obt-design-optimizer

# OBT Design Optimizer ## Overview Designs and optimizes One Big Table (OBT) patterns. This skill balances denormalization benefits with maintainability for analytical use cases. ## Capabilities - Column selection optimization - Denormalization strategy - Nested/repeated field design (BigQuery) - Clustering key selection - Partition strategy - Update frequency optimization - Query pattern analysis - Storage vs. performance tradeoffs ## Input Schema ```json { "sourceModels": ["object"], "queryPatterns": ["object"], "platform": "snowflake|bigquery|redshift", "constraints": { "maxColumns": "number", "refreshFrequency": "string" } } ``` ## Output Schema ```json { "obtDesign": { "columns": ["object"], "clustering": ["string"], "partitioning": "object" }, "buildStrategy": "object", "refreshConfig": "object", "estimatedQueryImprovement": "percentage" } ``` ## Target Processes - OBT Creation - BI Dashboard Development - Query Optimization ## Usage Guidelines 1. Analyze source models and relationships 2. Document common query patterns 3. Define platform and constraints 4. Balance column count with query needs ## Best Practices - Include only columns needed for known query patterns - Use appropriate clustering for common filter columns - Partition by date for time-series analysis - Schedule refreshes based on source update frequency - Monitor query performance and adjust design