Data Faker Generator

Genera dati di test realistici: nomi, email, indirizzi, numeri di telefono, date.

Output generato
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Come utilizzare Data Faker Generator

Define columns

Add a column for every field you need, assign a name and choose from 21 available types (name, email, address, date, UUID, company, etc).

Set number of rows and format

Choose how many rows to generate (1-1000) and the output format: JSON, CSV or SQL INSERT instructions (specifying table name).

Generate Data

Premi "Generate": the tool creates random rows consistent with each column type, showing a preview table of the first 5 rows.

Copy or download output

Pass to the "Raw" tab to view full output, then copy it to notes or download as .json, .csv, or .sql files.

Suggerimenti

  • Rename columns with exact destination table names to copy/paste output SQL without modifications.
  • Combine multiple column types (e.g. firstName + lastName + email) to generate realistic user datasets in just a few seconds.
  • Use the CSV format when you need to quickly import test data into spreadsheets or BI tools.

Domande frequenti

What types of data can I generate?

21 types: name, surname, full name, email, phone number, address, city and country (with realistic Italian/European data), CAP, date, integer, decimal, boolean, UUID v4, placeholder text, URL, IP address, company, professional title, color, and fictional credit card number.

Are generated data real or represent existing people?

No, all data is completely fabricated randomly generated from predefined lists (names, surnames, cities) or pseudo-random algorithms (emails, UUIDs, numbers), and do not correspond to real people or entities.

How many lines can I generate in a single execution?

Up to 1000 lines per generation. It's a limit designed to keep the tool reactive in the browser; for larger test datasets, you can generate multiple batches and combine them.

What database formats are compatible with SQL INSERT?

Generate generic SQL syntax with identifiers between backticks, compatible mainly with MySQL/MariaDB. For PostgreSQL or SQLite, you may need to replace backticks with double quotes.