Data Pipeline Demo Data Pipeline

data-pipeline-demo-data-pipeline

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Project

Data pipeline workflows for extraction, validation, transformation, and reporting.

Workflow

• Locate source data, schema contracts, and expected output destinations
• Run validation first, such as npm run data:validate, before transforming data
• Run extraction or transformation on a small sample or dry run
• Compare row counts, null rates, key fields, and generated report artifacts
• Document assumptions, skipped checks, and any remaining data quality risk

Commands

• install: npm install
• test: npm test
• data:validate: npm run data:validate
• data:transform: npm run data:transform
• data:report: npm run data:report

Principles

• Preserve raw inputs and keep derived outputs separate
• Validate schemas, row counts, checksums, and representative samples
• Run transformations on a narrow sample before full pipeline execution
• Record data assumptions, freshness, and known quality gaps