86 lines
3 KiB
Markdown
86 lines
3 KiB
Markdown
# Data Catalog
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## Overview
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The Data Catalog service provides a centralized system for data asset discovery, management, and governance within the stock-bot platform. It serves as the single source of truth for all data assets, their metadata, and relationships, enabling efficient data discovery and utilization across the platform.
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## Key Features
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### Data Asset Management
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- **Asset Registration**: Automated and manual registration of data assets
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- **Metadata Management**: Comprehensive metadata for all data assets
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- **Versioning**: Tracks changes to data assets over time
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- **Schema Registry**: Central repository of data schemas and formats
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### Data Discovery
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- **Search Capabilities**: Advanced search across all data assets
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- **Categorization**: Hierarchical categorization of data assets
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- **Tagging**: Flexible tagging system for improved findability
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- **Popularity Tracking**: Identifies most-used data assets
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### Data Governance
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- **Access Control**: Fine-grained access control for data assets
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- **Lineage Tracking**: Visualizes data origins and transformations
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- **Quality Metrics**: Monitors and reports on data quality
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- **Compliance Tracking**: Ensures regulatory compliance for sensitive data
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### Integration Framework
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- **API-first Design**: Comprehensive API for programmatic access
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- **Event Notifications**: Real-time notifications for data changes
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- **Bulk Operations**: Efficient handling of batch operations
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- **Extensibility**: Plugin architecture for custom extensions
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## Integration Points
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### Upstream Connections
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- Data Processor (for processed data assets)
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- Feature Store (for feature metadata)
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- Market Data Gateway (for market data assets)
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### Downstream Consumers
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- Strategy Development Environment
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- Data Analysis Tools
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- Machine Learning Pipeline
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- Reporting Systems
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## Technical Implementation
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### Technology Stack
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- **Runtime**: Node.js with TypeScript
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- **Database**: Document database for flexible metadata storage
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- **Search**: Elasticsearch for advanced search capabilities
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- **API**: GraphQL for flexible querying
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- **UI**: React-based web interface
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### Architecture Pattern
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- Domain-driven design for complex metadata management
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- Microservice architecture for scalability
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- Event sourcing for change tracking
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- CQRS for optimized read/write operations
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## Development Guidelines
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### Metadata Standards
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- Adherence to common metadata standards
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- Required vs. optional metadata fields
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- Validation rules for metadata quality
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- Consistent naming conventions
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### Extension Development
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- Plugin architecture documentation
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- Custom metadata field guidelines
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- Integration hook documentation
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- Testing requirements for extensions
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### Performance Considerations
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- Indexing strategies for efficient search
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- Caching recommendations
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- Bulk operation best practices
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- Query optimization techniques
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## Future Enhancements
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- Automated metadata extraction
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- Machine learning for data classification
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- Advanced lineage visualization
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- Enhanced data quality scoring
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- Collaborative annotations and discussions
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- Integration with external data marketplaces
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