Overview
Overview This workflow automatically converts CSV or Excel files into a production-ready database schema using AI and rule-based validation. It analyzes uploaded data, detects column types, relationships, and data quality, then generates a normalized schema. The output includes SQL DDL scripts, ERD diagrams, a data dictionary, and a load plan. This eliminates manual schema design and accelerates database setup from raw data. How It Works File Upload (Webhook) Accepts CSV or XLSX files via webhook endpoint Initializes workflow configuration (thresholds, retry limits) File Extraction Detects file format (CSV or Excel) Extracts rows into structured JSON Merges extracted datasets Data Cleaning & Profiling Removes duplicates and normalizes values Detects data types (integer, float, date, boolean, string) Computes column statistics (nulls, uniqueness, distributions) Generates file hash and sample dataset Column Profiling Engine Identifies potential primary keys Detects cardinality and uniqueness levels Suggests foreign key relationships based on value overlap AI Schema Generation Uses an AI agent to design normalized tables Assigns SQL data types based on real data Defines primary keys, foreign keys, constraints, and indexes Validation Layer Ensures schema matches actual data Validates: Data types Primary key uniqueness Foreign key overlap (>70%) Constraint consistency Detects circular dependencies Revision Loop If validation fails: Sends feedback to AI agent Regenerates schema Retries up to configured limit Schema Output Generation Generates: SQL DDL scripts ERD (Mermaid format) Data dictionary Load plan with dependency graph Load Plan Engine Computes optimal table insertion order Detects circular dependencies Suggests batching strategy Combine & Explain Merges all outputs Optional AI explanation of schema decisions Response Output Returns structured JSON via webhook: SQL schema ERD summary Data dictionary Load plan Optional explanation Setup Instructions Activate the workflow and copy the webhook URL Send a POST request with a CSV or XLSX file Configure OpenAI credentials (used by AI agent) Adjust thresholds if needed (FK overlap, retries, confidence) Execute workflow and review generated outputs Use Cases Auto-generate database schema from CSV/Excel files Data migration and onboarding pipelines Rapid database prototyping Reverse engineering datasets AI-assisted data modeling Requirements n8n (latest version recommended) OpenAI API credentials LangChain nodes enabled CSV or XLSX input file. An n8n automation workflow template by ResilNext.
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