I Built a Fake-Data Generator for Developers and QA — Here’s Why It Matters

Sandeep Kumar — Sat, 22 Nov 2025 11:33:34 +0000

As developers, we often need quick access to clean, realistic test data — for APIs, UI states, database seeding, search filters, demos, or handling edge cases. Preparing this data manually can be repetitive and time-consuming.

So I wanted to create something that makes the process smoother.

Introducing https://fakeru.com — a simple, fast web app that helps you generate natural-looking fake data by selecting just the fields you need. No setup, no scripting, no configuration files — just instant data in the format you want.

The Problem Developers Face

In every project, we need sample data that feels real:

Testing user flows
Populating tables and cards
Trying out different API states
Generating mock files
Building dashboards
Doing QA without exposing sensitive information

The challenge?

Enterprise tools are complex and not beginner-friendly.
Real data (copied from production) risks privacy and security.
Manual creation is slow, boring, and repetitive. I built Fakeru to eliminate these pain points.

What Fakeru Can Do

1. Choose Your Fields
Pick exactly the fields you need — names, emails, phones, companies, countries, addresses, and more.

2. Multi-Locale Support
Need Indian names?
US addresses?
German phone numbers?
Spanish cities?
Fakeru supports multiple locales to generate culturally accurate data.

3. Export in 3 Formats
Fakeru exports data in:

CSV — perfect for spreadsheets & quick imports
JSON — ideal for APIs and frontend testing
SQL Query — ready-to-run INSERT statements for databases.

The SQL export is especially useful for seeding dev environments or preparing demo data.

4. Bulk Data Generation
Generate hundreds or thousands of rows instantly. No rate limit. No credits. Just clean data.

5. Clean UI, No Learning Curve
Choose locale(Optional) → Pick fields → Generate → Choose format → Download.

Why Realistic Fake Data Matters

Using production data is a privacy risk.
Using dummy “Lorem Ipsum”-style values limits testing.

Good fake data helps:

Validate edge cases
Produce accurate UI demos
Test sorting, filtering, and search
Prepare sample databases
Share APIs with other teams
Do QA without exposing real user info

Real-looking data makes testing and development much smoother.

How It’s Built

Fakeru is powered by a blend of custom field logic and the reliability of Faker.js, enhanced with additional rules to generate more natural-looking values.
On top of that, I built custom mappers for locale-aware data and transformers to convert the same dataset into CSV, JSON, and SQL INSERT formats instantly.

How this tool is a bit different?

Fakeru isn’t trying to replace or compete with existing tools — it simply focuses on a few areas that I personally needed in my workflow. It provides multiple locale support, so you can generate region-specific names, addresses, and phone numbers. It also supports SQL query export, which makes it easier to seed databases or prepare demo environments without writing insert statements manually.

Final Thoughts

I built Fakeru because I was tired of repetitive work and boring test data.
If you want clean, realistic fake data with CSV/JSON/SQL export and locale support, try it out.

Would love feedback from the community!