# Data Catalog

## Overview
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.

## Key Features

### Data Asset Management
- **Asset Registration**: Automated and manual registration of data assets
- **Metadata Management**: Comprehensive metadata for all data assets
- **Versioning**: Tracks changes to data assets over time
- **Schema Registry**: Central repository of data schemas and formats

### Data Discovery
- **Search Capabilities**: Advanced search across all data assets
- **Categorization**: Hierarchical categorization of data assets
- **Tagging**: Flexible tagging system for improved findability
- **Popularity Tracking**: Identifies most-used data assets

### Data Governance
- **Access Control**: Fine-grained access control for data assets
- **Lineage Tracking**: Visualizes data origins and transformations
- **Quality Metrics**: Monitors and reports on data quality
- **Compliance Tracking**: Ensures regulatory compliance for sensitive data

### Integration Framework
- **API-first Design**: Comprehensive API for programmatic access
- **Event Notifications**: Real-time notifications for data changes
- **Bulk Operations**: Efficient handling of batch operations
- **Extensibility**: Plugin architecture for custom extensions

## Integration Points

### Upstream Connections
- Data Processor (for processed data assets)
- Feature Store (for feature metadata)
- Market Data Gateway (for market data assets)

### Downstream Consumers
- Strategy Development Environment
- Data Analysis Tools
- Machine Learning Pipeline
- Reporting Systems

## Technical Implementation

### Technology Stack
- **Runtime**: Node.js with TypeScript
- **Database**: Document database for flexible metadata storage
- **Search**: Elasticsearch for advanced search capabilities
- **API**: GraphQL for flexible querying
- **UI**: React-based web interface

### Architecture Pattern
- Domain-driven design for complex metadata management
- Microservice architecture for scalability
- Event sourcing for change tracking
- CQRS for optimized read/write operations

## Development Guidelines

### Metadata Standards
- Adherence to common metadata standards
- Required vs. optional metadata fields
- Validation rules for metadata quality
- Consistent naming conventions

### Extension Development
- Plugin architecture documentation
- Custom metadata field guidelines
- Integration hook documentation
- Testing requirements for extensions

### Performance Considerations
- Indexing strategies for efficient search
- Caching recommendations
- Bulk operation best practices
- Query optimization techniques

## Future Enhancements
- Automated metadata extraction
- Machine learning for data classification
- Advanced lineage visualization
- Enhanced data quality scoring
- Collaborative annotations and discussions
- Integration with external data marketplaces