Effortless Random Mock Data Generator
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Quickly generate customizable random data for testing and development purposes. This n8n workflow provides a robust solution for creating mock user profiles, complete with first name, last name, occupation, and derived email addresses, all without writing a single line of code.
About This Workflow
This beginner-friendly n8n workflow empowers you to effortlessly generate realistic mock data for all your testing and development needs. Starting from a basic set of input values, it intelligently combines all possible permutations of first names, last names, and occupations. The workflow then randomizes the order of these generated entries and limits the output to a specified number.
A powerful feature is the ability to automatically derive new fields, such as creating unique email addresses from the generated names. It's a zero-coding, self-contained solution, perfect for populating databases, testing new automations, or creating sample data for demos. A linked tutorial provides a detailed walkthrough to help you get started quickly.
Key Features
- Comprehensive Data Permutations: Generates all possible combinations from your input lists (e.g., first names, last names, occupations).
- Randomized Output: Shuffles the generated data to provide a truly random selection.
- Output Limiting: Control the exact number of data items you need with an adjustable limit.
- Dynamic Data Derivation: Easily add nodes to create new fields based on existing data, like generating email addresses from names.
- No-Code & Self-Contained: Get started immediately without external dependencies or complex coding.
How To Use
- Start the Workflow: Click 'Execute Workflow' to manually trigger the data generation process.
- Define Source Data: Modify the
Codenode to input your desired arrays of first names, last names, occupations, or any other fields you wish to combine. - Adjust Combinations: The
Setnodes (Firstname1,Lastname,Occupation) andMergenodes work together to create permutations. You can add moreSetnodes for additional fields and connect them to theMergestructure. - Randomize & Limit: Use the
Random(Sort) node to shuffle the order of your generated data and adjust theLimitnode'smaxItemsparameter to specify the number of output records. - Customize Output: The
Emailnode demonstrates deriving a new field. Add or modifySetnodes after theLimitnode to perform further post-processing or create additional calculated fields based on your generated data.
Apps Used
Workflow JSON
{
"id": "3b6f8c93-f79f-47bd-bf7d-2e97a797ff6a",
"name": "Effortless Random Mock Data Generator",
"nodes": 11,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 3b6f8c93-f79f...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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