Fake User Data Generator
Free online Fake User Data Generator that runs directly in your browser.
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1Enter data
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2Click the button
The tool will immediately process your data in the browser. -
3Get the result
Copy the finished text or save the file to your device.
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Other tools you may find usefulFictitious user data generator - complete test persona
Fictitious user data is essential for creating: UI mockups, test databases, seed scripts, product demos and tests without GDPR risk. The generator creates complete, realistic-looking profiles with all fields typical of the users' system.
What's included in the test profile
Name and surname: realistic Polish or foreign. Email: composed of firstname+lastname@domain. Telephone: Polish format +48 6xx-xxx-xxx. Address: street, postal code, city, province. Date of birth: random within the age range. PESEL: validated by an algorithm (checksum). Password (hashed): bcrypt. Avatar: placeholder image.
GDPR and test data
GDPR (GDPR) Art. 5: personal data = "information relating to an identified or identifiable natural person". Fictitious data: is not personal data (does not refer to a real person). Safe alternatives: (1) dummy data generator, (2) anonymization of real data. Production: never real data in testing/staging!
PESEL algorithm – validation
PESEL: 11 digits. String: YYMMDDXXXXY (Y=year, M=month, D=day, X=ordinal number, Y=check digit). Born in the 20th century: YYMMDD. In the 21st century: month + 20 (e.g. 2001 = month 01 → 21). Control: weights 1,3,7,9,1,3,7,9,1,3 → sum mod 10 = (10 - mod) mod 10.
Popular libraries for generating data
JavaScript: @faker-js/faker. faker.person.fullName(), faker.internet.email(), faker.location.city(). Python: Faker. fake = Faker("pl_PL"); fake.name(). PHP: fakerphp/faker. $faker = Faker\Factory::create("pl_PL"). Java: Java Faker (com.github.javafaker). C#: Bogus (NuGet). All of them support Polish localization.
Frequently asked questions
How to generate PESEL with date of birth?
1. Determine the year and month of birth. 2. If ≥ 2000: add 20 to the month. 3. Generate random 4 digits XXX (ordinal) + even/odd for gender (last before control). 4. Calculate the check digit: weights 1,3,7,9,1,3,7,9,1,3. sum × appropriate digit → sum mod 10 → checksum = (10 - sum mod 10) mod 10.
How to generate realistic test emails?
Format: [email protected]. Test domains: @example.com, @test.com, @mailtest.net (RFC 2606 reserved). Avoid: @gmail.com, @wp.pl (possibility of collisions with real ones). Faker: faker.internet.email("John", "Kowalski") = "[email protected]". Subaddressing: [email protected].
How to import dummy data into MySQL?
PHP: foreach ($faker->count(100)) → INSERT. Laravel seeder: UserFactory::count(100)->create(). Node.js: faker loop + mysql2 query. SQL: load from CSV (LOAD DATA INFILE). Python: faker loop + pymysql execute. Tip: use transactions (BEGIN/COMMIT) for speed with large sets.
What fields should a user record contain?
Minimum: id (UUID), email (unique), password_hash. Standard: + first_name, last_name, created_at, updated_at. E-commerce: + address, phone, date_of_birth. PL system: + PESEL (encrypted), NIP (for companies). Avatar: URL to S3 or placeholder. Soft delete: deleted_at (nullable). Email verified: email_verified_at.
How to anonymize real production data for testing?
Anonymization script: foreach user: user.email = fake.email(); user.phone = fake.phone(). Pseudonymization: hash(real_email + salt) → traceability preserved. Tools: ARX Data Anonymization Tool, Amnesia. AWS: You have detects PII, Glue + DynamoDB for masking. Remember: production