Random Test Data Generator Tutorial Part 2: Master Field Configuration and Data Constraints

Random Test Data Generator Tutorial Part 2: Master Field Configuration and Data Constraints

Advanced guide to customizing test data fields, setting constraints, and creating complex datasets. Learn about field types, validation rules, and custom formats.

👤 QELab Team 📅 8/4/2025 ⏱️ 5 min read
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Random Test Data Generator Tutorial Part 2: Advanced Field Configuration and Customization

Welcome to Part 2 of our Random Test Data Generator tutorial series! Now that you understand the basics, we'll explore the powerful customization features that make this tool professional-grade.

Prerequisites

  • Completed Part 1 of this tutorial series

  • Basic understanding of data types and validation

  • Familiarity with date formats and regular expressions (helpful but not required)

Objectives

By the end of Part 2, you'll master:

  • Field configuration and constraint settings

  • Custom format patterns

  • Advanced field types and categories

  • Field ordering and visibility controls

  • Locale-specific data generation

Step 1: Understanding Field Categories

The tool organizes fields into 18 categories. Here are few of them listed below. However, you can find all of them right inside the UI.

Core Categories


  • Personal: Names, emails, phone numbers, job titles, avatar, gender, date of birth

  • Address: Street addresses, cities, postal codes, coordinates, timezone

  • Commerce: Products, prices, departments, materials, adjective, product description

  • Company: Business names, catch phrases, identifiers, business id

  • Finance: Account numbers, credit cards, currency codes, bitcoin address, amount, routing number

Specialized Categories


  • Internet: URLs, usernames, passwords, IP addresses, mac address, user agent, domain name

  • Date: Past/future dates, weekdays, months, anytime

  • Lorem: Text generation for content words, paragraph, slug

  • Database: UUIDs, MongoDB IDs, database types, Nano id, database engine

  • Science: Chemical elements, formulas, DNA sequences, coordinates

Step 2: Field Management Operations

Adding Multiple Fields


  • Click "Add Field" button

  • Use search bar to find specific field types or navigate throught different types on the left side of the panel

  • Select multiple fields by selecting them

  • Click "Add Selected Fields" or "Add fields" to batch add

    • Reordering Fields


    • Use up/down arrows to change field order (in case you want to see the output in any specific order)

    • Order determines column sequence in output

    Field Visibility


    • Eye icon toggles field visibility

    • Hidden fields remain configured but don't appear in output

    • Useful for temporarily excluding fields

    Step 3: Field Configuration Deep Dive

    Number Fields Configuration

    Fields: Price, Amount, Integer, Float, Latitude, Longitude

    Available Constraints:

    • Minimum Value: Set lower bound (e.g., 0 for positive numbers)

    • Maximum Value: Set upper bound (e.g., 1000 for reasonable prices)

    • Decimal Precision: Control decimal places (0-10)

    Example: Lets configure a dataset with id, name and salary field where salary is:

    • Min: 30000

    • Max: 200000

    • Decimal Precision: 1

    !Field configuration dialog showing number constraints

    Date Fields Configuration


    Fields: Birth Date, Past Date, Future Date, Recent Date

    Available Constraints:

    • Start Date: Earliest possible date

    • End Date: Latest possible date

    • Date Format: Output format options

    Format Options:

    • YYYY-MM-DD: 2024-01-15

    • MM/DD/YYYY: 01/15/2024

    • DD/MM/YYYY: 15/01/2024

    • MMMM DD, YYYY: January 15, 2024

    !Date field configuration with format options

    Text Fields Configuration


    Fields: Lorem Words, Sentences, Paragraphs, Bio

    Available Constraints:

    • Number of Words: For word generation (1-20)

    • Min/Max Length: Character count limits

    • Min/Max Paragraphs: For paragraph generation

    Password Fields Configuration


    Available Constraints:
    • Length: Min/max character count

    • Character Sets:

    - Uppercase letters (A-Z)
    - Lowercase letters (a-z)
    - Numbers (0-9)
    - Symbols (!@#$%^&*)

    Example: You can create a corporate password based on the policy as needed

    • Min Length: 12

    • Max Length: 16

    • Include all character sets

    Step 4: Custom Format Patterns

    Custom formats transform generated data using patterns. In case, you would like to read the detailed documentation on custom formatting, click here:

    Pattern Syntax


    • #: Random digit (0-9)

    • {value}: Original generated value

    Common Examples


    • Employee ID: EMP-#### → EMP-1234

    • Product Code: PROD-{value}-## → PROD-Laptop-42

    • Phone Format: +1-###-###-#### → +1-555-123-4567

    Advanced Patterns


    • Serial Number: SN{value}####

    • Reference Code: REF-##-{value}-##

    • Custom ID: {value}-####-COMP

    !Custom format pattern examples

    Step 5: Locale-Specific Generation

    Supported Locales


    The tool supports 20+ locales with region-specific formatting:

    English Variants:

    • United States (en_US)

    • United Kingdom (en_GB)

    • Canada (en_CA)

    • Australia (en_AU)

    European:

    • Germany (de) - German names, postcodes

    • France (fr) - French names, phone formats

    • Spain (es), Italy (it), Netherlands (nl)

    Asian:

    • Japan (ja) - Japanese names, postal codes

    • China (zh_CN), Korea (ko), India (en_IN)

    Locale Impact Examples


    Phone Numbers:
    • US: +1 (555) 123-4567

    • UK: +44 1234 567890

    • Germany: +49 123 4567890

    • Japan: 03-1234-5678

    Postal Codes:

    • US: 90210

    • UK: SW1A 1AA

    • Germany: 10115

    • Canada: K1A 0A6

    Step 6: Complex Field Combinations

    Customer Profile Example


  • Personal Data:

    • - first_name, last_name (US locale)
    - email (derived from names)
    - phone (US format)
    - date_of_birth (1950-2000 range)

  • Address Data:

    • - street_address, city, state, zip_code
    - All constrained to US format

  • Commerce Data:

    • - customer_id (Custom format: CUST-######)
    - account_balance (Min: 0, Max: 50000, 2 decimals)
    - registration_date (Past 5 years)


    Step 7: Validation and Testing

    Field Validation


    • Test constraints with small datasets first

    • Verify custom formats produce expected patterns

    • Check locale-specific formatting

    Common Issues and Solutions


    • Date ranges: Ensure start_date < end_date

    • Number ranges: Verify min < max values

    • Custom formats: Test patterns with sample data

    • Text length: Balance min/max for realistic content

    Practice Exercise

    Try creating a realistic employee dataset with these fields:

  • Employee ID (Custom format: EMP-####)

  • First Name and Last Name (US locale)

  • Email address

  • Hire Date (Past 10 years)

  • Salary (Range: $35,000 - $120,000)

  • Department (from predefined list)

    • Try the Exercise

    Summary

    In Part 2, you mastered:

    • Advanced field configuration options

    • Constraint settings for different data types

    • Custom format patterns for professional data

    • Locale-specific data generation

    • Complex field combinations and validation

    Next Up: In Part 3, we'll explore export workflows, integration strategies, and professional use cases for maximum productivity.

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