How to use the Synthetic Dataset from an Excel File
Load real data and get new rows that behave like it, without copying any real row.
The Synthetic Data Generator learns from your own file and makes new rows that behave like it. Number and date columns keep their range, spread and the way they move together, such as age and salary. Category columns keep their shares. Names, emails, phones and similar fields get new fake values, ids are renumbered, free text gets the same shape without the same words, and rare values are hidden. No real row is copied. It runs in your browser, and a table shows the real and the synthetic numbers side by side so you can check.
Load your real file
Check how each column will be made
Generate and compare with the real data
Tips
Choose Statistical (learns ranges and relationships) or Random sampling (only values that exist in your data).
Cities keep their real values by default. Switch a column to New fake values if you want different ones.
More real rows give better results. Under 100 rows is only a rough copy.
Use Leave out for columns you do not need, such as notes.
Review the data before sharing it publicly: synthetic data lowers risk but is not a guarantee.
Yes. Load the .xlsx file; the first sheet is read. CSV, JSON and Parquet files also work.
Do the columns still relate to each other?
Number and date columns keep their relationships, for example age and salary moving together. Category columns keep their shares.
How is the Synthetic Data Generator different from the Data Generator?
The Data Generator makes random rows from column types you choose, such as names, emails and dates, so the columns do not relate to each other. The Synthetic Data Generator learns from your own file and makes rows that match its ranges, shares and the way number columns move together, so the result looks like your real data. Use the Data Generator for quick fake data, and the Synthetic Data Generator when the data should behave like production.
Is synthetic data safe to share?
No real row is copied, names and emails are replaced, ids are renumbered and rare values are hidden. That lowers the risk a lot, but it is not a guarantee, so review it before you share it publicly.
Generate Synthetic Data from a CSV: Upload a CSV and generate synthetic rows that match its distributions and number relationships. Names and emails are replaced. Free, no upload.
Privacy-Safe Test Data from Real Data: Create test data that looks like production without copying production rows. Names and emails are replaced and rare values are hidden. Free, no upload.