TSG Analytics Data Plane
The Analytics Data Plane is a specialized implementation designed for distributed analytics and secure computation across multiple dataspace participants. It enables collaborative analysis while preserving data sovereignty and privacy, making it ideal for use cases requiring cross-organizational insights without direct data sharing.
Overview
The Analytics Data Plane extends the TSG ecosystem with sophisticated distributed analytics capabilities. It orchestrates complex analytics workflows across multiple parties, ensuring data privacy and security while enabling powerful collaborative analysis scenarios.
Key Capabilities:
- Distributed Analytics: Execute analytics workflows across multiple independent participants
- Privacy-Preserving Computation: Secure computation protocols that protect sensitive data
- Workflow Orchestration: Complex multi-step analytics pipelines with dependency management
- Result Aggregation: Secure collection and combination of distributed computation results
- Event-Driven Coordination: Asynchronous coordination for long-running analytics operations
Development Status: The Analytics Data Plane is currently in active development and not ready for production use. The architecture and interfaces are subject to change as development progresses.
Documentation
For Developers
- Module Architecture - Technical overview of Analytics Data Plane modules and their responsibilities
- Configuration - Configuration options and environment setup
- Build Process - Development workflow and build instructions
For System Architects
- System Architecture - Overall TSG architecture and design principles
- Distributed Analytics Design - Analytics-specific architectural patterns
For Operators
- Deployment Guide - Using the TSG CLI for deployment and management
- Configuration Reference - Complete configuration documentation
Development Roadmap
The Analytics Data Plane is being developed with the following priorities:
- Core Infrastructure - Event-driven coordination and workflow management
- Privacy Protocols - Secure multi-party computation capabilities
- ML/AI Integration - Native support for machine learning workloads
- Performance Optimization - High-throughput distributed processing