Monitor data quality with Notion rules, SQL checks & AI-powered alerts
Description This workflow continuously validates data quality using rules stored in Notion, runs anomaly checks against your SQL database, generates AI-powered diagnostics, and alerts your team only when real issues o...
Template notes
Description
This workflow continuously validates data quality using rules stored in Notion, runs anomaly checks against your SQL database, generates AI-powered diagnostics, and alerts your team only when real issues occur.
Notion holds all data quality rules (source, field, condition, severity). n8n reads them on schedule, converts them into live SQL queries, and aggregates anomalies into a global run summary.
The workflow then scores data health, creates a Notion run record, optionally opens a Jira issue, and sends a Slack/email alert including AI-generated root cause & recommended fixes.
Target users Perfect for: - DataOps - Analytics - Product Data - BI - Compliance - ETL/ELT pipelines - Platform reliability teams.
Workflow steps 
How it works 1) Notion → Rules Database Each entry defines a check (table, field, condition, severity). 2) n8n → Dynamic Query Execution Rules are converted into SQL and checked automatically.
3) Summary Engine Aggregates anomalies, computes data quality score.