Skip to content

Knowledge Base Introduction

The Datus Agent Knowledge Base is a multi-modal intelligence system that transforms scattered data assets into a unified, searchable repository. Think of it as "Google for your data" with deep understanding of SQL, business metrics, and data relationships.

Core Purpose

  • Data Discovery: Find relevant tables, columns, and patterns
  • Query Intelligence: Understand business intent and generate SQL
  • Knowledge Preservation: Capture and organize SQL expertise
  • Semantic Search: Find information by meaning, not keywords

Core Components

1. Schema Metadata

Purpose: Understand database structure and provide intelligent table recommendations.

  • Stores: Table definitions, column info, sample data, statistics
  • Capabilities: Find tables by business meaning, get table structures, semantic search
  • Use: Automatic table selection, data discovery, schema understanding

2. Semantic Models

Purpose: Enrich database schemas with semantic information for better SQL generation.

  • Stores: Table structures, dimensions, measures, entity relationships
  • Capabilities: Schema linking, column usage patterns, foreign key discovery
  • Use: Accurate ad-hoc SQL generation, smart filtering, proper JOIN construction

3. Business Metrics

Purpose: Manage and query standardized business KPIs.

  • Stores: Metric definitions, subject tree categorization
  • Capabilities: Direct metric queries via MetricFlow, metrics-first strategy
  • Use: Consistent reporting, eliminate duplicate SQL, standardized definitions

4. Reference SQL

Purpose: Capture, analyze, and make searchable SQL expertise.

  • Stores: Historical queries, LLM summaries, query patterns, best practices
  • Capabilities: Find queries by intent, get similar queries, learn patterns
  • Use: Knowledge sharing, optimization through examples, team onboarding

5. External Knowledge

Purpose: Process and index domain-specific business knowledge for intelligent search.

  • Stores: Business terminology, rules, concepts, hierarchical categorization
  • Capabilities: Semantic search for business terms, context enrichment, term resolution
  • Use: Agent context enhancement, terminology standardization, knowledge onboarding

Key Features

  • Unified Search: Single interface across all knowledge domains
  • Semantic Search: Find by meaning using vector embeddings
  • Intelligent Classification: Automatic categorization and organization
  • Scalable: Lazy loading, batch processing, incremental updates