Zero Snippet

Dummy data generator — fake names, emails, and addresses as JSON or CSV

Use this free online dummy data generator to build synthetic people records for Storybook, Cypress, Playwright, Postman collections, and SQL seed scripts. Toggle first name, last name, email, phone, company, job title, and realistic mailing-style addresses (street, city, US state abbreviation, ZIP, country). Need columns that match an existing spreadsheet? Paste names or upload a header row — the tool infers sensible fake values from labels like “email” or “postal code.” Export pretty JSON or RFC-style CSV with escaped quotes, then copy from the preview or download a file. Generation uses cryptographically strong randomness in your browser; nothing is sent to our servers. After export, validate structure with the JSON formatter & validator, pivot into spreadsheets via JSON to CSV, or walk the inverse path with CSV to JSON.

Output format
Standard fields

Output

10 rows · JSON

Random values use crypto.getRandomValues. Emails use safe test-style domains—not real inboxes. Regenerate whenever you need a fresh batch for a new test run.

Why developers still reach for a fake data generator in 2026

Modern stacks ship faster when every layer has believable payloads: design systems need populated tables, integration tests need unique rows, and sales demos need charts that do not leak customer PII. A lightweight test data generator keeps product, QA, and engineering aligned on shape and edge cases without standing up a full staging clone on day one. This page focuses on developer-grade fixtures—not regulated synthetic populations for ML training—so you can iterate quickly and still follow your company's data-handling policy.

Compared with hard-coded lorem paragraphs, structured JSON dummy data mirrors real API contracts: typed strings in predictable keys, variety across rows, and easy diffing when schemas evolve. Pair generated IDs with our UUID generator when you need opaque primary keys in the same fixture bundle.

How to use this dummy data generator (step by step)

  1. Select the standard fields your UI or API expects. The defaults cover a typical contact card (name, email, address). Add phone, company, or job title when you are mocking CRM or HR screens.
  2. Optionally list custom column names — one per line — or click Upload columns to import a CSV header row or a plain list. Headers such as “customer_email” or “PostalCode” steer the heuristic filler.
  3. Set the row count, choose JSON or CSV, and enable pretty-printing when you want readable JSON in Git. Click Regenerate data whenever you need a fresh random batch.
  4. Use the floating copy control on the output pane or Download to save dummy-data.json or dummy-data.csv. For checksums on frozen fixtures, run strings through the hash generator.

Keywords and search intents this page covers

Teams search for a fake name generator for testing, sample CSV data, mock REST payload, or address generator for forms. This tool answers those intents with explicit export formats and privacy-preserving local generation. If your pipeline already speaks YAML, convert samples using YAML to JSON after you copy JSON output.

Privacy, compliance, and realistic expectations

Because randomness and formatting happen in the browser, you can draft datasets on a VPN or offline tab without uploading proprietary schemas. Still, synthetic rows can occasionally resemble real people—treat exports as non-production artifacts and scrub before public screenshots. Emails intentionally use non-deliverable domains suitable for documentation; never spam arbitrary addresses. When you validate live endpoints, switch to your API sandbox and our HTTP header checker or response code checker to confirm environment behavior—not this generator—for network truth.

Related developer tools

Browse the full code and developer tools catalog. Highlights:

  • JSON Formatter & Validator — Format, validate, minify, and explore JSON in a collapsible tree—fix payloads before they hit production.
  • JSON to CSV Converter — Turn JSON arrays into downloadable CSV with automatic column detection for spreadsheets and BI tools.
  • JSON to YAML Converter — Convert JSON to readable YAML for configs and Kubernetes—copy or download the result.
  • CSV to JSON Converter — Paste or upload CSV and get structured JSON with header-aware typing for APIs and apps.
  • YAML to JSON Converter — Parse YAML to valid JSON with clear errors—ideal for CI configs and cloud templates.
  • XML Formatter & Validator — Beautify and validate XML with structure insight and actionable parse errors.
  • Regex Tester & Debugger — Test patterns live with highlights, capture groups, and flags—debug regex without leaving the browser.
  • SQL Formatter — Pretty-print SQL with indentation and keyword casing for readable queries and code review.
  • HTML Formatter & Minifier — Beautify or minify HTML and compare raw markup with a quick rendered preview.
  • CSS Formatter & Minifier — Format messy stylesheets or minify CSS for faster loads—keep design tokens consistent.
  • JavaScript Formatter & Minifier — Pretty-print or minify JavaScript for debugging locally and shipping smaller bundles.
  • HTML to Markdown Converter — Convert HTML snippets to Markdown for docs, CMS migrations, and README cleanup.
  • Markdown to HTML Converter — Turn Markdown into HTML with a live preview—handy for emails, blogs, and static pages.
  • Code Diff Checker — Compare two code blocks side by side with clear add/remove highlighting for reviews.

Frequently asked questions

What is a dummy data generator used for?
Teams generate fake names, emails, and addresses to populate forms, Storybook stories, API mocks, database fixtures, and load tests without exposing real customer data. JSON and CSV exports slot into seed scripts, spreadsheets, and contract tests.
Is this fake data safe for production databases?
No. These values are synthetic examples for development and QA only. They are not verified identities, deliverable email addresses, or legally compliant stand-ins for PII in every jurisdiction. Use production-grade data policies and anonymization for real user-like records.
Does my data leave the browser?
No. Rows are built entirely in your tab with the Web Crypto API for randomness. Nothing is uploaded to our servers unless you navigate to another tool that explicitly performs network requests.
How do I match columns from an existing CSV or schema?
Use Upload columns to load a header row or a newline-separated list. The tool guesses types from header text (for example “email”, “phone”, “city”). For full control, pick standard fields with checkboxes and add extra column names in the text area.
Can I get reproducible rows every time I click generate?
Each run uses fresh random values. For deterministic fixtures, generate once, copy or download the file, and commit it to your repo—or use a seeded library in your backend tests. Our UUID generator is a better fit when you only need stable identifier strings.
JSON vs CSV—which should I choose?
Choose JSON when your tests, mocks, or APIs expect objects or arrays. Choose CSV when you are importing into Excel, Google Sheets, or legacy importers. You can convert between tabular formats later with the JSON to CSV and CSV to JSON tools on the home page.
Are emails and phone numbers valid?
They look realistic but use test domains (for example example.com and .test TLDs where used) and synthetic phone patterns. Do not send marketing or SMS to generated numbers; use your provider’s sandbox modes instead.
Which other tools pair well with dummy datasets?
Validate JSON payloads with the JSON formatter and validator, convert exports with JSON to CSV or CSV to JSON, generate opaque IDs with the UUID generator, and hash stable snapshots with the hash generator—all listed under code and developer tools.