Data Quality Framework

Data Quality Framework Trust your data. A pluggable quality engine with built-in checks for completeness, uniqueness, validity, freshness, and consistency — plus automated reporting to Slack, HTML, and Delta Lake. By Datanest Digital | Version 1.0.0 | $49 What You Get Quality Engine — Rule-based engine that loads checks from YAML, executes them against any Spark DataFrame, aggregates results, and produces structured reports 6 Check Types — Completeness (null/empty), uniqueness (duplicates), validity (regex, range, enum), freshness (staleness), consistency (cross-table), and custom (arbitrary SQL expressions) 3 Reporters — Slack webhook notifications, standalone HTML reports, and Delta Lake audit table writer for historical trending YAML Configuration — Define rules and thresholds in human-readable YAML; no code changes needed to add new checks Databricks Notebook — Ready-to-run notebook for executing quality checks as a scheduled job Strategy Guide — Best practices for implementing dat