agentic-data-stack-community/data-core/checklists/data-quality-checklist.yaml

AI Agentic Data Stack Framework - Community Edition. Open source data engineering framework with 4 core agents, essential templates, and 3-dimensional quality validation.

# Data Quality Validation Checklist - Community Edition
# Simplified checklist focusing on 3 essential quality dimensions

metadata:
  checklist_id: "data-quality-checklist-community"
  name: "Data Quality Validation Checklist - Community Edition"
  version: "1.0.0"
  description: "Community-focused data quality validation with 3 core dimensions"
  category: "quality-validation"
  tags: ["data-quality", "validation", "accuracy", "completeness", "consistency", "community"]
  created_by: "AI Agentic Data Stack Framework - Community"
  created_date: "2025-01-24"

# Core Quality Dimensions (Community Edition: 3 of 7)
quality_dimensions:
  completeness:
    description: "Ensures all required data is present and accounts for missing values"
    checks:
      - [ ] All required fields are populated
      - [ ] No unexpected null values in mandatory fields
      - [ ] Record counts match business expectations
      - [ ] All expected data sources are included
      - [ ] Missing data patterns documented and understood
    
  accuracy:
    description: "Validates data correctness and format compliance"
    checks:
      - [ ] Data values are within valid ranges
      - [ ] Data types are correctly applied
      - [ ] Format standards are followed consistently
      - [ ] Business rules are correctly implemented
      - [ ] Manual spot checks confirm accuracy
    
  consistency:
    description: "Ensures data alignment across systems and over time"
    checks:
      - [ ] Data is consistent across different systems
      - [ ] Referential integrity is maintained
      - [ ] Naming conventions are followed
      - [ ] Duplicate records are identified and handled
      - [ ] Cross-field validations pass

# Basic Data Profiling
data_profiling:
  basic_statistics:
    - [ ] Count of records calculated
    - [ ] Null value percentages identified
    - [ ] Basic statistics computed (min, max, average)
    - [ ] Data type distribution analyzed
    - [ ] Outliers identified and documented
    
  pattern_analysis:
    - [ ] Common data patterns identified
    - [ ] Format consistency verified
    - [ ] Special characters and encoding handled
    - [ ] Pattern violations documented

# Essential Quality Rules
quality_rules:
  validation_rules:
    - [ ] Field-level validations defined
    - [ ] Cross-field validations implemented
    - [ ] Business rule catalog created
    - [ ] Quality thresholds established
    - [ ] Exception handling procedures defined

# Basic Quality Monitoring
quality_monitoring:
  monitoring_setup:
    - [ ] Quality checks integrated into data pipelines
    - [ ] Basic quality metrics tracked
    - [ ] Alert thresholds configured for critical issues
    - [ ] Quality scorecard framework established
    - [ ] Regular quality assessment scheduled

# Issue Management (Simplified)
issue_management:
  detection_and_resolution:
    - [ ] Issue detection methods implemented
    - [ ] Issue severity classification defined
    - [ ] Resolution workflows documented
    - [ ] Root cause analysis procedures established
    - [ ] Issue tracking system in place

# Documentation and Communication
documentation:
  essential_documentation:
    - [ ] Quality requirements documented
    - [ ] Quality check definitions maintained
    - [ ] Issue resolution procedures documented
    - [ ] Quality metrics and KPIs defined
    - [ ] Stakeholder communication plan established

# Community Testing
testing_validation:
  basic_testing:
    - [ ] Test data sets created for validation
    - [ ] Quality test cases defined and executed
    - [ ] Source-to-target validation performed
    - [ ] Business validation completed
    - [ ] Performance of quality checks acceptable

# Sign-off
sign_off:
  community_certification:
    - [ ] 3-dimensional quality standards met
    - [ ] Community stakeholder approval obtained
    - [ ] Quality gates for essential dimensions passed
    - [ ] Documentation complete and accessible
    - [ ] Ongoing monitoring plan established

# Upgrade Path to Enterprise
enterprise_upgrade_info:
  additional_dimensions_available:
    - "Timeliness: Real-time data freshness validation"
    - "Validity: Advanced business rule validation"
    - "Uniqueness: ML-powered duplicate detection"
    - "Business Value: ROI and impact measurement"
  
  contact_info:
    email: "enterprise@agenticdata.com"
    website: "https://enterprise.agenticdata.com"
    description: "For advanced 7-dimensional quality framework with ML enhancement"