n8n Workflow: Inventory Personal Data in Data Tables

Inventory personal data in your n8n Data Tables—automatically

This n8n workflow scans all (non-excluded) n8n Data Tables to inventory personal data, identifies sensitive columns using regex patterns and Groq-assisted classification, and logs the results into dedicated Data Tables. If any special-category data (health, biometric, belief, criminal) is detected, it also sends an alert to Discord.

What this workflow does

• Runs on demand or on a schedule every Monday at 07:00.
• Loads scan settings and detection patterns from the n8n Data Table pattern store, then enumerates all Data Tables on the instance while skipping excluded table names.
• For each table, samples a few rows and classifies each column using name and value regexes while masking sampled values into non-sensitive “shapes.”
• Sends only column names and masked shapes for ambiguous candidates to Groq, which proposes the table purpose and additional personal-data columns.
• Stores a run summary in pdi_runs and upserts one inventory record per detected column into pdi_inventory (including category, sensitivity, confidence, source, evidence, and sample shape).
• Posts a Discord webhook alert when special-category columns are found.

Use cases

• Audit a SaaS automation environment by cataloging personal-data fields across multiple n8n Data Tables.
• Help operators prepare for privacy reviews by producing a structured inventory (confidence + evidence + masked shape).
• Continuously reduce risk as tables change by running the scan weekly and flagging special-category data.

Technical details

• Groq integration: requires a Groq API credential for the Groq chat model node.
• Discord integration: uses a Discord webhook credential to post special-category alerts.
• Uses nodes including if, set, code, discord, data table, and sticky note.
• Includes a setup step: “Set Up Tables” to initialize the required Data Tables.