Test Data Faker Builder

Test Data Faker Builder | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Generator
Input types: textarea, number, select
Output type: json
Sample coverage: 4
API ready: Yes

Overview

The Test Data Faker Builder is a powerful utility designed to generate realistic, structured mock data for software development and QA testing. By defining your schema through a simple JSON configuration, you can instantly create batches of synthetic records including names, emails, credit cards, IDs, and custom regex-based patterns.

When to use

Populating databases or frontend applications with realistic mock records for UI testing.
Generating large volumes of synthetic data to stress-test API endpoints and data processing pipelines.
Creating specific edge-case datasets using regex patterns for validation and error handling scenarios.

How it works

1Define your data structure in the Field Config JSON, specifying field names and types like faker, regex, or pick.
2Set the desired record count to determine the volume of data generated.
3Select your preferred output format, choosing between JSON, NDJSON, or CSV.
4Execute the generation to receive your structured dataset ready for immediate integration.

Use cases

Generating thousands of user profiles for performance testing a new database schema.
Creating mock transaction logs with valid-looking credit card numbers for payment gateway integration testing.
Building seed data for frontend prototypes to ensure UI components handle various data lengths and states.

Examples

1. Generate QA seed users

QA Engineer

Background

Need to populate a new user management dashboard with realistic data to test search and filtering functionality.

Problem

Manually creating 50+ user records is inefficient and prone to errors.

How to use

Configure the fields for name, email, credit card, and status, then set the count to 50.

{"fields": [{"name": "fullName", "type": "fullName"}, {"name": "email", "type": "email"}, {"name": "creditCard", "type": "creditCard"}, {"name": "status", "type": "pick", "values": ["active", "blocked"]}]}

Outcome

A clean JSON file containing 50 unique user records ready for database import.

2. Mock Order System Data

Backend Developer

Background

Testing an API that processes order codes and scores.

Problem

Need to verify that the system correctly handles specific order code formats and numeric ranges.

How to use

Use the regex type for order codes and the number type for scores, then export as NDJSON.

FAQ

What data formats can I export?

You can export your generated data in JSON, NDJSON, or CSV formats.

Can I generate specific patterns like order codes?

Yes, use the 'regex' type in your configuration to define custom patterns like 'ORD-[A-Z0-9]{8}'.

Is there a limit to how many records I can generate?

You can generate between 1 and 1,000 records per batch.

Can I pick values from a predefined list?

Yes, use the 'pick' type and provide an array of values to randomly select from for that field.

Does it support international data?

Yes, certain faker fields like 'fullName' support locale settings to generate region-specific data.

{"fields": [{"name": "orderCode", "type": "regex", "pattern": "ORD-[0-9]{5}"}, {"name": "score", "type": "number", "min": 0, "max": 100}]}

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Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Generate QA seed users

2. Mock Order System Data

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