federated model. This enables the creation of analytical models from extensive datasets without necessitating data movement, backed by a comprehensive framework of governance, security, and privacy that guarantees adherence to applicable regulations from the very beginning. As a result, Apheris not only fosters enhanced collaboration but also plays a crucial role in protecting essential data assets, making it an invaluable resource for organizations navigating the complexities of data utilization. Furthermore, this capability positions Apheris as a forward-thinking solution in an increasingly data-driven world.

Media

Media

Integrations Supported

Amazon S3
Amazon Web Services (AWS)
Azure Databricks
Google Cloud Platform
Looker
Microsoft Azure
Mindfuel
Snowflake

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Harbr

Date Founded

2017

Company Location

United Kingdom

Company Website

www.harbrdata.com

Company Facts

Organization Name

Apheris

Company Location

Germany

Company Website

www.apheris.com

Categories and Features

Data Exchange

Not specified

Data Integration

Not specified

Data Lake

Not specified

Data Management

Not specified

Data Marketplaces

Not specified

Data Monetization

Not specified

Categories and Features

Data Collaboration

Not specified

Data Exchange

Not specified

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