data-governance-lineage

Track data freshness and validate schema contracts by running automated diagnostics on input CSV files. This generates a JSON diagnostics report that enforces data quality thresholds before any downstream model release. It checks schema versions and monitors freshness objectives automatically.

Data lineage completeness verifies that full lineage metadata is available before downstream release. You need to verify it when onboarding new data feeds for critical financial models to ensure schema contracts and freshness meet predefined quality thresholds, quarantining data that fails.

Automate data governance lineage workflows by executing Python scripts that manage schema contracts, freshness tracking, and lineage completeness. These scripts run deterministic diagnostics and apply risk controls, outputting results to a JSON file for production monitoring.

Yes, you can use Python scripts to quarantine data feeds. When onboarding a new data feed, the scripts run diagnostics on schema, freshness, and completeness, automatically quarantining the feed if it fails to meet predefined data quality thresholds.

Yes, Python is required to run diagnostics and check schema versions. The Skill relies on Python scripts to execute data governance workflows, enforce data contracts, and generate JSON diagnostics, while using markdown references for operational playbooks and checklists.