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Obt design optimizer

Skill a5c-ai/babysitter/library/specializations/data-engineering-analytics/skills/obt-design-optimizer

Designs and optimizes One Big Table (OBT) patternsFrom its SKILL.md

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npx -y skills add a5c-ai/babysitter --skill obt-design-optimizer

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SKILL.md

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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

{
  "sourceModels": ["object"],
  "queryPatterns": ["object"],
  "platform": "snowflake|bigquery|redshift",
  "constraints": {
    "maxColumns": "number",
    "refreshFrequency": "string"
  }
}

Output Schema

{
  "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

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