data-integrity-suite

Data pipeline validation is automated by sequentially executing seven specialized checks covering source auditing, pipeline integrity, signal freshness, and quality scoring. This orchestrates a full end-to-end audit to generate a consolidated compliance report before production deployment.

Data provenance checking validates the origin and lineage of data sources through automated auditing. It ensures data freshness and quality by verifying unbroken pipelines, assigning confidence scores, and citing provenance within a unified report.

Yes, data auditing requires access to codebase directories and governance documents to validate pipeline integrity. These inputs provide the necessary context for verifying data provenance, freshness, quality, and merchandising compliance.

A comprehensive data quality audit is executed by running a sequential suite of seven specialized validation skills. This approach consolidates feed source auditing, signal validation, and confidence scoring into a single unified compliance report.

Yes, data merchandising compliance is validated alongside pipeline integrity through an intelligence-merchandiser check. The suite enforces merchandising rules while simultaneously auditing source legitimacy, pipeline continuity, and data quality.