Advanced CSV Mapper
Map, transform and join multiple CSV sources into one
Load up to 5 CSV files, define a canonical target schema, map columns from each source with per-field transforms (rename, concat, split, lookup, default), join sources on a key and export the consolidated result as CSV or JSON — all in the browser.
Fuentes CSV
Carga hasta 5 archivos CSV. Se detectan cabeceras y delimitadores automáticamente.
// quick guide
The Advanced CSV Mapper allows data engineers, analysts, and MDM specialists to clean, align, and consolidate multiple disparate CSV files into a single standardized schema without writing scripts or uploading data to servers.
How to use this tool:
- Load up to 5 CSV files using the file inputs.
- Define your **Target Schema** (declare column names and types).
- Map source columns to target columns. You can apply transformations (such as renaming, concatenation, splitting, lookups, or defaults).
- Specify join conditions to merge rows from different files based on a key (e.g. Employee ID or SKU).
- Export the unified, clean dataset as a new CSV or JSON file.
// frequently asked questions
Is my CSV data uploaded to a server?
No. The entire mapping, merging, and transformation process runs locally in your browser memory using JavaScript and local file buffers. Your data never leaves your computer, making it compliant with strict privacy regulations.
What transformations are supported?
You can apply string operations (uppercase, lowercase, trim), split columns by delimiter, concatenate multiple columns, map values, and supply fallback default values for missing data.
How does the join strategy work?
The tool performs joins by matching row keys across the files you load. If you define a primary key, it will align matching rows into a single target row based on that identifier, similar to a SQL JOIN query.