This workflow automatically monitors and reports data quality for any SQL table using configurable checks and threshold…
This workflow automatically monitors and reports data quality for any SQL table using configurable checks and thresholds. It evaluates key metrics—including null values, duplicate records, row count anomalies, and outliers—and assigns a clear PASS, WARN, or FAIL status. Designed for efficiency, the workflow dynamically injects table and column names from a central Config node, so you don’t need to edit SQL queries manually. All checks run in parallel, and results are consolidated into a structured HTML report with clear status indicators. The report is automatically sent via email and logged into Google Sheets for historical tracking, auditing, and trend analysis. ⚙️ Setup Update the Config node with your table name, column names, thresholds, and email recipient. Connect your database credentials (Postgres/MySQL) in all query nodes. Set up Gmail or SMTP credentials in the email node. Connect your Google Sheets account and ensure required columns exist. Activate the workflow (runs daily by default, can be customized). This workflow is ideal for data analysts and analytics engineers who want a lightweight, automated solution to proactively monitor data quality without exporting large datasets or building complex pipelines. An n8n automation workflow template by Bhautik Trambadia.
Bhautik Trambadia
web
free
Others in the same category, ranked by how often they are opened.
