I Built a Free Synthetic Data Generator — Here's How (React + Tailwind)

Source: Dev.to

Overview

We’ve all been there — you need 10,000 realistic user records to test your app, or a batch of fake healthcare data for a demo, or transaction logs to stress‑test a dashboard. So you either:

• Write a janky script that generates “User_1, User_2, User_3…”
• Spend 30 minutes configuring a CLI tool
• Use a SaaS tool that limits you to 100 rows on the free tier

I got tired of this, so I built DataForge — a free, browser‑based synthetic data generator that creates realistic fake data instantly. No signup, no server, no limits.

🔗 Try it live

What It Does

DataForge generates realistic fake data across 9 data types in two categories.

📊 General Data

• Users – Names, emails, phones, DOB, company, job title
• Addresses – Street, city, state, ZIP, coordinates
• Transactions – Amounts, merchants, categories, status

🏥 Healthcare / HIPAA‑Safe

• Patients – MRN, blood type, allergies, conditions, insurance
• Medical Records – ICD‑10 codes, vitals, visit types, clinical notes
• Prescriptions – Real medications, dosages, DEA numbers, NDC codes
• Lab Results – 26 real lab tests with reference ranges and flags
• Insurance Claims – Charged/allowed/paid amounts, claim status
• Healthcare Providers – NPI numbers, specialties, credentials

All data is 100 % synthetic — no real patient data, no HIPAA risk.

Key Features

⚡ Generate Up to 50,000 Records Instantly

Everything runs client‑side. No API calls, no server. Your data never leaves your browser.

🎬 Custom Scenarios

Preset Scenarios

• 🧓 Elderly Patient Cohort (ages 65+)
• 👶 Pediatric Cohort (ages 0‑17)
• 🚨 Critical Lab Values
• 💰 High‑Value Transactions ($5K+)
• 🕵️ Fraud Patterns
• ❌ Denied Claims Batch
• 🗑️ Dirty/Messy Data (with nulls and errors)

Custom Builder

• Set null rates per field (0‑80 %)
• Define value ranges (e.g., age 65‑95, amount $10K+)
• Force specific values (e.g., status = "Denied")
• Add custom value pools
• Control duplicate rates and error injection

📤 Export Formats

• JSON – Standard structured data
• CSV – For spreadsheets and databases
• SQL – Ready‑to‑run INSERT statements
• HL7 FHIR – Healthcare interoperability standard

🌱 Reproducible with Seeds

Set a seed value and get the exact same data every time. Perfect for consistent test suites.

How I Built It

Tech Stack

• React 18 + TypeScript
• Tailwind CSS – Dark HD interface
• Vite – Fast builds
• Custom seeded PRNG – No external faker library needed

The Seeded Random Number Generator

Instead of using Math.random() (which isn’t seedable), I built a custom PRNG based on a simple linear congruential generator:

class SeededRandom {
  private seed: number;

  constructor(seed: number) {
    this.seed = seed;
  }

  next(): number {
    this.seed = (this.seed * 16807 + 0) % 2147483647;
    return this.seed / 2147483647;
  }

  nextInt(min: number, max: number): number {
    return Math.floor(this.next() * (max - min + 1)) + min;
  }

  pick<T>(array: T[]): T {
    return array[this.nextInt(0, array.length - 1)];
  }
}

If you work in Health IT, you know the pain:

• ❌ You can’t use real patient data for testing (HIPAA)
• ❌ Epic/Cerner sandboxes have limited test patients
• ❌ Synthea is powerful but requires Java + CLI setup
• ❌ Most online generators don’t understand healthcare data

DataForge fills this gap:

• ✅ FHIR‑native export — Generate valid FHIR Bundles
• ✅ Real ICD‑10 & CPT codes — Not random strings
• ✅ Clinical scenarios — Elderly cohorts, critical labs, denied claims
• ✅ Runs in the browser — Share the URL with your QA team
• ✅ 50 K records — Enough for load testing

What’s Next

• Custom schema builder (define your own data types)
• API endpoint mode (use as a mock API)
• Relationships between tables (foreign keys)
• More healthcare standards (HL7v2 messages, C‑CDA)
• Localization (non‑US names, addresses, phone formats)

If this tool saves you time, drop a ⭐ on the repo or leave a comment. I’d love to hear how you’re using it!