Best Data Collaboration Platforms for Linux

Fasoo Data Radar (FDR) is a data discovery and classification solution that helps organizations locate, analyze, and manage sensitive unstructured data across on-premise servers, cloud storage, and endpoints. It scans and classifies files based on keywords, regex patterns, file formats, and other predefined policies, ensuring organizations maintain control over critical information. With real-time monitoring and centralized policy enforcement, FDR enhances data security by identifying risks, preventing unauthorized access, and assisting with compliance requirements such as GDPR, HIPAA, and CCPA. Its integration with enterprise security frameworks allows organizations to apply consistent data protection policies while improving operation workflows. By automating data classification and governance, FDR increases efficiency and enhances data visibility for security and compliance management.

Confidently branch, review, and merge data as you experiment with complete history and recoverability. Track your code and data together for always-in-sync development and guaranteed reproducibility. Automate reports, audit access, and manage metadata in a centralized location for everyone. XetHub is ideal for teams who already use Git to track their code changes, and want to leverage the power of infinite history, pull requests, and difference-based tracking for larger assets such as datasets or media files. Managing complete projects with familiar Git semantics makes change tracking and continuous integration a breeze, especially for workflows that use code to generate or augment assets.

MLReef enables domain experts and data scientists to securely collaborate via a hybrid of pro-code & no-code development approaches. 75% increase in productivity due to distributed workloads. This enables teams to complete more ML projects faster. Domain experts and data scientists collaborate on the same platform reducing 100% of unnecessary communication ping-pong. MLReef works on your premises and uniquely enables 100% reproducibility and continuity. Rebuild all work at any time. You can use already well-known and established git repositories to create explorable, interoperable, and versioned AI modules. AI Modules created by your data scientists become drag-and-drop elements. These are adjustable by parameters, versioned, interoperable, and explorable within your entire organization. Data handling often requires expert knowledge that a single data scientist often lacks. MLReef enables your field experts to relieve your data processing task, reducing complexities.

Easily create rich, interactive dashboards that accelerate analytical insights across your enterprise. Cloudera Data Visualization enables data engineers, business analysts, and data scientists to quickly and easily explore data, collaborate, and share insights across the data lifecycle—from data ingest to data insights and beyond. Delivered natively as part of Cloudera, Data Visualization delivers a consistent and easy-to-use data visualization experience with intuitive and accessible drag-and-drop dashboards and custom application creation. Data Visualization is fully secured by SDX, enabling augmented data workflows across all your data and analytic workflows. Build predictive applications from ML models served in Cloudera Machine Learning, or leverage your data warehouse to power fast intelligent reporting without moving data or using third-party tools.