Data Mapping Generator

Create comprehensive ETL mapping documentation instantly with our intelligent Data Mapping Generator. This tool analyzes your source and target database schemas to automatically match fields based on naming patterns, data types, and common business rules. Perfect for data migration projects, ETL development, data warehouse documentation, and integration mapping. Export professional mapping documents in multiple formats including Excel, CSV, JSON, and HTML.

Intelligent Field Matching Business Rule Detection Multiple Export Formats Transformation Suggestions Data Quality Rules

Quick Examples

EXACT_MATCH: customer_id → customer_id (100% match)
FUZZY_MATCH: cust_name → customer_name (85% similarity)
TYPE_CONVERSION: VARCHAR(50) → NVARCHAR(100) with padding

Source Schema

Input Type

Source Definition

Enter CREATE TABLE statements or CSV headers

Target Schema

Target Definition

Enter CREATE TABLE statements or CSV headers

Mapping Configuration

Matching Sensitivity

Loose (50%) 75% Strict (100%)

Mapping Strategy

Suggest Transformations

Detect Business Rules

Include Data Quality Rules

Sample Schemas

Generated Mappings

Mapping results will appear here...

Mapping Statistics

Mapped Fields

Unmapped Source

Unmapped Target

Suggested Transformations

Data Quality Rules

Export Documentation

Help & Related Tools

Everything you need to know

FAQ Frequently Asked Questions

What mapping capabilities does this tool offer?

The Data Mapping Generator provides intelligent field matching using multiple algorithms including exact name matching, fuzzy string matching, data type compatibility, and pattern recognition. It suggests transformations, identifies data quality rules, and generates comprehensive documentation.

How do I generate ETL mapping documentation?

Paste your source and target schemas (CREATE TABLE statements) into the respective fields, configure matching sensitivity, and click Generate. The tool automatically analyzes both schemas and creates detailed mapping documentation with transformation rules.

What database formats are supported?

The tool supports SQL DDL from MySQL, PostgreSQL, SQL Server, Oracle, and other major databases. It can also process CSV headers for flat file mappings and handles complex data types including JSON and XML fields.

How accurate is the automatic field matching?

The matching algorithm achieves 95%+ accuracy for exact matches and 80%+ for fuzzy matches. It uses Levenshtein distance, soundex algorithms, and common abbreviation patterns. All mappings include confidence scores for manual review.

Can I customize the mapping rules and transformations?

Yes, after automatic generation you can edit mappings, add custom transformation rules, specify data quality checks, and define business logic. The tool supports complex transformations including lookups, concatenation, and conditional logic.